Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-26T08:37:40.694Z Has data issue: false hasContentIssue false

Optimal Portfolios under Time-Varying Investment Opportunities, Parameter Uncertainty, and Ambiguity Aversion

Published online by Cambridge University Press:  03 June 2019

Thomas Dangl*
Affiliation:
Dangl, [email protected], Vienna University of Technology Institute of Management Science, Vienna Graduate School of Finance, and Spängler IQAM Invest
Alex Weissensteiner
Affiliation:
Weissensteiner, [email protected], Free University of Bozen-Bolzano School of Economics and Management
*
Dangl (corresponding author), [email protected]

Abstract

We study the implications of predictability on the optimal asset allocation of ambiguity-averse long-term investors and analyze the term structure of the multivariate risk–return trade-off considering parameter uncertainty. We calibrate the model to real returns of U.S. stocks, long-term bonds, cash, real estate, and gold using the term spread and the dividend–price ratio as additional predictive variables, and we show that over long horizons, the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. The ambiguity-averse long-term investor optimally tilts his or her portfolio toward a seemingly inefficient portfolio, which shows maximum robustness against estimation errors.

Type
Research Article
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We thank Jennifer Conrad (the editor) and Victor DeMiguel (the referee) for their great support during the refereeing process. We gratefully acknowledge comments from Nicole Branger, Lorenzo Garlappi, Holger Kraft, Christoph Meinerding, Raman Uppal, and Josef Zechner.

References

Ameriks, J., and Zelden, S. P.. “How Do Household Portfolio Shares Vary with Age?” Working Paper, Columbia University (2004).Google Scholar
Avramov, D.Stock Return Predictability and Model Uncertainty.” Journal of Financial Economics, 64 (2002), 423458.Google Scholar
Avramov, D., and Zhou, G.. “Bayesian Portfolio Analysis.” Annual Review of Financial Economics, 2 (2010), 2547.Google Scholar
Barberis, N.Investing for the Long Run When Returns Are Predictable.” Journal of Finance, 55 (2000), 225264.Google Scholar
Bauer, M. D.; Rudebusch, G. D.; and Wu, J. C.. “Correcting Estimation Bias in Dynamic Term Structure Models.” Journal of Business and Economic Statistics, 30 (2012), 454467.Google Scholar
Bawa, V. S.; Brown, S. J.; and Klein, R. W.. Estimation Risk and Optimal Portfolio Choice. Netherlands, Amsterdam: North Holland (1979).Google Scholar
Bekaert, G.; Hodrick, R. J.; and Marshall, D. A.. “On Biases in Tests of the Expectations Hypothesis of the Term Structure of Interest Rates.” Journal of Financial Economics, 44 (1997), 309348.Google Scholar
Bilias, Y.; Georgarakos, D.; and Haliassos, M.. “Portfolio Inertia and Stock Market Fluctuations.” Journal of Money, Credit and Banking, 42 (2010), 715742.Google Scholar
Blume, M. E., and Keim, D. B.. “Institutional Investors and Stock Market Liquidity: Trends and Relationships.” Working Paper, University of Pennsylvania (2012).Google Scholar
Brennan, M. J.; Schwartz, E. S.; and Lagnado, R.. “Strategic Asset Allocation.” Journal of Economic Dynamics and Control, 21 (1997), 13771403.Google Scholar
Bullard, J.“The Aftermath of the Housing Bubble.” Speech given at the Federal Reserve Bank of St. Louis, June 5, 2012. Available at https://www.stlouisfed.org/∼/media/Files/PDFs/Bullard/remarks/BullardBipartisanPolicyCenter5June2012Final.pdf (2012).Google Scholar
Campbell, J. Y.Household Finance.” Journal of Finance, 61 (2006), 15531604.Google Scholar
Campbell, J. Y.; Chan, Y. L.; and Viceira, L. M.. “A Multivariate Model of Strategic Asset Allocation.” Journal of Financial Economics, 67 (2003), 4180.Google Scholar
Campbell, J. Y., and Shiller, R. J.. “The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors.” Review of Financial Studies, 1 (1988), 195228.Google Scholar
Campbell, J. Y., and Thompson, S. B.. “Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?Review of Financial Studies, 21 (2008), 15091531.Google Scholar
Campbell, J. Y., and Viceira, L. M.. Strategic Asset Allocation: Portfolio Choice for Long-Term Investors. New York, NY: Oxford University Press (2002).Google Scholar
Campbell, J. Y., and Viceira, L. M.. “The Term Structure of the Risk-Return Trade-Off.” Financial Analysts Journal, 61 (2005), 3444.Google Scholar
Chopra, V. K., and Ziemba, W. T.. “The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice.” Journal of Portfolio Management, 19 (1993), 611.Google Scholar
Cieslak, A., and Povala, P.. “Expected Returns in Treasury Bonds.” Review of Financial Studies, 28 (2015), 28592901.Google Scholar
Clarke, R.; De Silva, H.; and Thorley, S.. “Minimum-Variance Portfolio Composition.” Journal of Portfolio Management, 37 (2011), 3145.Google Scholar
Cochrane, J. H.A Mean-Variance Benchmark for Intertemporal Portfolio Theory.” Journal of Finance, 69 (2014), 149.Google Scholar
Cochrane, J. H., and Piazzesi, M.. “Bond Risk Premia.” American Economic Review, 95 (2005), 138160.Google Scholar
Cremers, M. K. J.Stock Return Predictability: A Bayesian Model Selection Perspective.” Review of Financial Studies, 15 (2002), 12231249.Google Scholar
Cronqvist, H.; Thaler, R. H.; and Yu, F.. “When Nudges Are Forever: Inertia in the Swedish Premium Pension Plan.” AEA Papers and Proceedings, 108 (2018), 153158.Google Scholar
Dangl, T., and Halling, M.. “Predictive Regressions with Time-Varying Coefficients.” Journal of Financial Economics, 106 (2012), 157181.Google Scholar
Davis, M. A.; Lehnert, A.; and Martin, R. F.. “The Rent-Price Ratio for the Aggregate Stock of Owner-Occupied Housing.” Review of Income and Wealth, 54 (2008), 279284.Google Scholar
Diebold, F. X., and Li, C.. “Forecasting the Term Structure of Government Bond Yields.” Journal of Econometrics, 130 (2006), 337364.Google Scholar
Engsted, T., and Pedersen, T. Q.. “Return Predictability and Intertemporal Asset Allocation: Evidence from a Bias-Adjusted VAR Model.” Journal of Empirical Finance, 19 (2012), 241253.Google Scholar
Engsted, T., and Pedersen, T. Q.. “Bias-Correction in Vector Autoregressive Models: A Simulation Study.” Econometrics, 2 (2014), 4571.Google Scholar
Fama, E. F.Multiperiod Consumption-Investment Decisions.” American Economic Review, 60 (1970), 163174.Google Scholar
Fama, E. F., and Bliss, R. R.. “The Information in Long-Maturity Forward Rates.” American Economic Review, 77 (1987), 680692.Google Scholar
Fama, E. F., and French, K. R.. “Dividend Yields and Expected Stock Returns.” Journal of Financial Economics, 22 (1988a), 325.Google Scholar
Fama, E. F., and French, K. R.. “Permanent and Temporary Components of Stock Prices.” Journal of Political Economy, 96 (1988b), 246273.Google Scholar
Fama, E. F., and Schwert, G. W.. “Asset Returns and Inflation.” Journal of Financial Economics, 5 (1977), 115146.Google Scholar
Flavin, M., and Yamashita, T.. “Owner-Occupied Housing and the Composition of the Household Portfolio.” American Economic Review, 92 (2002), 345362.Google Scholar
Garlappi, L.; Uppal, R.; and Wang, T.. “Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach.” Review of Financial Studies, 20 (2007), 4181.Google Scholar
Gilboa, I., and Schmeidler, D.. “Maxmin Expected Utility with Non-Unique Prior.” Journal of Mathematical Economics, 18 (1989), 141153.Google Scholar
Gorton, G. B.; Hayashi, F.; and Rouwenhorst, K. G.. “The Fundamentals of Commodity Futures Returns.” Review of Finance, 17 (2012), 35105.Google Scholar
Hurst, B.; Ooi, Y. H.; and Pedersen, L. H.. “A Century of Evidence on Trend-Following Investing.” Journal of Portfolio Management, 44 (2017), 1529.Google Scholar
Jones, C. M.“A Century of Stock Market Liquidity and Trading Costs.” Working Paper, Columbia Business School (2002).Google Scholar
Kan, R., and Zhou, G.. “Optimal Portfolio Choice with Parameter Uncertainty.” Journal of Financial and Quantitative Analysis, 42 (2007), 621656.Google Scholar
Kandel, S., and Stambaugh, R. F.. “On the Predictability of Stock Returns: An Asset-Allocation Perspective.” Journal of Finance, 51 (1996), 385424.Google Scholar
Keim, D. B., and Stambaugh, R. F.. “Predicting Returns in the Stock and Bond Markets.” Journal of Financial Economics, 17 (1986), 357390.Google Scholar
Kilian, L.Small-Sample Confidence Intervals for Impulse Response Functions.” Review of Economics and Statistics, 80 (1998), 218230.Google Scholar
Kim, T. S., and Omberg, E.. “Dynamic Nonmyopic Portfolio Behavior.” Review of Financial Studies, 9 (1996), 141161.Google Scholar
Knight, F.Risk, Uncertainty, and Profit. New York, NY: Houghton Mifflin (1921).Google Scholar
Li, C. W.; Tiwari, A.; and Tong, L.. “Investment Decisions under Ambiguity: Evidence from Mutual Fund Investor Behavior.” Management Science, 63 (2017), 25092528.Google Scholar
Marida, K. V.; Kent, J. T.; and Bibby, J. M.. Multivariate Analysis. London, England: Academic Press (1979).Google Scholar
Merton, R. C.Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case.” Review of Economics and Statistics, 51 (1969), 247257.Google Scholar
Merton, R. C.Optimum Consumption and Portfolio Rules in a Continuous-Time Model.” Journal of Economic Theory, 3 (1971), 373413.Google Scholar
Merton, R. C.An Intertemporal Capital Asset Pricing Model.” Econometrica, 41 (1973), 867887.Google Scholar
Meucci, A.Risk and Asset Allocation. Berlin, Germany: Springer Science & Business Media (2009).Google Scholar
Nicholls, D. F., and Pope, A. L.. “Bias in the Estimation of Autoregressions.” Australian Journal of Statistics, 30 (1988), 296309.Google Scholar
Pastor, L., and Stambaugh, R. F.. “Are Stocks Really Less Volatile in the Long Run?Journal of Finance, 67 (2012), 431477.Google Scholar
Pope, A. L.Biases of Estimators in Multivariate Non-Gaussian Autoregressions.” Journal of Time Series Analysis, 11 (1990), 249258.Google Scholar
Rapach, D. E.; Strauss, J. K.; and Zhou, G.. “Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy.” Review of Financial Studies, 23 (2010), 821862.Google Scholar
Samuelson, P. A.Lifetime Portfolio Selection by Dynamic Stochastic Programming.” Review of Economics and Statistics, 51 (1969), 239246.Google Scholar
Samuelson, W., and Zeckhauser, R.. “Status Quo Bias in Decision Making.” Journal of Risk and Uncertainty, 1 (1988), 759.Google Scholar
Sharpe, W. F.Imputing Expected Security Returns from Portfolio Composition.” Journal of Financial and Quantitative Analysis, 9 (1974), 463472.Google Scholar
Shiller, R. J.Irrational Exuberance. Princeton, NJ: Princeton University Press (2015).Google Scholar
Stambaugh, R. F.Predictive Regressions.” Journal of Financial Economics, 54 (1999), 375421.Google Scholar
Welch, I., and Goyal, A.. “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction.” Review of Financial Studies, 21 (2008), 14551508.Google Scholar
Xia, Y.Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation.” Journal of Finance, 56 (2001), 205246.Google Scholar
Zagst, R., and Pöschik, M.. “Inverse Portfolio Optimisation under Constraints.” Journal of Asset Management, 9 (2008), 239253.Google Scholar
Zellner, A.An Introduction to Bayesian Inference in Econometrics. New York, NY: John Wiley & Sons (1971).Google Scholar
Supplementary material: File

Dangl and Weissensteiner supplementary material

Online Appendix

Download Dangl and Weissensteiner supplementary material(File)
File 341.3 KB