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

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+---
+title: Predicting EUR/USD With Hanning Windows
+description: A weekend frequency-domain experiment that did a passable job on EUR/USD. I would not have trusted it with my money, and I didn't.
+date: 2026-05-03
+period: 'Autumn 2019'
+thumbnail:
+  src: ./_assets/forex.jpg
+  alt: Chart comparing predicted and actual EUR/USD exchange rates.
+article:
+  tags: ['systems', 'tools']
+  role: Experiment author
+  stack: ['Python', 'NumPy', 'SciPy', 'Flask', 'MQL4']
+  outcome: A prediction server, an MQL4 trading client, and a clearer view of how far my edge wasn't
+  audience: technical
+project:
+  title: Foreign Exchange Prediction Experiment
+  description: A Hanning-windowed STFT experiment on EUR/USD. Passable backtest, sober conclusions, no real money risked.
+  thumbnail:
+    alt: Chart from a foreign exchange prediction experiment.
+---
+
+In the autumn of 2019 I was an undergrad with a few weekends free and the quiet conviction that I could find a small edge on EUR/USD. The screenshots were flattering: the prediction (blue) hugged the actual rate (green) in a way that looked like skill. A linear regression in the frequency domain, dressed up. I did not trade real money with it, and that restraint is the only thing about the project that aged well.
+
+The pipeline:
+
+- Smooth the input series.
+- Differentiate.
+- Short-time Fourier transform with overlapped, Hanning-windowed frames.
+- Extrapolate the frequency-domain coefficients.
+- Invert everything back to a predicted price series.
+
+A Python server (NumPy, SciPy, Flask) ran the model. An MQL4 client on a broker terminal called the server and would have placed trades if I'd dared.
+
+What I actually learned: even a naive model can show a sometimes-profitable backtest, and that's the trap. The real game is built by people with co-located servers, microsecond ticks, and millions in infrastructure. This project taught me how far my edge wasn't.