Add project writeups

src/content/posts/foreign-exchange-prediction-experiment.md

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+---
+title: A Frequency-Domain Foreign Exchange Prediction Experiment
+description: An older EUR/USD prediction experiment built from smoothing, short-time Fourier transforms, extrapolation, and a Python prediction server.
+date: 2026-05-03
+projectPeriod: 'Autumn 2019'
+thumbnail:
+  src: ./_assets/forex.jpg
+  alt: Chart comparing predicted and actual EUR/USD exchange rates.
+tags: ['systems', 'tools']
+role: Experiment author
+stack: ['Python', 'NumPy', 'SciPy', 'Flask', 'MQL4']
+outcome: A working prediction server connected to an MQL4 client for trading experiments
+audience: technical
+links: []
+---
+
+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.