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

Communications in Nonlinear Science and Numerical Simulation 2021

Posted: 17 Mar 2021

See all articles by Aydin Cecen

Aydin Cecen

Central Michigan University

Pawan Jain

West Virginia University

Linlan Xiao

Central Michigan University

Date Written: January 27, 2021

Abstract

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.

Keywords: Heavy-tails, High frequency trading, Markov property, Multi scale entropy

Suggested Citation

Cecen, Aydin and Jain, Pawan and Xiao, Linlan, High frequency trading and stock index returns: A nonlinear dynamic analysis (January 27, 2021). Communications in Nonlinear Science and Numerical Simulation 2021, Available at SSRN: https://ssrn.com/abstract=3774567

Aydin Cecen

Central Michigan University ( email )

307 Sloan
Mt. Pleasant, MI 48858
United States
19897743870 (Phone)
1 9897742040 (Fax)

Pawan Jain

West Virginia University ( email )

PO Box 6025
Morgantown, WV 26506
United States

Linlan Xiao (Contact Author)

Central Michigan University ( email )

Mt. Pleasant, MI 48858
United States

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