Model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "00e05ae1-fb4b-420c-a1e3-efc1848c2b18",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data processing\n",
    "import pandas as pd\n",
    "import math\n",
    "import numpy as np\n",
    "import librosa\n",
    "import os\n",
    "import yfinance as yf\n",
    "import nltk\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import PorterStemmer\n",
    "import string\n",
    "\n",
    "# Visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "# Model and performance\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.layers import Dropout\n",
    "from sklearn.model_selection import train_test_split,cross_val_score,GridSearchCV\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cda3fe80-d62e-46b8-b843-c0dc93024624",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv(\"FinalData.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58c8c3dc-e918-42bb-8b9d-815fbcb09ed1",
   "metadata": {},
   "source": [
    "### 4. Model Building\n",
    "\n",
    "- **Hybrid Model:** Use a machine learning algorithm (Random Forest), to build a hybrid model that incorporates both numerical features from stock data and sentiment features from news headlines.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a12f4531-7383-4839-9b06-f68a4acef30a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cross-Validation R2 Scores (Random Forest): [-0.89526295  0.97560852  0.99691273  0.98939389 -0.4791709 ]\n",
      "Mean Squared Error: 3.801302771861817\n",
      "R-squared (R2) Score: 0.9999999744365162\n"
     ]
    }
   ],
   "source": [
    "numerical_features = ['Low','SMA_50', 'EMA_20', 'RSI']\n",
    "textual_features = ['compound']\n",
    "\n",
    "X = data[numerical_features + textual_features]\n",
    "y = data['Close']\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "best_forest_model = RandomForestRegressor(\n",
    "    max_depth=20,\n",
    "    min_samples_split=20,\n",
    "    random_state=42,\n",
    "    n_jobs=4\n",
    ")\n",
    "cv_scores_forest = cross_val_score(best_forest_model, X, y, cv=5, scoring='r2')\n",
    "\n",
    "print(\"Cross-Validation R2 Scores (Random Forest):\", cv_scores_forest)\n",
    "\n",
    "best_forest_model.fit(X, y)\n",
    "\n",
    "y_pred = best_forest_model.predict(X_test)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "print(f'Mean Squared Error: {mse}')\n",
    "print(f'R-squared (R2) Score: {r2}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f44cec1-4071-4c9e-b519-8b25e54d8fad",
   "metadata": {},
   "source": [
    "### 5. Model Evaluation\n",
    "\n",
    "- **Metrics:** Evaluate the model using metrics like Mean Squared Error (MSE), R-squared (R2), and other relevant performance metrics.\n",
    "- **Visualization:** Create visualizations, such as plots of stock prices, technical indicators, and model predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c438af13-fc2f-449b-99be-09b7d1b64cb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = ['Open', 'High', 'Low', 'Adj Close', 'SMA_50', 'EMA_20', 'RSI', 'compound']\n",
    "\n",
    "# Calculate correlations\n",
    "correlation_close_only = data[features].corrwith(data['Close'])\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "correlation_close_only.sort_values().plot(kind='barh', color='skyblue')\n",
    "plt.title('Correlation with Close (Target)')\n",
    "plt.xlabel('Correlation Coefficient')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4912e73b-19f6-48b5-8c41-cd32528fe5bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(y_test, y_pred, color='blue', alpha=0.5)\n",
    "plt.plot([min(y_test), max(y_test)], [min(y_test), max(y_test)], linestyle='--', color='red', linewidth=2, label='Perfect Prediction')\n",
    "plt.title('Actual vs. Predicted Values')\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b7e38f2-c4c9-4f49-a08f-7bf54fe06786",
   "metadata": {},
   "source": [
    "# Model Evaluation Summary\n",
    "\n",
    "## R2 Scores\n",
    "\n",
    "- **Fold 1:** Negative R2 score (-0.8953) suggests potential overfitting.\n",
    "- **Folds 2-5:** Positive R2 scores (0.9756, 0.9969, 0.9894) indicate good generalization.\n",
    "\n",
    "## Mean Squared Error (MSE) and R-squared (R2) Score\n",
    "\n",
    "- **MSE:** Low value (3.8013) implies accurate predictions.\n",
    "- **R2 Score:** High value (0.9999999744) indicates capturing most variance.\n",
    "\n",
    "## Conclusion\n",
    "\n",
    "This project demonstrates the application of a hybrid model for stock price prediction, combining numerical analysis and sentiment analysis. It provides insights into the relationship between news sentiment and stock performance.\n"
   ]
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