A genetic programming approach for delta hedging

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Yin:GPEM,

• author = "Zheng Yin and Anthony Brabazon and Conall O'Sullivan and Philip A. Hamill",
• title = "A genetic programming approach for delta hedging",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2019",
• volume = "20",
• number = "1",
• pages = "67--92",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Hedging, Delta neutrality",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-018-9334-3",
• size = "26 pages",
• abstract = "In this paper, using high-frequency intra-daily data from the UK market, we employ genetic programming (GP) to uncover a hedging strategy for FTSE 100 call options, hedged using FTSE 100 futures contracts. The output from the evolved strategies is a rebalancing signal which is conditioned upon a range of dynamic non-linear factors related to market conditions including liquidity and volatility. When this signal exceeds threshold values during the trading day, the hedge position is rebalanced. The performance of the GP-evolved strategy is evaluated against a number of commonly used, time-based, deterministic hedging strategies where the hedge position is rebalanced at fixed time intervals ranging from 5 minutes to one day. Assuming the delta hedger pays the bid-ask spread on the futures contract whenever the portfolio is rebalanced, this study finds that the GP-evolved hedging strategy out-performs standard, deterministic, time-based approaches. Empirical analysis shows that the superior performance of the GP strategy is driven by its ability to account for non-linear intra-day persistence in high frequency measures of liquidity and volatility. This study is the first to apply a GP methodology for the task of delta hedging with high frequency data, a significant risk management issue for investors and market makers in financial options.",

}

Genetic Programming entries for Zheng Yin Anthony Brabazon Conall O'Sullivan Philip A Hamill

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