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A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications

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  • Xiangkang Yin
  • Jing Zhao

Abstract

This paper develops a novel approach to information‐based securities trading by characterizing the hidden state of the market, which varies following a Markov process. Extensive simulation demonstrates that the approach can successfully identify market states and generate dynamic measures of information‐based trading that outperform prevailing models. A sample of 120 NYSE stocks further verifies that it can better depict trading dynamics. With this sample, we characterize the features of information asymmetry and belief dispersion around earnings announcements. The sample is also applied to the study of the co‐movements of trading activities due to private information or disputable public information. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Xiangkang Yin & Jing Zhao, 2015. "A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1210-1234, November.
    • Handle: RePEc:wly:japmet:v:30:y:2015:i:7:p:1210-1234
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    Cited by:

    1. Xu, Liao & Xu, Lu & Zhao, Jing & Zhao, Yang, 2020. "Information-based trading and information propagation: Evidence from the exchange traded fund market," International Review of Financial Analysis, Elsevier, vol. 70(C).
    2. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
    3. Ping-Chen Tsai & Chi-Ming Tsai, 2021. "Estimating the proportion of informed and speculative traders in financial markets: evidence from exchange rate," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 443-470, July.
    4. Xie, Minghua & Yi, Xiangyu & Liu, Kui & Sun, Chuanwang & Kong, Qingbao, 2023. "How much natural gas does China need: An empirical study from the perspective of energy transition," Energy, Elsevier, vol. 266(C).
    5. Xu, Liao & Gao, Han & Shi, Yukun & Zhao, Yang, 2020. "The heterogeneous volume-volatility relations in the exchange-traded fund market: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 400-408.
    6. Xu, Liao & Yin, Xiangkang & Zhao, Jing, 2019. "The sidedness and informativeness of ETF trading and the market efficiency of their underlying indexes," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    7. Xiao, Yuewen & Zhao, Jing, 2021. "Price dynamics of individual stocks: Jumps and information," Finance Research Letters, Elsevier, vol. 38(C).
    8. Xu, Liao & Xue, Mingqi & Zhang, Xuan & Zhao, Yang, 2023. "Heterogeneously informed trading and the stock market efficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 87(C).

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