Algorithmic Trading Model
An LSTM in TensorFlow and Keras for price movement, combined with mean reversion and backtested honestly.
The problem
Predicting price from price alone is close to the hardest version of a forecasting problem, and it is very easy to build something that looks profitable and is actually reading the future.
What I built
An LSTM built in TensorFlow and Keras over historical series pulled from the Yahoo Finance API, combined with regression and a mean-reversion signal.
The part that mattered was the backtest — walking the model forward over held-out history rather than scoring it on data it had already seen.
Measured
- Working sequence model over real historical data.
- Backtesting harness that scores on unseen history rather than training data.
- Two independent signals combined rather than one over-trusted.
Plan
Plan
5 items · scale 1:1What I'd redraw
I did not model transaction costs or slippage. A strategy that trades often can be profitable on paper and unprofitable the moment you charge it for every trade — that omission makes the returns indicative at best, and I'd treat it as the first thing to fix.