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This project aims to provide an advanced and dynamic system for predicting stock prices and monitoring their movements in real-time. Utilizing various machine learning techniques and technical indicators, this system continuously updates itself with the latest stock market data and retrains its predictive models to ensure accuracy.

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Sana0124/Stock-Price-Prediction-Model

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Stock-Price-Prediction-Model

Introduction

Welcome to the Stock Price Prediction and Monitoring System!

This project aims to provide an advanced and dynamic system for predicting stock prices and monitoring their movements in real-time. Utilizing various machine learning techniques and technical indicators, this system continuously updates itself with the latest stock market data and retrains its predictive models to ensure accuracy.

Features

Dynamic Data Fetching: Automatically fetches the latest stock data from Yahoo Finance.

Real-Time Monitoring: Continuously updates stock predictions at user-defined intervals.

Technical Indicators: Incorporates a wide range of technical indicators such as Moving Averages, Bollinger Bands, Relative Strength Index (RSI), and more.

Option Greeks: Calculates Greeks (Delta, Gamma, Theta, Vega, Rho) for a more comprehensive analysis.

Interactive Plots: Provides interactive plots with mplcursors to display exact stock prices on hover.

Buy/Sell Signals: Generates buy and sell signals based on technical indicators.

Technologies Used

Python: The core programming language.

TensorFlow/Keras: For building and training LSTM models.

Pandas: For data manipulation and analysis.

NumPy: For numerical computations.

Matplotlib: For plotting and visualization.

mplcursors: For interactive plot annotations.

yfinance: For fetching stock data from Yahoo Finance.

TA-Lib: For technical analysis indicators.

About

This project aims to provide an advanced and dynamic system for predicting stock prices and monitoring their movements in real-time. Utilizing various machine learning techniques and technical indicators, this system continuously updates itself with the latest stock market data and retrains its predictive models to ensure accuracy.

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