Rajit Datta

Quantitative Researcher · Mumbai, India

Long-short equities portfolio research covering multiple geographies.

• Built and deployed 200+ alpha signals from fundamental datasets — sales, earnings, institutional flow — across global equity markets, achieving Sharpe > 1.
• Applied Barra multi-factor risk models to control for style/industry exposures and isolate idiosyncratic alpha in the long-short book.
• Engineered mid-frequency trading (MFT) signals from aggregated limit-order-book data.

Quantitative Researcher · Nifty Options Strategy Research, Python

• Created an end-to-end framework for backtesting intraday options strategies on 1-minute bars.
• Onboarded historical data from 2021 from external sources.
• Built efficient signals and backtesting for fast research cycles — a 4-year backtest runs in 15 minutes on a standard 4-core, 16GB RAM machine.
• Ideated and constructed 30+ new features, with a systematic testing pipeline.
• Delivered a strategy with Sharpe 2.8, Calmar 4.6 over a 4.5-year backtest.

Served Non-Compete · Bengaluru, India

• Mentored students from his alma mater as part of LogicLabs — lectures on quant finance topics, interview preparation, and guidance through the application process.
• Read Active Portfolio Management by Grinold and Kahn and implemented the techniques in Python.

Quantitative Research and Trading · Bengaluru, India

Mid-frequency strategies in India NSE F&O. Co-managed a long-short equities portfolio (NSE Futures) as part of a five-member team. Independently developed NSE index option strategies deployed with AUM of ₹20Cr (~$2.5M).

• Independently developed two NSE Index option strategies with annual Sharpes 2.5 & 3.8, Calmar 3.2 & 7.6.
• Improved options risk management, reducing shock risk from 60% of margin to 40%.
• Improved existing alphas and contributed 3 new technical alphas, each with annual Sharpe > 1.5.
• Performed post-market analysis and risk reporting for the long-short portfolio.
• Briefly explored limit-order-book data for short-horizon signal ideas — early-stage investigation.

Vice President, Model Risk Management · Bengaluru, India

Validated pricing models for interest-rate products and exotics — cancellable swaps, range accrual features, and options on averages of interest rates — using stochastic calculus, American Monte Carlo, and Whaley's approximation.

• Model for the difference of swap rates (e.g. 30y USD − 5y USD) using Ornstein–Uhlenbeck diffusion.
• Validated a new SABR-style model for Caplets on daily-compounding risk-free rates with a decay function for volatility.
• Model for Caplets on averages of risk-free rates, with an independent Monte-Carlo Hull-White benchmark.
• Model for Bond Future Options, with an independent SABR-like benchmark.
• Market-making model for treasury future options using Whaley's approximation.
• CCAR PPNR Credit Flow model based on regression over macroeconomic factors.