Dishant Majithia

Researched statistical arbitrage and pairs trading strategies for Nifty-Sensex and Nifty100 stocks using cointegration (Engle-Granger, Johansen), ADF tests, and mean-reversion half-life estimation. Conducted econometric modelling of Nifty volatility — constructing an IV term structure using ARIMA/GARCH to extract forward volatility for regime-aware strategy selection; built a realized vol engine and volatility cone to benchmark current implied vol against it. Studied mean-reversion and skewness/kurtosis of multi-leg spreads (butterflies, condors, calendars, double calendars, ratio spreads) via a DTE × VIX × time-of-day regime classification.

Derivative Strategist - Junomoneta Finsol Pvt Ltd - Mumbai

(2025-08 - 2026-07)

• Researched statistical arbitrage and pairs trading strategies for Nifty-Sensex and Nifty100 stocks using cointegration (Engle-Granger, Johansen), ADF tests, and mean-reversion half-life estimation.
• Conducted econometric modelling of Nifty volatility — constructing an IV term structure using ARIMA/GARCH to extract forward volatility for regime-aware strategy selection; built a realized vol engine and volatility cone to benchmark current implied vol against it.
• Studied mean-reversion and skewness/kurtosis of multi-leg spreads (butterflies, condors, calendars, double calendars, ratio spreads) via a DTE × VIX × time-of-day regime classification.
• Built dealer positioning models using aggregated Gamma Exposure (GEX) and Vanna Exposure (VEX) across the options chain to infer market-maker hedging flows and spot pinning near expiry.
• Strong understanding of NSE options market microstructure — order flow imbalances and bid-ask spread dynamics to study accumulation/distribution and liquidity for intraday trading.
• Hands-on with data engineering in Python (Scikit-learn, Statsmodels, SciPy), with working exposure to machine learning (XGBoost); skilled in handling large data pipelines.

Assistant PM – Consultant - Bloomstar Capital - India (Remote)

(2024-11 - 2025-01)

• Built predictive Machine Learning based models in QuantConnect LEAN in Options segment in attempt to spot Volatility arbitrage by predicting realized volatility using 1-min frequency data.
• Developed and back-tested various discretionary and systematic trading strategies using large, diverse datasets via walk-forward optimization and robustness validation checks.

Execution Trader (US Market) - Quantatative Ltd - London, UK

(2023-06 - 2024-08)

• Systematically executing trades of $5 million notional value daily in US Equity and ETF systems, ensuring accurate order execution & monitoring of 30+ algorithmic trading strategies.
• Successfully designed systematic trading strategies from the ground up, including idea generation, statistical modeling, rigorous backtesting, and enabling deployment for live trading environments.
• Proficient in trading 0DTE Options by analyzing Greeks, Implied Volatility, and Order-flow behaviour.
• Designed real-time Option Greeks visualization tool, enabling actionable insights into market dynamics as leading indicators.
• Shortened execution time using Python (REST API) to implement automated trading systems.

Analyst - DTC Consultants Pvt Ltd - Pune

(2019-10 - 2022-03)

• Successfully executed a variety of structured Options strategies including spreads, iron condors, butterflies, strangles and straddles, consistently achieving profitable outcomes.
• Prepared 100+ research reports, analyzed business news, financial statements, and other relevant data to evaluate the performance and financial standing of companies listed on the stock market.

MSc - Quantitative Finance - Bayes Business School (2022-09 - 2023-09)

Bachelor of Engineering - Electronics and Telecommunications - University of Pune (2012-08 - 2016-07)