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+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# Estratégia Magic Formula de Joel Greenblatt\n",
+    "\n",
+    "A Magic Formula é uma estratégia de investimento que classifica ações com base em dois critérios principais:\n",
+    "\n",
+    "- **Qualidade**: medida pelo Retorno sobre o Capital Investido (ROIC)\n",
+    "- **Valor**: medida pelo Rendimento de Lucros (Earnings Yield)"
+   ],
+   "id": "f0f9bbafd34ec9e"
+  },
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:27:04.058395Z",
+     "start_time": "2025-04-13T20:26:52.206786Z"
+    }
+   },
+   "source": "!pip install pandas numpy requests beautifulsoup4",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/usr/bin/bash: warning: setlocale: LC_ALL: cannot change locale (en_US.UTF-8): No such file or directory\r\n",
+      "Collecting pandas\r\n",
+      "  Using cached pandas-2.2.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (89 kB)\r\n",
+      "Collecting numpy\r\n",
+      "  Using cached numpy-2.2.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (62 kB)\r\n",
+      "Collecting yfinance\r\n",
+      "  Using cached yfinance-0.2.55-py2.py3-none-any.whl.metadata (5.8 kB)\r\n",
+      "Requirement already satisfied: requests in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (2.32.3)\r\n",
+      "Requirement already satisfied: beautifulsoup4 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (4.13.3)\r\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from pandas) (2.9.0.post0)\r\n",
+      "Collecting pytz>=2020.1 (from pandas)\r\n",
+      "  Using cached pytz-2025.2-py2.py3-none-any.whl.metadata (22 kB)\r\n",
+      "Collecting tzdata>=2022.7 (from pandas)\r\n",
+      "  Using cached tzdata-2025.2-py2.py3-none-any.whl.metadata (1.4 kB)\r\n",
+      "Collecting multitasking>=0.0.7 (from yfinance)\r\n",
+      "  Using cached multitasking-0.0.11-py3-none-any.whl.metadata (5.5 kB)\r\n",
+      "Requirement already satisfied: platformdirs>=2.0.0 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from yfinance) (4.3.7)\r\n",
+      "Collecting frozendict>=2.3.4 (from yfinance)\r\n",
+      "  Using cached frozendict-2.4.6-py313-none-any.whl.metadata (23 kB)\r\n",
+      "Collecting peewee>=3.16.2 (from yfinance)\r\n",
+      "  Using cached peewee-3.17.9-cp313-cp313-linux_x86_64.whl\r\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from requests) (3.4.1)\r\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from requests) (3.10)\r\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from requests) (2.4.0)\r\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from requests) (2025.1.31)\r\n",
+      "Requirement already satisfied: soupsieve>1.2 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from beautifulsoup4) (2.6)\r\n",
+      "Requirement already satisfied: typing-extensions>=4.0.0 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from beautifulsoup4) (4.13.2)\r\n",
+      "Requirement already satisfied: six>=1.5 in /home/geron/Projects/python-for-finances/.venv/lib/python3.13/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\r\n",
+      "Using cached pandas-2.2.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.7 MB)\r\n",
+      "Using cached numpy-2.2.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.1 MB)\r\n",
+      "Using cached yfinance-0.2.55-py2.py3-none-any.whl (109 kB)\r\n",
+      "Using cached frozendict-2.4.6-py313-none-any.whl (16 kB)\r\n",
+      "Using cached multitasking-0.0.11-py3-none-any.whl (8.5 kB)\r\n",
+      "Using cached pytz-2025.2-py2.py3-none-any.whl (509 kB)\r\n",
+      "Using cached tzdata-2025.2-py2.py3-none-any.whl (347 kB)\r\n",
+      "Installing collected packages: pytz, peewee, multitasking, tzdata, numpy, frozendict, pandas, yfinance\r\n",
+      "Successfully installed frozendict-2.4.6 multitasking-0.0.11 numpy-2.2.4 pandas-2.2.3 peewee-3.17.9 pytz-2025.2 tzdata-2025.2 yfinance-0.2.55\r\n"
+     ]
+    }
+   ],
+   "execution_count": 1
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:27:40.137379Z",
+     "start_time": "2025-04-13T20:27:39.725248Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import requests\n",
+    "from bs4 import BeautifulSoup"
+   ],
+   "id": "737ea007e532eace",
+   "outputs": [],
+   "execution_count": 2
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:39.461968Z",
+     "start_time": "2025-04-13T20:55:39.453184Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "def obter_acoes_b3():\n",
+    "    url = \"https://www.fundamentus.com.br/resultado.php\"\n",
+    "    headers = {\n",
+    "        'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64; rv:136.0) Gecko/20100101 Firefox/136.0'\n",
+    "    }\n",
+    "\n",
+    "    response = requests.get(url, headers=headers)\n",
+    "    soup = BeautifulSoup(response.text, 'html.parser')\n",
+    "\n",
+    "    tabela = soup.find('table', {'id': 'resultado'})\n",
+    "    dados = []\n",
+    "\n",
+    "    for linha in tabela.find_all('tr')[1:]:\n",
+    "        colunas = linha.find_all('td')\n",
+    "        ticker = colunas[0].text.strip()\n",
+    "\n",
+    "        # Extrair métricas fundamentalistas\n",
+    "        ev_ebit = colunas[10].text.strip().replace('.', '').replace(',', '.')\n",
+    "        roic = colunas[16].text.strip().replace('.', '').replace(',', '.')\n",
+    "        liquidez = colunas[18].text.strip().replace('.', '').replace(',', '.')\n",
+    "        divida_pl = colunas[19].text.strip().replace('.', '').replace(',', '.')\n",
+    "\n",
+    "        # Converter para float, tratando valores inválidos\n",
+    "        try:\n",
+    "            ev_ebit = float(ev_ebit) if ev_ebit != '-' else np.nan\n",
+    "            roic = float(roic[:-1]) if '%' in roic else float(roic)\n",
+    "            liquidez = float(liquidez)\n",
+    "            divida_pl = float(divida_pl)\n",
+    "\n",
+    "            # Calcular Earnings Yield (inverso do EV/EBIT)\n",
+    "            earnings_yield = 1 / ev_ebit if ev_ebit > 0 else np.nan\n",
+    "\n",
+    "            dados.append({\n",
+    "                'Ticker': ticker,\n",
+    "                'ROIC': roic,\n",
+    "                'EV/EBIT': ev_ebit,\n",
+    "                'Earnings Yield': earnings_yield,\n",
+    "                'Liquidez Media': liquidez,\n",
+    "                'Divida Bruta/PL': divida_pl\n",
+    "            })\n",
+    "        except (ValueError, ZeroDivisionError):\n",
+    "            continue\n",
+    "\n",
+    "    return pd.DataFrame(dados)"
+   ],
+   "id": "5a0af3f299da432",
+   "outputs": [],
+   "execution_count": 33
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:40.849860Z",
+     "start_time": "2025-04-13T20:55:40.092717Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "acoes_df = obter_acoes_b3()\n",
+    "acoes_df"
+   ],
+   "id": "eee764781bd7c385",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "     Ticker    ROIC  EV/EBIT  Earnings Yield  Liquidez Media  Divida Bruta/PL\n",
+       "0     PORP4   -2.08     0.00             NaN    2.239900e+07             0.00\n",
+       "1     POPR4   19.93     0.00             NaN    5.458030e+08             0.82\n",
+       "2     MNSA3  145.70     0.00             NaN   -9.105000e+06            -6.52\n",
+       "3     CFLU4   32.15     0.00             NaN    6.035100e+07             0.06\n",
+       "4     CSTB4   20.11     0.00             NaN    8.420670e+09             0.14\n",
+       "..      ...     ...      ...             ...             ...              ...\n",
+       "986   UBBR4    0.33     0.00             NaN    1.031720e+10             0.00\n",
+       "987   VSTE3    0.06    25.50        0.039216    1.043280e+09             0.33\n",
+       "988  UBBR11    0.33     0.00             NaN    1.031720e+10             0.00\n",
+       "989   UBBR3    0.33     0.00             NaN    1.031720e+10             0.00\n",
+       "990   LJQQ3    0.03     4.86        0.205761    5.459970e+08             0.98\n",
+       "\n",
+       "[991 rows x 6 columns]"
+      ],
+      "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>Ticker</th>\n",
+       "      <th>ROIC</th>\n",
+       "      <th>EV/EBIT</th>\n",
+       "      <th>Earnings Yield</th>\n",
+       "      <th>Liquidez Media</th>\n",
+       "      <th>Divida Bruta/PL</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>PORP4</td>\n",
+       "      <td>-2.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.239900e+07</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>POPR4</td>\n",
+       "      <td>19.93</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5.458030e+08</td>\n",
+       "      <td>0.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>MNSA3</td>\n",
+       "      <td>145.70</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-9.105000e+06</td>\n",
+       "      <td>-6.52</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CFLU4</td>\n",
+       "      <td>32.15</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>6.035100e+07</td>\n",
+       "      <td>0.06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>CSTB4</td>\n",
+       "      <td>20.11</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.420670e+09</td>\n",
+       "      <td>0.14</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>986</th>\n",
+       "      <td>UBBR4</td>\n",
+       "      <td>0.33</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.031720e+10</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>987</th>\n",
+       "      <td>VSTE3</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>25.50</td>\n",
+       "      <td>0.039216</td>\n",
+       "      <td>1.043280e+09</td>\n",
+       "      <td>0.33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>988</th>\n",
+       "      <td>UBBR11</td>\n",
+       "      <td>0.33</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.031720e+10</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>989</th>\n",
+       "      <td>UBBR3</td>\n",
+       "      <td>0.33</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.031720e+10</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>990</th>\n",
+       "      <td>LJQQ3</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>4.86</td>\n",
+       "      <td>0.205761</td>\n",
+       "      <td>5.459970e+08</td>\n",
+       "      <td>0.98</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>991 rows × 6 columns</p>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 34
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:41.458678Z",
+     "start_time": "2025-04-13T20:55:41.454935Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "def filtrar_acoes(df):\n",
+    "    \"\"\"Filtra ações conforme recomendação de Greenblatt\"\"\"\n",
+    "\n",
+    "    # Remover empresas com baixa liquidez (menor que 1M)\n",
+    "    df_filtrado = df[df['Liquidez Media'] > 1_000_000]\n",
+    "\n",
+    "    # Remover empresas com dívida muito alta\n",
+    "    df_filtrado = df_filtrado[(df_filtrado['Divida Bruta/PL'] > 0) & (df_filtrado['Divida Bruta/PL'] < 4)]\n",
+    "\n",
+    "    return df_filtrado"
+   ],
+   "id": "f91f75a047ff57bf",
+   "outputs": [],
+   "execution_count": 35
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:42.184602Z",
+     "start_time": "2025-04-13T20:55:42.181491Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "acoes_df = filtrar_acoes(acoes_df)",
+   "id": "17276b69637e2cbe",
+   "outputs": [],
+   "execution_count": 36
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:42.796804Z",
+     "start_time": "2025-04-13T20:55:42.793964Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "def magic_formula(df):\n",
+    "    # Remover dados inválidos\n",
+    "    df = df[df['Earnings Yield'].notna()].copy()\n",
+    "\n",
+    "    # Classificar as ações (ranking)\n",
+    "    df['ROIC_Rank'] = df['ROIC'].rank(ascending=False)\n",
+    "    df['EY_Rank'] = df['Earnings Yield'].rank(ascending=False)\n",
+    "\n",
+    "    # Calcular o ranking combinado\n",
+    "    df['Magic_Rank'] = df['ROIC_Rank'] + df['EY_Rank']\n",
+    "\n",
+    "    # Ordenar pelo ranking combinado (do menor para o maior)\n",
+    "    df_result = df.sort_values('Magic_Rank')\n",
+    "\n",
+    "    return df_result"
+   ],
+   "id": "32611e00190bf868",
+   "outputs": [],
+   "execution_count": 37
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:43.475901Z",
+     "start_time": "2025-04-13T20:55:43.454407Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "resultado = magic_formula(acoes_df)\n",
+    "\n",
+    "# Selecionar as 15 melhores ações\n",
+    "top_acoes = resultado.head(15)\n",
+    "top_acoes"
+   ],
+   "id": "625cd15e9bf429eb",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "     Ticker   ROIC  EV/EBIT  Earnings Yield  Liquidez Media  Divida Bruta/PL  \\\n",
+       "453   AHEB3  61.47     2.17        0.460829    2.444130e+08             0.02   \n",
+       "455   AHEB5  61.47     2.48        0.403226    2.444130e+08             0.02   \n",
+       "459   AHEB6  61.47     2.80        0.357143    2.444130e+08             0.02   \n",
+       "367   CSPC4  45.33     1.43        0.699301    2.126670e+09             1.48   \n",
+       "371   CSPC3  45.33     1.43        0.699301    2.126670e+09             1.48   \n",
+       "433   SYNE3  50.87     2.41        0.414938    1.073780e+09             0.76   \n",
+       "435   CPFG4  36.99     0.95        1.052632    3.614430e+09             0.42   \n",
+       "437   CPFG3  36.99     0.97        1.030928    3.614430e+09             0.42   \n",
+       "396  PALF11  46.56     2.84        0.352113    3.055110e+09             3.00   \n",
+       "403   PALF5  46.56     2.87        0.348432    3.055110e+09             3.00   \n",
+       "405   PALF3  46.56     2.88        0.347222    3.055110e+09             3.00   \n",
+       "380   ENER3  51.72     3.09        0.323625    1.167120e+09             3.89   \n",
+       "381   ENER6  51.72     3.09        0.323625    1.167120e+09             3.89   \n",
+       "379   ENER5  51.72     3.09        0.323625    1.167120e+09             3.89   \n",
+       "382  TEFC11  46.72     3.45        0.289855    4.585600e+10             2.95   \n",
+       "\n",
+       "     ROIC_Rank  EY_Rank  Magic_Rank  \n",
+       "453        7.0     25.0        32.0  \n",
+       "455        7.0     30.0        37.0  \n",
+       "459        7.0     32.0        39.0  \n",
+       "367       23.5     16.5        40.0  \n",
+       "371       23.5     16.5        40.0  \n",
+       "433       16.0     28.0        44.0  \n",
+       "435       37.5      7.0        44.5  \n",
+       "437       37.5      8.0        45.5  \n",
+       "396       19.0     33.0        52.0  \n",
+       "403       19.0     34.0        53.0  \n",
+       "405       19.0     35.0        54.0  \n",
+       "380       11.0     44.0        55.0  \n",
+       "381       11.0     44.0        55.0  \n",
+       "379       11.0     44.0        55.0  \n",
+       "382       17.0     52.0        69.0  "
+      ],
+      "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>Ticker</th>\n",
+       "      <th>ROIC</th>\n",
+       "      <th>EV/EBIT</th>\n",
+       "      <th>Earnings Yield</th>\n",
+       "      <th>Liquidez Media</th>\n",
+       "      <th>Divida Bruta/PL</th>\n",
+       "      <th>ROIC_Rank</th>\n",
+       "      <th>EY_Rank</th>\n",
+       "      <th>Magic_Rank</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>453</th>\n",
+       "      <td>AHEB3</td>\n",
+       "      <td>61.47</td>\n",
+       "      <td>2.17</td>\n",
+       "      <td>0.460829</td>\n",
+       "      <td>2.444130e+08</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>455</th>\n",
+       "      <td>AHEB5</td>\n",
+       "      <td>61.47</td>\n",
+       "      <td>2.48</td>\n",
+       "      <td>0.403226</td>\n",
+       "      <td>2.444130e+08</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>37.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>459</th>\n",
+       "      <td>AHEB6</td>\n",
+       "      <td>61.47</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>0.357143</td>\n",
+       "      <td>2.444130e+08</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>367</th>\n",
+       "      <td>CSPC4</td>\n",
+       "      <td>45.33</td>\n",
+       "      <td>1.43</td>\n",
+       "      <td>0.699301</td>\n",
+       "      <td>2.126670e+09</td>\n",
+       "      <td>1.48</td>\n",
+       "      <td>23.5</td>\n",
+       "      <td>16.5</td>\n",
+       "      <td>40.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>371</th>\n",
+       "      <td>CSPC3</td>\n",
+       "      <td>45.33</td>\n",
+       "      <td>1.43</td>\n",
+       "      <td>0.699301</td>\n",
+       "      <td>2.126670e+09</td>\n",
+       "      <td>1.48</td>\n",
+       "      <td>23.5</td>\n",
+       "      <td>16.5</td>\n",
+       "      <td>40.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>433</th>\n",
+       "      <td>SYNE3</td>\n",
+       "      <td>50.87</td>\n",
+       "      <td>2.41</td>\n",
+       "      <td>0.414938</td>\n",
+       "      <td>1.073780e+09</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>44.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>435</th>\n",
+       "      <td>CPFG4</td>\n",
+       "      <td>36.99</td>\n",
+       "      <td>0.95</td>\n",
+       "      <td>1.052632</td>\n",
+       "      <td>3.614430e+09</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>37.5</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>44.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>437</th>\n",
+       "      <td>CPFG3</td>\n",
+       "      <td>36.99</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>1.030928</td>\n",
+       "      <td>3.614430e+09</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>37.5</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>45.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>396</th>\n",
+       "      <td>PALF11</td>\n",
+       "      <td>46.56</td>\n",
+       "      <td>2.84</td>\n",
+       "      <td>0.352113</td>\n",
+       "      <td>3.055110e+09</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>52.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>403</th>\n",
+       "      <td>PALF5</td>\n",
+       "      <td>46.56</td>\n",
+       "      <td>2.87</td>\n",
+       "      <td>0.348432</td>\n",
+       "      <td>3.055110e+09</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>53.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>405</th>\n",
+       "      <td>PALF3</td>\n",
+       "      <td>46.56</td>\n",
+       "      <td>2.88</td>\n",
+       "      <td>0.347222</td>\n",
+       "      <td>3.055110e+09</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>54.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>380</th>\n",
+       "      <td>ENER3</td>\n",
+       "      <td>51.72</td>\n",
+       "      <td>3.09</td>\n",
+       "      <td>0.323625</td>\n",
+       "      <td>1.167120e+09</td>\n",
+       "      <td>3.89</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>55.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>381</th>\n",
+       "      <td>ENER6</td>\n",
+       "      <td>51.72</td>\n",
+       "      <td>3.09</td>\n",
+       "      <td>0.323625</td>\n",
+       "      <td>1.167120e+09</td>\n",
+       "      <td>3.89</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>55.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>379</th>\n",
+       "      <td>ENER5</td>\n",
+       "      <td>51.72</td>\n",
+       "      <td>3.09</td>\n",
+       "      <td>0.323625</td>\n",
+       "      <td>1.167120e+09</td>\n",
+       "      <td>3.89</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>55.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>382</th>\n",
+       "      <td>TEFC11</td>\n",
+       "      <td>46.72</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>0.289855</td>\n",
+       "      <td>4.585600e+10</td>\n",
+       "      <td>2.95</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>69.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 38
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-13T20:55:47.816488Z",
+     "start_time": "2025-04-13T20:55:47.812631Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# Salvar resultados em um CSV\n",
+    "top_acoes.to_csv('magic_formula_b3_resultado.csv', index=False)\n",
+    "print(\"\\nResultados salvos em 'magic_formula_b3_resultado.csv'\")"
+   ],
+   "id": "605685dca910a47c",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Resultados salvos em 'magic_formula_b3_resultado.csv'\n"
+     ]
+    }
+   ],
+   "execution_count": 39
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": "",
+   "id": "cdcab25ed5f48c3b"
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/magic-formula/magic_formula_b3_resultado.csv b/magic-formula/magic_formula_b3_resultado.csv
new file mode 100644
index 0000000..50afd9c
--- /dev/null
+++ b/magic-formula/magic_formula_b3_resultado.csv
@@ -0,0 +1,16 @@
+Ticker,ROIC,EV/EBIT,Earnings Yield,Liquidez Media,Divida Bruta/PL,ROIC_Rank,EY_Rank,Magic_Rank
+AHEB3,61.47,2.17,0.4608294930875576,244413000.0,0.02,7.0,25.0,32.0
+AHEB5,61.47,2.48,0.40322580645161293,244413000.0,0.02,7.0,30.0,37.0
+AHEB6,61.47,2.8,0.35714285714285715,244413000.0,0.02,7.0,32.0,39.0
+CSPC4,45.33,1.43,0.6993006993006994,2126670000.0,1.48,23.5,16.5,40.0
+CSPC3,45.33,1.43,0.6993006993006994,2126670000.0,1.48,23.5,16.5,40.0
+SYNE3,50.87,2.41,0.41493775933609955,1073780000.0,0.76,16.0,28.0,44.0
+CPFG4,36.99,0.95,1.0526315789473684,3614430000.0,0.42,37.5,7.0,44.5
+CPFG3,36.99,0.97,1.0309278350515465,3614430000.0,0.42,37.5,8.0,45.5
+PALF11,46.56,2.84,0.35211267605633806,3055110000.0,3.0,19.0,33.0,52.0
+PALF5,46.56,2.87,0.3484320557491289,3055110000.0,3.0,19.0,34.0,53.0
+PALF3,46.56,2.88,0.3472222222222222,3055110000.0,3.0,19.0,35.0,54.0
+ENER3,51.72,3.09,0.3236245954692557,1167120000.0,3.89,11.0,44.0,55.0
+ENER6,51.72,3.09,0.3236245954692557,1167120000.0,3.89,11.0,44.0,55.0
+ENER5,51.72,3.09,0.3236245954692557,1167120000.0,3.89,11.0,44.0,55.0
+TEFC11,46.72,3.45,0.2898550724637681,45856000000.0,2.95,17.0,52.0,69.0