Algorithmic Trading in the FOREX Market

Description

• The price of a FOREX market is dependent on numerous inter-linked factors that contribute to volatility in the stock.
• The nexus of information corresponding to a particular asset is analyzed to determine patterns exhibited in connected services for developing trading strategies.
• The objective of this project is to investigate various branches in the corporate and government sector along with the market sentiments to predict the FOREX market price with accuracy and minimum confidence interval

Research Objective

• Find factors influencing a particular asset of the forex market
• To perform co-integration test for filtering features

Model Construction

• LSTM
• ARIMA
• Kalman Filter
• Moving Average
• Exponential Moving Average
• Auto-correlation

Trading Strategies

• Applying trading strategies:
  • Bollinger Band
  • Double Cross-over
  • Mean Revertion
  • Momentum Trading

Ensemble Model

• Selecting model based on lowest RSME metric

Build With

• JupterNotebook
• TensorFlow
• Keras

Requirements

• Jupyter Notebook (Anaconda Distribution Prefered)
• Install python dependencies
  • requirements.sh