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It’s All in the Timing: Simple Active Portfolio Strategies that Outperform Naïve Diversification

Published online by Cambridge University Press:  20 January 2012

Chris Kirby
Affiliation:
Belk College of Business, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223. christopher.kirby@uncc.edu
Barbara Ostdiek
Affiliation:
Jones Graduate School of Business, Rice University, PO Box 2932, Houston, TX 77252. ostdiek@rice.edu

Abstract

DeMiguel, Garlappi, and Uppal (2009) report that naïve diversification dominates mean-variance optimization in out-of-sample asset allocation tests. Our analysis suggests that this is largely due to their research design, which focuses on portfolios that are subject to high estimation risk and extreme turnover. We find that mean-variance optimization often outperforms naïve diversification, but turnover can erode its advantage in the presence of transaction costs. To address this issue, we develop 2 new methods of mean-variance portfolio selection (volatility timing and reward-to-risk timing) that deliver portfolios characterized by low turnover. These timing strategies outperform naïve diversification even in the presence of high transaction costs.

Type
Research Articles
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2012

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References

Balduzzi, P., and Lynch, A. W.. “Transaction Costs and Predictability: Some Utility Cost Calculations.” Journal of Financial Economics, 52 (1999), 4778.CrossRefGoogle Scholar
Brown, S. “Optimal Portfolio Choice under Uncertainty: A Bayesian Approach.” In Estimation Risk and Optimal Portfolio Choice, Bawa, V., Brown, S., and Klein, R., eds. Amsterdam: North Holland (1979).Google Scholar
Carhart, M. M. “On Persistence in Mutual Fund Performance.” Journal of Finance, 52 (1997), 5782.CrossRefGoogle Scholar
Crawford, S.; Hansen, J.; and Price, R.. “CRSP Portfolio Methodology and the Effect on Benchmark Returns.” Working Paper, Rice University (2009).Google Scholar
DeMiguel, V.; Garlappi, L.; and Uppal, R.. “Optimal versus Naive Diversification: How Inefficient Is the 1/ N Portfolio Strategy.” Review of Financial Studies, 22 (2009), 19151953.CrossRefGoogle Scholar
Fama, E. F., and French, K. R.. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics, 33 (1993), 356.CrossRefGoogle Scholar
Fleming, J.; Kirby, C.; and Ostdiek, B.. “The Economic Value of Volatility Timing.” Journal of Finance, 56 (2001), 329352.CrossRefGoogle Scholar
Fleming, J.; Kirby, C.; and Ostdiek, B.. “The Economic Value of Volatility Timing Using ‘Realized’ Volatility.” Journal of Financial Economics, 67 (2003), 473509.CrossRefGoogle 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.CrossRefGoogle Scholar
Hamilton, J. D. Time Series Analysis. Princeton, NJ: Princeton University Press (1994).CrossRefGoogle Scholar
Hansen, L. P. “Large Sample Properties of Generalized Method of Moments Estimators.” Econometrica, 50 (1982), 10291054.CrossRefGoogle Scholar
Jagannathan, R., and Ma, T.. “Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps.” Journal of Finance, 58 (2003), 16511683.CrossRefGoogle Scholar
Jegadeesh, N., and Titman, S.. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance, 48 (1993), 6591.CrossRefGoogle Scholar
Jorion, P.International Portfolio Diversification with Estimation Risk.” Journal of Business, 58 (1985), 259278.CrossRefGoogle Scholar
Jorion, P.Bayesian and CAPM Estimators of the Means: Implications for Portfolio Selection.” Journal of Banking and Finance, 15 (1991), 717727.CrossRefGoogle Scholar
Kan, R., and Zhou, G.. “Optimal Portfolio Choice with Parameter Uncertainty.” Journal of Financial and Quantitative Analysis, 42 (2007), 621656.CrossRefGoogle Scholar
Ledoit, O., and Wolf, M.. “Improved Estimation of the Covariance Matrix of Stock Returns with an Application to Portfolio Selection.” Journal of Empirical Finance, 10 (2003), 603621.CrossRefGoogle Scholar
Ledoit, O., and Wolf, M.. “Honey, I Shrunk the Sample Covariance Matrix: Problems in Mean-Variance Optimization.” Journal of Portfolio Management, 30 (2004), 110119.CrossRefGoogle Scholar
MacKinlay, A. C., and Pastor, L.. “Asset Pricing Models: Implications for Expected Returns and Portfolio Selection.” Review of Financial Studies, 13 (2000), 883916.CrossRefGoogle Scholar
Merton, R. C. “On Estimating the Expected Return on the Market: An Exploratory Investigation.” Journal of Financial Economics, 8 (1980), 323361.CrossRefGoogle Scholar
Pastor, L.Portfolio Selection and Asset Pricing Models.” Journal of Finance, 55 (2000), 179223.CrossRefGoogle Scholar
Pastor, L., and Stambaugh, R. F.. “Comparing Asset Pricing Models: An Investment Perspective.” Journal of Financial Economics, 56 (2000), 335381.CrossRefGoogle Scholar
Politis, D. N., and Romano, J. P.. “The Stationary Bootstrap.” Journal of the American Statistical Association, 89 (1994), 13031313.CrossRefGoogle Scholar
Tu, J., and Zhou, G.. “Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty.” Journal of Financial and Quantitative Analysis, 45 (2010), 959986.CrossRefGoogle Scholar
Tu, J., and Zhou, G.. “Markowitz Meets Talmud: A Combination of Sophisticated and Naive Diversification Strategies.” Journal of Financial Economics, 99 (2011), 204215.CrossRefGoogle Scholar