pyhou-02-17-2026
Unverified ML strategy on Multi by ababber. BotFinder score 37 out of 100.
A companion repo to "Quantitative Trading: A First Look With QuantConnect". This YouTube series is a reproduction of a live PyHou Meetup from February 17, 2026.
Source: github
BotFinder analysis pending.
pyhou-02-17-2026
Quantitative Trading: A First Look With QuantConnect Can machine learning predict financial markets? This repo accompanies a 3-part video series where I test three generations of ML — from a 1970 linear model to a 2024 foundation model — on the same backtesting platform. 📺 Click here to watch the full playlist on YouTube! --- Quick Navigation Part 1: Classical ML (Ridge Regression) Part 2: Deep Learning (Temporal CNN) Part 3: Foundation Models (Amazon Chronos) Note: When opening in Colab, you'll see a "This notebook was not authored by Google" warning — click Run anyway to proceed. --- Part 1: Classical ML (Ridge Regression) ▶️ Watch the Part 1 Video The first video covers ridge regression — a classical linear model from 1970 — applied to inverse volatility weighting on 12 futures contracts. The strategy: - Trade 12 futures (indices, energy, grains) - Predict next-week volatility using ridge regression - Allocate inversely: less volatile contracts get more capital - Rebalance weekly The result: Sharpe 0.212, Alpha -0.062. The model tracks the market with extra drawdown. It doesn't ge
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