Algorithmic trading signal prediction. The project aims at analyzing how SMA (short moving average) and EMA (exponential moving average) can be used to generate buy/sell signals.

For this project I'm using Adjusted Closing Price to compare with EMA. This is done because ACP provides a more accurate inight into the stock's market movement, while Closing Price only shows the price at which the stock was last traded at.

As stock prices are highly affected by financial news, I'm using Sentiment Score of news articles as a feature while defining the trading startegy. The news aricles are scraped from Reuters.

The list of words to calculate Sentiments is taken from the work presented here

In order to test the implemeted strategy, I have implemented backtesting as well. The idea is to start with an amount of $100000 and using the trading signals generated from the strategy, calculate the annual return from stock and VAR from the returns.

VAR is calculated using the Variance-Covariance method.