This project focuses on analyzing and predicting stock prices for NVDA, MARA, and CLSK.
It's interactive graphs are available on kaggle notebook preview. You can enter the link to see them.
The analysis includes extracting data, performing exploratory data analysis (EDA), and forecasting stock prices using different models.
- Data Extraction: Stock data for NVDA, MARA, and CLSK was extracted from stooq.
- EDA: Visualizations were created using cufflinks-plotly to explore stock returns, rolling averages, volatility, and Bollinger Bands.
- Prediction Models: The closing price of NVDA was predicted using: SARIMAX model with auto ARIMA and LSTM neural network.
Extracting Data
- Set up the time range explicitly using dates.
- Pulled stock data from stooq.
EDA
- Visualized the data with cufflinks-plotly.
- Explored returns, rolling averages, volatility and Bollinger Bands.
Forecasting
- Used SARIMAX with auto ARIMA to predict NVDA's closing price.
- Compared the predictions with those from an LSTM neural network.
Hope you enjoy this project!