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Predicting Covariance Matrices with Financial Conditions Indexes

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Author Info

  • Anne Opschoor

    (Erasmus University Rotterdam)

  • Dick van Dijk

    (Erasmus University Rotterdam)

  • Michel van der Wel

    (Erasmus University Rotterdam)

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    Abstract

    We model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we consider daily stock returns of US deposit banks during the period 1994-2011, and proxy financial conditions by the Bloomberg Financial Condi- tions Index (FCI) which comprises the money, bond, and equity markets. We find that worse financial conditions are associated with both higher volatility and higher average correlations between stock returns. Especially during crises the additional impact of the FCI indicator is considerable, with an increase in correlations by 0.15. Moreover, including the FCI in volatility and correlation modeling improves Value-at-Risk forecasts, particularly at short horizons.

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    Bibliographic Info

    Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 13-113/III.

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    Date of creation: 09 Aug 2013
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    Handle: RePEc:dgr:uvatin:20130113

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    Web page: http://www.tinbergen.nl

    Related research

    Keywords: Dynamic correlations; Volatility modeling; Financial Conditions Indexes; Bank holding companies;

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