In this paper we introduce an intra-sector dynamic trading strategy that captures mean-reversion opportunities across liquid U.S. stocks. Our strategy combines the Avellaneda and Lee methodology (AL; Quant. Financ. 2010, 10, 761–782) within the Black and Litterman framework (BL; J. Fixed Income, 1991, 1, 7–18; Financ. Anal. J. 1992, 48, 28–43). In particular, we incorporate the s-scores and the conditional mean returns from the Orstein and Ulhembeck ( Phys. Rev. 1930, 36, 823–841) process into BL. We find that our combined strategy ALBL has generated a 45% increase in Sharpe Ratio when compared to the uncombined AL strategy over the period from January 2, 2001 to May 27, 2010. These new indices, built to capture dynamic trading strategies, will definitely be an interesting addition to the growing hedge fund index offerings. This paper introduces our first “focused-core” strategy, namely, U.S. Equity Mean-Reversion.
References
[1]
He, G.; Litterman, R. The Intuition Behind Black–Litterman Model Portfolio. Goldman Sachs, Investment Management Division: San Fransisco, CA, USA, 1999.
[2]
Poterba, M.J.; Summers, L.H. Mean reversion in stock prices: Evidence and implications. J. Financ. Econ. 1988, 22, 27–59, doi:10.1016/0304-405X(88)90021-9.
[3]
Fama, E.F.; French, K.R. Common risk factors in the returns on stocks and bonds. J. Financ. Econ. 1993, 33, 3–56, doi:10.1016/0304-405X(93)90023-5.
[4]
Fama, E.F.; French, K.R. Luck vs. skill in the cross section of mutual fund returns. J. Financ. 2010, 65, 1915–1947, doi:10.1111/j.1540-6261.2010.01598.x.
[5]
Carhart, M. On persistence in mutual fund performance. J. Financ. 1997, 52, 57–82, doi:10.1111/j.1540-6261.1997.tb03808.x.
[6]
Avellaneda, M.; Lee, J.H. Statistical arbitrage in the U.S. equity market. Quant. Financ. 2010, 10, 761–782, doi:10.1080/14697680903124632.
[7]
Black, F.; Litterman, R. Asset allocation: Combining investors’ views with market equilibrium. J. Fixed Income 1991, 1, 7–18, doi:10.3905/jfi.1991.408013.
[8]
Black, F.; Litterman, R. Global portfolio optimization. Financ. Anal. J. 1992, 48, 28–43, doi:10.2469/faj.v48.n5.28.
[9]
Herold, U. Portfolio construction with qualitative forecasts. J. Portfolio Manag. 2003, 30, 61–72, doi:10.3905/jpm.2003.319920.
[10]
Da Silva, A.S.; Lee, W.; Pornrojnangkool, B. The Black–Litterman model for active portfolio management. J. Portfolio Manag. 2009, 35, 61–70.
[11]
Uhlenbeck, E.G.; Ornstein, L.S. On the theory of the Brownian motion. Phys. Rev. 1930, 36, 823–841, doi:10.1103/PhysRev.36.823.
[12]
Lo, W.A.; MacKinlay, A.C. When are contrarian profits due to stock market overreaction? Rev. Financ. Stud. 1990, 3, 175–205, doi:10.1093/rfs/3.2.175.
[13]
Jegadeesh, N.; Titman, S. Returns to buying winners and selling losers: Implications for stock market efficiency. J. Financ. 1993, 48, 65–91, doi:10.1111/j.1540-6261.1993.tb04702.x.
[14]
Jegadeesh, N.; Titman, S. Overreaction, delayed reaction, and contrarian profits. Rev. Financ. Stud. 1995, 8, 973–993, doi:10.1093/rfs/8.4.973.
[15]
Satchell, S.; Scowcroft, A. A demystification of the Black–Litterman model: Managing quantitative and traditional portfolio construction. J. Asset Manag. 2000, 1, 138–150, doi:10.1057/palgrave.jam.2240011.
[16]
Idzorek, T. A Step-by-Step Guide to the Black–Litterman Model. In Forecasting Expected Returns in the Financial Markets; Satchell, S., Ed.; Academic Press: Waltham, MA, USA, 2007.
[17]
Yahoo! Finance Website. Available online: http://finance.yahoo.com (accessed on 1 October 2013).
