Sid Ghatak’s Deep Learning Revolution: A New Era of Alpha Generation in Equity Markets
Ai & Machine Learning News / Trading & Investing News
Sid Ghatak, a highly respected artificial intelligence leader and the founder of Increase Alpha, unveiled one of the most rigorously tested deep learning frameworks in modern quantitative finance. Developed over nearly a decade, represents a profound shift in how institutional investors can generate uncorrelated, high-confidence alpha from public data sources alone.
The Increase Alpha system has been independently verified across more than 800 of the largest Russell 3000 equities!
Its out-of-sample, forward-tested framework has achieved an accuracy rate exceeding 70 percent over four years!
Each prediction is bias-free and entirely independent of look-ahead data—engineered to provide daily long and short recommendations with rolling ten-day price forecasts. The model has demonstrated an average maximum drawdown below 5 percent, with over 90 percent of returns representing pure alpha.
Unlike large language model-based systems, Ghatak’s predictive engine uses structured deep learning designed for transparency, causality, and explainability. The model’s architecture avoids generative AI altogether, relying instead on feature-engineered datasets drawn from public sources such as SEC filings, price, and volume data. The result is a predictive intelligence network capable of performing across macro shocks, interest rate regimes, and sector rotations.
Increase Alpha’s technology produces actionable, daily trading signals. Among its top long predictions, equities such as Progressive (PGR), Visa (V), Apple (AAPL), and Laboratory Corporation of America (LH) achieved predictive accuracy rates above 85 percent. Its top short positions—like MicroVision (MVIS), AMC Networks (AMCX), and Novavax (NVAX)—consistently exceeded 75 percent accuracy.
Ghatak’s credentials span three decades at the intersection of AI, finance, and public policy.
Before launching Increase Alpha, he advised the U.S. government on AI ethics and safety, co-authored the Federal AI Maturity Model, and served as Chief AI Architect for the Federal Energy Regulatory Commission. His prior leadership roles include work at JP Morgan, the London Stock Exchange Group, and Merck, along with teaching Villanova University’s Master’s Certificate in Business Intelligence.
Increase Alpha’s system is designed for hedge funds, asset managers, and institutional investors seeking independent predictive intelligence and robust signal architecture. With proven results, bias-free data design, and strong out-of-sample performance, Sid Ghatak’s work signals a new chapter in systematic trading—one where deep learning becomes a measurable, transparent driver of consistent equity alpha.
