Using 2012-2016 open Google stock price to predict 2017 opening google stock price using Recurrent Neural Network stacked LSTM.

A Python project for analyzing and predicting Google's stock price using statistical methods, technical indicators, and Monte Carlo simulation. It fetches historical data, calculates moving averages, assesses risk (VaR), runs 10,000 simulated future price paths, and visualizes results to help investors understand trends, risk, and expected returns.