A Frequency-Domain Foreign Exchange Prediction Experiment

This was an experiment in predicting EUR/USD rates. The animation from the old portfolio showed the implementation doing a passable job: the prediction was the blue graph and the actual values were the green one. I would not have trusted it with my money.

The algorithm was a fancy linear regression in the frequency domain. The steps were: smoothing the input values, differentiating, applying a short-time Fourier transformation with overlapped and Hanning-windowed windows, extrapolating, and then applying the inverse of these transformations to the resulting values.

The prediction server was written in Python using NumPy, SciPy, and Flask. It communicated with an MQL4 client that was responsible for handling financial transactions based on the generated data.

There was still plenty of room for improvement, but even with this simple algorithm, a sometimes profitable strategy was viable. The project was mostly a look into trading algorithms, their complexity, and the competition around them.