High frequency trading and stock index returns: A nonlinear dynamic analysis

Aydin A. Cecen, Pawan Jain, Linlan Xiao

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This study seeks to understand whether and to what extent High Frequency Trading (HFT) affects the probabilistic properties of the stock returns in five markets. More specifically, it focuses on the impact of HFT/Machine trading on five major stock indices, DAX, Nikkei 225, S&P 500, Russell 2000, and TOPIX. The empirical analysis demonstrates that while the introduction of machine trading and/or HFT appears to make the return series more “predictable” by reducing their Multiscale Entropy, it does not affect the Markov property, which, not surprisingly, does not hold for the entire return series under study.

Original languageEnglish
Article number105710
JournalCommunications in Nonlinear Science and Numerical Simulation
StatePublished - Jun 2021


  • Heavy-tails
  • High frequency trading
  • Markov property
  • Multi scale entropy


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