High-Frequency Options Trading | With Portfolio Optimization
Sid Bhatia

TL;DR
This study evaluates high-frequency options trading strategies enhanced by advanced portfolio optimization, demonstrating that sophisticated approaches using Greeks and dynamic models can outperform basic methods in volatile markets.
Contribution
It introduces a novel combination of high-frequency trading with advanced portfolio optimization techniques, emphasizing the importance of adaptability and complex Greeks in options trading.
Findings
Sophisticated strategies outperform basic long-short approaches.
Advanced Greeks like Vega and Rho improve portfolio performance.
Dynamic optimization enhances responsiveness in volatile markets.
Abstract
This paper explores the effectiveness of high-frequency options trading strategies enhanced by advanced portfolio optimization techniques, investigating their ability to consistently generate positive returns compared to traditional long or short positions on options. Utilizing SPY options data recorded in five-minute intervals over a one-month period, we calculate key metrics such as Option Greeks and implied volatility, applying the Binomial Tree model for American options pricing and the Newton-Raphson algorithm for implied volatility calculation. Investment universes are constructed based on criteria like implied volatility and Greeks, followed by the application of various portfolio optimization models, including Standard Mean-Variance and Robust Methods. Our research finds that while basic long-short strategies centered on implied volatility and Greeks generally underperform, more…
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Taxonomy
TopicsStochastic processes and financial applications
Methods7 Fastest Ways to Call American Airlines Reservations Number (USA Guide)
