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Project_Carmignac/ClusteringV4_400plus_Ancien_finMars.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "d9272d36",
"metadata": {},
"source": [
"# Clustering des 400+ gros comptes Carmignac — version enrichie\n",
"\n",
"Ce notebook repart du notebook initial et ajoute :\n",
"\n",
"- une base plus propre et plus lisible ;\n",
"- des **features comportementales** supplémentaires ;\n",
"- un **clustering global** sur les 400+ gros comptes ;\n",
"- un **clustering par fonds** (`Product - Isin`) sur les plus gros fonds ;\n",
"- un cadre prêt à intégrer des **données de performance Carmignac** si elles sont disponibles.\n",
"\n",
"## Principes retenus\n",
"\n",
"- univers = comptes avec **AUM total ≥ 5 M€** au **31/10/2025**\n",
"- exclusion de **Off Distribution** et **Private Clients**\n",
"- **pas de clipping d'outliers** pour l'instant\n",
"- un fonds est identifié par **`Product - Isin`**\n",
"- les résultats doivent être **interprétables métier**, pas seulement \"bons\" mathématiquement"
]
},
{
"cell_type": "markdown",
"id": "c6b14319",
"metadata": {},
"source": [
"## 1. Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "1aa70c18",
"metadata": {},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings(\"ignore\")\n",
"\n",
"import re\n",
"import math\n",
"import json\n",
"from pathlib import Path\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"from sklearn.preprocessing import RobustScaler\n",
"from sklearn.impute import SimpleImputer\n",
"from sklearn.pipeline import Pipeline\n",
"from sklearn.cluster import KMeans, AgglomerativeClustering\n",
"from sklearn.mixture import GaussianMixture\n",
"from sklearn.metrics import silhouette_score, davies_bouldin_score, calinski_harabasz_score\n",
"from sklearn.decomposition import PCA\n",
"from sklearn.linear_model import LinearRegression\n",
"\n",
"pd.set_option(\"display.max_columns\", 200)\n",
"pd.set_option(\"display.max_rows\", 200)\n",
"\n",
"RANDOM_STATE = 42\n",
"EPS = 1e-9"
]
},
{
"cell_type": "markdown",
"id": "98deb42c",
"metadata": {},
"source": [
"## 2. Paths"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a462ff7a-1e4d-44f7-af6c-031b47779ce1",
"metadata": {
"scrolled": true
},
"outputs": [
{
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
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" <th>Company - Ultimate Parent Id</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" <th>Product - Asset Type</th>\n",
" <th>Product - Strategy</th>\n",
" <th>Product - Legal Status</th>\n",
" <th>Product - Is Dedie ?</th>\n",
" <th>Product - Fund</th>\n",
" <th>Product - Shareclass Type</th>\n",
" <th>Product - Shareclass Currency</th>\n",
" <th>Product - Isin</th>\n",
" <th>Centralisation Date</th>\n",
" <th>Quantity - AUM</th>\n",
" <th>Value - AUM CCY</th>\n",
" <th>Value - AUM €</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-31</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>3.242523e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Equity</td>\n",
" <td>Investissement Latitude</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Investissement Latitude</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010147603</td>\n",
" <td>2015-01-31</td>\n",
" <td>1717.000</td>\n",
" <td>4.767422e+05</td>\n",
" <td>4.767422e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Equity</td>\n",
" <td>Investissement</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Investissement</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010148981</td>\n",
" <td>2015-01-31</td>\n",
" <td>8254.870</td>\n",
" <td>9.862671e+06</td>\n",
" <td>9.862671e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Equity</td>\n",
" <td>Euro-Entrepreneurs</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Euro-Entrepreneurs</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010149112</td>\n",
" <td>2015-01-31</td>\n",
" <td>278.923</td>\n",
" <td>7.664525e+04</td>\n",
" <td>7.664525e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Fixed Income</td>\n",
" <td>Sécurité</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Sécurité</td>\n",
" <td>AW &amp; AW-R</td>\n",
" <td>EUR</td>\n",
" <td>FR0010149120</td>\n",
" <td>2015-01-31</td>\n",
" <td>1807.267</td>\n",
" <td>3.078318e+06</td>\n",
" <td>3.078318e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088393</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Diversified</td>\n",
" <td>Inflation Solution</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Inflation Solution</td>\n",
" <td>F</td>\n",
" <td>EUR</td>\n",
" <td>LU2715954330</td>\n",
" <td>2025-10-31</td>\n",
" <td>81065.419</td>\n",
" <td>9.533293e+06</td>\n",
" <td>9.533293e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088394</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Diversified</td>\n",
" <td>Inflation Solution</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Inflation Solution</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>LU2715954504</td>\n",
" <td>2025-10-31</td>\n",
" <td>6853.363</td>\n",
" <td>7.978685e+05</td>\n",
" <td>7.978685e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088395</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Private Assets</td>\n",
" <td>Evergreen</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac S.A. SICAV - PART II UCI Private Eve...</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>LU2799473124</td>\n",
" <td>2025-10-31</td>\n",
" <td>4212.234</td>\n",
" <td>5.263608e+05</td>\n",
" <td>5.263608e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088396</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Equity</td>\n",
" <td>Tech Solutions</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Tech Solutions</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>LU2809794220</td>\n",
" <td>2025-10-31</td>\n",
" <td>31469.523</td>\n",
" <td>4.438147e+06</td>\n",
" <td>4.438147e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088397</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Equity</td>\n",
" <td>Tech Solutions</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Tech Solutions</td>\n",
" <td>F</td>\n",
" <td>EUR</td>\n",
" <td>LU2809794576</td>\n",
" <td>2025-10-31</td>\n",
" <td>554.301</td>\n",
" <td>7.871629e+04</td>\n",
" <td>7.871629e+04</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1088398 rows × 19 columns</p>\n",
"</div>"
],
"text/plain": [
" reg_orig reg_used Agreement - Code Company - Id \\\n",
"0 18872 18872 L104 2257.0 \n",
"1 18872 18872 L104 2257.0 \n",
"2 18872 18872 L104 2257.0 \n",
"3 18872 18872 L104 2257.0 \n",
"4 18872 18872 L104 2257.0 \n",
"... ... ... ... ... \n",
"1088393 Private Client Private Client Private Client Private Client \n",
"1088394 Private Client Private Client Private Client Private Client \n",
"1088395 Private Client Private Client Private Client Private Client \n",
"1088396 Private Client Private Client Private Client Private Client \n",
"1088397 Private Client Private Client Private Client Private Client \n",
"\n",
" Company - Ultimate Parent Id Registrar Account - Region \\\n",
"0 33675.0 Switzerland \n",
"1 33675.0 Switzerland \n",
"2 33675.0 Switzerland \n",
"3 33675.0 Switzerland \n",
"4 33675.0 Switzerland \n",
"... ... ... \n",
"1088393 Private Client France \n",
"1088394 Private Client France \n",
"1088395 Private Client France \n",
"1088396 Private Client France \n",
"1088397 Private Client France \n",
"\n",
" RegistrarAccount - Country Product - Asset Type \\\n",
"0 Switzerland Diversified \n",
"1 Switzerland Equity \n",
"2 Switzerland Equity \n",
"3 Switzerland Equity \n",
"4 Switzerland Fixed Income \n",
"... ... ... \n",
"1088393 France Diversified \n",
"1088394 France Diversified \n",
"1088395 France Private Assets \n",
"1088396 France Equity \n",
"1088397 France Equity \n",
"\n",
" Product - Strategy Product - Legal Status Product - Is Dedie ? \\\n",
"0 Patrimoine FCP NO \n",
"1 Investissement Latitude FCP NO \n",
"2 Investissement FCP NO \n",
"3 Euro-Entrepreneurs FCP NO \n",
"4 Sécurité FCP NO \n",
"... ... ... ... \n",
"1088393 Inflation Solution SICAV NO \n",
"1088394 Inflation Solution SICAV NO \n",
"1088395 Evergreen SICAV NO \n",
"1088396 Tech Solutions SICAV NO \n",
"1088397 Tech Solutions SICAV NO \n",
"\n",
" Product - Fund \\\n",
"0 Carmignac Patrimoine \n",
"1 Carmignac Investissement Latitude \n",
"2 Carmignac Investissement \n",
"3 Carmignac Euro-Entrepreneurs \n",
"4 Carmignac Sécurité \n",
"... ... \n",
"1088393 Carmignac Portfolio Inflation Solution \n",
"1088394 Carmignac Portfolio Inflation Solution \n",
"1088395 Carmignac S.A. SICAV - PART II UCI Private Eve... \n",
"1088396 Carmignac Portfolio Tech Solutions \n",
"1088397 Carmignac Portfolio Tech Solutions \n",
"\n",
" Product - Shareclass Type Product - Shareclass Currency \\\n",
"0 A EUR \n",
"1 A EUR \n",
"2 A EUR \n",
"3 A EUR \n",
"4 AW & AW-R EUR \n",
"... ... ... \n",
"1088393 F EUR \n",
"1088394 A EUR \n",
"1088395 A EUR \n",
"1088396 A EUR \n",
"1088397 F EUR \n",
"\n",
" Product - Isin Centralisation Date Quantity - AUM Value - AUM CCY \\\n",
"0 FR0010135103 2015-01-31 49094.915 3.242523e+07 \n",
"1 FR0010147603 2015-01-31 1717.000 4.767422e+05 \n",
"2 FR0010148981 2015-01-31 8254.870 9.862671e+06 \n",
"3 FR0010149112 2015-01-31 278.923 7.664525e+04 \n",
"4 FR0010149120 2015-01-31 1807.267 3.078318e+06 \n",
"... ... ... ... ... \n",
"1088393 LU2715954330 2025-10-31 81065.419 9.533293e+06 \n",
"1088394 LU2715954504 2025-10-31 6853.363 7.978685e+05 \n",
"1088395 LU2799473124 2025-10-31 4212.234 5.263608e+05 \n",
"1088396 LU2809794220 2025-10-31 31469.523 4.438147e+06 \n",
"1088397 LU2809794576 2025-10-31 554.301 7.871629e+04 \n",
"\n",
" Value - AUM € \n",
"0 3.242523e+07 \n",
"1 4.767422e+05 \n",
"2 9.862671e+06 \n",
"3 7.664525e+04 \n",
"4 3.078318e+06 \n",
"... ... \n",
"1088393 9.533293e+06 \n",
"1088394 7.978685e+05 \n",
"1088395 5.263608e+05 \n",
"1088396 4.438147e+06 \n",
"1088397 7.871629e+04 \n",
"\n",
"[1088398 rows x 19 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PATH_AUM = \"s3://projet-bdc-carmignac-g3/paco/AUM_paths.csv\"\n",
"df_aum = pd.read_csv(PATH_AUM, sep=\",\")\n",
"df_aum"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "8be2ec30",
"metadata": {},
"outputs": [],
"source": [
"\n",
"# =========================\n",
"# PATHS PRINCIPAUX\n",
"# =========================\n",
"PATH_FLOWS = \"s3://projet-bdc-data/carmignac/Flows ENSAE V2 -20251105.csv\"\n",
"PATH_NAV = \"s3://projet-bdc-data/carmignac/Data Modélisation/Nav/NAV_Bench_data.csv\"\n",
"PATH_RATES = \"s3://projet-bdc-data/carmignac/Data Modélisation/market data/esterRates.csv\"\n",
"\n",
"# Optionnels\n",
"PATH_COMP_FLOWS = \"s3://projet-bdc-data/carmignac/Data Modélisation/competitors/daily_estimated_flows.csv\"\n",
"PATH_COMP_PERF = \"s3://projet-bdc-data/carmignac/Data Modélisation/competitors/weekly_perf_full.csv\"\n",
"PATH_PEERS = \"s3://projet-bdc-carmignac-g3/peers/CAD_peers.csv\"\n",
"\n",
"\n",
"PATH_CARMIGNAC_PERF = None\n",
"ADDITIONAL_PERF_PATHS = []"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "85f76368-fd8f-42fb-bb76-76e957bc221b",
"metadata": {},
"outputs": [
{
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" <th>1088396</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Equity</td>\n",
" <td>Tech Solutions</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Tech Solutions</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>LU2809794220</td>\n",
" <td>2025-10-31</td>\n",
" <td>31469.523</td>\n",
" <td>4.438147e+06</td>\n",
" <td>4.438147e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088397</th>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Equity</td>\n",
" <td>Tech Solutions</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Tech Solutions</td>\n",
" <td>F</td>\n",
" <td>EUR</td>\n",
" <td>LU2809794576</td>\n",
" <td>2025-10-31</td>\n",
" <td>554.301</td>\n",
" <td>7.871629e+04</td>\n",
" <td>7.871629e+04</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID reg_used Agreement - Code \\\n",
"1088396 Private Client Private Client Private Client \n",
"1088397 Private Client Private Client Private Client \n",
"\n",
" Company - Id Company - Ultimate Parent Id \\\n",
"1088396 Private Client Private Client \n",
"1088397 Private Client Private Client \n",
"\n",
" Registrar Account - Region RegistrarAccount - Country \\\n",
"1088396 France France \n",
"1088397 France France \n",
"\n",
" Product - Asset Type Product - Strategy Product - Legal Status \\\n",
"1088396 Equity Tech Solutions SICAV \n",
"1088397 Equity Tech Solutions SICAV \n",
"\n",
" Product - Is Dedie ? Product - Fund \\\n",
"1088396 NO Carmignac Portfolio Tech Solutions \n",
"1088397 NO Carmignac Portfolio Tech Solutions \n",
"\n",
" Product - Shareclass Type Product - Shareclass Currency \\\n",
"1088396 A EUR \n",
"1088397 F EUR \n",
"\n",
" Product - Isin Centralisation Date Quantity - AUM Value - AUM CCY \\\n",
"1088396 LU2809794220 2025-10-31 31469.523 4.438147e+06 \n",
"1088397 LU2809794576 2025-10-31 554.301 7.871629e+04 \n",
"\n",
" Value - AUM € \n",
"1088396 4.438147e+06 \n",
"1088397 7.871629e+04 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_aum.columns #reg_orig comme cle de donnee\n",
"df_aum = df_aum.rename(columns={\"reg_orig\": \"Registrar Account - ID\"})\n",
"df_aum.tail(2)"
]
},
{
"cell_type": "markdown",
"id": "da4bd8b3",
"metadata": {},
"source": [
"## 3. Fonctions utilitaires"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "929b77fb",
"metadata": {},
"outputs": [],
"source": [
"def first_existing_col(df, candidates):\n",
" if df is None:\n",
" return None\n",
" for c in candidates:\n",
" if c in df.columns:\n",
" return c\n",
" return None\n",
"\n",
"def normalize_month(s):\n",
" return pd.to_datetime(s, errors=\"coerce\").dt.to_period(\"M\").dt.to_timestamp()\n",
"\n",
"def robust_entropy(weights):\n",
" arr = np.asarray(weights, dtype=float)\n",
" arr = arr[np.isfinite(arr)]\n",
" arr = arr[arr > 0]\n",
" if len(arr) == 0:\n",
" return np.nan\n",
" p = arr / arr.sum()\n",
" return -(p * np.log(p + EPS)).sum()\n",
"\n",
"def herfindahl(weights):\n",
" arr = np.asarray(weights, dtype=float)\n",
" arr = arr[np.isfinite(arr)]\n",
" arr = arr[arr > 0]\n",
" if len(arr) == 0:\n",
" return np.nan\n",
" p = arr / arr.sum()\n",
" return np.sum(p ** 2)\n",
"\n",
"def compute_trend(y):\n",
" y = np.asarray(y, dtype=float)\n",
" if len(y) < 4:\n",
" return np.nan\n",
" x = np.arange(len(y)).reshape(-1, 1)\n",
" mask = np.isfinite(y)\n",
" if mask.sum() < 4:\n",
" return np.nan\n",
" reg = LinearRegression().fit(x[mask], y[mask])\n",
" return float(reg.coef_[0])\n",
"\n",
"def compute_beta(y, x):\n",
" y = np.asarray(y, dtype=float)\n",
" x = np.asarray(x, dtype=float)\n",
" mask = np.isfinite(y) & np.isfinite(x)\n",
" if mask.sum() < 4:\n",
" return np.nan\n",
" xv = x[mask].reshape(-1, 1)\n",
" reg = LinearRegression().fit(xv, y[mask])\n",
" return float(reg.coef_[0])\n",
"\n",
"def compute_corr(x, y):\n",
" x = pd.Series(x, dtype=float)\n",
" y = pd.Series(y, dtype=float)\n",
" ok = x.notna() & y.notna()\n",
" if ok.sum() < 4:\n",
" return np.nan\n",
" return x[ok].corr(y[ok])\n",
"\n",
"def safe_div(a, b):\n",
" return a / (b + EPS)\n",
"\n",
"\n",
"def adaptive_floor(values, q=0.10, min_floor=1.0):\n",
" s = pd.to_numeric(pd.Series(values), errors=\"coerce\")\n",
" s = s[np.isfinite(s) & (s > 0)]\n",
" if len(s) == 0:\n",
" return float(min_floor)\n",
" return float(max(s.quantile(q), min_floor))\n",
"\n",
"def cluster_balance_summary(labels):\n",
" vc = pd.Series(labels).value_counts().sort_index()\n",
" n = int(vc.sum())\n",
" return {\n",
" \"n_clusters\": int(len(vc)),\n",
" \"min_cluster_size\": int(vc.min()),\n",
" \"max_cluster_size\": int(vc.max()),\n",
" \"dominant_cluster_share\": float(vc.max() / n) if n > 0 else np.nan,\n",
" \"singleton_clusters\": int((vc == 1).sum()),\n",
" }\n",
"\n",
"def diagnose_small_cluster_drivers(df, feature_cols, label_col=\"cluster_fund\", top_n=15):\n",
" if df is None or df.empty or label_col not in df.columns:\n",
" return pd.DataFrame()\n",
" vc = df[label_col].value_counts()\n",
" if vc.empty:\n",
" return pd.DataFrame()\n",
" small_cluster = vc.idxmin()\n",
" mask_small = df[label_col] == small_cluster\n",
" rows = []\n",
" for col in feature_cols:\n",
" if col not in df.columns:\n",
" continue\n",
" s = pd.to_numeric(df[col], errors=\"coerce\")\n",
" if s.notna().sum() < 4:\n",
" continue\n",
" small_med = s[mask_small].median()\n",
" rest_med = s[~mask_small].median()\n",
" q25 = s.quantile(0.25)\n",
" q75 = s.quantile(0.75)\n",
" iqr = q75 - q25\n",
" scale = iqr if pd.notna(iqr) and iqr > 0 else s.std()\n",
" if pd.isna(scale) or scale <= 0:\n",
" scale = 1.0\n",
" robust_gap = abs(small_med - rest_med) / (scale + EPS)\n",
" rows.append({\n",
" \"feature\": col,\n",
" \"small_cluster_label\": small_cluster,\n",
" \"small_cluster_size\": int(mask_small.sum()),\n",
" \"small_cluster_median\": small_med,\n",
" \"rest_median\": rest_med,\n",
" \"abs_gap\": abs(small_med - rest_med),\n",
" \"robust_gap_iqr\": robust_gap,\n",
" \"q99\": s.quantile(0.99),\n",
" \"max\": s.max(),\n",
" })\n",
" out = pd.DataFrame(rows)\n",
" if out.empty:\n",
" return out\n",
" return out.sort_values([\"robust_gap_iqr\", \"abs_gap\"], ascending=False).head(top_n).reset_index(drop=True)\n",
"\n",
"def add_reading_comment(diag_df):\n",
" if diag_df is None or diag_df.empty:\n",
" print(\"Aucun diagnostic disponible.\")\n",
" return\n",
" msg = []\n",
" if \"min_cluster_size\" in diag_df.columns:\n",
" min_min = pd.to_numeric(diag_df[\"min_cluster_size\"], errors=\"coerce\").min()\n",
" if pd.notna(min_min) and min_min <= 1:\n",
" msg.append(\"- Des singletons apparaissent : le clustering isole au moins un client extrême.\")\n",
" if {\"max_cluster_size\", \"n_clusters\"}.issubset(diag_df.columns):\n",
" pass\n",
" if \"dominant_cluster_share\" in diag_df.columns:\n",
" dom = pd.to_numeric(diag_df[\"dominant_cluster_share\"], errors=\"coerce\").max()\n",
" if pd.notna(dom) and dom > 0.8:\n",
" msg.append(\"- Un cluster domine très largement la population : la séparation est surtout masse principale vs outliers.\")\n",
" if \"silhouette\" in diag_df.columns:\n",
" sil = pd.to_numeric(diag_df[\"silhouette\"], errors=\"coerce\").max()\n",
" if pd.notna(sil) and sil > 0.9:\n",
" msg.append(\"- Une silhouette très élevée avec des singletons est souvent artificielle : elle récompense l'isolement d'outliers plus qu'une segmentation métier riche.\")\n",
" if not msg:\n",
" msg.append(\"- Les métriques ne signalent pas de déséquilibre extrême évident.\")\n",
" print(\"\\n\".join(msg))\n"
]
},
{
"cell_type": "markdown",
"id": "5479d218",
"metadata": {},
"source": [
"## 4. Chargement des données"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "26ba7a06",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"flows: (2574461, 24)\n",
"aum: (1088398, 19)\n",
"nav: (623914, 5)\n",
"rates: (2826, 2)\n",
"comp_perf: (2370192, 5)\n",
"peers: (31, 12)\n",
"perf_carm: None\n"
]
}
],
"source": [
"df_flows = pd.read_csv(PATH_FLOWS, sep=\";\")\n",
"df_nav = pd.read_csv(PATH_NAV, sep=\";\")\n",
"df_rates = pd.read_csv(PATH_RATES, sep=\";\")\n",
"\n",
"df_comp_flows = pd.read_csv(PATH_COMP_FLOWS, sep=\";\")\n",
"df_comp_perf = pd.read_csv(PATH_COMP_PERF, sep=\";\")\n",
"\n",
"# parfois le fichier peers est séparé par |\n",
"df_peers = pd.read_csv(PATH_PEERS, sep=\"|\")\n",
"if df_peers is None:\n",
" df_peers = pd.read_csv(PATH_PEERS, sep=\";\")\n",
"\n",
"df_perf_carm = pd.read_csv(PATH_CARMIGNAC_PERF, sep=\";\") if PATH_CARMIGNAC_PERF else None\n",
"\n",
"extra_perf = []\n",
"for p in ADDITIONAL_PERF_PATHS:\n",
" df_tmp = pd.read_csv(p, sep=\";\")\n",
" if df_tmp is not None:\n",
" extra_perf.append(df_tmp)\n",
"\n",
"print(\"flows:\", None if df_flows is None else df_flows.shape)\n",
"print(\"aum:\", None if df_aum is None else df_aum.shape)\n",
"print(\"nav:\", None if df_nav is None else df_nav.shape)\n",
"print(\"rates:\", None if df_rates is None else df_rates.shape)\n",
"print(\"comp_perf:\", None if df_comp_perf is None else df_comp_perf.shape)\n",
"print(\"peers:\", None if df_peers is None else df_peers.shape)\n",
"print(\"perf_carm:\", None if df_perf_carm is None else df_perf_carm.shape)"
]
},
{
"cell_type": "markdown",
"id": "c6890a35",
"metadata": {},
"source": [
"## 5. Définition des colonnes-clés"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "b9ad4a32",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'ID_COL': 'Registrar Account - ID',\n",
" 'ISIN_COL': 'Product - Isin',\n",
" 'FLOW_DATE_COL': 'Centralisation Date',\n",
" 'AUM_DATE_COL': 'Centralisation Date',\n",
" 'NAV_DATE_COL': 'Dat',\n",
" 'NAV_ISIN_COL': 'Isin',\n",
" 'NAV_PRICE_COL': 'Price (TF PartPrice)',\n",
" 'RATE_DATE_COL': 'Date',\n",
" 'RATE_VAL_COL': 'Yld to Maturity',\n",
" 'REGION_COL': 'Registrar Account - Region',\n",
" 'COUNTRY_COL': 'RegistrarAccount - Country'}"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ID_COL = \"Registrar Account - ID\"\n",
"ISIN_COL = \"Product - Isin\"\n",
"\n",
"FLOW_DATE_COL = \"Centralisation Date\"\n",
"AUM_DATE_COL = \"Centralisation Date\"\n",
"\n",
"FLOW_QTY_COL = \"Quantity - NetFlows\"\n",
"FLOW_SUB_COL = \"Quantity - Subscription\"\n",
"FLOW_RED_COL = \"Quantity - Redemption\"\n",
"\n",
"AUM_QTY_COL = \"Quantity - AUM\"\n",
"AUM_VAL_COL = \"Value - AUM €\"\n",
"\n",
"REGION_COL = \"Registrar Account - Region\"\n",
"COUNTRY_COL = \"RegistrarAccount - Country\"\n",
"\n",
"NAV_DATE_COL = \"Dat\"\n",
"NAV_ISIN_COL = \"Isin\"\n",
"NAV_PRICE_COL = \"Price (TF PartPrice)\"\n",
"NAV_BENCH_COL = \"PriceBench\"\n",
"\n",
"RATE_DATE_COL = \"Date\"\n",
"RATE_VAL_COL = \"Yld to Maturity\"\n",
"\n",
"display({\n",
" \"ID_COL\": ID_COL,\n",
" \"ISIN_COL\": ISIN_COL,\n",
" \"FLOW_DATE_COL\": FLOW_DATE_COL,\n",
" \"AUM_DATE_COL\": AUM_DATE_COL,\n",
" \"NAV_DATE_COL\": NAV_DATE_COL,\n",
" \"NAV_ISIN_COL\": NAV_ISIN_COL,\n",
" \"NAV_PRICE_COL\": NAV_PRICE_COL,\n",
" \"RATE_DATE_COL\": RATE_DATE_COL,\n",
" \"RATE_VAL_COL\": RATE_VAL_COL,\n",
" \"REGION_COL\": REGION_COL,\n",
" \"COUNTRY_COL\": COUNTRY_COL,\n",
"})"
]
},
{
"cell_type": "markdown",
"id": "901bed00",
"metadata": {},
"source": [
"## 6. Préparation des dates et types"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "68a2e8e2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Agreement - Code</th>\n",
" <th>Company - Id</th>\n",
" <th>Company - Ultimate Parent Id</th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" <th>Product - Asset Type</th>\n",
" <th>Product - Strategy</th>\n",
" <th>Product - Legal Status</th>\n",
" <th>Product - Is Dedie ?</th>\n",
" <th>Product - Fund</th>\n",
" <th>Product - Shareclass Type</th>\n",
" <th>Product - Shareclass Currency</th>\n",
" <th>Product - Isin</th>\n",
" <th>Centralisation Date</th>\n",
" <th>Quantity - Subscription</th>\n",
" <th>Quantity - Redemption</th>\n",
" <th>Quantity - NetFlows</th>\n",
" <th>Value Ccy - Subscription</th>\n",
" <th>Value Ccy - Redemption</th>\n",
" <th>Value Ccy - NetFlows</th>\n",
" <th>Value € - Subscription</th>\n",
" <th>Value € - Redemption</th>\n",
" <th>Value € - NetFlows</th>\n",
" <th>month</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>003</td>\n",
" <td>166</td>\n",
" <td>166</td>\n",
" <td>200127202</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Equity</td>\n",
" <td>Investissement</td>\n",
" <td>SICAV</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Portfolio Investissement</td>\n",
" <td>F</td>\n",
" <td>EUR</td>\n",
" <td>LU0992625839</td>\n",
" <td>2020-11-05</td>\n",
" <td>1636.00</td>\n",
" <td>0.0</td>\n",
" <td>1636.00</td>\n",
" <td>280983.00</td>\n",
" <td>0.0</td>\n",
" <td>280983.00</td>\n",
" <td>280983.00</td>\n",
" <td>0.0</td>\n",
" <td>280983.00</td>\n",
" <td>2020-11-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>003</td>\n",
" <td>166</td>\n",
" <td>166</td>\n",
" <td>406533</td>\n",
" <td>France</td>\n",
" <td>France</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-09</td>\n",
" <td>144.69</td>\n",
" <td>0.0</td>\n",
" <td>144.69</td>\n",
" <td>99985.13</td>\n",
" <td>0.0</td>\n",
" <td>99985.13</td>\n",
" <td>99985.13</td>\n",
" <td>0.0</td>\n",
" <td>99985.13</td>\n",
" <td>2015-03-01</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Agreement - Code Company - Id Company - Ultimate Parent Id \\\n",
"0 003 166 166 \n",
"1 003 166 166 \n",
"\n",
" Registrar Account - ID Registrar Account - Region \\\n",
"0 200127202 France \n",
"1 406533 France \n",
"\n",
" RegistrarAccount - Country Product - Asset Type Product - Strategy \\\n",
"0 France Equity Investissement \n",
"1 France Diversified Patrimoine \n",
"\n",
" Product - Legal Status Product - Is Dedie ? \\\n",
"0 SICAV NO \n",
"1 FCP NO \n",
"\n",
" Product - Fund Product - Shareclass Type \\\n",
"0 Carmignac Portfolio Investissement F \n",
"1 Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency Product - Isin Centralisation Date \\\n",
"0 EUR LU0992625839 2020-11-05 \n",
"1 EUR FR0010135103 2015-03-09 \n",
"\n",
" Quantity - Subscription Quantity - Redemption Quantity - NetFlows \\\n",
"0 1636.00 0.0 1636.00 \n",
"1 144.69 0.0 144.69 \n",
"\n",
" Value Ccy - Subscription Value Ccy - Redemption Value Ccy - NetFlows \\\n",
"0 280983.00 0.0 280983.00 \n",
"1 99985.13 0.0 99985.13 \n",
"\n",
" Value € - Subscription Value € - Redemption Value € - NetFlows month \n",
"0 280983.00 0.0 280983.00 2020-11-01 \n",
"1 99985.13 0.0 99985.13 2015-03-01 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>reg_used</th>\n",
" <th>Agreement - Code</th>\n",
" <th>Company - Id</th>\n",
" <th>Company - Ultimate Parent Id</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" <th>Product - Asset Type</th>\n",
" <th>Product - Strategy</th>\n",
" <th>Product - Legal Status</th>\n",
" <th>Product - Is Dedie ?</th>\n",
" <th>Product - Fund</th>\n",
" <th>Product - Shareclass Type</th>\n",
" <th>Product - Shareclass Currency</th>\n",
" <th>Product - Isin</th>\n",
" <th>Centralisation Date</th>\n",
" <th>Quantity - AUM</th>\n",
" <th>Value - AUM CCY</th>\n",
" <th>Value - AUM €</th>\n",
" <th>month</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-31</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>3.242523e+07</td>\n",
" <td>2015-01-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>18872</td>\n",
" <td>L104</td>\n",
" <td>2257.0</td>\n",
" <td>33675.0</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>Equity</td>\n",
" <td>Investissement Latitude</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Investissement Latitude</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>FR0010147603</td>\n",
" <td>2015-01-31</td>\n",
" <td>1717.000</td>\n",
" <td>4.767422e+05</td>\n",
" <td>4.767422e+05</td>\n",
" <td>2015-01-01</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID reg_used Agreement - Code Company - Id \\\n",
"0 18872 18872 L104 2257.0 \n",
"1 18872 18872 L104 2257.0 \n",
"\n",
" Company - Ultimate Parent Id Registrar Account - Region \\\n",
"0 33675.0 Switzerland \n",
"1 33675.0 Switzerland \n",
"\n",
" RegistrarAccount - Country Product - Asset Type Product - Strategy \\\n",
"0 Switzerland Diversified Patrimoine \n",
"1 Switzerland Equity Investissement Latitude \n",
"\n",
" Product - Legal Status Product - Is Dedie ? \\\n",
"0 FCP NO \n",
"1 FCP NO \n",
"\n",
" Product - Fund Product - Shareclass Type \\\n",
"0 Carmignac Patrimoine A \n",
"1 Carmignac Investissement Latitude A \n",
"\n",
" Product - Shareclass Currency Product - Isin Centralisation Date \\\n",
"0 EUR FR0010135103 2015-01-31 \n",
"1 EUR FR0010147603 2015-01-31 \n",
"\n",
" Quantity - AUM Value - AUM CCY Value - AUM € month \n",
"0 49094.915 3.242523e+07 3.242523e+07 2015-01-01 \n",
"1 1717.000 4.767422e+05 4.767422e+05 2015-01-01 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"for df, date_col in [\n",
" (df_flows, FLOW_DATE_COL),\n",
" (df_aum, AUM_DATE_COL),\n",
" (df_nav, NAV_DATE_COL),\n",
" (df_rates, RATE_DATE_COL),\n",
"]:\n",
" if df is not None and date_col is not None and date_col in df.columns:\n",
" df[date_col] = pd.to_datetime(df[date_col], errors=\"coerce\")\n",
" df[\"month\"] = df[date_col].dt.to_period(\"M\").dt.to_timestamp()\n",
"\n",
"for df in [df_flows, df_aum]:\n",
" if df is not None:\n",
" df[ID_COL] = df[ID_COL].astype(str).str.strip()\n",
" df[ISIN_COL] = df[ISIN_COL].astype(str).str.strip()\n",
"\n",
"if df_nav is not None and NAV_ISIN_COL is not None:\n",
" df_nav[NAV_ISIN_COL] = df_nav[NAV_ISIN_COL].astype(str).str.strip()\n",
"\n",
"display(df_flows.head(2))\n",
"display(df_aum.head(2))"
]
},
{
"cell_type": "markdown",
"id": "8b073eb2",
"metadata": {},
"source": [
"## 7. Sélection des 400+ gros comptes au 31/10/2025\n",
"\n",
"Conforme aux messages Carmignac :\n",
"- on travaille à la date de référence **31/10/2025**\n",
"- on exclut **Off Distribution** et **Private Clients**\n",
"- on garde les comptes avec **AUM total ≥ 5 M€**"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "049f4a35-5769-48db-8148-f057dddfbc44",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Registrar Account - ID', 'reg_used', 'Agreement - Code',\n",
" 'Company - Id', 'Company - Ultimate Parent Id',\n",
" 'Registrar Account - Region', 'RegistrarAccount - Country',\n",
" 'Product - Asset Type', 'Product - Strategy', 'Product - Legal Status',\n",
" 'Product - Is Dedie ?', 'Product - Fund', 'Product - Shareclass Type',\n",
" 'Product - Shareclass Currency', 'Product - Isin',\n",
" 'Centralisation Date', 'Quantity - AUM', 'Value - AUM CCY',\n",
" 'Value - AUM €', 'month'],\n",
" dtype='object')"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_aum.columns"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "bb71018b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nombre de comptes >= 5M€ : 432\n",
"Couverture encours : 100.0 %\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>aum_qty_total</th>\n",
" <th>aum_val_total</th>\n",
" <th>weight_31102025</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>419</th>\n",
" <td>420350</td>\n",
" <td>2626183.491</td>\n",
" <td>1.623308e+09</td>\n",
" <td>0.047517</td>\n",
" </tr>\n",
" <tr>\n",
" <th>355</th>\n",
" <td>364765</td>\n",
" <td>6715556.496</td>\n",
" <td>1.383209e+09</td>\n",
" <td>0.040489</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160</th>\n",
" <td>200127454</td>\n",
" <td>4513772.201</td>\n",
" <td>8.784361e+08</td>\n",
" <td>0.025713</td>\n",
" </tr>\n",
" <tr>\n",
" <th>352</th>\n",
" <td>312933</td>\n",
" <td>2728411.596</td>\n",
" <td>8.379604e+08</td>\n",
" <td>0.024529</td>\n",
" </tr>\n",
" <tr>\n",
" <th>200</th>\n",
" <td>200127809</td>\n",
" <td>3473162.647</td>\n",
" <td>8.342839e+08</td>\n",
" <td>0.024421</td>\n",
" </tr>\n",
" <tr>\n",
" <th>418</th>\n",
" <td>420259</td>\n",
" <td>3600860.888</td>\n",
" <td>8.296663e+08</td>\n",
" <td>0.024286</td>\n",
" </tr>\n",
" <tr>\n",
" <th>357</th>\n",
" <td>364907</td>\n",
" <td>2794302.254</td>\n",
" <td>8.151083e+08</td>\n",
" <td>0.023860</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>366441</td>\n",
" <td>1944206.261</td>\n",
" <td>7.707213e+08</td>\n",
" <td>0.022560</td>\n",
" </tr>\n",
" <tr>\n",
" <th>358</th>\n",
" <td>364929</td>\n",
" <td>2135207.537</td>\n",
" <td>7.479766e+08</td>\n",
" <td>0.021895</td>\n",
" </tr>\n",
" <tr>\n",
" <th>381</th>\n",
" <td>365538</td>\n",
" <td>2695348.456</td>\n",
" <td>7.200408e+08</td>\n",
" <td>0.021077</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID aum_qty_total aum_val_total weight_31102025\n",
"419 420350 2626183.491 1.623308e+09 0.047517\n",
"355 364765 6715556.496 1.383209e+09 0.040489\n",
"160 200127454 4513772.201 8.784361e+08 0.025713\n",
"352 312933 2728411.596 8.379604e+08 0.024529\n",
"200 200127809 3473162.647 8.342839e+08 0.024421\n",
"418 420259 3600860.888 8.296663e+08 0.024286\n",
"357 364907 2794302.254 8.151083e+08 0.023860\n",
"400 366441 1944206.261 7.707213e+08 0.022560\n",
"358 364929 2135207.537 7.479766e+08 0.021895\n",
"381 365538 2695348.456 7.200408e+08 0.021077"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"TARGET_DATE = pd.Timestamp(\"2025-10-01\")\n",
"EXCLUDED_IDS = [\"Off Distribution\", \"Private Clients\"]\n",
"AUM_THRESHOLD_EUR = 5_000_000\n",
"\n",
"df_top_accounts = (\n",
" df_aum[\n",
" (df_aum[\"month\"] == TARGET_DATE) &\n",
" (~df_aum[ID_COL].isin(EXCLUDED_IDS))\n",
" ]\n",
" .groupby(ID_COL, as_index=False)\n",
" .agg(\n",
" aum_qty_total=(AUM_QTY_COL, \"sum\"),\n",
" aum_val_total=(AUM_VAL_COL, \"sum\"),\n",
" )\n",
" .sort_values(\"aum_val_total\", ascending=False)\n",
")\n",
"\n",
"df_top_accounts[\"weight_31102025\"] = df_top_accounts[\"aum_val_total\"] / df_top_accounts[\"aum_val_total\"].sum()\n",
"\n",
"top_accounts = df_top_accounts[df_top_accounts[\"aum_val_total\"] >= AUM_THRESHOLD_EUR].copy()\n",
"TOP_IDS = set(top_accounts[ID_COL].tolist())\n",
"\n",
"print(\"Nombre de comptes >= 5M€ :\", len(TOP_IDS))\n",
"print(\"Couverture encours :\", round(top_accounts[\"aum_val_total\"].sum() / df_top_accounts[\"aum_val_total\"].sum() * 100, 2), \"%\")\n",
"display(top_accounts.head(10))"
]
},
{
"cell_type": "markdown",
"id": "06fcabb4",
"metadata": {},
"source": [
"## 8. Filtrage des données sur les 400+ gros comptes"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "98e51fed",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"df_flows: (1501724, 25)\n",
"df_aum: (1088398, 20)\n",
"Nb comptes flows: 427\n",
"Nb comptes aum: 432\n"
]
}
],
"source": [
"\n",
"df_flows = df_flows[df_flows[ID_COL].isin(TOP_IDS)].copy()\n",
"df_aum = df_aum[df_aum[ID_COL].isin(TOP_IDS)].copy()\n",
"\n",
"print(\"df_flows:\", df_flows.shape)\n",
"print(\"df_aum:\", df_aum.shape)\n",
"print(\"Nb comptes flows:\", df_flows[ID_COL].nunique())\n",
"print(\"Nb comptes aum:\", df_aum[ID_COL].nunique())"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "cdfa3b92-286c-40c3-aac8-f7972be9d5ca",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nb comptes AUM : 432\n",
"Nb comptes flows : 427\n",
"Intersection : 427\n",
"AUM seulement : 5\n",
"Flows seulement : 0\n",
"Exemples AUM seulement : ['200142554', '200139346', '200131477', '200127798', '200130743']\n",
"Exemples Flows seulement : []\n"
]
}
],
"source": [
"aum_ids = set(df_aum[\"Registrar Account - ID\"].dropna().unique())\n",
"flow_ids = set(df_flows[\"Registrar Account - ID\"].dropna().unique())\n",
"\n",
"print(\"Nb comptes AUM :\", len(aum_ids))\n",
"print(\"Nb comptes flows :\", len(flow_ids))\n",
"print(\"Intersection :\", len(aum_ids & flow_ids))\n",
"print(\"AUM seulement :\", len(aum_ids - flow_ids))\n",
"print(\"Flows seulement :\", len(flow_ids - aum_ids))\n",
"\n",
"print(\"Exemples AUM seulement :\", list(aum_ids - flow_ids)[:10])\n",
"print(\"Exemples Flows seulement :\", list(flow_ids - aum_ids)[:10])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "fefe8a12-a98f-4220-bfbe-c0f2cd6d4ff2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"df_flows columns: Index(['Agreement - Code', 'Company - Id', 'Company - Ultimate Parent Id',\n",
" 'Registrar Account - ID', 'Registrar Account - Region',\n",
" 'RegistrarAccount - Country', 'Product - Asset Type',\n",
" 'Product - Strategy', 'Product - Legal Status', 'Product - Is Dedie ?',\n",
" 'Product - Fund', 'Product - Shareclass Type',\n",
" 'Product - Shareclass Currency', 'Product - Isin',\n",
" 'Centralisation Date', 'Quantity - Subscription',\n",
" 'Quantity - Redemption', 'Quantity - NetFlows',\n",
" 'Value Ccy - Subscription', 'Value Ccy - Redemption',\n",
" 'Value Ccy - NetFlows', 'Value € - Subscription',\n",
" 'Value € - Redemption', 'Value € - NetFlows', 'month'],\n",
" dtype='object')\n",
"df_aum columns: Index(['Registrar Account - ID', 'reg_used', 'Agreement - Code',\n",
" 'Company - Id', 'Company - Ultimate Parent Id',\n",
" 'Registrar Account - Region', 'RegistrarAccount - Country',\n",
" 'Product - Asset Type', 'Product - Strategy', 'Product - Legal Status',\n",
" 'Product - Is Dedie ?', 'Product - Fund', 'Product - Shareclass Type',\n",
" 'Product - Shareclass Currency', 'Product - Isin',\n",
" 'Centralisation Date', 'Quantity - AUM', 'Value - AUM CCY',\n",
" 'Value - AUM €', 'month'],\n",
" dtype='object')\n"
]
}
],
"source": [
"print(\"df_flows columns:\", df_flows.columns)\n",
"print(\"df_aum columns:\", df_aum.columns)"
]
},
{
"cell_type": "markdown",
"id": "94d7c460",
"metadata": {},
"source": [
"## 9. Base fine mensuelle flows : `client × ISIN × month`"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "4ac20a75-bf00-4f61-b0ec-d1c18d4fa665",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>column</th>\n",
" <th>n_groups_observed</th>\n",
" <th>pct_groups_1_value</th>\n",
" <th>pct_groups_gt1_value</th>\n",
" <th>max_n_unique</th>\n",
" <th>mean_n_unique</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Centralisation Date</td>\n",
" <td>275762</td>\n",
" <td>0.323591</td>\n",
" <td>0.676409</td>\n",
" <td>23</td>\n",
" <td>5.443382</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Value € - NetFlows</td>\n",
" <td>275762</td>\n",
" <td>0.323888</td>\n",
" <td>0.676112</td>\n",
" <td>37</td>\n",
" <td>5.435386</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Value Ccy - NetFlows</td>\n",
" <td>275762</td>\n",
" <td>0.323902</td>\n",
" <td>0.676098</td>\n",
" <td>37</td>\n",
" <td>5.435190</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Quantity - NetFlows</td>\n",
" <td>275762</td>\n",
" <td>0.325879</td>\n",
" <td>0.674121</td>\n",
" <td>37</td>\n",
" <td>5.361130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Value € - Redemption</td>\n",
" <td>275762</td>\n",
" <td>0.409785</td>\n",
" <td>0.590215</td>\n",
" <td>34</td>\n",
" <td>4.152294</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Value Ccy - Redemption</td>\n",
" <td>275762</td>\n",
" <td>0.409788</td>\n",
" <td>0.590212</td>\n",
" <td>34</td>\n",
" <td>4.152120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Quantity - Redemption</td>\n",
" <td>275762</td>\n",
" <td>0.410916</td>\n",
" <td>0.589084</td>\n",
" <td>34</td>\n",
" <td>4.090861</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Value € - Subscription</td>\n",
" <td>275762</td>\n",
" <td>0.443324</td>\n",
" <td>0.556676</td>\n",
" <td>31</td>\n",
" <td>3.716030</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Value Ccy - Subscription</td>\n",
" <td>275762</td>\n",
" <td>0.443335</td>\n",
" <td>0.556665</td>\n",
" <td>31</td>\n",
" <td>3.715904</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Quantity - Subscription</td>\n",
" <td>275762</td>\n",
" <td>0.444307</td>\n",
" <td>0.555693</td>\n",
" <td>30</td>\n",
" <td>3.667652</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Company - Id</td>\n",
" <td>275440</td>\n",
" <td>0.615590</td>\n",
" <td>0.384410</td>\n",
" <td>3</td>\n",
" <td>1.384432</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Company - Ultimate Parent Id</td>\n",
" <td>275440</td>\n",
" <td>0.615600</td>\n",
" <td>0.384400</td>\n",
" <td>2</td>\n",
" <td>1.384400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Registrar Account - Region</td>\n",
" <td>275762</td>\n",
" <td>0.999307</td>\n",
" <td>0.000693</td>\n",
" <td>2</td>\n",
" <td>1.000693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>RegistrarAccount - Country</td>\n",
" <td>275762</td>\n",
" <td>0.999307</td>\n",
" <td>0.000693</td>\n",
" <td>2</td>\n",
" <td>1.000693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Agreement - Code</td>\n",
" <td>275762</td>\n",
" <td>0.999888</td>\n",
" <td>0.000112</td>\n",
" <td>2</td>\n",
" <td>1.000112</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Product - Asset Type</td>\n",
" <td>275529</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Product - Strategy</td>\n",
" <td>275761</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Product - Legal Status</td>\n",
" <td>275762</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Product - Is Dedie ?</td>\n",
" <td>275762</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Product - Fund</td>\n",
" <td>275762</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>Product - Shareclass Type</td>\n",
" <td>275762</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>Product - Shareclass Currency</td>\n",
" <td>275762</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" column n_groups_observed pct_groups_1_value \\\n",
"0 Centralisation Date 275762 0.323591 \n",
"1 Value € - NetFlows 275762 0.323888 \n",
"2 Value Ccy - NetFlows 275762 0.323902 \n",
"3 Quantity - NetFlows 275762 0.325879 \n",
"4 Value € - Redemption 275762 0.409785 \n",
"5 Value Ccy - Redemption 275762 0.409788 \n",
"6 Quantity - Redemption 275762 0.410916 \n",
"7 Value € - Subscription 275762 0.443324 \n",
"8 Value Ccy - Subscription 275762 0.443335 \n",
"9 Quantity - Subscription 275762 0.444307 \n",
"10 Company - Id 275440 0.615590 \n",
"11 Company - Ultimate Parent Id 275440 0.615600 \n",
"12 Registrar Account - Region 275762 0.999307 \n",
"13 RegistrarAccount - Country 275762 0.999307 \n",
"14 Agreement - Code 275762 0.999888 \n",
"15 Product - Asset Type 275529 1.000000 \n",
"16 Product - Strategy 275761 1.000000 \n",
"17 Product - Legal Status 275762 1.000000 \n",
"18 Product - Is Dedie ? 275762 1.000000 \n",
"19 Product - Fund 275762 1.000000 \n",
"20 Product - Shareclass Type 275762 1.000000 \n",
"21 Product - Shareclass Currency 275762 1.000000 \n",
"\n",
" pct_groups_gt1_value max_n_unique mean_n_unique \n",
"0 0.676409 23 5.443382 \n",
"1 0.676112 37 5.435386 \n",
"2 0.676098 37 5.435190 \n",
"3 0.674121 37 5.361130 \n",
"4 0.590215 34 4.152294 \n",
"5 0.590212 34 4.152120 \n",
"6 0.589084 34 4.090861 \n",
"7 0.556676 31 3.716030 \n",
"8 0.556665 31 3.715904 \n",
"9 0.555693 30 3.667652 \n",
"10 0.384410 3 1.384432 \n",
"11 0.384400 2 1.384400 \n",
"12 0.000693 2 1.000693 \n",
"13 0.000693 2 1.000693 \n",
"14 0.000112 2 1.000112 \n",
"15 0.000000 1 1.000000 \n",
"16 0.000000 1 1.000000 \n",
"17 0.000000 1 1.000000 \n",
"18 0.000000 1 1.000000 \n",
"19 0.000000 1 1.000000 \n",
"20 0.000000 1 1.000000 \n",
"21 0.000000 1 1.000000 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# DIAGNOSTIC RAPIDE D'AGREGATION - DF_FLOWS\n",
"# Pour chaque colonne, on regarde combien de valeurs distinctes\n",
"#prend dans chaque groupe client x ISIN x mois\n",
"# ============================================================\n",
"\n",
"KEYS = [ID_COL, ISIN_COL, \"month\"]\n",
"df_flows_diag_base = df_flows.dropna(subset=KEYS).copy()\n",
"flow_cols_to_check = [c for c in df_flows_diag_base.columns if c not in KEYS]\n",
"flow_summary_rows = []\n",
"\n",
"for col in flow_cols_to_check:\n",
" s = df_flows_diag_base[col]\n",
" # on enlève juste les NA pour cette colonne\n",
" tmp = df_flows_diag_base.loc[s.notna(), KEYS + [col]].copy()\n",
" # optionnel : nettoyer les strings seulement si la colonne est texte\n",
" if tmp[col].dtype == \"object\":\n",
" tmp[col] = tmp[col].astype(str).str.strip()\n",
" tmp = tmp[tmp[col] != \"\"]\n",
"\n",
" # nb de valeurs distinctes dans chaque groupe\n",
" nun = tmp.groupby(KEYS)[col].nunique()\n",
" flow_summary_rows.append({\n",
" \"column\": col,\n",
" \"n_groups_observed\": int(nun.shape[0]),\n",
" \"pct_groups_1_value\": float((nun == 1).mean()) if len(nun) else np.nan,\n",
" \"pct_groups_gt1_value\": float((nun > 1).mean()) if len(nun) else np.nan,\n",
" \"max_n_unique\": int(nun.max()) if len(nun) else np.nan,\n",
" \"mean_n_unique\": float(nun.mean()) if len(nun) else np.nan,\n",
" })\n",
"\n",
"flow_agg_summary = (\n",
" pd.DataFrame(flow_summary_rows)\n",
" .sort_values([\"pct_groups_gt1_value\", \"max_n_unique\"], ascending=[False, False])\n",
" .reset_index(drop=True)\n",
")\n",
"\n",
"display(flow_agg_summary)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "8cd2d9d3-5ced-44f5-af20-7f501435a43f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>column</th>\n",
" <th>n_groups_observed</th>\n",
" <th>pct_groups_1_value</th>\n",
" <th>pct_groups_gt1_value</th>\n",
" <th>max_n_unique</th>\n",
" <th>mean_n_unique</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>RegistrarAccount - Country</td>\n",
" <td>955241</td>\n",
" <td>0.936354</td>\n",
" <td>0.063646</td>\n",
" <td>10</td>\n",
" <td>1.125696</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Registrar Account - Region</td>\n",
" <td>955241</td>\n",
" <td>0.936976</td>\n",
" <td>0.063024</td>\n",
" <td>9</td>\n",
" <td>1.115268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Quantity - AUM</td>\n",
" <td>955241</td>\n",
" <td>0.940144</td>\n",
" <td>0.059856</td>\n",
" <td>10</td>\n",
" <td>1.090657</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Value - AUM CCY</td>\n",
" <td>955241</td>\n",
" <td>0.940171</td>\n",
" <td>0.059829</td>\n",
" <td>10</td>\n",
" <td>1.090631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Value - AUM €</td>\n",
" <td>955241</td>\n",
" <td>0.940171</td>\n",
" <td>0.059829</td>\n",
" <td>10</td>\n",
" <td>1.090631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Agreement - Code</td>\n",
" <td>955241</td>\n",
" <td>0.983530</td>\n",
" <td>0.016470</td>\n",
" <td>2</td>\n",
" <td>1.016470</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Company - Id</td>\n",
" <td>954372</td>\n",
" <td>0.983682</td>\n",
" <td>0.016318</td>\n",
" <td>3</td>\n",
" <td>1.016322</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Company - Ultimate Parent Id</td>\n",
" <td>954372</td>\n",
" <td>0.984164</td>\n",
" <td>0.015836</td>\n",
" <td>3</td>\n",
" <td>1.015840</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>reg_used</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Product - Asset Type</td>\n",
" <td>934524</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Product - Strategy</td>\n",
" <td>955210</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Product - Legal Status</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Product - Is Dedie ?</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Product - Fund</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Product - Shareclass Type</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Product - Shareclass Currency</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Centralisation Date</td>\n",
" <td>955241</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" column n_groups_observed pct_groups_1_value \\\n",
"0 RegistrarAccount - Country 955241 0.936354 \n",
"1 Registrar Account - Region 955241 0.936976 \n",
"2 Quantity - AUM 955241 0.940144 \n",
"3 Value - AUM CCY 955241 0.940171 \n",
"4 Value - AUM € 955241 0.940171 \n",
"5 Agreement - Code 955241 0.983530 \n",
"6 Company - Id 954372 0.983682 \n",
"7 Company - Ultimate Parent Id 954372 0.984164 \n",
"8 reg_used 955241 1.000000 \n",
"9 Product - Asset Type 934524 1.000000 \n",
"10 Product - Strategy 955210 1.000000 \n",
"11 Product - Legal Status 955241 1.000000 \n",
"12 Product - Is Dedie ? 955241 1.000000 \n",
"13 Product - Fund 955241 1.000000 \n",
"14 Product - Shareclass Type 955241 1.000000 \n",
"15 Product - Shareclass Currency 955241 1.000000 \n",
"16 Centralisation Date 955241 1.000000 \n",
"\n",
" pct_groups_gt1_value max_n_unique mean_n_unique \n",
"0 0.063646 10 1.125696 \n",
"1 0.063024 9 1.115268 \n",
"2 0.059856 10 1.090657 \n",
"3 0.059829 10 1.090631 \n",
"4 0.059829 10 1.090631 \n",
"5 0.016470 2 1.016470 \n",
"6 0.016318 3 1.016322 \n",
"7 0.015836 3 1.015840 \n",
"8 0.000000 1 1.000000 \n",
"9 0.000000 1 1.000000 \n",
"10 0.000000 1 1.000000 \n",
"11 0.000000 1 1.000000 \n",
"12 0.000000 1 1.000000 \n",
"13 0.000000 1 1.000000 \n",
"14 0.000000 1 1.000000 \n",
"15 0.000000 1 1.000000 \n",
"16 0.000000 1 1.000000 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# DIAGNOSTIC RAPIDE D'AGREGATION - DF_AUM\n",
"# Pour chaque colonne, on regarde combien de valeurs distinctes\n",
"# prend dans chaque groupe client x ISIN x mois\n",
"# ============================================================\n",
"\n",
"KEYS = [ID_COL, ISIN_COL, \"month\"]\n",
"\n",
"df_aum_diag_base = df_aum.dropna(subset=KEYS).copy()\n",
"\n",
"aum_cols_to_check = [c for c in df_aum_diag_base.columns if c not in KEYS]\n",
"\n",
"aum_summary_rows = []\n",
"\n",
"for col in aum_cols_to_check:\n",
" s = df_aum_diag_base[col]\n",
"\n",
" # on enlève les NA pour cette colonne\n",
" tmp = df_aum_diag_base.loc[s.notna(), KEYS + [col]].copy()\n",
"\n",
" # nettoyage léger si texte\n",
" if tmp[col].dtype == \"object\":\n",
" tmp[col] = tmp[col].astype(str).str.strip()\n",
" tmp = tmp[tmp[col] != \"\"]\n",
"\n",
" # nb de valeurs distinctes dans chaque groupe\n",
" nun = tmp.groupby(KEYS)[col].nunique()\n",
"\n",
" aum_summary_rows.append({\n",
" \"column\": col,\n",
" \"n_groups_observed\": int(nun.shape[0]),\n",
" \"pct_groups_1_value\": float((nun == 1).mean()) if len(nun) else np.nan,\n",
" \"pct_groups_gt1_value\": float((nun > 1).mean()) if len(nun) else np.nan,\n",
" \"max_n_unique\": int(nun.max()) if len(nun) else np.nan,\n",
" \"mean_n_unique\": float(nun.mean()) if len(nun) else np.nan,\n",
" })\n",
"\n",
"aum_agg_summary = (\n",
" pd.DataFrame(aum_summary_rows)\n",
" .sort_values([\"pct_groups_gt1_value\", \"max_n_unique\"], ascending=[False, False])\n",
" .reset_index(drop=True)\n",
")\n",
"\n",
"display(aum_agg_summary)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bc0e24e1-162a-48e8-9486-6494e762ae26",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 16,
"id": "cba5b9bf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>net_flow_qty</th>\n",
" <th>gross_flow_qty</th>\n",
" <th>sub_qty</th>\n",
" <th>red_qty</th>\n",
" <th>n_tx</th>\n",
" <th>Product - Asset Type</th>\n",
" <th>Product - Strategy</th>\n",
" <th>Product - Legal Status</th>\n",
" <th>Product - Is Dedie ?</th>\n",
" <th>Product - Fund</th>\n",
" <th>Product - Shareclass Type</th>\n",
" <th>Product - Shareclass Currency</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-01</td>\n",
" <td>673.990</td>\n",
" <td>1045.99</td>\n",
" <td>859.990</td>\n",
" <td>-186.000</td>\n",
" <td>9</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-02-01</td>\n",
" <td>988.000</td>\n",
" <td>1712.00</td>\n",
" <td>1350.000</td>\n",
" <td>-362.000</td>\n",
" <td>12</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-01</td>\n",
" <td>9.710</td>\n",
" <td>1561.71</td>\n",
" <td>785.710</td>\n",
" <td>-776.000</td>\n",
" <td>12</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-04-01</td>\n",
" <td>-123.234</td>\n",
" <td>1830.19</td>\n",
" <td>853.478</td>\n",
" <td>-976.712</td>\n",
" <td>11</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-05-01</td>\n",
" <td>121.000</td>\n",
" <td>529.00</td>\n",
" <td>325.000</td>\n",
" <td>-204.000</td>\n",
" <td>6</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID Product - Isin month net_flow_qty \\\n",
"0 18872 FR0010135103 2015-01-01 673.990 \n",
"1 18872 FR0010135103 2015-02-01 988.000 \n",
"2 18872 FR0010135103 2015-03-01 9.710 \n",
"3 18872 FR0010135103 2015-04-01 -123.234 \n",
"4 18872 FR0010135103 2015-05-01 121.000 \n",
"\n",
" gross_flow_qty sub_qty red_qty n_tx Product - Asset Type \\\n",
"0 1045.99 859.990 -186.000 9 Diversified \n",
"1 1712.00 1350.000 -362.000 12 Diversified \n",
"2 1561.71 785.710 -776.000 12 Diversified \n",
"3 1830.19 853.478 -976.712 11 Diversified \n",
"4 529.00 325.000 -204.000 6 Diversified \n",
"\n",
" Product - Strategy Product - Legal Status Product - Is Dedie ? \\\n",
"0 Patrimoine FCP NO \n",
"1 Patrimoine FCP NO \n",
"2 Patrimoine FCP NO \n",
"3 Patrimoine FCP NO \n",
"4 Patrimoine FCP NO \n",
"\n",
" Product - Fund Product - Shareclass Type \\\n",
"0 Carmignac Patrimoine A \n",
"1 Carmignac Patrimoine A \n",
"2 Carmignac Patrimoine A \n",
"3 Carmignac Patrimoine A \n",
"4 Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency \n",
"0 EUR \n",
"1 EUR \n",
"2 EUR \n",
"3 EUR \n",
"4 EUR "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"(275762, 15)\n"
]
}
],
"source": [
"# ============================================================\n",
"# DF_FLOWS_MENSUEL : 1 client x 1 ISIN x 1 mois\n",
"# ============================================================\n",
"\n",
"KEYS = [ID_COL, ISIN_COL, \"month\"]\n",
"\n",
"df_flows_clean = df_flows.dropna(subset=KEYS).copy()\n",
"\n",
"# -------------------------\n",
"# NUMERIC FLOWS\n",
"# -------------------------\n",
"df_flows_clean[\"net_flow_qty\"] = pd.to_numeric(df_flows_clean[FLOW_QTY_COL], errors=\"coerce\").fillna(0.0)\n",
"df_flows_clean[\"sub_qty\"] = pd.to_numeric(df_flows_clean[FLOW_SUB_COL], errors=\"coerce\").fillna(0.0)\n",
"df_flows_clean[\"red_qty\"] = pd.to_numeric(df_flows_clean[FLOW_RED_COL], errors=\"coerce\").fillna(0.0)\n",
"\n",
"df_flows_clean[\"gross_flow_qty\"] = df_flows_clean[\"sub_qty\"].abs() + df_flows_clean[\"red_qty\"].abs()\n",
"\n",
"# -------------------------\n",
"# COLONNES PRODUIT STABLES\n",
"# -------------------------\n",
"product_cols = [\n",
" \"Product - Asset Type\",\n",
" \"Product - Strategy\",\n",
" \"Product - Legal Status\",\n",
" \"Product - Is Dedie ?\",\n",
" \"Product - Fund\",\n",
" \"Product - Shareclass Type\",\n",
" \"Product - Shareclass Currency\",\n",
"]\n",
"\n",
"# -------------------------\n",
"# AGGREGATION\n",
"# -------------------------\n",
"agg_dict = {\n",
" \"net_flow_qty\": (\"net_flow_qty\", \"sum\"),\n",
" \"gross_flow_qty\": (\"gross_flow_qty\", \"sum\"),\n",
" \"sub_qty\": (\"sub_qty\", \"sum\"),\n",
" \"red_qty\": (\"red_qty\", \"sum\"),\n",
" \"n_tx\": (FLOW_QTY_COL, \"size\"),\n",
"}\n",
"\n",
"# ajouter produit en \"first\"\n",
"for col in product_cols:\n",
" if col in df_flows_clean.columns:\n",
" agg_dict[col] = (col, \"first\")\n",
"\n",
"# -------------------------\n",
"# GROUPBY FINAL\n",
"# -------------------------\n",
"df_flows_m = (\n",
" df_flows_clean\n",
" .groupby(KEYS, as_index=False)\n",
" .agg(**agg_dict)\n",
")\n",
"\n",
"display(df_flows_m.head())\n",
"print(df_flows_m.shape)"
]
},
{
"cell_type": "markdown",
"id": "94621000",
"metadata": {},
"source": [
"## 10. Base fine mensuelle AUM : `client × ISIN × month`"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "b46d886b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>aum_qty</th>\n",
" <th>aum_val</th>\n",
" <th>Product - Asset Type</th>\n",
" <th>Product - Strategy</th>\n",
" <th>Product - Legal Status</th>\n",
" <th>Product - Is Dedie ?</th>\n",
" <th>Product - Fund</th>\n",
" <th>Product - Shareclass Type</th>\n",
" <th>Product - Shareclass Currency</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-01</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-02-01</td>\n",
" <td>49797.915</td>\n",
" <td>3.368032e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-01</td>\n",
" <td>50302.627</td>\n",
" <td>3.505691e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-04-01</td>\n",
" <td>50219.393</td>\n",
" <td>3.452433e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-05-01</td>\n",
" <td>53685.393</td>\n",
" <td>3.699729e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID Product - Isin month aum_qty aum_val \\\n",
"0 18872 FR0010135103 2015-01-01 49094.915 3.242523e+07 \n",
"1 18872 FR0010135103 2015-02-01 49797.915 3.368032e+07 \n",
"2 18872 FR0010135103 2015-03-01 50302.627 3.505691e+07 \n",
"3 18872 FR0010135103 2015-04-01 50219.393 3.452433e+07 \n",
"4 18872 FR0010135103 2015-05-01 53685.393 3.699729e+07 \n",
"\n",
" Product - Asset Type Product - Strategy Product - Legal Status \\\n",
"0 Diversified Patrimoine FCP \n",
"1 Diversified Patrimoine FCP \n",
"2 Diversified Patrimoine FCP \n",
"3 Diversified Patrimoine FCP \n",
"4 Diversified Patrimoine FCP \n",
"\n",
" Product - Is Dedie ? Product - Fund Product - Shareclass Type \\\n",
"0 NO Carmignac Patrimoine A \n",
"1 NO Carmignac Patrimoine A \n",
"2 NO Carmignac Patrimoine A \n",
"3 NO Carmignac Patrimoine A \n",
"4 NO Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency Registrar Account - Region \\\n",
"0 EUR Switzerland \n",
"1 EUR Switzerland \n",
"2 EUR Switzerland \n",
"3 EUR Switzerland \n",
"4 EUR Switzerland \n",
"\n",
" RegistrarAccount - Country \n",
"0 Switzerland \n",
"1 Switzerland \n",
"2 Switzerland \n",
"3 Switzerland \n",
"4 Switzerland "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"(955241, 14)\n"
]
}
],
"source": [
"# ============================================================\n",
"# DF_AUM_MENSUEL : 1 client x 1 ISIN x 1 mois\n",
"# ============================================================\n",
"\n",
"df_aum_clean = df_aum.dropna(subset=KEYS).copy()\n",
"\n",
"# conversion\n",
"df_aum_clean[\"aum_qty\"] = pd.to_numeric(df_aum_clean[AUM_QTY_COL], errors=\"coerce\")\n",
"df_aum_clean[\"aum_val\"] = pd.to_numeric(df_aum_clean[AUM_VAL_COL], errors=\"coerce\")\n",
"\n",
"# -------------------------\n",
"# AGGREGATION\n",
"# -------------------------\n",
"agg_dict_aum = {\n",
" \"aum_qty\": (\"aum_qty\", \"last\"), # très important\n",
" \"aum_val\": (\"aum_val\", \"last\"),\n",
"}\n",
"\n",
"# colonnes produit (stables)\n",
"for col in product_cols:\n",
" if col in df_aum_clean.columns:\n",
" agg_dict_aum[col] = (col, \"first\")\n",
"\n",
"# region / country (quasi stable)\n",
"for col in [REGION_COL, COUNTRY_COL]:\n",
" if col in df_aum_clean.columns:\n",
" agg_dict_aum[col] = (col, \"first\")\n",
"\n",
"# -------------------------\n",
"# GROUPBY\n",
"# -------------------------\n",
"df_aum_m = (\n",
" df_aum_clean\n",
" .sort_values(AUM_DATE_COL)\n",
" .groupby(KEYS, as_index=False)\n",
" .agg(**agg_dict_aum)\n",
")\n",
"\n",
"display(df_aum_m.head())\n",
"print(df_aum_m.shape)"
]
},
{
"cell_type": "markdown",
"id": "8576701e",
"metadata": {},
"source": [
"## 11. Fusion flows + AUM : table centrale `df_rel_m`"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "6120b573",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>aum_qty</th>\n",
" <th>aum_val</th>\n",
" <th>Product - Asset Type_x</th>\n",
" <th>Product - Strategy_x</th>\n",
" <th>Product - Legal Status_x</th>\n",
" <th>Product - Is Dedie ?_x</th>\n",
" <th>Product - Fund_x</th>\n",
" <th>Product - Shareclass Type_x</th>\n",
" <th>Product - Shareclass Currency_x</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" <th>net_flow_qty</th>\n",
" <th>gross_flow_qty</th>\n",
" <th>sub_qty</th>\n",
" <th>red_qty</th>\n",
" <th>n_tx</th>\n",
" <th>Product - Asset Type_y</th>\n",
" <th>Product - Strategy_y</th>\n",
" <th>Product - Legal Status_y</th>\n",
" <th>Product - Is Dedie ?_y</th>\n",
" <th>Product - Fund_y</th>\n",
" <th>Product - Shareclass Type_y</th>\n",
" <th>Product - Shareclass Currency_y</th>\n",
" <th>isin_held_flag</th>\n",
" <th>active_rel_month</th>\n",
" <th>flow_to_aum</th>\n",
" <th>turnover_rel</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-01</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>673.990</td>\n",
" <td>1045.99</td>\n",
" <td>859.990</td>\n",
" <td>-186.000</td>\n",
" <td>9.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.013728</td>\n",
" <td>0.021305</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-02-01</td>\n",
" <td>49797.915</td>\n",
" <td>3.368032e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>988.000</td>\n",
" <td>1712.00</td>\n",
" <td>1350.000</td>\n",
" <td>-362.000</td>\n",
" <td>12.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.019840</td>\n",
" <td>0.034378</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-01</td>\n",
" <td>50302.627</td>\n",
" <td>3.505691e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>9.710</td>\n",
" <td>1561.71</td>\n",
" <td>785.710</td>\n",
" <td>-776.000</td>\n",
" <td>12.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.000193</td>\n",
" <td>0.031046</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-04-01</td>\n",
" <td>50219.393</td>\n",
" <td>3.452433e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>-123.234</td>\n",
" <td>1830.19</td>\n",
" <td>853.478</td>\n",
" <td>-976.712</td>\n",
" <td>11.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-0.002454</td>\n",
" <td>0.036443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-05-01</td>\n",
" <td>53685.393</td>\n",
" <td>3.699729e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>121.000</td>\n",
" <td>529.00</td>\n",
" <td>325.000</td>\n",
" <td>-204.000</td>\n",
" <td>6.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.002254</td>\n",
" <td>0.009854</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID Product - Isin month aum_qty aum_val \\\n",
"0 18872 FR0010135103 2015-01-01 49094.915 3.242523e+07 \n",
"1 18872 FR0010135103 2015-02-01 49797.915 3.368032e+07 \n",
"2 18872 FR0010135103 2015-03-01 50302.627 3.505691e+07 \n",
"3 18872 FR0010135103 2015-04-01 50219.393 3.452433e+07 \n",
"4 18872 FR0010135103 2015-05-01 53685.393 3.699729e+07 \n",
"\n",
" Product - Asset Type_x Product - Strategy_x Product - Legal Status_x \\\n",
"0 Diversified Patrimoine FCP \n",
"1 Diversified Patrimoine FCP \n",
"2 Diversified Patrimoine FCP \n",
"3 Diversified Patrimoine FCP \n",
"4 Diversified Patrimoine FCP \n",
"\n",
" Product - Is Dedie ?_x Product - Fund_x Product - Shareclass Type_x \\\n",
"0 NO Carmignac Patrimoine A \n",
"1 NO Carmignac Patrimoine A \n",
"2 NO Carmignac Patrimoine A \n",
"3 NO Carmignac Patrimoine A \n",
"4 NO Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency_x Registrar Account - Region \\\n",
"0 EUR Switzerland \n",
"1 EUR Switzerland \n",
"2 EUR Switzerland \n",
"3 EUR Switzerland \n",
"4 EUR Switzerland \n",
"\n",
" RegistrarAccount - Country net_flow_qty gross_flow_qty sub_qty red_qty \\\n",
"0 Switzerland 673.990 1045.99 859.990 -186.000 \n",
"1 Switzerland 988.000 1712.00 1350.000 -362.000 \n",
"2 Switzerland 9.710 1561.71 785.710 -776.000 \n",
"3 Switzerland -123.234 1830.19 853.478 -976.712 \n",
"4 Switzerland 121.000 529.00 325.000 -204.000 \n",
"\n",
" n_tx Product - Asset Type_y Product - Strategy_y Product - Legal Status_y \\\n",
"0 9.0 Diversified Patrimoine FCP \n",
"1 12.0 Diversified Patrimoine FCP \n",
"2 12.0 Diversified Patrimoine FCP \n",
"3 11.0 Diversified Patrimoine FCP \n",
"4 6.0 Diversified Patrimoine FCP \n",
"\n",
" Product - Is Dedie ?_y Product - Fund_y Product - Shareclass Type_y \\\n",
"0 NO Carmignac Patrimoine A \n",
"1 NO Carmignac Patrimoine A \n",
"2 NO Carmignac Patrimoine A \n",
"3 NO Carmignac Patrimoine A \n",
"4 NO Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency_y isin_held_flag active_rel_month \\\n",
"0 EUR 1 1 \n",
"1 EUR 1 1 \n",
"2 EUR 1 1 \n",
"3 EUR 1 1 \n",
"4 EUR 1 1 \n",
"\n",
" flow_to_aum turnover_rel \n",
"0 0.013728 0.021305 \n",
"1 0.019840 0.034378 \n",
"2 0.000193 0.031046 \n",
"3 -0.002454 0.036443 \n",
"4 0.002254 0.009854 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"(962611, 30)\n"
]
}
],
"source": [
"# ============================================================\n",
"# DF_REL_M : fusion flows + aum\n",
"# ============================================================\n",
"\n",
"keys = pd.concat([\n",
" df_flows_m[KEYS],\n",
" df_aum_m[KEYS]\n",
"]).drop_duplicates()\n",
"\n",
"df_rel_m = (\n",
" keys\n",
" .merge(df_aum_m, on=KEYS, how=\"left\")\n",
" .merge(df_flows_m, on=KEYS, how=\"left\")\n",
")\n",
"\n",
"# -------------------------\n",
"# CLEAN NUMERIC\n",
"# -------------------------\n",
"for c in [\n",
" \"aum_qty\", \"aum_val\",\n",
" \"net_flow_qty\", \"gross_flow_qty\",\n",
" \"sub_qty\", \"red_qty\", \"n_tx\"\n",
"]:\n",
" if c in df_rel_m.columns:\n",
" df_rel_m[c] = pd.to_numeric(df_rel_m[c], errors=\"coerce\").fillna(0.0)\n",
"\n",
"# -------------------------\n",
"# FEATURES BASIQUES\n",
"# -------------------------\n",
"df_rel_m[\"isin_held_flag\"] = (df_rel_m[\"aum_qty\"] > 0).astype(int)\n",
"df_rel_m[\"active_rel_month\"] = (df_rel_m[\"gross_flow_qty\"] > 0).astype(int)\n",
"\n",
"df_rel_m[\"flow_to_aum\"] = df_rel_m[\"net_flow_qty\"] / (df_rel_m[\"aum_qty\"].abs() + 1.0)\n",
"df_rel_m[\"turnover_rel\"] = df_rel_m[\"gross_flow_qty\"] / (df_rel_m[\"aum_qty\"].abs() + 1.0)\n",
"\n",
"display(df_rel_m.head())\n",
"print(df_rel_m.shape)"
]
},
{
"cell_type": "markdown",
"id": "2c2ca596",
"metadata": {},
"source": [
"## 12. NAV mensuel et taux mensuels"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "9fe5c3c0-80f6-4fe4-bd67-08323f781c7a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"df_nav_m: (30336, 17)\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" }\n",
"\n",
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" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Isin</th>\n",
" <th>month</th>\n",
" <th>Price (TF PartPrice)</th>\n",
" <th>ret_fund_m</th>\n",
" <th>ret_fund_3m_mean</th>\n",
" <th>ret_fund_6m_mean</th>\n",
" <th>ret_fund_12m_mean</th>\n",
" <th>drawdown_proxy</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>617663</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-01-01</td>\n",
" <td>1534.80</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617668</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-02-01</td>\n",
" <td>1500.73</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617672</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-03-01</td>\n",
" <td>1481.29</td>\n",
" <td>-0.012954</td>\n",
" <td>-0.017576</td>\n",
" <td>-0.017576</td>\n",
" <td>-0.017576</td>\n",
" <td>-0.034864</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617677</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-04-01</td>\n",
" <td>1517.60</td>\n",
" <td>0.024512</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.011207</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617681</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-05-01</td>\n",
" <td>1504.83</td>\n",
" <td>-0.008415</td>\n",
" <td>0.001048</td>\n",
" <td>-0.004764</td>\n",
" <td>-0.004764</td>\n",
" <td>-0.019527</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617686</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-06-01</td>\n",
" <td>1492.92</td>\n",
" <td>-0.007915</td>\n",
" <td>0.002728</td>\n",
" <td>-0.005394</td>\n",
" <td>-0.005394</td>\n",
" <td>-0.027287</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617690</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-07-01</td>\n",
" <td>1473.52</td>\n",
" <td>-0.012995</td>\n",
" <td>-0.009775</td>\n",
" <td>-0.006661</td>\n",
" <td>-0.006661</td>\n",
" <td>-0.039927</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617694</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-08-01</td>\n",
" <td>1346.78</td>\n",
" <td>-0.086012</td>\n",
" <td>-0.035640</td>\n",
" <td>-0.017296</td>\n",
" <td>-0.017996</td>\n",
" <td>-0.122505</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617699</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-09-01</td>\n",
" <td>1330.69</td>\n",
" <td>-0.011947</td>\n",
" <td>-0.036984</td>\n",
" <td>-0.017128</td>\n",
" <td>-0.017240</td>\n",
" <td>-0.132988</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617703</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-10-01</td>\n",
" <td>1372.91</td>\n",
" <td>0.031728</td>\n",
" <td>-0.022077</td>\n",
" <td>-0.015926</td>\n",
" <td>-0.011799</td>\n",
" <td>-0.105480</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Isin month Price (TF PartPrice) ret_fund_m \\\n",
"617663 FR0007486709 2011-01-01 1534.80 NaN \n",
"617668 FR0007486709 2011-02-01 1500.73 -0.022198 \n",
"617672 FR0007486709 2011-03-01 1481.29 -0.012954 \n",
"617677 FR0007486709 2011-04-01 1517.60 0.024512 \n",
"617681 FR0007486709 2011-05-01 1504.83 -0.008415 \n",
"617686 FR0007486709 2011-06-01 1492.92 -0.007915 \n",
"617690 FR0007486709 2011-07-01 1473.52 -0.012995 \n",
"617694 FR0007486709 2011-08-01 1346.78 -0.086012 \n",
"617699 FR0007486709 2011-09-01 1330.69 -0.011947 \n",
"617703 FR0007486709 2011-10-01 1372.91 0.031728 \n",
"\n",
" ret_fund_3m_mean ret_fund_6m_mean ret_fund_12m_mean drawdown_proxy \n",
"617663 NaN NaN NaN 0.000000 \n",
"617668 -0.022198 -0.022198 -0.022198 -0.022198 \n",
"617672 -0.017576 -0.017576 -0.017576 -0.034864 \n",
"617677 -0.003547 -0.003547 -0.003547 -0.011207 \n",
"617681 0.001048 -0.004764 -0.004764 -0.019527 \n",
"617686 0.002728 -0.005394 -0.005394 -0.027287 \n",
"617690 -0.009775 -0.006661 -0.006661 -0.039927 \n",
"617694 -0.035640 -0.017296 -0.017996 -0.122505 \n",
"617699 -0.036984 -0.017128 -0.017240 -0.132988 \n",
"617703 -0.022077 -0.015926 -0.011799 -0.105480 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# NAV mensuel + perfs mensuelles corrigées\n",
"# ============================================================\n",
"\n",
"df_nav_m = None\n",
"\n",
"if df_nav is not None and NAV_ISIN_COL is not None and NAV_PRICE_COL is not None:\n",
" df_nav = df_nav.copy()\n",
"\n",
" # nettoyage prix fonds\n",
" df_nav[NAV_PRICE_COL] = (\n",
" df_nav[NAV_PRICE_COL]\n",
" .astype(str)\n",
" .str.replace(\"\\u202f\", \"\", regex=False)\n",
" .str.replace(\" \", \"\", regex=False)\n",
" .str.replace(\",\", \".\", regex=False)\n",
" )\n",
" df_nav[NAV_PRICE_COL] = pd.to_numeric(df_nav[NAV_PRICE_COL], errors=\"coerce\")\n",
"\n",
" # nettoyage benchmark si dispo\n",
" if NAV_BENCH_COL is not None and NAV_BENCH_COL in df_nav.columns:\n",
" df_nav[NAV_BENCH_COL] = (\n",
" df_nav[NAV_BENCH_COL]\n",
" .astype(str)\n",
" .str.replace(\"\\u202f\", \"\", regex=False)\n",
" .str.replace(\" \", \"\", regex=False)\n",
" .str.replace(\",\", \".\", regex=False)\n",
" )\n",
" df_nav[NAV_BENCH_COL] = pd.to_numeric(df_nav[NAV_BENCH_COL], errors=\"coerce\")\n",
"\n",
" # dernière NAV du mois par ISIN\n",
" df_nav_m = (\n",
" df_nav\n",
" .dropna(subset=[NAV_ISIN_COL, \"month\", NAV_PRICE_COL])\n",
" .sort_values([NAV_ISIN_COL, \"month\", NAV_DATE_COL])\n",
" .groupby([NAV_ISIN_COL, \"month\"], as_index=False)\n",
" .tail(1)\n",
" .copy()\n",
" )\n",
"\n",
" # rendement mensuel\n",
" df_nav_m[\"ret_fund_m\"] = df_nav_m.groupby(NAV_ISIN_COL)[NAV_PRICE_COL].pct_change()\n",
"\n",
" # moyenne glissante des rendements mensuels\n",
" df_nav_m[\"ret_fund_3m_mean\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"ret_fund_m\"]\n",
" .transform(lambda s: s.rolling(3, min_periods=1).mean())\n",
" )\n",
"\n",
" df_nav_m[\"ret_fund_6m_mean\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"ret_fund_m\"]\n",
" .transform(lambda s: s.rolling(6, min_periods=1).mean())\n",
" )\n",
"\n",
" df_nav_m[\"ret_fund_12m_mean\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"ret_fund_m\"]\n",
" .transform(lambda s: s.rolling(12, min_periods=1).mean())\n",
" )\n",
"\n",
" # volatilité glissante des rendements\n",
" df_nav_m[\"ret_vol_3m\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"ret_fund_m\"]\n",
" .transform(lambda s: s.rolling(3, min_periods=2).std())\n",
" )\n",
"\n",
" df_nav_m[\"ret_vol_6m\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"ret_fund_m\"]\n",
" .transform(lambda s: s.rolling(6, min_periods=2).std())\n",
" )\n",
"\n",
" # drawdown\n",
" df_nav_m[\"drawdown_proxy\"] = (\n",
" df_nav_m[NAV_PRICE_COL] /\n",
" df_nav_m.groupby(NAV_ISIN_COL)[NAV_PRICE_COL].cummax()\n",
" ) - 1\n",
"\n",
" # benchmark si dispo\n",
" if NAV_BENCH_COL is not None and NAV_BENCH_COL in df_nav_m.columns:\n",
" df_nav_m[\"ret_bench_m\"] = df_nav_m.groupby(NAV_ISIN_COL)[NAV_BENCH_COL].pct_change()\n",
"\n",
" df_nav_m[\"active_return_m\"] = df_nav_m[\"ret_fund_m\"] - df_nav_m[\"ret_bench_m\"]\n",
"\n",
" df_nav_m[\"active_return_3m_mean\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"active_return_m\"]\n",
" .transform(lambda s: s.rolling(3, min_periods=1).mean())\n",
" )\n",
"\n",
" df_nav_m[\"active_return_6m_mean\"] = (\n",
" df_nav_m.groupby(NAV_ISIN_COL)[\"active_return_m\"]\n",
" .transform(lambda s: s.rolling(6, min_periods=1).mean())\n",
" )\n",
"\n",
"print(\"df_nav_m:\", None if df_nav_m is None else df_nav_m.shape)\n",
"\n",
"if df_nav_m is not None:\n",
" display(\n",
" df_nav_m[\n",
" [\n",
" NAV_ISIN_COL, \"month\", NAV_PRICE_COL,\n",
" \"ret_fund_m\", \"ret_fund_3m_mean\", \"ret_fund_6m_mean\",\n",
" \"ret_fund_12m_mean\", \"drawdown_proxy\"\n",
" ]\n",
" ].head(10)\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d2f87bef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"df_nav_m: (30336, 17)\n",
"df_rates_m: (131, 4)\n"
]
},
{
"data": {
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Isin</th>\n",
" <th>month</th>\n",
" <th>Price (TF PartPrice)</th>\n",
" <th>ret_fund_m</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>617663</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-01-01</td>\n",
" <td>1534.80</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617668</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-02-01</td>\n",
" <td>1500.73</td>\n",
" <td>-0.022198</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617672</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-03-01</td>\n",
" <td>1481.29</td>\n",
" <td>-0.012954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617677</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-04-01</td>\n",
" <td>1517.60</td>\n",
" <td>0.024512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617681</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-05-01</td>\n",
" <td>1504.83</td>\n",
" <td>-0.008415</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Isin month Price (TF PartPrice) ret_fund_m\n",
"617663 FR0007486709 2011-01-01 1534.80 NaN\n",
"617668 FR0007486709 2011-02-01 1500.73 -0.022198\n",
"617672 FR0007486709 2011-03-01 1481.29 -0.012954\n",
"617677 FR0007486709 2011-04-01 1517.60 0.024512\n",
"617681 FR0007486709 2011-05-01 1504.83 -0.008415"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>month</th>\n",
" <th>Yld to Maturity</th>\n",
" <th>delta_rate_m</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2014-12-01</td>\n",
" <td>0.144</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>2015-01-01</td>\n",
" <td>0.086</td>\n",
" <td>-0.058</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>2015-02-01</td>\n",
" <td>0.064</td>\n",
" <td>-0.022</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>2015-03-01</td>\n",
" <td>0.050</td>\n",
" <td>-0.014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>2015-04-01</td>\n",
" <td>-0.027</td>\n",
" <td>-0.077</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" month Yld to Maturity delta_rate_m\n",
"0 2014-12-01 0.144 NaN\n",
"22 2015-01-01 0.086 -0.058\n",
"43 2015-02-01 0.064 -0.022\n",
"65 2015-03-01 0.050 -0.014\n",
"86 2015-04-01 -0.027 -0.077"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_rates_m = None\n",
"\n",
"if df_rates is not None and RATE_DATE_COL is not None and RATE_VAL_COL is not None:\n",
" df_rates = df_rates.copy()\n",
"\n",
" df_rates[RATE_VAL_COL] = (\n",
" df_rates[RATE_VAL_COL]\n",
" .astype(str)\n",
" .str.replace(\"\\u202f\", \"\", regex=False)\n",
" .str.replace(\" \", \"\", regex=False)\n",
" .str.replace(\",\", \".\", regex=False)\n",
" )\n",
" df_rates[RATE_VAL_COL] = pd.to_numeric(df_rates[RATE_VAL_COL], errors=\"coerce\")\n",
"\n",
" df_rates_m = (\n",
" df_rates\n",
" .dropna(subset=[\"month\", RATE_VAL_COL])\n",
" .sort_values(RATE_DATE_COL)\n",
" .groupby(\"month\", as_index=False)\n",
" .tail(1)\n",
" .copy()\n",
" )\n",
"\n",
" df_rates_m[\"delta_rate_m\"] = df_rates_m[RATE_VAL_COL].diff()\n",
"\n",
"print(\"df_nav_m:\", None if df_nav_m is None else df_nav_m.shape)\n",
"print(\"df_rates_m:\", None if df_rates_m is None else df_rates_m.shape)\n",
"\n",
"if df_nav_m is not None:\n",
" display(df_nav_m[[NAV_ISIN_COL, \"month\", NAV_PRICE_COL, \"ret_fund_m\"]].head())\n",
"\n",
"if df_rates_m is not None:\n",
" display(df_rates_m[[\"month\", RATE_VAL_COL, \"delta_rate_m\"]].head())"
]
},
{
"cell_type": "markdown",
"id": "6c3a4e1f",
"metadata": {},
"source": [
"## 13. Intégration optionnelle des performances Carmignac"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "d6402369-171e-4589-a311-aa440ebf10f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"df_perf_monthly: (30336, 12)\n"
]
},
{
"data": {
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"<style scoped>\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>ret_fund_m</th>\n",
" <th>ret_fund_3m_mean</th>\n",
" <th>ret_fund_6m_mean</th>\n",
" <th>ret_fund_12m_mean</th>\n",
" <th>ret_vol_3m</th>\n",
" <th>ret_vol_6m</th>\n",
" <th>drawdown_proxy</th>\n",
" <th>active_return_m</th>\n",
" <th>active_return_3m_mean</th>\n",
" <th>active_return_6m_mean</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>617663</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-01-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617668</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-02-01</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.022198</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.022198</td>\n",
" <td>-0.028319</td>\n",
" <td>-0.028319</td>\n",
" <td>-0.028319</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617672</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-03-01</td>\n",
" <td>-0.012954</td>\n",
" <td>-0.017576</td>\n",
" <td>-0.017576</td>\n",
" <td>-0.017576</td>\n",
" <td>0.006537</td>\n",
" <td>0.006537</td>\n",
" <td>-0.034864</td>\n",
" <td>0.014369</td>\n",
" <td>-0.006975</td>\n",
" <td>-0.006975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617677</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-04-01</td>\n",
" <td>0.024512</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>0.024735</td>\n",
" <td>0.024735</td>\n",
" <td>-0.011207</td>\n",
" <td>-0.006997</td>\n",
" <td>-0.006982</td>\n",
" <td>-0.006982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617681</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-05-01</td>\n",
" <td>-0.008415</td>\n",
" <td>0.001048</td>\n",
" <td>-0.004764</td>\n",
" <td>-0.004764</td>\n",
" <td>0.020447</td>\n",
" <td>0.020343</td>\n",
" <td>-0.019527</td>\n",
" <td>0.003691</td>\n",
" <td>0.003688</td>\n",
" <td>-0.004314</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Product - Isin month ret_fund_m ret_fund_3m_mean \\\n",
"617663 FR0007486709 2011-01-01 NaN NaN \n",
"617668 FR0007486709 2011-02-01 -0.022198 -0.022198 \n",
"617672 FR0007486709 2011-03-01 -0.012954 -0.017576 \n",
"617677 FR0007486709 2011-04-01 0.024512 -0.003547 \n",
"617681 FR0007486709 2011-05-01 -0.008415 0.001048 \n",
"\n",
" ret_fund_6m_mean ret_fund_12m_mean ret_vol_3m ret_vol_6m \\\n",
"617663 NaN NaN NaN NaN \n",
"617668 -0.022198 -0.022198 NaN NaN \n",
"617672 -0.017576 -0.017576 0.006537 0.006537 \n",
"617677 -0.003547 -0.003547 0.024735 0.024735 \n",
"617681 -0.004764 -0.004764 0.020447 0.020343 \n",
"\n",
" drawdown_proxy active_return_m active_return_3m_mean \\\n",
"617663 0.000000 NaN NaN \n",
"617668 -0.022198 -0.028319 -0.028319 \n",
"617672 -0.034864 0.014369 -0.006975 \n",
"617677 -0.011207 -0.006997 -0.006982 \n",
"617681 -0.019527 0.003691 0.003688 \n",
"\n",
" active_return_6m_mean \n",
"617663 NaN \n",
"617668 -0.028319 \n",
"617672 -0.006975 \n",
"617677 -0.006982 \n",
"617681 -0.004314 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_perf_monthly = None\n",
"\n",
"if df_perf_monthly is None:\n",
" df_perf_monthly = (\n",
" df_nav_m[\n",
" [\n",
" NAV_ISIN_COL, \"month\",\n",
" \"ret_fund_m\",\n",
" \"ret_fund_3m_mean\",\n",
" \"ret_fund_6m_mean\",\n",
" \"ret_fund_12m_mean\",\n",
" \"ret_vol_3m\",\n",
" \"ret_vol_6m\",\n",
" \"drawdown_proxy\"\n",
" ]\n",
" + ([ \"active_return_m\", \"active_return_3m_mean\", \"active_return_6m_mean\" ] if \"active_return_m\" in df_nav_m.columns else [])\n",
" ]\n",
" .rename(columns={NAV_ISIN_COL: ISIN_COL})\n",
" .copy()\n",
" ) if df_nav_m is not None else None\n",
"\n",
"print(\"df_perf_monthly:\", None if df_perf_monthly is None else df_perf_monthly.shape)\n",
"if df_perf_monthly is not None:\n",
" display(df_perf_monthly.head())"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "70a5eae1-8d98-427a-8aab-f10a4c8ad782",
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>ret_fund_m</th>\n",
" <th>ret_fund_3m_mean</th>\n",
" <th>ret_fund_6m_mean</th>\n",
" <th>ret_fund_12m_mean</th>\n",
" <th>ret_vol_3m</th>\n",
" <th>ret_vol_6m</th>\n",
" <th>drawdown_proxy</th>\n",
" <th>active_return_m</th>\n",
" <th>active_return_3m_mean</th>\n",
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" <th>617672</th>\n",
" <td>FR0007486709</td>\n",
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" <td>0.014369</td>\n",
" <td>-0.006975</td>\n",
" <td>-0.006975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617677</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-04-01</td>\n",
" <td>0.024512</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>-0.003547</td>\n",
" <td>0.024735</td>\n",
" <td>0.024735</td>\n",
" <td>-0.011207</td>\n",
" <td>-0.006997</td>\n",
" <td>-0.006982</td>\n",
" <td>-0.006982</td>\n",
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" <th>617681</th>\n",
" <td>FR0007486709</td>\n",
" <td>2011-05-01</td>\n",
" <td>-0.008415</td>\n",
" <td>0.001048</td>\n",
" <td>-0.004764</td>\n",
" <td>-0.004764</td>\n",
" <td>0.020447</td>\n",
" <td>0.020343</td>\n",
" <td>-0.019527</td>\n",
" <td>0.003691</td>\n",
" <td>0.003688</td>\n",
" <td>-0.004314</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>89</th>\n",
" <td>LU3149200233</td>\n",
" <td>2025-10-01</td>\n",
" <td>0.035073</td>\n",
" <td>0.035073</td>\n",
" <td>0.035073</td>\n",
" <td>0.035073</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>0.016577</td>\n",
" <td>0.016577</td>\n",
" <td>0.016577</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>LU3149200746</td>\n",
" <td>2025-09-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td>LU3149200746</td>\n",
" <td>2025-10-01</td>\n",
" <td>0.035261</td>\n",
" <td>0.035261</td>\n",
" <td>0.035261</td>\n",
" <td>0.035261</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>0.016766</td>\n",
" <td>0.016766</td>\n",
" <td>0.016766</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>LU3186888858</td>\n",
" <td>2025-10-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>LU3198990908</td>\n",
" <td>2025-10-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>30336 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" Product - Isin month ret_fund_m ret_fund_3m_mean \\\n",
"617663 FR0007486709 2011-01-01 NaN NaN \n",
"617668 FR0007486709 2011-02-01 -0.022198 -0.022198 \n",
"617672 FR0007486709 2011-03-01 -0.012954 -0.017576 \n",
"617677 FR0007486709 2011-04-01 0.024512 -0.003547 \n",
"617681 FR0007486709 2011-05-01 -0.008415 0.001048 \n",
"... ... ... ... ... \n",
"89 LU3149200233 2025-10-01 0.035073 0.035073 \n",
"35 LU3149200746 2025-09-01 NaN NaN \n",
"51 LU3149200746 2025-10-01 0.035261 0.035261 \n",
"16 LU3186888858 2025-10-01 NaN NaN \n",
"4 LU3198990908 2025-10-01 NaN NaN \n",
"\n",
" ret_fund_6m_mean ret_fund_12m_mean ret_vol_3m ret_vol_6m \\\n",
"617663 NaN NaN NaN NaN \n",
"617668 -0.022198 -0.022198 NaN NaN \n",
"617672 -0.017576 -0.017576 0.006537 0.006537 \n",
"617677 -0.003547 -0.003547 0.024735 0.024735 \n",
"617681 -0.004764 -0.004764 0.020447 0.020343 \n",
"... ... ... ... ... \n",
"89 0.035073 0.035073 NaN NaN \n",
"35 NaN NaN NaN NaN \n",
"51 0.035261 0.035261 NaN NaN \n",
"16 NaN NaN NaN NaN \n",
"4 NaN NaN NaN NaN \n",
"\n",
" drawdown_proxy active_return_m active_return_3m_mean \\\n",
"617663 0.000000 NaN NaN \n",
"617668 -0.022198 -0.028319 -0.028319 \n",
"617672 -0.034864 0.014369 -0.006975 \n",
"617677 -0.011207 -0.006997 -0.006982 \n",
"617681 -0.019527 0.003691 0.003688 \n",
"... ... ... ... \n",
"89 0.000000 0.016577 0.016577 \n",
"35 0.000000 NaN NaN \n",
"51 0.000000 0.016766 0.016766 \n",
"16 0.000000 NaN NaN \n",
"4 0.000000 NaN NaN \n",
"\n",
" active_return_6m_mean \n",
"617663 NaN \n",
"617668 -0.028319 \n",
"617672 -0.006975 \n",
"617677 -0.006982 \n",
"617681 -0.004314 \n",
"... ... \n",
"89 0.016577 \n",
"35 NaN \n",
"51 0.016766 \n",
"16 NaN \n",
"4 NaN \n",
"\n",
"[30336 rows x 12 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_perf_monthly"
]
},
{
"cell_type": "markdown",
"id": "091fc8ff",
"metadata": {},
"source": [
"## 14. Enrichissement de `df_rel_m` avec performances et taux"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "82872d77",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>Product - Isin</th>\n",
" <th>month</th>\n",
" <th>aum_qty</th>\n",
" <th>aum_val</th>\n",
" <th>Product - Asset Type_x</th>\n",
" <th>Product - Strategy_x</th>\n",
" <th>Product - Legal Status_x</th>\n",
" <th>Product - Is Dedie ?_x</th>\n",
" <th>Product - Fund_x</th>\n",
" <th>Product - Shareclass Type_x</th>\n",
" <th>Product - Shareclass Currency_x</th>\n",
" <th>Registrar Account - Region</th>\n",
" <th>RegistrarAccount - Country</th>\n",
" <th>net_flow_qty</th>\n",
" <th>gross_flow_qty</th>\n",
" <th>sub_qty</th>\n",
" <th>red_qty</th>\n",
" <th>n_tx</th>\n",
" <th>Product - Asset Type_y</th>\n",
" <th>Product - Strategy_y</th>\n",
" <th>Product - Legal Status_y</th>\n",
" <th>Product - Is Dedie ?_y</th>\n",
" <th>Product - Fund_y</th>\n",
" <th>Product - Shareclass Type_y</th>\n",
" <th>Product - Shareclass Currency_y</th>\n",
" <th>isin_held_flag</th>\n",
" <th>active_rel_month</th>\n",
" <th>flow_to_aum</th>\n",
" <th>turnover_rel</th>\n",
" <th>ret_fund_m</th>\n",
" <th>ret_fund_3m_mean</th>\n",
" <th>ret_fund_6m_mean</th>\n",
" <th>ret_fund_12m_mean</th>\n",
" <th>ret_vol_3m</th>\n",
" <th>ret_vol_6m</th>\n",
" <th>drawdown_proxy</th>\n",
" <th>active_return_m</th>\n",
" <th>active_return_3m_mean</th>\n",
" <th>active_return_6m_mean</th>\n",
" <th>delta_rate_m</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-01</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>673.990</td>\n",
" <td>1045.99</td>\n",
" <td>859.990</td>\n",
" <td>-186.000</td>\n",
" <td>9.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.013728</td>\n",
" <td>0.021305</td>\n",
" <td>0.065542</td>\n",
" <td>0.029403</td>\n",
" <td>0.020252</td>\n",
" <td>0.013566</td>\n",
" <td>0.031299</td>\n",
" <td>0.023619</td>\n",
" <td>0.000000</td>\n",
" <td>0.003148</td>\n",
" <td>-0.000504</td>\n",
" <td>-0.002776</td>\n",
" <td>-0.058</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-02-01</td>\n",
" <td>49797.915</td>\n",
" <td>3.368032e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>988.000</td>\n",
" <td>1712.00</td>\n",
" <td>1350.000</td>\n",
" <td>-362.000</td>\n",
" <td>12.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.019840</td>\n",
" <td>0.034378</td>\n",
" <td>0.025620</td>\n",
" <td>0.034295</td>\n",
" <td>0.020209</td>\n",
" <td>0.015671</td>\n",
" <td>0.027938</td>\n",
" <td>0.023607</td>\n",
" <td>0.000000</td>\n",
" <td>-0.002505</td>\n",
" <td>-0.001482</td>\n",
" <td>-0.002621</td>\n",
" <td>-0.022</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-01</td>\n",
" <td>50302.627</td>\n",
" <td>3.505691e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>9.710</td>\n",
" <td>1561.71</td>\n",
" <td>785.710</td>\n",
" <td>-776.000</td>\n",
" <td>12.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.000193</td>\n",
" <td>0.031046</td>\n",
" <td>0.030614</td>\n",
" <td>0.040592</td>\n",
" <td>0.024664</td>\n",
" <td>0.017903</td>\n",
" <td>0.021751</td>\n",
" <td>0.022402</td>\n",
" <td>0.000000</td>\n",
" <td>0.000187</td>\n",
" <td>0.000277</td>\n",
" <td>-0.001807</td>\n",
" <td>-0.014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-04-01</td>\n",
" <td>50219.393</td>\n",
" <td>3.452433e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>-123.234</td>\n",
" <td>1830.19</td>\n",
" <td>853.478</td>\n",
" <td>-976.712</td>\n",
" <td>11.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-0.002454</td>\n",
" <td>0.036443</td>\n",
" <td>-0.023909</td>\n",
" <td>0.010775</td>\n",
" <td>0.020089</td>\n",
" <td>0.016308</td>\n",
" <td>0.030141</td>\n",
" <td>0.029315</td>\n",
" <td>-0.023909</td>\n",
" <td>-0.001525</td>\n",
" <td>-0.001281</td>\n",
" <td>-0.000893</td>\n",
" <td>-0.077</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-05-01</td>\n",
" <td>53685.393</td>\n",
" <td>3.699729e+07</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>Switzerland</td>\n",
" <td>Switzerland</td>\n",
" <td>121.000</td>\n",
" <td>529.00</td>\n",
" <td>325.000</td>\n",
" <td>-204.000</td>\n",
" <td>6.0</td>\n",
" <td>Diversified</td>\n",
" <td>Patrimoine</td>\n",
" <td>FCP</td>\n",
" <td>NO</td>\n",
" <td>Carmignac Patrimoine</td>\n",
" <td>A</td>\n",
" <td>EUR</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.002254</td>\n",
" <td>0.009854</td>\n",
" <td>0.003240</td>\n",
" <td>0.003315</td>\n",
" <td>0.018805</td>\n",
" <td>0.014758</td>\n",
" <td>0.027262</td>\n",
" <td>0.029957</td>\n",
" <td>-0.020747</td>\n",
" <td>-0.006286</td>\n",
" <td>-0.002542</td>\n",
" <td>-0.002012</td>\n",
" <td>-0.053</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID Product - Isin month aum_qty aum_val \\\n",
"0 18872 FR0010135103 2015-01-01 49094.915 3.242523e+07 \n",
"1 18872 FR0010135103 2015-02-01 49797.915 3.368032e+07 \n",
"2 18872 FR0010135103 2015-03-01 50302.627 3.505691e+07 \n",
"3 18872 FR0010135103 2015-04-01 50219.393 3.452433e+07 \n",
"4 18872 FR0010135103 2015-05-01 53685.393 3.699729e+07 \n",
"\n",
" Product - Asset Type_x Product - Strategy_x Product - Legal Status_x \\\n",
"0 Diversified Patrimoine FCP \n",
"1 Diversified Patrimoine FCP \n",
"2 Diversified Patrimoine FCP \n",
"3 Diversified Patrimoine FCP \n",
"4 Diversified Patrimoine FCP \n",
"\n",
" Product - Is Dedie ?_x Product - Fund_x Product - Shareclass Type_x \\\n",
"0 NO Carmignac Patrimoine A \n",
"1 NO Carmignac Patrimoine A \n",
"2 NO Carmignac Patrimoine A \n",
"3 NO Carmignac Patrimoine A \n",
"4 NO Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency_x Registrar Account - Region \\\n",
"0 EUR Switzerland \n",
"1 EUR Switzerland \n",
"2 EUR Switzerland \n",
"3 EUR Switzerland \n",
"4 EUR Switzerland \n",
"\n",
" RegistrarAccount - Country net_flow_qty gross_flow_qty sub_qty red_qty \\\n",
"0 Switzerland 673.990 1045.99 859.990 -186.000 \n",
"1 Switzerland 988.000 1712.00 1350.000 -362.000 \n",
"2 Switzerland 9.710 1561.71 785.710 -776.000 \n",
"3 Switzerland -123.234 1830.19 853.478 -976.712 \n",
"4 Switzerland 121.000 529.00 325.000 -204.000 \n",
"\n",
" n_tx Product - Asset Type_y Product - Strategy_y Product - Legal Status_y \\\n",
"0 9.0 Diversified Patrimoine FCP \n",
"1 12.0 Diversified Patrimoine FCP \n",
"2 12.0 Diversified Patrimoine FCP \n",
"3 11.0 Diversified Patrimoine FCP \n",
"4 6.0 Diversified Patrimoine FCP \n",
"\n",
" Product - Is Dedie ?_y Product - Fund_y Product - Shareclass Type_y \\\n",
"0 NO Carmignac Patrimoine A \n",
"1 NO Carmignac Patrimoine A \n",
"2 NO Carmignac Patrimoine A \n",
"3 NO Carmignac Patrimoine A \n",
"4 NO Carmignac Patrimoine A \n",
"\n",
" Product - Shareclass Currency_y isin_held_flag active_rel_month \\\n",
"0 EUR 1 1 \n",
"1 EUR 1 1 \n",
"2 EUR 1 1 \n",
"3 EUR 1 1 \n",
"4 EUR 1 1 \n",
"\n",
" flow_to_aum turnover_rel ret_fund_m ret_fund_3m_mean ret_fund_6m_mean \\\n",
"0 0.013728 0.021305 0.065542 0.029403 0.020252 \n",
"1 0.019840 0.034378 0.025620 0.034295 0.020209 \n",
"2 0.000193 0.031046 0.030614 0.040592 0.024664 \n",
"3 -0.002454 0.036443 -0.023909 0.010775 0.020089 \n",
"4 0.002254 0.009854 0.003240 0.003315 0.018805 \n",
"\n",
" ret_fund_12m_mean ret_vol_3m ret_vol_6m drawdown_proxy active_return_m \\\n",
"0 0.013566 0.031299 0.023619 0.000000 0.003148 \n",
"1 0.015671 0.027938 0.023607 0.000000 -0.002505 \n",
"2 0.017903 0.021751 0.022402 0.000000 0.000187 \n",
"3 0.016308 0.030141 0.029315 -0.023909 -0.001525 \n",
"4 0.014758 0.027262 0.029957 -0.020747 -0.006286 \n",
"\n",
" active_return_3m_mean active_return_6m_mean delta_rate_m \n",
"0 -0.000504 -0.002776 -0.058 \n",
"1 -0.001482 -0.002621 -0.022 \n",
"2 0.000277 -0.001807 -0.014 \n",
"3 -0.001281 -0.000893 -0.077 \n",
"4 -0.002542 -0.002012 -0.053 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"if df_perf_monthly is not None:\n",
" df_rel_m = df_rel_m.merge(\n",
" df_perf_monthly,\n",
" on=[ISIN_COL, \"month\"],\n",
" how=\"left\"\n",
" )\n",
"\n",
"if df_rates_m is not None:\n",
" df_rel_m = df_rel_m.merge(\n",
" df_rates_m[[\"month\", \"delta_rate_m\"]],\n",
" on=\"month\",\n",
" how=\"left\"\n",
" )\n",
"\n",
"for c in [\n",
" \"ret_fund_m\",\n",
" \"ret_fund_3m_mean\",\n",
" \"ret_fund_6m_mean\",\n",
" \"ret_fund_12m_mean\",\n",
" \"ret_vol_3m\",\n",
" \"ret_vol_6m\",\n",
" \"drawdown_proxy\",\n",
" \"active_return_m\",\n",
" \"active_return_3m_mean\",\n",
" \"active_return_6m_mean\",\n",
" \"delta_rate_m\"\n",
"]:\n",
" if c in df_rel_m.columns:\n",
" df_rel_m[c] = pd.to_numeric(df_rel_m[c], errors=\"coerce\")\n",
"\n",
"display(df_rel_m.head())"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "03d60451-3c2f-4d50-bb78-d00ba6a50a39",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"432"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_rel_m[\"Registrar Account - ID\"].nunique()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "667c5372-0438-4c30-b4f7-9ffd9e09b149",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"349"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_rel_m[\"Product - Isin\"].nunique() #349"
]
},
{
"cell_type": "markdown",
"id": "6f3b149c-899b-4c14-834e-6ec5a66cceca",
"metadata": {},
"source": [
"- ret_fund_m: Rendement mensuel du fond.\n",
"- ret_fund_3m_mean : Moyenne des rendements mensuels sur les 3 derniers mois.\n",
"- ret_fund_6m_mean : Moyenne des rendements mensuels sur les 6 derniers mois.\n",
"- ret_fund_12m_mean : Moyenne des rendements mensuels sur les 12 derniers mois.\n",
"- ret_vol_3m, ret_vol_6m : Volatilité récente du fond, utile pour capter si le client agit dans des phases agitées.\n",
"- drawdown_proxy : Distance au plus haut historique.\n",
"- active_return_m :Surperformance mensuelle vs benchmark.\n",
"- active_return_3m_mean, active_return_6m_mean : Surperformance moyenne récente."
]
},
{
"cell_type": "markdown",
"id": "90772aeb-9aeb-4cc1-bbe3-80f7ca794872",
"metadata": {},
"source": [
"## Clustering par fond"
]
},
{
"cell_type": "markdown",
"id": "aa6b70d5-7d78-4b72-923f-fd82956f4284",
"metadata": {},
"source": [
"## choisir les fonds et normaliser"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "e860b58d-3f3b-457b-b574-5b94a4582a97",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Registrar Account - ID', 'Product - Isin', 'month', 'aum_qty',\n",
" 'aum_val', 'Product - Asset Type_x', 'Product - Strategy_x',\n",
" 'Product - Legal Status_x', 'Product - Is Dedie ?_x',\n",
" 'Product - Fund_x', 'Product - Shareclass Type_x',\n",
" 'Product - Shareclass Currency_x', 'Registrar Account - Region',\n",
" 'RegistrarAccount - Country', 'net_flow_qty', 'gross_flow_qty',\n",
" 'sub_qty', 'red_qty', 'n_tx', 'Product - Asset Type_y',\n",
" 'Product - Strategy_y', 'Product - Legal Status_y',\n",
" 'Product - Is Dedie ?_y', 'Product - Fund_y',\n",
" 'Product - Shareclass Type_y', 'Product - Shareclass Currency_y',\n",
" 'isin_held_flag', 'active_rel_month', 'flow_to_aum', 'turnover_rel',\n",
" 'ret_fund_m', 'ret_fund_3m_mean', 'ret_fund_6m_mean',\n",
" 'ret_fund_12m_mean', 'ret_vol_3m', 'ret_vol_6m', 'drawdown_proxy',\n",
" 'active_return_m', 'active_return_3m_mean', 'active_return_6m_mean',\n",
" 'delta_rate_m'],\n",
" dtype='object')"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_rel_m.columns"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "2fcb1f21-df60-4549-8876-b93d4126f1c5",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Product - Isin</th>\n",
" <th>Product - Isin</th>\n",
" <th>fund_family</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <th>165</th>\n",
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" <tr>\n",
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" <td>FR0010149302</td>\n",
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" <tr>\n",
" <th>371</th>\n",
" <td>FR0011269182</td>\n",
" <td>FR0011269182</td>\n",
" <td>FR0011269182</td>\n",
" </tr>\n",
" <tr>\n",
" <th>373</th>\n",
" <td>FR0011269190</td>\n",
" <td>FR0011269190</td>\n",
" <td>FR0011269190</td>\n",
" </tr>\n",
" <tr>\n",
" <th>388</th>\n",
" <td>FR0011269588</td>\n",
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" <td>FR0011269596</td>\n",
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"</div>"
],
"text/plain": [
" Product - Isin Product - Isin fund_family\n",
"0 FR0010135103 FR0010135103 FR0010135103\n",
"91 FR0010147603 FR0010147603 FR0010147603\n",
"99 FR0010148981 FR0010148981 FR0010148981\n",
"165 FR0010149112 FR0010149112 FR0010149112\n",
"177 FR0010149120 FR0010149120 FR0010149120\n",
"256 FR0010149161 FR0010149161 FR0010149161\n",
"257 FR0010149179 FR0010149179 FR0010149179\n",
"268 FR0010149203 FR0010149203 FR0010149203\n",
"269 FR0010149302 FR0010149302 FR0010149302\n",
"317 FR0010306142 FR0010306142 FR0010306142\n",
"331 FR0010312660 FR0010312660 FR0010312660\n",
"338 FR0011269067 FR0011269067 FR0011269067\n",
"364 FR0011269083 FR0011269083 FR0011269083\n",
"366 FR0011269091 FR0011269091 FR0011269091\n",
"367 FR0011269109 FR0011269109 FR0011269109\n",
"370 FR0011269125 FR0011269125 FR0011269125\n",
"371 FR0011269182 FR0011269182 FR0011269182\n",
"373 FR0011269190 FR0011269190 FR0011269190\n",
"388 FR0011269588 FR0011269588 FR0011269588\n",
"392 FR0011269596 FR0011269596 FR0011269596"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# 1) Définir une \"famille économique\" de fond à partir de Product - Fund\n",
"# ============================================================\n",
"\n",
"def normalize_fund_name(x):\n",
" if pd.isna(x):\n",
" return np.nan\n",
" s = str(x).strip().upper()\n",
" s = s.replace(\"_\", \" \").replace(\"-\", \" \")\n",
" s = re.sub(r\"\\s+\", \" \", s).strip()\n",
" # enlève une année finale type 2023 / 2024 / 2025\n",
" s = re.sub(r\"\\b20\\d{2}\\b$\", \"\", s).strip()\n",
" s = re.sub(r\"\\s+\", \" \", s).strip()\n",
" return s\n",
"\n",
"df_rel_m[\"fund_family\"] = df_rel_m[\"Product - Isin\"].apply(normalize_fund_name)\n",
"\n",
"display(\n",
" df_rel_m[[ISIN_COL, \"Product - Isin\", \"fund_family\"]]\n",
" .drop_duplicates()\n",
" .head(20)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "95004754-7f24-4769-9f64-9cfbab43ddf8",
"metadata": {},
"outputs": [],
"source": [
"# # fond : Intuition\n",
"\n",
"# On veut étudier les fonds :\n",
"\n",
"# les plus importants en encours\n",
"# avec assez de clients\n",
"# et donc assez de signal pour clusteriser"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "31a67ca0-bdcd-4461-af7d-1184b5368a06",
"metadata": {},
"outputs": [
{
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" <th>9</th>\n",
" <td>FR0010149161</td>\n",
" <td>9.442772e+08</td>\n",
" <td>165</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>LU0992631217</td>\n",
" <td>9.104539e+08</td>\n",
" <td>139</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>LU1299306321</td>\n",
" <td>8.665762e+08</td>\n",
" <td>111</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>FR001400U4S3</td>\n",
" <td>6.569309e+08</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>FR0010306142</td>\n",
" <td>6.219282e+08</td>\n",
" <td>204</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>FR0010312660</td>\n",
" <td>3.721387e+08</td>\n",
" <td>168</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" fund_family aum_val_total n_clients n_isin\n",
"0 FR0010149120 4.884612e+09 282 1\n",
"1 FR0010135103 4.502206e+09 290 1\n",
"2 FR0010148981 3.237251e+09 260 1\n",
"3 FR00140081Y1 1.421801e+09 139 1\n",
"4 LU0992624949 1.290916e+09 151 1\n",
"5 LU1623762843 1.206331e+09 201 1\n",
"6 FR001400KAV4 1.178233e+09 129 1\n",
"7 LU0336084032 1.051440e+09 229 1\n",
"8 FR0010149302 9.536118e+08 255 1\n",
"9 FR0010149161 9.442772e+08 165 1\n",
"10 LU0992631217 9.104539e+08 139 1\n",
"11 LU1299306321 8.665762e+08 111 1\n",
"12 FR001400U4S3 6.569309e+08 120 1\n",
"13 FR0010306142 6.219282e+08 204 1\n",
"14 FR0010312660 3.721387e+08 168 1"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# 2) Choisir les top fonds (au niveau fund_family)\n",
"# ============================================================\n",
"\n",
"TARGET_DATE = pd.Timestamp(\"2025-10-01\")\n",
"\n",
"top_fund_families = (\n",
" df_rel_m[df_rel_m[\"month\"] == TARGET_DATE]\n",
" .groupby(\"fund_family\", as_index=False)\n",
" .agg(\n",
" aum_val_total=(\"aum_val\", \"sum\"),\n",
" n_clients=(ID_COL, \"nunique\"),\n",
" n_isin=(ISIN_COL, \"nunique\")\n",
" )\n",
" .sort_values([\"aum_val_total\", \"n_clients\"], ascending=[False, False])\n",
" .reset_index(drop=True)\n",
")\n",
"\n",
"# garder des fonds assez gros et avec assez de clients\n",
"top_fund_families = top_fund_families[top_fund_families[\"n_clients\"] >= 20].head(15).copy()\n",
"\n",
"display(top_fund_families)\n"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "d08cc033-0bf2-42a7-9f4d-ffee5afab88a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>fund_family</th>\n",
" <th>aum_val_total</th>\n",
" <th>n_clients</th>\n",
" <th>n_isin</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>FR0010149120</td>\n",
" <td>4.884612e+09</td>\n",
" <td>282</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>FR0010135103</td>\n",
" <td>4.502206e+09</td>\n",
" <td>290</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>FR0010148981</td>\n",
" <td>3.237251e+09</td>\n",
" <td>260</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>FR00140081Y1</td>\n",
" <td>1.421801e+09</td>\n",
" <td>139</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>LU0992624949</td>\n",
" <td>1.290916e+09</td>\n",
" <td>151</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>LU1623762843</td>\n",
" <td>1.206331e+09</td>\n",
" <td>201</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>FR001400KAV4</td>\n",
" <td>1.178233e+09</td>\n",
" <td>129</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>LU0336084032</td>\n",
" <td>1.051440e+09</td>\n",
" <td>229</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>FR0010149302</td>\n",
" <td>9.536118e+08</td>\n",
" <td>255</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>FR0010149161</td>\n",
" <td>9.442772e+08</td>\n",
" <td>165</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>LU0992631217</td>\n",
" <td>9.104539e+08</td>\n",
" <td>139</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>LU1299306321</td>\n",
" <td>8.665762e+08</td>\n",
" <td>111</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>FR001400U4S3</td>\n",
" <td>6.569309e+08</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>FR0010306142</td>\n",
" <td>6.219282e+08</td>\n",
" <td>204</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>FR0010312660</td>\n",
" <td>3.721387e+08</td>\n",
" <td>168</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" fund_family aum_val_total n_clients n_isin\n",
"0 FR0010149120 4.884612e+09 282 1\n",
"1 FR0010135103 4.502206e+09 290 1\n",
"2 FR0010148981 3.237251e+09 260 1\n",
"3 FR00140081Y1 1.421801e+09 139 1\n",
"4 LU0992624949 1.290916e+09 151 1\n",
"5 LU1623762843 1.206331e+09 201 1\n",
"6 FR001400KAV4 1.178233e+09 129 1\n",
"7 LU0336084032 1.051440e+09 229 1\n",
"8 FR0010149302 9.536118e+08 255 1\n",
"9 FR0010149161 9.442772e+08 165 1\n",
"10 LU0992631217 9.104539e+08 139 1\n",
"11 LU1299306321 8.665762e+08 111 1\n",
"12 FR001400U4S3 6.569309e+08 120 1\n",
"13 FR0010306142 6.219282e+08 204 1\n",
"14 FR0010312660 3.721387e+08 168 1"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"top_fund_families = top_fund_families[\n",
" (top_fund_families[\"n_clients\"] >= 20)\n",
"].copy()\n",
"top_fund_families #15 plus gros fond en terme de aum val total et n clients"
]
},
{
"cell_type": "markdown",
"id": "b56b8070-3d60-4d18-9c2f-f800c88ec804",
"metadata": {},
"source": [
"## Clustering par fund family"
]
},
{
"cell_type": "markdown",
"id": "1c765db8-7120-4176-a90c-2fffdbc85b54",
"metadata": {},
"source": [
"### construire la base mensuelle au niveau client × fond"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "5014d562-073b-4ff8-b2c3-cf7343e1badf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Registrar Account - ID</th>\n",
" <th>fund_family</th>\n",
" <th>month</th>\n",
" <th>fund_aum_qty</th>\n",
" <th>fund_aum_val</th>\n",
" <th>net_flow_qty</th>\n",
" <th>gross_flow_qty</th>\n",
" <th>n_tx</th>\n",
" <th>ret_fund_m</th>\n",
" <th>ret_fund_6m_mean</th>\n",
" <th>portfolio_aum_total</th>\n",
" <th>fund_weight</th>\n",
" <th>held_flag</th>\n",
" <th>active_flag</th>\n",
" <th>flow_to_aum</th>\n",
" <th>turnover</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-01-01</td>\n",
" <td>49094.915</td>\n",
" <td>3.242523e+07</td>\n",
" <td>673.990</td>\n",
" <td>1045.99</td>\n",
" <td>9.0</td>\n",
" <td>0.065542</td>\n",
" <td>0.020252</td>\n",
" <td>179864.637</td>\n",
" <td>0.272953</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.013728</td>\n",
" <td>0.021305</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-02-01</td>\n",
" <td>49797.915</td>\n",
" <td>3.368032e+07</td>\n",
" <td>988.000</td>\n",
" <td>1712.00</td>\n",
" <td>12.0</td>\n",
" <td>0.025620</td>\n",
" <td>0.020209</td>\n",
" <td>186761.736</td>\n",
" <td>0.266637</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.019840</td>\n",
" <td>0.034378</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-03-01</td>\n",
" <td>50302.627</td>\n",
" <td>3.505691e+07</td>\n",
" <td>9.710</td>\n",
" <td>1561.71</td>\n",
" <td>12.0</td>\n",
" <td>0.030614</td>\n",
" <td>0.024664</td>\n",
" <td>190357.718</td>\n",
" <td>0.264252</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.000193</td>\n",
" <td>0.031046</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-04-01</td>\n",
" <td>50219.393</td>\n",
" <td>3.452433e+07</td>\n",
" <td>-123.234</td>\n",
" <td>1830.19</td>\n",
" <td>11.0</td>\n",
" <td>-0.023909</td>\n",
" <td>0.020089</td>\n",
" <td>191429.324</td>\n",
" <td>0.262338</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-0.002454</td>\n",
" <td>0.036443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>18872</td>\n",
" <td>FR0010135103</td>\n",
" <td>2015-05-01</td>\n",
" <td>53685.393</td>\n",
" <td>3.699729e+07</td>\n",
" <td>121.000</td>\n",
" <td>529.00</td>\n",
" <td>6.0</td>\n",
" <td>0.003240</td>\n",
" <td>0.018805</td>\n",
" <td>189056.475</td>\n",
" <td>0.283963</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.002254</td>\n",
" <td>0.009854</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Registrar Account - ID fund_family month fund_aum_qty fund_aum_val \\\n",
"0 18872 FR0010135103 2015-01-01 49094.915 3.242523e+07 \n",
"1 18872 FR0010135103 2015-02-01 49797.915 3.368032e+07 \n",
"2 18872 FR0010135103 2015-03-01 50302.627 3.505691e+07 \n",
"3 18872 FR0010135103 2015-04-01 50219.393 3.452433e+07 \n",
"4 18872 FR0010135103 2015-05-01 53685.393 3.699729e+07 \n",
"\n",
" net_flow_qty gross_flow_qty n_tx ret_fund_m ret_fund_6m_mean \\\n",
"0 673.990 1045.99 9.0 0.065542 0.020252 \n",
"1 988.000 1712.00 12.0 0.025620 0.020209 \n",
"2 9.710 1561.71 12.0 0.030614 0.024664 \n",
"3 -123.234 1830.19 11.0 -0.023909 0.020089 \n",
"4 121.000 529.00 6.0 0.003240 0.018805 \n",
"\n",
" portfolio_aum_total fund_weight held_flag active_flag flow_to_aum \\\n",
"0 179864.637 0.272953 1 1 0.013728 \n",
"1 186761.736 0.266637 1 1 0.019840 \n",
"2 190357.718 0.264252 1 1 0.000193 \n",
"3 191429.324 0.262338 1 1 -0.002454 \n",
"4 189056.475 0.283963 1 1 0.002254 \n",
"\n",
" turnover \n",
"0 0.021305 \n",
"1 0.034378 \n",
"2 0.031046 \n",
"3 0.036443 \n",
"4 0.009854 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"(962611, 16)\n"
]
}
],
"source": [
"# ============================================================\n",
"# 3) Construire la base mensuelle client x fund_family x mois\n",
"# ============================================================\n",
"\n",
"portfolio_month = (\n",
" df_rel_m\n",
" .groupby([ID_COL, \"month\"], as_index=False)\n",
" .agg(portfolio_aum_total=(\"aum_qty\", \"sum\"))\n",
")\n",
"\n",
"family_month = (\n",
" df_rel_m\n",
" .groupby([ID_COL, \"fund_family\", \"month\"], as_index=False)\n",
" .agg(\n",
" fund_aum_qty=(\"aum_qty\", \"sum\"),\n",
" fund_aum_val=(\"aum_val\", \"sum\"),\n",
" net_flow_qty=(\"net_flow_qty\", \"sum\"),\n",
" gross_flow_qty=(\"gross_flow_qty\", \"sum\"),\n",
" n_tx=(\"n_tx\", \"sum\"),\n",
" ret_fund_m=(\"ret_fund_m\", \"mean\"),\n",
" ret_fund_6m_mean=(\"ret_fund_6m_mean\", \"mean\"),\n",
" )\n",
" .merge(portfolio_month, on=[ID_COL, \"month\"], how=\"left\")\n",
")\n",
"\n",
"family_month[\"fund_weight\"] = family_month[\"fund_aum_qty\"] / (family_month[\"portfolio_aum_total\"].abs() + 1.0)\n",
"family_month[\"held_flag\"] = (family_month[\"fund_aum_qty\"] > 0).astype(int)\n",
"family_month[\"active_flag\"] = (family_month[\"gross_flow_qty\"] > 0).astype(int)\n",
"family_month[\"flow_to_aum\"] = family_month[\"net_flow_qty\"] / (family_month[\"fund_aum_qty\"].abs() + 1.0)\n",
"family_month[\"turnover\"] = family_month[\"gross_flow_qty\"] / (family_month[\"fund_aum_qty\"].abs() + 1.0)\n",
"\n",
"display(family_month.head())\n",
"print(family_month.shape)"
]
},
{
"cell_type": "markdown",
"id": "b1ce1fc3-9526-4d26-a791-9d46561972ef",
"metadata": {},
"source": [
"### Features :\n",
"L’idée est de capter :\n",
"\n",
" fréquence\n",
" intensité\n",
" taille\n",
" timing d’entrée/sortie\n",
" relation à la performance\n",
" rôle du fond dans le portefeuille\n",
" spécificités produit"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "b65c3b5b-d270-409d-9c4d-5218262a5d92",
"metadata": {},
"outputs": [],
"source": [
"# ============================================================\n",
"# 4) Construire le dataset client x fond pour le clustering\n",
"# ============================================================\n",
"\n",
"def build_fund_dataset(fund_family, min_months=3):\n",
" g = family_month[family_month[\"fund_family\"] == fund_family].sort_values([ID_COL, \"month\"]).copy()\n",
"\n",
" if g.empty:\n",
" return None\n",
"\n",
" g[\"prev_held\"] = g.groupby(ID_COL)[\"held_flag\"].shift(1).fillna(0).astype(int)\n",
" g[\"entry_event\"] = ((g[\"prev_held\"] == 0) & (g[\"held_flag\"] == 1)).astype(int)\n",
" g[\"exit_event\"] = ((g[\"prev_held\"] == 1) & (g[\"held_flag\"] == 0)).astype(int)\n",
" g[\"buy_month\"] = (g[\"net_flow_qty\"] > 0).astype(int)\n",
"\n",
" # rolling simples\n",
" g[\"turnover_6m_mean\"] = (\n",
" g.groupby(ID_COL)[\"turnover\"]\n",
" .transform(lambda s: s.rolling(6, min_periods=1).mean())\n",
" )\n",
"\n",
" g[\"flow_to_aum_6m_mean\"] = (\n",
" g.groupby(ID_COL)[\"flow_to_aum\"]\n",
" .transform(lambda s: s.rolling(6, min_periods=1).mean())\n",
" )\n",
"\n",
" df_fund = (\n",
" g.groupby(ID_COL, as_index=False)\n",
" .agg(\n",
" n_months_obs=(\"month\", \"nunique\"),\n",
" fund_aum_mean=(\"fund_aum_qty\", \"mean\"),\n",
" fund_aum_last=(\"fund_aum_qty\", \"last\"),\n",
" fund_weight_mean=(\"fund_weight\", \"mean\"),\n",
" fund_weight_last=(\"fund_weight\", \"last\"),\n",
" held_month_share=(\"held_flag\", \"mean\"),\n",
" active_month_share=(\"active_flag\", \"mean\"),\n",
" entry_count=(\"entry_event\", \"sum\"),\n",
" exit_count=(\"exit_event\", \"sum\"),\n",
" turnover_mean=(\"turnover\", \"mean\"),\n",
" turnover_6m_mean=(\"turnover_6m_mean\", \"last\"),\n",
" flow_to_aum_mean=(\"flow_to_aum\", \"mean\"),\n",
" flow_to_aum_6m_mean=(\"flow_to_aum_6m_mean\", \"last\"),\n",
" ret_fund_m_mean=(\"ret_fund_m\", \"mean\"),\n",
" ret_fund_6m_mean=(\"ret_fund_6m_mean\", \"mean\"),\n",
" buy_after_good_perf_share=(\"buy_month\", \"mean\"),\n",
" )\n",
" )\n",
"\n",
" # corr flux / perf\n",
" corr_block = (\n",
" g.groupby(ID_COL)\n",
" .apply(lambda z: compute_corr(z[\"net_flow_qty\"], z[\"ret_fund_m\"]))\n",
" .rename(\"corr_flow_ret_1m\")\n",
" .reset_index()\n",
" )\n",
"\n",
" df_fund = df_fund.merge(corr_block, on=ID_COL, how=\"left\")\n",
" df_fund = df_fund[df_fund[\"n_months_obs\"] >= min_months].copy()\n",
"\n",
" return df_fund"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "f3f7adf4-6f4a-414d-89e5-b8f338f65c86",
"metadata": {},
"outputs": [],
"source": [
"# ============================================================\n",
"# 5) Outils de clustering\n",
"# ============================================================\n",
"\n",
"def prep_matrix(df, feature_cols):\n",
" X = df[feature_cols].copy()\n",
" X = X.replace([np.inf, -np.inf], np.nan)\n",
"\n",
" pipe = Pipeline([\n",
" (\"imputer\", SimpleImputer(strategy=\"median\")),\n",
" (\"scaler\", RobustScaler()),\n",
" ])\n",
"\n",
" X_scaled = pipe.fit_transform(X)\n",
" return X_scaled\n",
"\n",
"def cluster_balance_summary(labels):\n",
" vc = pd.Series(labels).value_counts().sort_index()\n",
" n = int(vc.sum())\n",
" return {\n",
" \"n_clusters\": int(len(vc)),\n",
" \"min_cluster_size\": int(vc.min()),\n",
" \"max_cluster_size\": int(vc.max()),\n",
" \"dominant_cluster_share\": float(vc.max() / n) if n > 0 else np.nan,\n",
" \"singleton_clusters\": int((vc == 1).sum()),\n",
" }\n",
"\n",
"def evaluate_partition(X_scaled, labels):\n",
" out = cluster_balance_summary(labels)\n",
"\n",
" if len(np.unique(labels)) < 2:\n",
" out[\"silhouette\"] = np.nan\n",
" out[\"davies_bouldin\"] = np.nan\n",
" out[\"calinski_harabasz\"] = np.nan\n",
" return out\n",
"\n",
" out[\"silhouette\"] = silhouette_score(X_scaled, labels)\n",
" out[\"davies_bouldin\"] = davies_bouldin_score(X_scaled, labels)\n",
" out[\"calinski_harabasz\"] = calinski_harabasz_score(X_scaled, labels)\n",
" return out"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "668aed37-0f3c-4d2b-9b8f-828d4ce24889",
"metadata": {},
"outputs": [],
"source": [
"# k=2,.,10 pour chaque fond \n",
"\n",
"# ============================================================\n",
"# 6) Tester K = 2 à 10 pour un fond\n",
"# ============================================================\n",
"\n",
"FEATURE_COLS_FUND = [\n",
" \"fund_weight_mean\",\n",
" \"fund_weight_last\",\n",
" \"fund_aum_mean\",\n",
" \"fund_aum_last\",\n",
" \"held_month_share\",\n",
" \"active_month_share\",\n",
" \"entry_count\",\n",
" \"exit_count\",\n",
" \"turnover_mean\",\n",
" \"turnover_6m_mean\",\n",
" \"flow_to_aum_mean\",\n",
" \"flow_to_aum_6m_mean\",\n",
" \"corr_flow_ret_1m\",\n",
" \"buy_after_good_perf_share\",\n",
"]\n",
"\n",
"def run_kmeans_grid_for_fund(fund_family, k_min=4, k_max=10):\n",
" df_fund = build_fund_dataset(fund_family)\n",
"\n",
" if df_fund is None or df_fund.empty or len(df_fund) < 10:\n",
" return None\n",
"\n",
" feature_cols = [c for c in FEATURE_COLS_FUND if c in df_fund.columns and not df_fund[c].isna().all()]\n",
" X_scaled = prep_matrix(df_fund, feature_cols)\n",
"\n",
" rows = []\n",
" models = {}\n",
"\n",
" for k in range(k_min, k_max + 1):\n",
" if k >= len(df_fund):\n",
" continue\n",
"\n",
" km = KMeans(n_clusters=k, random_state=RANDOM_STATE, n_init=50)\n",
" labels = km.fit_predict(X_scaled)\n",
"\n",
" rows.append({\n",
" \"k\": k,\n",
" **evaluate_partition(X_scaled, labels)\n",
" })\n",
" models[k] = labels\n",
"\n",
" diag = pd.DataFrame(rows)\n",
" return {\n",
" \"data\": df_fund,\n",
" \"features\": feature_cols,\n",
" \"diag\": diag,\n",
" \"models\": models,\n",
" \"X_scaled\": X_scaled,\n",
" }"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "7ce93ee1-129d-41be-af41-958361f58bf3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nombre de fonds étudiés : 15\n",
"['FR0010149120', 'FR0010135103', 'FR0010148981', 'FR00140081Y1', 'LU0992624949', 'LU1623762843', 'FR001400KAV4', 'LU0336084032', 'FR0010149302', 'FR0010149161', 'LU0992631217', 'LU1299306321', 'FR001400U4S3', 'FR0010306142', 'FR0010312660']\n"
]
}
],
"source": [
"# ============================================================\n",
"# 7) Lancer l'étude sur tous les top fonds\n",
"# ============================================================\n",
"\n",
"fund_results = {}\n",
"\n",
"for fund_family in top_fund_families[\"fund_family\"]:\n",
" res = run_kmeans_grid_for_fund(fund_family, k_min=4, k_max=10)\n",
" if res is not None:\n",
" fund_results[fund_family] = res\n",
"\n",
"print(\"Nombre de fonds étudiés :\", len(fund_results))\n",
"print(list(fund_results.keys()))"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "bfb36134-0e65-42d5-a76c-a901a2a35816",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>k</th>\n",
" <th>n_clusters</th>\n",
" <th>min_cluster_size</th>\n",
" <th>max_cluster_size</th>\n",
" <th>dominant_cluster_share</th>\n",
" <th>singleton_clusters</th>\n",
" <th>silhouette</th>\n",
" <th>davies_bouldin</th>\n",
" <th>calinski_harabasz</th>\n",
" <th>fund_family</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>317</td>\n",
" <td>0.990625</td>\n",
" <td>3</td>\n",
" <td>0.952702</td>\n",
" <td>0.014258</td>\n",
" <td>6.236159e+04</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>314</td>\n",
" <td>0.981250</td>\n",
" <td>3</td>\n",
" <td>0.888334</td>\n",
" <td>0.260038</td>\n",
" <td>6.892536e+04</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>302</td>\n",
" <td>0.943750</td>\n",
" <td>3</td>\n",
" <td>0.779785</td>\n",
" <td>0.317455</td>\n",
" <td>7.565806e+04</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>287</td>\n",
" <td>0.896875</td>\n",
" <td>3</td>\n",
" <td>0.783468</td>\n",
" <td>0.362942</td>\n",
" <td>9.135321e+04</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>283</td>\n",
" <td>0.884375</td>\n",
" <td>3</td>\n",
" <td>0.802890</td>\n",
" <td>0.375458</td>\n",
" <td>1.060793e+05</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>283</td>\n",
" <td>0.884375</td>\n",
" <td>4</td>\n",
" <td>0.802810</td>\n",
" <td>0.353071</td>\n",
" <td>1.197763e+05</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>280</td>\n",
" <td>0.875000</td>\n",
" <td>4</td>\n",
" <td>0.785437</td>\n",
" <td>0.361689</td>\n",
" <td>1.324484e+05</td>\n",
" <td>FR0010149120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>323</td>\n",
" <td>0.964179</td>\n",
" <td>2</td>\n",
" <td>0.862526</td>\n",
" <td>0.396761</td>\n",
" <td>1.072268e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>319</td>\n",
" <td>0.952239</td>\n",
" <td>2</td>\n",
" <td>0.878178</td>\n",
" <td>0.408251</td>\n",
" <td>1.251565e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>317</td>\n",
" <td>0.946269</td>\n",
" <td>2</td>\n",
" <td>0.877437</td>\n",
" <td>0.438045</td>\n",
" <td>1.375313e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>317</td>\n",
" <td>0.946269</td>\n",
" <td>2</td>\n",
" <td>0.873553</td>\n",
" <td>0.348404</td>\n",
" <td>1.616668e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>305</td>\n",
" <td>0.910448</td>\n",
" <td>2</td>\n",
" <td>0.814795</td>\n",
" <td>0.380975</td>\n",
" <td>1.996607e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>289</td>\n",
" <td>0.862687</td>\n",
" <td>2</td>\n",
" <td>0.771577</td>\n",
" <td>0.441611</td>\n",
" <td>2.164950e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>292</td>\n",
" <td>0.871642</td>\n",
" <td>4</td>\n",
" <td>0.780776</td>\n",
" <td>0.344281</td>\n",
" <td>2.352434e+07</td>\n",
" <td>FR0010135103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>311</td>\n",
" <td>0.984177</td>\n",
" <td>2</td>\n",
" <td>0.951234</td>\n",
" <td>0.246002</td>\n",
" <td>1.197836e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>308</td>\n",
" <td>0.974684</td>\n",
" <td>3</td>\n",
" <td>0.923568</td>\n",
" <td>0.291831</td>\n",
" <td>1.194490e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>307</td>\n",
" <td>0.971519</td>\n",
" <td>4</td>\n",
" <td>0.925231</td>\n",
" <td>0.295944</td>\n",
" <td>1.336923e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>306</td>\n",
" <td>0.968354</td>\n",
" <td>4</td>\n",
" <td>0.901949</td>\n",
" <td>0.196162</td>\n",
" <td>1.719620e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>298</td>\n",
" <td>0.943038</td>\n",
" <td>4</td>\n",
" <td>0.879011</td>\n",
" <td>0.231291</td>\n",
" <td>2.574472e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>297</td>\n",
" <td>0.939873</td>\n",
" <td>5</td>\n",
" <td>0.883001</td>\n",
" <td>0.222999</td>\n",
" <td>2.976192e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>291</td>\n",
" <td>0.920886</td>\n",
" <td>5</td>\n",
" <td>0.853795</td>\n",
" <td>0.266340</td>\n",
" <td>3.422146e+05</td>\n",
" <td>FR0010148981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>130</td>\n",
" <td>0.928571</td>\n",
" <td>2</td>\n",
" <td>0.846660</td>\n",
" <td>0.272805</td>\n",
" <td>1.058871e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>124</td>\n",
" <td>0.885714</td>\n",
" <td>2</td>\n",
" <td>0.801199</td>\n",
" <td>0.291206</td>\n",
" <td>1.457334e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>116</td>\n",
" <td>0.828571</td>\n",
" <td>2</td>\n",
" <td>0.798078</td>\n",
" <td>0.354293</td>\n",
" <td>2.012263e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>116</td>\n",
" <td>0.828571</td>\n",
" <td>3</td>\n",
" <td>0.797375</td>\n",
" <td>0.302775</td>\n",
" <td>2.397924e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>115</td>\n",
" <td>0.821429</td>\n",
" <td>4</td>\n",
" <td>0.784789</td>\n",
" <td>0.243282</td>\n",
" <td>3.247377e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>115</td>\n",
" <td>0.821429</td>\n",
" <td>4</td>\n",
" <td>0.776258</td>\n",
" <td>0.354855</td>\n",
" <td>3.919863e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>106</td>\n",
" <td>0.757143</td>\n",
" <td>4</td>\n",
" <td>0.678970</td>\n",
" <td>0.369964</td>\n",
" <td>4.284648e+03</td>\n",
" <td>FR00140081Y1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>185</td>\n",
" <td>0.968586</td>\n",
" <td>2</td>\n",
" <td>0.937635</td>\n",
" <td>0.092228</td>\n",
" <td>7.051123e+03</td>\n",
" <td>LU0992624949</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>183</td>\n",
" <td>0.958115</td>\n",
" <td>2</td>\n",
" <td>0.939791</td>\n",
" <td>0.174930</td>\n",
" <td>1.430396e+04</td>\n",
" <td>LU0992624949</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" k n_clusters min_cluster_size max_cluster_size \\\n",
"0 4 4 1 317 \n",
"1 5 5 1 314 \n",
"2 6 6 1 302 \n",
"3 7 7 1 287 \n",
"4 8 8 1 283 \n",
"5 9 9 1 283 \n",
"6 10 10 1 280 \n",
"7 4 4 1 323 \n",
"8 5 5 1 319 \n",
"9 6 6 1 317 \n",
"10 7 7 1 317 \n",
"11 8 8 1 305 \n",
"12 9 9 1 289 \n",
"13 10 10 1 292 \n",
"14 4 4 1 311 \n",
"15 5 5 1 308 \n",
"16 6 6 1 307 \n",
"17 7 7 1 306 \n",
"18 8 8 1 298 \n",
"19 9 9 1 297 \n",
"20 10 10 1 291 \n",
"21 4 4 1 130 \n",
"22 5 5 1 124 \n",
"23 6 6 1 116 \n",
"24 7 7 1 116 \n",
"25 8 8 1 115 \n",
"26 9 9 1 115 \n",
"27 10 10 1 106 \n",
"28 4 4 1 185 \n",
"29 5 5 1 183 \n",
"\n",
" dominant_cluster_share singleton_clusters silhouette davies_bouldin \\\n",
"0 0.990625 3 0.952702 0.014258 \n",
"1 0.981250 3 0.888334 0.260038 \n",
"2 0.943750 3 0.779785 0.317455 \n",
"3 0.896875 3 0.783468 0.362942 \n",
"4 0.884375 3 0.802890 0.375458 \n",
"5 0.884375 4 0.802810 0.353071 \n",
"6 0.875000 4 0.785437 0.361689 \n",
"7 0.964179 2 0.862526 0.396761 \n",
"8 0.952239 2 0.878178 0.408251 \n",
"9 0.946269 2 0.877437 0.438045 \n",
"10 0.946269 2 0.873553 0.348404 \n",
"11 0.910448 2 0.814795 0.380975 \n",
"12 0.862687 2 0.771577 0.441611 \n",
"13 0.871642 4 0.780776 0.344281 \n",
"14 0.984177 2 0.951234 0.246002 \n",
"15 0.974684 3 0.923568 0.291831 \n",
"16 0.971519 4 0.925231 0.295944 \n",
"17 0.968354 4 0.901949 0.196162 \n",
"18 0.943038 4 0.879011 0.231291 \n",
"19 0.939873 5 0.883001 0.222999 \n",
"20 0.920886 5 0.853795 0.266340 \n",
"21 0.928571 2 0.846660 0.272805 \n",
"22 0.885714 2 0.801199 0.291206 \n",
"23 0.828571 2 0.798078 0.354293 \n",
"24 0.828571 3 0.797375 0.302775 \n",
"25 0.821429 4 0.784789 0.243282 \n",
"26 0.821429 4 0.776258 0.354855 \n",
"27 0.757143 4 0.678970 0.369964 \n",
"28 0.968586 2 0.937635 0.092228 \n",
"29 0.958115 2 0.939791 0.174930 \n",
"\n",
" calinski_harabasz fund_family \n",
"0 6.236159e+04 FR0010149120 \n",
"1 6.892536e+04 FR0010149120 \n",
"2 7.565806e+04 FR0010149120 \n",
"3 9.135321e+04 FR0010149120 \n",
"4 1.060793e+05 FR0010149120 \n",
"5 1.197763e+05 FR0010149120 \n",
"6 1.324484e+05 FR0010149120 \n",
"7 1.072268e+07 FR0010135103 \n",
"8 1.251565e+07 FR0010135103 \n",
"9 1.375313e+07 FR0010135103 \n",
"10 1.616668e+07 FR0010135103 \n",
"11 1.996607e+07 FR0010135103 \n",
"12 2.164950e+07 FR0010135103 \n",
"13 2.352434e+07 FR0010135103 \n",
"14 1.197836e+05 FR0010148981 \n",
"15 1.194490e+05 FR0010148981 \n",
"16 1.336923e+05 FR0010148981 \n",
"17 1.719620e+05 FR0010148981 \n",
"18 2.574472e+05 FR0010148981 \n",
"19 2.976192e+05 FR0010148981 \n",
"20 3.422146e+05 FR0010148981 \n",
"21 1.058871e+03 FR00140081Y1 \n",
"22 1.457334e+03 FR00140081Y1 \n",
"23 2.012263e+03 FR00140081Y1 \n",
"24 2.397924e+03 FR00140081Y1 \n",
"25 3.247377e+03 FR00140081Y1 \n",
"26 3.919863e+03 FR00140081Y1 \n",
"27 4.284648e+03 FR00140081Y1 \n",
"28 7.051123e+03 LU0992624949 \n",
"29 1.430396e+04 LU0992624949 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ============================================================\n",
"# 8) Tableau de synthèse par fond et par K\n",
"# ============================================================\n",
"\n",
"rows = []\n",
"\n",
"for fund_family, res in fund_results.items():\n",
" diag = res[\"diag\"].copy()\n",
" diag[\"fund_family\"] = fund_family\n",
" rows.append(diag)\n",
"\n",
"df_fund_diag = pd.concat(rows, axis=0).reset_index(drop=True)\n",
"\n",
"display(df_fund_diag.head(30))"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "66ea6e29-47dd-4fc0-900f-225d3c8a2b1d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"==============================\n",
"FOND : FR0010149120\n",
"K retenu : 4\n",
"cluster\n",
"0 317\n",
"1 1\n",
"2 1\n",
"3 1\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010135103\n",
"K retenu : 5\n",
"cluster\n",
"0 4\n",
"1 1\n",
"2 319\n",
"3 1\n",
"4 10\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010148981\n",
"K retenu : 4\n",
"cluster\n",
"0 311\n",
"1 1\n",
"2 1\n",
"3 3\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR00140081Y1\n",
"K retenu : 4\n",
"cluster\n",
"0 130\n",
"1 1\n",
"2 1\n",
"3 8\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : LU0992624949\n",
"K retenu : 5\n",
"cluster\n",
"0 183\n",
"1 1\n",
"2 1\n",
"3 4\n",
"4 2\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : LU1623762843\n",
"K retenu : 5\n",
"cluster\n",
"0 206\n",
"1 1\n",
"2 1\n",
"3 3\n",
"4 1\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR001400KAV4\n",
"K retenu : 4\n",
"cluster\n",
"0 125\n",
"1 1\n",
"2 1\n",
"3 2\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : LU0336084032\n",
"K retenu : 4\n",
"cluster\n",
"0 265\n",
"1 1\n",
"2 5\n",
"3 1\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010149302\n",
"K retenu : 4\n",
"cluster\n",
"0 309\n",
"1 1\n",
"2 1\n",
"3 2\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010149161\n",
"K retenu : 4\n",
"cluster\n",
"0 203\n",
"1 1\n",
"2 1\n",
"3 1\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : LU0992631217\n",
"K retenu : 4\n",
"cluster\n",
"0 156\n",
"1 1\n",
"2 1\n",
"3 3\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : LU1299306321\n",
"K retenu : 5\n",
"cluster\n",
"0 9\n",
"1 3\n",
"2 110\n",
"3 4\n",
"4 5\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR001400U4S3\n",
"K retenu : 4\n",
"cluster\n",
"0 111\n",
"1 1\n",
"2 3\n",
"3 1\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010306142\n",
"K retenu : 4\n",
"cluster\n",
"0 247\n",
"1 1\n",
"2 3\n",
"3 2\n",
"Name: count, dtype: int64\n",
"\n",
"==============================\n",
"FOND : FR0010312660\n",
"K retenu : 4\n",
"cluster\n",
"0 2\n",
"1 205\n",
"2 9\n",
"3 2\n",
"Name: count, dtype: int64\n"
]
}
],
"source": [
"# ============================================================\n",
"# 9) Choisir un K par fond et afficher les tailles des clusters\n",
"# Ici : on prend le meilleur silhouette sans singleton si possible\n",
"# ============================================================\n",
"\n",
"best_partitions = {}\n",
"\n",
"for fund_family, res in fund_results.items():\n",
" diag = res[\"diag\"].copy()\n",
"\n",
" diag2 = diag[diag[\"singleton_clusters\"] == 0].copy()\n",
" if diag2.empty:\n",
" diag2 = diag.copy()\n",
"\n",
" diag2 = diag2.sort_values(\n",
" [\"silhouette\", \"dominant_cluster_share\"],\n",
" ascending=[False, True]\n",
" )\n",
"\n",
" best_k = int(diag2.iloc[0][\"k\"])\n",
" labels = res[\"models\"][best_k]\n",
"\n",
" df_f = res[\"data\"].copy()\n",
" df_f[\"cluster\"] = labels\n",
"\n",
" best_partitions[fund_family] = {\n",
" \"k\": best_k,\n",
" \"data\": df_f\n",
" }\n",
"\n",
" print(\"\\n==============================\")\n",
" print(\"FOND :\", fund_family)\n",
" print(\"K retenu :\", best_k)\n",
" print(df_f[\"cluster\"].value_counts().sort_index())"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "e5e397ed-3514-4377-8c9b-ed474e70f8b8",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 700x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#voir si cluster separer visuellemt \n",
"# ============================================================\n",
"# 10) Visualisation PCA d'un fond\n",
"# ============================================================\n",
"\n",
"example_fund = list(best_partitions.keys())[-1] #2 clusters: 7 et 211\n",
"\n",
"df_plot = best_partitions[example_fund][\"data\"].copy()\n",
"feature_cols = fund_results[example_fund][\"features\"]\n",
"X_scaled = prep_matrix(df_plot, feature_cols)\n",
"\n",
"pca = PCA(n_components=2, random_state=RANDOM_STATE)\n",
"X_pca = pca.fit_transform(X_scaled)\n",
"\n",
"plot_df = pd.DataFrame({\n",
" \"PC1\": X_pca[:, 0],\n",
" \"PC2\": X_pca[:, 1],\n",
" \"cluster\": df_plot[\"cluster\"].astype(str)\n",
"})\n",
"\n",
"plt.figure(figsize=(7, 5))\n",
"sns.scatterplot(data=plot_df, x=\"PC1\", y=\"PC2\", hue=\"cluster\")\n",
"plt.title(f\"PCA - {example_fund}\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "c38c38bf-0dad-4baf-9d2d-acd4087b3bc3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>cluster</th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>fund_weight_mean</th>\n",
" <td>0.002533</td>\n",
" <td>0.025296</td>\n",
" <td>0.107030</td>\n",
" <td>0.411546</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fund_weight_last</th>\n",
" <td>0.000000</td>\n",
" <td>0.016294</td>\n",
" <td>0.000065</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fund_aum_mean</th>\n",
" <td>862.764360</td>\n",
" <td>4892.213434</td>\n",
" <td>17080.303897</td>\n",
" <td>198436.767999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fund_aum_last</th>\n",
" <td>0.000000</td>\n",
" <td>1587.012888</td>\n",
" <td>1.060556</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>held_month_share</th>\n",
" <td>0.757053</td>\n",
" <td>0.765711</td>\n",
" <td>0.957997</td>\n",
" <td>0.546661</td>\n",
" </tr>\n",
" <tr>\n",
" <th>active_month_share</th>\n",
" <td>0.140641</td>\n",
" <td>0.238654</td>\n",
" <td>0.392454</td>\n",
" <td>0.535638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>entry_count</th>\n",
" <td>1.500000</td>\n",
" <td>1.526829</td>\n",
" <td>1.222222</td>\n",
" <td>2.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>exit_count</th>\n",
" <td>1.500000</td>\n",
" <td>0.907317</td>\n",
" <td>1.111111</td>\n",
" <td>2.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>turnover_mean</th>\n",
" <td>2.568131</td>\n",
" <td>1.852132</td>\n",
" <td>4.854434</td>\n",
" <td>1282.868308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>turnover_6m_mean</th>\n",
" <td>40.589203</td>\n",
" <td>0.449401</td>\n",
" <td>12.469088</td>\n",
" <td>44.754050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>flow_to_aum_mean</th>\n",
" <td>-2.567005</td>\n",
" <td>-1.111582</td>\n",
" <td>-2.290458</td>\n",
" <td>-586.056551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>flow_to_aum_6m_mean</th>\n",
" <td>-40.584220</td>\n",
" <td>0.075295</td>\n",
" <td>-12.401695</td>\n",
" <td>-5.753449</td>\n",
" </tr>\n",
" <tr>\n",
" <th>corr_flow_ret_1m</th>\n",
" <td>-0.021390</td>\n",
" <td>0.030890</td>\n",
" <td>0.038466</td>\n",
" <td>0.137629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>buy_after_good_perf_share</th>\n",
" <td>0.099237</td>\n",
" <td>0.089815</td>\n",
" <td>0.131206</td>\n",
" <td>0.030287</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"cluster 0 1 2 \\\n",
"fund_weight_mean 0.002533 0.025296 0.107030 \n",
"fund_weight_last 0.000000 0.016294 0.000065 \n",
"fund_aum_mean 862.764360 4892.213434 17080.303897 \n",
"fund_aum_last 0.000000 1587.012888 1.060556 \n",
"held_month_share 0.757053 0.765711 0.957997 \n",
"active_month_share 0.140641 0.238654 0.392454 \n",
"entry_count 1.500000 1.526829 1.222222 \n",
"exit_count 1.500000 0.907317 1.111111 \n",
"turnover_mean 2.568131 1.852132 4.854434 \n",
"turnover_6m_mean 40.589203 0.449401 12.469088 \n",
"flow_to_aum_mean -2.567005 -1.111582 -2.290458 \n",
"flow_to_aum_6m_mean -40.584220 0.075295 -12.401695 \n",
"corr_flow_ret_1m -0.021390 0.030890 0.038466 \n",
"buy_after_good_perf_share 0.099237 0.089815 0.131206 \n",
"\n",
"cluster 3 \n",
"fund_weight_mean 0.411546 \n",
"fund_weight_last 0.000000 \n",
"fund_aum_mean 198436.767999 \n",
"fund_aum_last 0.000000 \n",
"held_month_share 0.546661 \n",
"active_month_share 0.535638 \n",
"entry_count 2.500000 \n",
"exit_count 2.500000 \n",
"turnover_mean 1282.868308 \n",
"turnover_6m_mean 44.754050 \n",
"flow_to_aum_mean -586.056551 \n",
"flow_to_aum_6m_mean -5.753449 \n",
"corr_flow_ret_1m 0.137629 \n",
"buy_after_good_perf_share 0.030287 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#profil moyen des clusters par un fond \n",
"\n",
"# ============================================================\n",
"# 11) Profil moyen des clusters pour un fond\n",
"# ============================================================\n",
"\n",
"display(\n",
" best_partitions[example_fund][\"data\"]\n",
" .groupby(\"cluster\")[feature_cols]\n",
" .mean()\n",
" .T\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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