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Long Memory and the Term Structure of Risk

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  • Schotman, Peter

    ()

  • Tschernig, Rolf

    ()

  • Budek, Jan

Abstract

This paper explores the implications of asset return predictability on long-term portfolio choice when return forecasting variables exhibit long memory. We model long memory using the class of fractionally integrated time series models. Important predictor variables for U.S. data, like the dividend-price ratio and nominal and real interest rates, are non-stationary with orders of integration around 0.8. These time series properties lead to substantial increases of the estimated long-term risk of stocks, bonds and cash compared to earlier estimates obtained from a stationary VAR. Long-term risk increases because the fluctuations in the predictor variables imply that expected returns themselves become a significant source of long-term risk. We find that results are sensitive to the specification of the prediction equation of excess stock returns. The inclusion of the short-term nominal interest rate among the predictor variables has the most profound impact. Jointly with the dividend-price ratio it has significant predictive power, but contrary to the dividend-price ratio the nominal interest rate does not induce mitigating effects through mean reversion.

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File URL: http://epub.uni-regensburg.de/5132/2/Regensburger_Diskussionsbeitraege_Nr427.pdf
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Bibliographic Info

Paper provided by University of Regensburg, Department of Economics in its series University of Regensburg Working Papers in Business, Economics and Management Information Systems with number 427.

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Date of creation: 2008
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Handle: RePEc:bay:rdwiwi:5132

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Keywords: Long-term portfolio choice; Term structure of risk; Linear processes with fractional integration;

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Cited by:
  1. Lubos Pastor & Robert F. Stambaugh, 2009. "Are Stocks Really Less Volatile in the Long Run?," NBER Working Papers 14757, National Bureau of Economic Research, Inc.
  2. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," Economics Letters, Elsevier, vol. 122(2), pages 299-302.
  3. Carlo A. Favero & Andrea Tamoni, 2010. "Demographics and the Econometrics of the Term Structure of Stock Market Risk," Working Papers 367, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  4. Gil-Alana, Luis A. & Moreno, Antonio, 2012. "Uncovering the US term premium: An alternative route," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1181-1193.
  5. Daniela Osterrieder & Peter C. Schotman, 2012. "The Volatility of Long-term Bond Returns: Persistent Interest Shocks and Time-varying Risk Premiums," CREATES Research Papers 2012-35, School of Economics and Management, University of Aarhus.
  6. Daniela Osterrieder, 2013. "Interest Rates with Long Memory: A Generalized Affine Term-Structure Model," CREATES Research Papers 2013-17, School of Economics and Management, University of Aarhus.

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