Mohan Sai

Quantitative researcher specialising in systematic trading, market making, and statistical arbitrage, with live crypto trading at Brew Labs managing a book at USD 125M monthly notional and 2.4 Sharpe (net of fees and funding). Work spans strategy research, execution, risk management, and production validation. Earlier founded the quantitative research function at Ashika Group, building a multi-factor equity platform that secured INR 100+ crore of institutional capital and a live multi-asset book at 2.3 Sharpe.

Quantitative Researcher, proprietary crypto trading at Brew Labs (2025-04 – Present)

• Market making | live across centralised exchanges and perpetual DEXs; owned quoting and inventory for a book at USD 125M monthly notional, 2.4 Sharpe, and 4.2% drawdown (net of fees and funding, live since Apr 2025). Improved maker capture to 1.8–2.6 bps by using a machine-learning microprice model based on short-horizon execution costs. Reduced fill-ratio forecast error from 22% to 6% with a queue model using order-flow intensity, and cut inventory variance 34% versus flattening through constrained reinforcement learning with position limits.
• Cross-exchange arbitrage | researched and deployed lead-lag and cross-chain strategies, generating 4.1–7.3 bps net edge per round trip after fees and market impact. Used adaptive spread and regime detection to distinguish persistent repricing from temporary liquidity changes; relative-value Sharpe improved from 1.6 to 2.2 and remained stable across volatility quartiles.
• Systematic trading, 70+ assets | live overnight carry and cross-sectional momentum across perpetuals, RWAs, FX and commodities, with 0.3 correlation to the high-frequency book. Used funding and basis forecasts to manage inventory, cutting overnight carry cost 40%; applied covariance shrinkage and clustering to control concentration and uncertainty-aware position sizing.
• Prediction markets | built and scaled pricing and market-making strategies to USD 500k deployed capital, using cross-outcome consistency checks, flow signals, and risk-adjusted position sizing to identify pricing discrepancies and control exposure.
• Research and validation | built a research pipeline with 300+ order-flow features, feature selection, and robust walkforward backtesting. Added drift monitoring and shadow-book validation before production; live cumulative P&L tracks simulation within 8%, and two strategies were rejected before capital deployment.

Founding Quantitative Researcher at Ashika Group (2023-03 – 2025-04)

• Built the multi-factor long-short equity platform that secured INR 100+ crore of institutional capital for a Category 3 AIF; generated 10%+ alpha over NIFTY 500 at information ratio above 1.5, with drawdown under 12%
• Delivered 32% CAGR at 2.3 Sharpe on a live multi-asset book across equities and derivatives, including intraday statistical arbitrage across 120+ pairs
• Improved NIFTY and BANKNIFTY options P&L by 28%, generating INR 22L+ monthly, using a gradient-boosted and LSTM ensemble with confidence-based position sizing

Integrated BS-MS in Master of Science in Physics and Mathematics – IISER Trivandrum, India (2019 – 2024)