Do futures improve genetically trained high-frequency technical trading rules for the Chinese index ETF market?

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@Article{PAN:2024:eswa,

• author = "Beier Pan and Eric Michael Scheffel",
• title = "Do futures improve genetically trained high-frequency technical trading rules for the Chinese index {ETF} market?",
• journal = "Expert Systems with Applications",
• year = "2024",
• volume = "242",
• pages = "122721",
• keywords = "genetic algorithms, genetic programming, Technical trading, Genetic program, Index futures, Arbitrage efficiency, Information spillover",
• ISSN = "0957-4174",
• URL = "https://dl.acm.org/doi/abs/10.1016/j.eswa.2023.122721",
• URL = "https://www.sciencedirect.com/science/article/pii/S0957417423032232",
• DOI = "doi:10.1016/j.eswa.2023.122721",
• abstract = "Using the evolutionary genetic program (GP) to search for optimal technical trading rules (TTRs) in high-frequency Chinese index exchange traded funds (ETFs), we investigate whether profit-taking opportunities can improve through index arbitrage. Our results show that with information spillover from index futures, consistent improvements in both the market timing and out-of-sample profitability of ETF TTRs are obtained, which are particularly pronounced for small-cap markets and TTRs trained using lower transaction costs. The additional information externality that futures provide, however, appears to have been eroded by lower futures liquidity levels and regulatory trading restrictions in effect since 2015",

}

Genetic Programming entries for Beier Pan Eric Michael Scheffel

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