At Dynamic Technology Labs Pvt. Ltd., I built a causal, multi-horizon forecasting framework for USD-M crypto futures. It combined minute-level market data, Ridge and LightGBM models, and purged chronological out-of-sample validation.
I studied market structure in USD-M perpetuals and found stable session- and funding-driven patterns. I also developed asset-specific trend–volatility regime conditioning, and the final architecture reached 3.24 gross Sharpe in 2024 OOS on 50 assets.
On MicroAlpha, I built an event-driven HFT research and backtesting platform using Databento MBP-10 data. I developed its market-data integrity pipeline and a causality-safe execution and accounting engine, validated through 96 tests.
For an undisclosed Singapore Hedge Fund project, I developed a market-neutral US equity long–short strategy and causal market-regime models. As Director of Quant and Investment Projects at IIT Madras, I lead industry-linked research initiatives and student project teams.
