
Your ultimate resource for mastering trading strategies, coding techniques, and market insights.
| Platform | Pricing | Freemium | Publishes | Daily | |
|---|---|---|---|---|---|
| Issues | 44 | Founded | 2 years ago | Last Issue | 5 days ago |
| Active | |||||

LazyPredict provides a fast and effective way to benchmark multiple ML models in quantitative finance. Across several financial applications (credit risk, fraud detection, churn, and stock prediction), it consistently shows that quick model...
AlgoEdge Research is live. 33 strategies scored every trading day, a regime detector, a full volatility suite, options flow, institutional data, and Python notebooks for every model — all in one browser tab. This is a complete walkthrough....
This study is focused on a TICA-based regime detection framework for equity markets. Results suggest the strategy successfully identifies market regimes using SPY and VIX data and consistently reduces risk, especially volatility and drawdow...
“The stock market is not a gamble; it is a business. And it should be conducted as such, and it must be, to be successful.” — Ralph Nelson Elliott
Image Design by the Author via Canva.
This blog presents a systematic trading framework based on Ehlers’ Hilbert transform methodology using MAMA/FAMA to adaptively detect market cycles and regime shifts across equities, bonds, commodities, and crypto from 2015 to 2026, impleme...
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The writers behind this newsletter.
\ud83d\udd25 Quant finance & algo trading in Python \ud83d\udd25 30+ backtested strategies published \ud83d\udd25 5,000+ traders read my free weekly notebook ↓ Grab 3 free ready-to-run https://algoedgeinsights.beehiiv.com/subscribe
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