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The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach

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  • Fady Barsoum

    ()
    (Department of Economics, University of Konstanz, Germany)

Abstract

This paper investigates the response of stock market volatility to a monetary policy shock using a structural factor-augmented Bayesian vector autoregressive (FAVAR) model. We construct a monthly dataset of realized volatilities of the constituents of the S&P500 index and extract volatility factors from this dataset using a suitable dynamic factor model (DFM). The volatility factors are included in a structural FAVAR model where the dynamic response of stock market volatility to a monetary policy shock is analyzed. This approach does not only allow us to study the response of the aggregate market volatility but also the responses of all the volatilities of the single stocks and the different sectors included in the dataset. In general, the results show that the stock market returns decrease and the stock market volatility increases following a monetary policy tightening. Although the magnitude of the volatility response to monetary policy shocks varies between the different stocks and sectors, the dynamics of the response does not differ widely. Both the magnitude and dynamics of the volatility response depend on the sample period examined.

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Bibliographic Info

Paper provided by Department of Economics, University of Konstanz in its series Working Paper Series of the Department of Economics, University of Konstanz with number 2013-15.

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Length: 35 pages
Date of creation: 15 Feb 2013
Date of revision:
Handle: RePEc:knz:dpteco:1315

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Related research

Keywords: dynamic factor model; Bayesian estimation; factor-augmented vector autoregression; monetary policy; stock market volatility; long memory;

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