Quantitative Research & Strategy Development
Systematic strategies that hold up out-of-sample.
I research and build systematic strategies for options, futures, and crypto markets.
Who this is for
- → Hedge funds and prop trading desks seeking alpha in options markets
- → Family offices wanting systematic strategy overlays
- → Crypto trading firms building HFT / MFT infrastructure
- → Asset managers needing quant overlays for portfolio management
Problems this solves
- • Strategies overfit to historical data and fail out-of-sample
- • No systematic framework for signal research, testing, and deployment
- • Backtests ignore execution costs, slippage, and regime changes
- • Research notebooks that never make it to production
What I do
Signal Research
Factor identification, statistical significance testing, information coefficient analysis
Backtesting
Walk-forward analysis, parameter stability, overfitting score, Monte Carlo risk
Execution Modeling
Slippage, latency, position sizing, risk-of-ruin, capital efficiency
Volatility Modeling
IV surfaces, skew analysis, vol regime classification, term structure
Live Deployment
Paper trading → small size → full capital progression with continuous monitoring
Deliverables
- ✓ Strategy research report with edge quantification
- ✓ Production-ready backtesting framework
- ✓ Documented execution and risk management logic
- ✓ Live monitoring dashboard setup
Example outcomes
Sharpe ratio of 4 in live index options strategies at Mastertrust
Multi-strategy portfolio managing ₹100+ crore AUM
Comprehensive backtesting framework with walk-forward and slippage modeling
Tools & methods
Related case studies
Lets collaborate!
Whether you need a quantitative researcher, an machine learning systems builder, or a technical advisor — I'm available for select consulting engagements.
Get in Touch →