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Macroeconomic factors strike back: A Bayesian change-point model of time-varying risk exposures and premia in the U.S. cross-section

  • Daniele Bianchi


    (Bocconi University)

  • Massimo Guidolin


    (IGIER Bocconi University)

  • Francesco Ravazzolo


    (Norges Bank (Central Bank of Norway) and BI Norwegian Business School)

This paper proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. stocks and bonds. The model assumes that risk exposures and idiosynchratic volatility follow a break-point latent process, allowing for changes at any point in time but not restricting them to change at all points. An empirical application to 40 years of U.S. data and 23 portfolios shows that the approach yields sensible results compared to previous two-step methods based on naive recursive estimation schemes, as well as a set of alternative model restrictions. A variance decomposition test shows that although most of the predictable variation comes from the market risk premium, a number of additional macroeconomic risks, including real output and inflation shocks, are significantly priced in the cross-section. A Bayes factor analysis decisively favors the proposed change-point model.

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Paper provided by Norges Bank in its series Working Paper with number 2013/19.

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Length: 52 pages
Date of creation: 22 Aug 2013
Date of revision:
Handle: RePEc:bno:worpap:2013_19
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  1. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February.
  2. Cochrane, John H. & Campbell, John, 1999. "By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Scholarly Articles 3119444, Harvard University Department of Economics.
  3. Harvey, Campbell R., 2001. "The specification of conditional expectations," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 573-637, December.
  4. John M. Maheu & Thomas H. McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Paper Series 19-07, The Rimini Centre for Economic Analysis, revised Jul 2007.
  5. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
  6. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-87, September.
  7. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  8. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
  9. Robert F. Dittmar, 2002. "Nonlinear Pricing Kernels, Kurtosis Preference, and Evidence from the Cross Section of Equity Returns," Journal of Finance, American Finance Association, vol. 57(1), pages 369-403, 02.
  10. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
  11. John M Maheu & Stephen Gordon, 2007. "Learning, Forecasting and Structural Breaks," Working Papers tecipa-284, University of Toronto, Department of Economics.
  12. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2000. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," NBER Working Papers 7590, National Bureau of Economic Research, Inc.
  13. Bekaert, Geert & Hodrick, Robert J. & Zhang, Xiaoyan, 2012. "Aggregate Idiosyncratic Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(06), pages 1155-1185, December.
  14. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
  15. Giordani, Paolo & Villani, Mattias, 2010. "Forecasting macroeconomic time series with locally adaptive signal extraction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 312-325, April.
  16. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
  17. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-87.
  18. Lamont, Owen A., 2001. "Economic tracking portfolios," Journal of Econometrics, Elsevier, vol. 105(1), pages 161-184, November.
  19. Sangjoon Kim, Neil Shephard & Siddhartha Chib, . "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
  20. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
  21. Jostova, Gergana & Philipov, Alexander, 2005. "Bayesian Analysis of Stochastic Betas," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(04), pages 747-778, December.
  22. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
  23. Martin Lettau & Sydney Ludvigson, 1999. "Resurrecting the (C)CAPM: a cross-sectional test when risk premia are time-varying," Staff Reports 93, Federal Reserve Bank of New York.
  24. Burmeister, Edwin & McElroy, Marjorie B, 1988. " Joint Estimation of Factor Sensitivities and Risk Premia for the Arbitrage Pricing Theory," Journal of Finance, American Finance Association, vol. 43(3), pages 721-33, July.
  25. Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper Series 43_14, The Rimini Centre for Economic Analysis.
  26. Shanken, Jay, 1992. "On the Estimation of Beta-Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 1-33.
  27. Luboš Pástor & Robert F. Stambaugh, . "Liquidity Risk and Expected Stock Returns," CRSP working papers 531, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
  28. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2009. "Real-Time Inflation Forecasting in a Changing World," Working Paper 2009/16, Norges Bank.
  29. Randi Næs & Johannes A. Skjeltorp & Bernt Arne Ødegaard, 2011. "Stock Market Liquidity and the Business Cycle," Journal of Finance, American Finance Association, vol. 66(1), pages 139-176, 02.
  30. Karolyi, G Andrew & Sanders, Anthony B, 1998. "The Variation of Economic Risk Premiums in Real Estate Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 17(3), pages 245-62, November.
  31. Gary Koop & Simon M. Potter, 2007. "Estimation and Forecasting in Models with Multiple Breaks," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 763-789.
  32. McCulloch, Robert & Rossi, Peter E., 1991. "A bayesian approach to testing the arbitrage pricing theory," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 141-168.
  33. Shanken, Jay & Weinstein, Mark I., 2006. "Economic forces and the stock market revisited," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 129-144, March.
  34. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  35. Geweke, John & Amisano, Gianni, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 0969, European Central Bank.
  36. Kramer, Charles, 1994. " Macroeconomic Seasonality and the January Effect," Journal of Finance, American Finance Association, vol. 49(5), pages 1883-91, December.
  37. Sermin Gungor & Richard Luger, 2013. "Testing Linear Factor Pricing Models With Large Cross Sections: A Distribution-Free Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 66-77, January.
  38. Nardari, Federico & Scruggs, John T., 2007. "Bayesian Analysis of Linear Factor Models with Latent Factors, Multivariate Stochastic Volatility, and APT Pricing Restrictions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(04), pages 857-891, December.
  39. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
  40. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
  41. Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 338-57, July.
  42. Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, vol. 13(3), pages 341-360, December.
  43. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
  44. Chan, Louis K. C. & Karceski, Jason & Lakonishok, Josef, 1998. "The Risk and Return from Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(02), pages 159-188, June.
  45. Shiller, Robert J, 1979. "The Volatility of Long-Term Interest Rates and Expectations Models of the Term Structure," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1190-1219, December.
  46. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-36, May-June.
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