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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.

Suggested Citation

  • Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
  • Handle: RePEc:knz:dpteco:1315
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    File URL: http://www.uni-konstanz.de/FuF/wiwi/workingpaperseries/WP_15-Barsoum_2013.pdf
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    1. Canova, Fabio, 1991. "The Sources of Financial Crisis: Pre- and Post-Fed Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 689-713, August.
    2. Ben S. Bernanke & Kenneth N. Kuttner, 2005. "What Explains the Stock Market's Reaction to Federal Reserve Policy?," Journal of Finance, American Finance Association, vol. 60(3), pages 1221-1257, June.
    3. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    4. Thorbecke, Willem, 1997. "On Stock Market Returns and Monetary Policy," Journal of Finance, American Finance Association, vol. 52(2), pages 635-654, June.
    5. Frederic S. Mishkin, 2009. "Monetary Policy Strategy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262513374, April.
    6. Gospodinov, Nikolay & Jamali, Ibrahim, 2012. "The effects of Federal funds rate surprises on S&P 500 volatility and volatility risk premium," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 497-510.
    7. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    9. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    10. John B. Taylor, 1999. "Introduction to "Monetary Policy Rules"," NBER Chapters, in: Monetary Policy Rules, pages 1-14, National Bureau of Economic Research, Inc.
    11. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    12. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    13. Brissimis, Sophocles N. & Magginas, Nicholas S., 2006. "Forward-looking information in VAR models and the price puzzle," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1225-1234, September.
    14. Bjørnland, Hilde C. & Leitemo, Kai, 2009. "Identifying the interdependence between US monetary policy and the stock market," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 275-282, March.
    15. Reinhart, Vincent & Simin, Timothy, 1997. "The market reaction to federal reserve policy action from 1989 to 1992," Journal of Economics and Business, Elsevier, vol. 49(2), pages 149-168.
    16. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    17. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    18. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    19. Refet S Gürkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    20. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    21. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    22. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    23. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
    24. Christopher A. Sims & Tao Zha, 1999. "Error Bands for Impulse Responses," Econometrica, Econometric Society, vol. 67(5), pages 1113-1156, September.
    25. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
    26. John B. Taylor, 1999. "A Historical Analysis of Monetary Policy Rules," NBER Chapters, in: Monetary Policy Rules, pages 319-348, National Bureau of Economic Research, Inc.
    27. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
    28. Tobin, James, 1969. "A General Equilibrium Approach to Monetary Theory," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 1(1), pages 15-29, February.
    29. Gospodinov, Nikolay & Jamali, Ibrahim, 2015. "The response of stock market volatility to futures-based measures of monetary policy shocks," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 42-54.
    30. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    31. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1228-1247, December.
    32. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    33. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    34. Blaes, Barno, 2009. "Money and monetary policy transmission in the euro area: evidence from FAVAR- and VAR approaches," Discussion Paper Series 1: Economic Studies 2009,18, Deutsche Bundesbank.
    35. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    36. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    37. Magnus Andersson, 2010. "Using Intraday Data to Gauge Financial Market Responses to Federal Reserve and ECB Monetary Policy Decisions," International Journal of Central Banking, International Journal of Central Banking, vol. 6(2), pages 117-146, June.
    38. Allan Zebedee & Eric Bentzen & Peter Hansen & Asger Lunde, 2008. "The Greenspan years: an analysis of the magnitude and speed of the equity market response to FOMC announcements," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 22(1), pages 3-20, March.
    39. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    40. Cook, Timothy & Hahn, Thomas, 1989. "The effect of changes in the federal funds rate target on market interest rates in the 1970s," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 331-351, November.
    41. Stephen P Millard & Simon J Wells, 2003. "The role of asset prices in transmitting monetary and other shocks," Bank of England working papers 188, Bank of England.
    42. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    43. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    44. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
    45. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
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    More about this item

    Keywords

    dynamic factor model; Bayesian estimation; factor-augmented vector autoregression; monetary policy; stock market volatility; long memory;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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