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A new statistic to capture the level dependence in stock price volatility

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  • Padmakumari, Lakshmi
  • S., Maheswaran

Abstract

In this paper, we propose a new covariance estimator based on daily opening, high, low and closing prices. We prove theoretically that the new estimator is unbiased for a pure random walk and further validate it with simulation studies. However, upon examining empirically four indices namely: NIFTY, S&P500, FTSE100 and DAX over the sample period from January 1996 to March 2015, we find that the estimator is upward biased for all the indices under study. This overreaction in stock indices can be attributed to the level dependence in stock indices, something that is not captured by the random walk model. So we explore an alternative to random walk, namely: Constant Elasticity of Variance (CEV) specification. Simulation studies provide supporting evidence that the CEV specification can capture the level dependence that makes the estimator upward biased as seen in the data. Therefore, through this specification exercise, we can see that it is possible to isolate the effect of intraday level dependence in stock prices using our estimator.

Suggested Citation

  • Padmakumari, Lakshmi & S., Maheswaran, 2017. "A new statistic to capture the level dependence in stock price volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 355-362.
    • Handle: RePEc:eee:quaeco:v:65:y:2017:i:c:p:355-362
    DOI: 10.1016/j.qref.2016.12.001
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    References listed on IDEAS

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    1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.

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    More about this item

    Keywords

    Volatility estimation; Random walk; Extreme values; Covariance; Constant Elasticity of Variance; Level dependence;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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