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Analysis of stock market volatility: Adjusted VPIN with high-frequency data

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  • Yang, Haijun
  • Xue, Feng

Abstract

The volume-synchronized probability of informed trading (VPIN) is widely accepted as a proxy of volatility in the high-frequency market. We propose a novel VPIN model, called Adjusted VPIN, to improve the performance of VPIN so that it can directly analyze and better predict the information asymmetry of individual stocks. We extend the VPIN model by optimizing the classification algorithm with a neural network method and high-frequency data. Both trading volume and trends are considered to capture stock volatility. Empirical results on three different trading volume groups generate a 37.86% higher relevant result with logarithm stock yield than the VPIN model.

Suggested Citation

  • Yang, Haijun & Xue, Feng, 2021. "Analysis of stock market volatility: Adjusted VPIN with high-frequency data," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 210-222.
    • Handle: RePEc:eee:reveco:v:75:y:2021:i:c:p:210-222
    DOI: 10.1016/j.iref.2021.04.003
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    Cited by:

    1. Yang Gao & Chengjie Zhao & Bianxia Sun & Wandi Zhao, 2022. "Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-30, December.

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    More about this item

    Keywords

    High-frequency trading; Volatility; Adjusted VPIN; Stock market;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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