Machines, Memory and the Markov Property in Stock Returns: Deus Ex Machina?

29 Pages Posted: 5 May 2017

See all articles by Aydin Cecen

Aydin Cecen

Central Michigan University

Pawan Jain

University of Wyoming - College of Business - Department of Economics and Finance

Linlan Xiao

Central Michigan University

Date Written: April 24, 2017

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 does not hold for the return series under study.

Keywords: Markov Property, Short Memory, High Frequency Trading, Entropy

JEL Classification: C14, D83, G15

Suggested Citation

Cecen, Aydin and Jain, Pawan and Xiao, Linlan, Machines, Memory and the Markov Property in Stock Returns: Deus Ex Machina? (April 24, 2017). Available at SSRN: https://ssrn.com/abstract=2963418 or http://dx.doi.org/10.2139/ssrn.2963418

Aydin Cecen

Central Michigan University ( email )

Mt. Pleasant, MI 48858
United States

Pawan Jain (Contact Author)

University of Wyoming - College of Business - Department of Economics and Finance ( email )

P.O. Box 3985
Laramie, WY 82071-3985
United States

Linlan Xiao

Central Michigan University ( email )

Mt. Pleasant, MI 48858
United States

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