Abstract
In this paper, we employ the stochastic dominance (SD) approach to rank the performance of commodity trading advisors (CTA) funds. An advantage of this approach is that it alleviates the problems that can arise if CTA returns are not normally distributed by utilizing the entire returns distribution. We find both first-order and higher-order SD relationships amongst the CTA funds and conclude that investors are better off investing in the first-order dominant funds to maximize their expected utilities and expected wealth. However, for higher-order dominant CTAs, risk-averse investors can maximize their expected utilities but not their expected wealth. In addition to the advantages of the SD approach in the case of non-normal returns, the paper concludes that the approach is more appropriate compared with traditional approaches as a filter in the CTA selection process as it provides meaningful economic interpretation of the results.
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References
Alles L, Murray L (2010) Non-normality and risk in developing Asian markets. Rev Pac Basin Financ Mark Policies 13:583–605
Altucher J (2005) No bull market in trend-following. http://thestreet.com/rmoney/jamesaltucher/10224829.html
Anderson G (1996) Nonparametric tests of stochastic dominance in income distributions. Econometrica 64:1183–1193
Anderson G (2004) Toward an empirical analysis of polarization. J Econom 122:1–26
Bai ZD, Liu HX, Wong WK (2009) Enhancement of the applicability of Markowitz’s portfolio optimization by utilizing random matrix theory. Math Financ 19:639–667
Bai ZD, Li H, Liu HX, Wong WK (2011a) Test statistics for prospect and Markowitz stochastic dominances with applications. Econom J 14:278–303
Bai ZD, Liu HX, Wong WK (2011b) Asymptotic properties of eigenmatrices of a large sample covariance matrix. Ann Appl Probab 21:1994–2015
Bai ZD, Wang KY, Wong WK (2011c) An improvement of the Sharpe-ratio test on small samples—mean-variance ratio test. Statistics and Probability Letters 81:1078–1085
Bai ZD, Hui YC, Wong WK, Zitikis R (2012) Evaluating prospect performance: making a case for a non-asymptotic UMPU test. J Financ Econom (forthcoming)
Barrett GF, Donald SG (2003) Consistent tests for stochastic dominance. Econometrica 71:71–104
Bernard VL, Seyhun HN (1997) Does post-earnings-announcement drift in stock prices reflect a market inefficiency? A stochastic dominance approach. Rev Quant Financ Account 9:17–34
Bishop JA, Formly JP, Thistle PD (1992) Convergence of the south and non-south income distributions. Am Econom Rev 82:262–272
Chan CY, de Peretti C, Qiao Z, Wong WK (2012) Empirical test of the efficiency of UK covered warrants market: stochastic dominance and likelihood ratio test approach. J Empir Financ 19:162–174
Collins DP (2005) How to select a CTA. In: Futures, option and derivatives traders, July. pp 70–74
Davidson R, Duclos JY (2000) Statistical inference for stochastic dominance and for the measurement of poverty and inequality. Econometrica 68:1435–1464
Falk H, Levy H (1989) Market reaction to quarterly earnings’ announcements: a stochastic dominance based test of market efficiency. Manag Sci 35:425–446
Fong WM, Wong WK, Lean HH (2005) International momentum strategies: a stochastic dominance approach. J Financ Mark 8:89–109
Fong WM, Lean HH, Wong WK (2008) Stochastic dominance and behavior towards risk: the market for internet stocks. J Econ Behav Organ 68:194–208
Fung W, Hsieh DA (2000) Performance characteristics of hedge funds and commodity funds: natural vs. spurious biases. J Financ Quant Anal 35:291–307
Gasbarro D, Wong WK, Zumwalt JK (2007) Stochastic dominance analysis of iShares. Eur J Financ 13:89–101
Jarrow R (1986) The relationship between arbitrage and first order stochastic dominance. J Financ 41:915–921
Jensen MC (1969) Risk the pricing of capital assets and the evaluation of investment portfolios. J Bus 42:167–247
Kat HM (2003) 10 things that investors should know about hedge funds. J Wealth Manag 5:72–81
Kat HM (2004a) Managed futures and hedge funds: a match made in heaven. J Invest Manag 2:32–40
Kat HM (2004b) In search of the optimal fund of hedge funds. J Wealth Manag 6:43–51
Kat HM, Menexe F (2003) Persistence in hedge fund performance: the true value of a track record. J Alternat Invest 5:62–72
Kaur A, Rao BL, Singh H (1994) Testing for second-order stochastic dominance of two distributions. Econometric Theory 10:849–866
Kjetsaa R, Kieff M (2003) Stochastic dominance analysis of equity mutual fund performance. Am Bus Rev 21:1–8
Kooli M, Amvella SP, Gueyie JP (2005) Hedge funds in a portfolio context: a mean-modified value-at-risk framework. Deriv Use Trading Regul 10:373–383
Larsen GA, Resnick BG (1999) A performance comparison between cross-sectional stochastic dominance and traditional event study methodologies. Rev Quant Financ Acc 12:103–112
Lean HH, Smyth R, Wong WK (2007) Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach. J Multinatl Financ Manag 17:125–141
Lean HH, Wong WK, Zhang XB (2008) The size and power of some stochastic dominance tests: a Monte Carlo study for correlated and heteroskedastic distributions. Mathematics and Computer in Simulation 79:30–48
Lean HH, McAleer M, Wong WK (2010) Market efficiency of oil spot and futures: a mean-variance and stochastic dominance approach. Energy Econom 32:979–986
Lee D, Koh F, Phoon KF (2004) CTA strategies for returns-enhancing diversification. In: Gregoriou K, Lhabitant R (eds) Commodity trading advisors: risk, performance analysis and selection. Wiley, New York
Lee D, Phoon KF, Wong CY (2006) Moments analysis in risk and performance measurement. J Wealth Manag 9:54–65
Leshno M, Levy H (2002) Preferred by “all” and preferred by “most” decision makers: almost stochastic dominance. Manage Sci 48:1074–1085
Leung PL, Wong WK (2008) On testing the equality of the multiple sharpe ratios, with application on the evaluation of iShares. J Risk 10:1–16
Levy H (1992) Stochastic dominance and expected utility: survey and analysis. Manage Sci 38:555–593
Levy H (1998) Stochastic dominance: investment decision making under uncertainty. Kluwer, Boston
Levy H, Sarnat M (1970) Alternative efficiency criteria: an empirical analysis. J Financ 25:1153–1158
Linton O, Maasoumi E, Whang JY (2005) Consistent testing for stochastic dominance under general sampling schemes. Rev Econ Stud 72:735–765
Markowitz HM (1952) Portfolio selection. J Financ 7:77–91
Markowitz HM (1991) Foundations of Portfolio theory. Les Prix Nobel 1990, Nobel Foundation, Stockholm
McFadden D (1989) Testing for stochastic dominance. In: Fomby S (ed) Studies in the economics of uncertainty. Springer, New York, pp 113–132
Porter RB (1973) An empirical comparison of stochastic dominance and mean-variance portfolio choice criteria. J Financ Quant Anal 8:587–608
Post T, Levy H (2005) Does risk loving drive asset prices? Rev Financ Stud 18:925–953
Post T, Versijp P (2006) Multivariate tests for stochastic dominance efficiency of a given portfolio. Journal of Financial and Quantitative Analysis 42:489–516
Richmond J (1982) A general method for constructing simultaneous confidence intervals. J Am Stat Assoc 77:455–460
Seyhun HN (1993) Can omitted risk factors explain the January effect? A stochastic dominance approach. J Financ Quant Anal 28:195–212
Shalit H, Yitzhaki S (2010) How does beta explain stochastic dominance efficiency? Rev Quant Financ Acc 35:431–444
Sharpe WF (1964) Capital asset prices: theory of market equilibrium under conditions of risk. J Financ 19:442–452
Sriboonchitta S, Wong WK, Dhompongsa S, Nguyen HT (2009) Stochastic dominance and applications to finance, risk and economics. Chapman and Hall/CRC, Taylor and Francis Group, Boca Raton, Florida
Stoline MR, Ury HK (1979) Tables of the studentized maximum modulus distribution and an application to multiple comparisons among means. Technometrics 21:87–93
Taylor WR, Yoder YA (1999) Load and no-load mutual fund dynamics during the 1987 market crash: a stochastic dominance analysis. J Econom Financ 23:255–265
Treynor JL (1965) How to rate management of investment funds. Harv Bus Rev 43:63–75
Tse YK, Zhang X (2004) A Monte Carlo investigation of some tests for stochastic dominance. J Stat Comput Simul 74:361–378
Vinod HD (2004) Ranking mutual funds using unconventional utility theory and stochastic dominance. J Empir Financ 11:353–377
Vuille S, Crisan C (2004) A quantitative analysis of CTA funds. SSRN Working Paper No. 623261
Wei S, Zhang C (2003) Statistical and economic significance of stock return predictability: a mean-variance analysis. J Multinatl Financ Manag 13:443–463
Wong WK (2007) Stochastic dominance and mean-variance measures of profit and loss for business planning and investment. Eur J Oper Res 182:829–843
Wong WK, Chan RH (2008) Prospect and Markowitz stochastic dominance. Ann Financ 4:105–129
Wong WK, Li CK (1999) A note on convex stochastic dominance theory. Econ Lett 62:293–300
Wong WK, Ma C (2008) Preferences over Meyer’s location-scale family. Econ Theor 37:119–146
Wong WK, Thompson HE, Wei S, Chow YF (2006) Do winners perform better than losers? A stochastic dominance approach. Adv Quant Anal Financ Account 4:219–254
Wong WK, Phoon KF, Lean HH (2008) Stochastic dominance analysis of Asian hedge funds. Pacific-Basin Financ J 16:204–223
Acknowledgments
The authors are most grateful to Professor C.F. Lee and the referee for their substantive comments and suggestions that significantly improved this manuscript. The third author would like to thank Professors Robert B. Miller and Howard E. Thompson for their continuous guidance and encouragement. The research is partially supported by Universiti Sains Malaysia, Singapore Management University, Hong Kong Baptist University, and the Research Grants Council (RGC) of Hong Kong. The first author would like to acknowledge Universiti Sains Malaysia (RU Grant No. 1001/PSOSIAL/816094).
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Lean, H.H., Phoon, K.F. & Wong, WK. Stochastic dominance analysis of CTA funds. Rev Quant Finan Acc 40, 155–170 (2013). https://doi.org/10.1007/s11156-012-0284-1
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DOI: https://doi.org/10.1007/s11156-012-0284-1