• This project contains the following:

1. An overview of some fundamentals about time series (stationarity, seasonality, trends, etc..) alongside some simple models widely used in signal processing like AR, MA or ARIMA models, and their applications for stock price forecasting.

2. A Python implementation of all the steps involved in developing various algorithmic trading strategies and technical indicators widely used in financial markets:

• SMA with trading volume.
• Short/long term SMA.
• Moving Average Convergence Divergence (MACD).
• Bollinger Bands (BB).
• Stochastic Oscillator.
• KDJ indicator.
• Relative Strength Index (RSI).

3. Adding market sentiment analysis of financial news for a stock with VADER, and analyze its performance.

PS: The financial data chosen for this project is Apple stock close prices over various time periods. It's from YahooFinance data source, and contains different price parameters for various S&P500 companies.

For any information, feedback or questions, please contact me