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An econometric analysis of volatility discovery

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  • Fruet Dias, Gustavo
  • Papailias, Fotis
  • Scherrer, Cristina

Abstract

We investigate information processing in the stochastic process driving stock’s volatility (volatility discovery). We apply fractionally cointegration techniques to decompose the estimates of the market-specific integrated variances into an estimate of the common integrated variance of the efficient price and a transitory component. The market weights on the common integrated variance of the efficient price are the volatility discovery measures. We relate the volatility discovery measure to the price discovery framework and formally show their roles on the identification of the integrated variance of the efficient price. We establish the limiting distribution of the volatility discovery measures by resorting to both long span and in-fill asymptotics. The empirical application is in line with our theoretical results, as it reveals that trading venues incorporate new information into the stochastic volatility process in an individual manner and that the volatility discovery analysis identifies a distinct information process than that based on the price discovery analysis.

Suggested Citation

  • Fruet Dias, Gustavo & Papailias, Fotis & Scherrer, Cristina, 2023. "An econometric analysis of volatility discovery," LSE Research Online Documents on Economics 121363, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:121363
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    File URL: http://eprints.lse.ac.uk/121363/
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    References listed on IDEAS

    as
    1. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    2. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
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    More about this item

    Keywords

    double asymptotics; fractionally cointegrated vector autoregressive model; high-frequency data; long memory; market microstructure; price discovery; realized measures;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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