Market Prediction using Neural Networks Git

Project summary

The scope of this classroom assignment is to analyze stock and currency data while examining the potential to accurately forecast indices by using neural networks and genetic algorithms.

The following indicators are implemented:

• RSI -- Relative Strength Index
• MACD -- Moving Average Convergence Divergence
• PPO -- Price Percentage Oscillation
• DPO -- Detrended Price Oscillation

Data can be loaded from CSV files. Included are:

• EUR/USD (2013-11-24 -- 2015-11-09)
• EUR/GBP (2013-11-24 -- 2015-11-09)
• EUR/RON (2013-11-24 -- 2015-11-09)
• XBT/USD (2013-01-01 -- 2015-12-22)

The underlying components behind the prediction experiments are implemented using the neural and genetic features of the AForge.NET Framework.

Instructions on how to use the application and the results of various prediction experiments are available in the form of a written report in LaTeX within this repository.