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Conditional Quantiles of Volatility in Equity Index and Foreign Exchange Data


  • John Galbraith
  • Serguei Zernov
  • Victoria Zinde-Walsh


This paper uses estimation techniques related to those of Galbraith and Zinde-Walsh (2000) for ARCH and GARCH models, based on realized volatility (Andersen and Bollerslev 1998, and others), to estimate the conditional quantiles of daily volatility in samples of equity index and foreign exchange data. These techniques in principle allow us to characterize the entire conditional distribution of volatility, conditioning on past realized volatility and past squared returns. We take samples of daily and intra-day returns on the Toronto Stock Exchange 35 index, the DM/$ US exchange rate and the Yen/$ US exchange rate. In addition to information about the conditional extremes of volatility, we find some evidence that lower percentiles of the conditional distribution rise proportionately less in high-volatility periods than do the higher percentiles. Nous utilisons des techniques d'estimation de modèle reliées à ceux de Galbraith et Zinde-Walsh (2000) pour les modèles ARCH et GARCH, basées sur la realized volatility (Andersen et Bollerslev 1998, et autres), afin d'obtenir les quantiles conditionnels de volatilité quotidienne dans les données provenant des marchés boursiers et des marchés de devises étrangères. Ces méthodes nous permettent en principe de caractériser la distribution entière de volatilité en utilisant la volatilité réalisée et les retours carrés. Nous prenons des échantillons de rendements quotidiens et intrajournaliers de l'indice 35 du TSE, et des taux de change DM/$ US et Yen/$ US. Nos résultats montrent également que les percentiles inférieurs de la distribution conditionnelle augmentent proportionnellement moins en périodes de volatilité extrême que les percentiles supérieurs.

Suggested Citation

  • John Galbraith & Serguei Zernov & Victoria Zinde-Walsh, 2001. "Conditional Quantiles of Volatility in Equity Index and Foreign Exchange Data," CIRANO Working Papers 2001s-61, CIRANO.
  • Handle: RePEc:cir:cirwor:2001s-61

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    References listed on IDEAS

    1. Christoffersen, Peter & Ghysels, Eric & Swanson, Norman R., 2002. "Let's get "real" about using economic data," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 343-360, August.
    2. Nathalie de Marcellis-Warin & Erwann Michel-Kerjan, 2001. "The Public-Private Sector Risk-Sharing in the French Insurance "Cat. Nat. System"""," CIRANO Working Papers 2001s-60, CIRANO.
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    More about this item


    GARCH model; integrated volatility; quantile regression; Modèle GARCH; volatilité intégrée; régression quantile;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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