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

Beier Pan, Eric Michael Scheffel

Research output: Journal PublicationArticlepeer-review

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.

Original languageEnglish
Article number122721
JournalExpert Systems with Applications
Volume242
DOIs
Publication statusPublished - 15 May 2024

Keywords

  • Arbitrage efficiency
  • Genetic program
  • Index futures
  • Information spillover
  • Technical trading

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

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