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Investor-herding and risk-profiles: A State-Space model-based assessment

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  • Nath, Harmindar B.
  • Brooks, Robert D.

Abstract

This paper, using the Australian stock market data, examines the investor-herding and risk-profiles link that has implications for asset pricing, portfolio diversification and foreign investments. As investors may herd towards a specific factor, sector or style to combat market conditions for optimizing investment returns, examining such herding can reveal investors' risk profiles. We employ State-Space models for extracting time series of herd dynamics and the proportion of signal explained by herding (PoSEH). The possibility of a leverage effect between market returns and volatility and its implications are discussed. The change in market volatility strengthens PoSEH; its impact is maximum on high return days of stocks. Quantile regression analysis shows that herding and adverse herding can emerge during the worst and best performance days of stock returns, but extreme uncertainty can bring both herding behaviours to a near halt. The study reveals the presence of a regulated stock market environment and the change in volatility and risk-aversion as the determinants of herding behaviour.

Suggested Citation

  • Nath, Harmindar B. & Brooks, Robert D., 2020. "Investor-herding and risk-profiles: A State-Space model-based assessment," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:pacfin:v:62:y:2020:i:c:s0927538x2030055x
    DOI: 10.1016/j.pacfin.2020.101383
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    Cited by:

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    2. Christian Espinosa-Méndez & José Arias, 2021. "Herding Behaviour in Asutralian stock market: Evidence on COVID-19 effect," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1898-1901, December.

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    More about this item

    Keywords

    Herd behaviour; Risk aversion; State-Space models; Quantile regression; Leverage effect;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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

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