Googles Stock Price Prediction

📈 Stock Price Prediction using Facebook Prophet
Forecasting | Time Series Analysis | Python

Overview
This project demonstrates how to predict Google’s stock prices using the Facebook Prophet model. It involves time series forecasting based on historical data obtained from Yahoo Finance, enabling accurate stock trend prediction for the next 365 days.

Objective
Utilize Facebook Prophet to forecast future stock prices and uncover seasonal trends using time series modeling techniques.

Tools & Libraries

Python – Pandas, NumPy, Matplotlib

Facebook Prophet – Time series forecasting

Jupyter Notebook – For data analysis and model building

Project Steps

Loaded historical Google stock data

Preprocessed data to meet Prophet’s input format

Trained the Prophet model on historical trends

Forecasted stock prices for 365 future days

Visualized both predictions and seasonal components

Output Highlights

📊 Line chart: Historical vs. Predicted Stock Prices

⏳ Seasonal Components: Trend, weekly, and yearly patterns

📅 Forecast graph for next 1 year of stock movement

Outcome
Successfully built a robust forecasting model using Prophet. This project illustrates my ability to work with real-world financial datasets, perform time series modeling, and extract business-relevant insights.