Performance examination of trading strategy based on Stochastic Dominance

Subject Areas : Financial Knowledge of Securities Analysis

Maryam Davallou ¹ , Shayan Meskinimood ²

1 - Assistant Prof., Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
2 - MSc. in Financial Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

Received: 2017-05-05 Accepted : 2017-07-23 Published : 2019-03-21

Keywords: Risk Adjusted Return, Stochastic Dominance, Trading Strategy,

Abstract :

The aim of this research is to examine the performance of a trading strategy based on stochastic dominance in Iran’s stock market. To achieve this purpose, we used a sample including the daily returns of the stocks listed on Tehran stock exchange, between 2001 and 2015, and exploited the portfolio study approach. In this way, for each month portfolios are constructed based on second and third degree stochastic dominance, by buying the dominance stocks and selling the dominated ones. Then the performance of this trading strategy is tested with the respect to the obtained alphas from an extended five-factor model. The results show that the arbitrage portfolios based on stochastic dominance produce positive, statistically significant, excess returns. In addition, these returns are robust even after being adjusted to risk premiums (Market, Size, Value, Liquidity and Momentum premiums). Consequently, the results support the fact that the stochastic dominance factor is engaged in pricing of the Tehran stock exchange. Moreover, it is crucial to notice that the potential price distortions related to infrequent trading have an enormous impact on the results of the study.

References:

*      اکبری، مجتبی و زمانیان، غلامرضا. (1394). سنجش ریسک و رتبه‌بندی شرکت‌های صنعت خودرو در بورس اوراق بهادار تهران با استفاده از معیار تسلط تصادفی و مقایسه آن با انحراف معیار. چهارمین کنفرانس ملی مدیریت و حسابداری.

*      بدری، احمد.، عرب‌مازار یزدی، محمد.،  حمیدی‌زاده، محمدرضا و عبدالباقی، عبدالمجید. (1392). برتری تصادفی مبتنی بر صرف ارزش و رفتار ریسک‌گریزانه سرمایه‌گذاران در بورس اوراق بهادار تهران. فصلنامه مدیریت دارایی و تامین مالی، 1(1)، 45-62.

*      پدرام، پرهام. (1388). تبیین و آزمون الگوریتم روش تسلط تصادفی برای ارزیابی کارایی پرتفوی بهینه، مطالعات مالی، 1، 65-83.

*      ترجمان، وینا و راعی، رضا. (1390). محاسبه ریسک با معیار تسلط تصادفی و مقایسه آن با سایر معیارهای متداول در بورس اوراق بهادار تهران. دو ماهنامه دانشور رفتار/مدیریت و پیشرفت، 18(2-47)، 355-370.

*      زمانیان، غلامرضا و جمشیدی، سجاد. (1394). ارزیابی عملکرد و رتبه‌بندی شرکت‌های فرابورس ایران با استفاده از معیار تسلط تصادفی. کنفرانس بین‌المللی مدیریت، اقتصاد و سیستم‌های مالی.

*      شایگان‌مهر، علی و شایگان‌مهر، سیما. (1394). بررسی اثرات تقویمی در بورس اوراق بهادار تهران با رویکرد معیار تسلط تصادفی. دانش سرمایه‌گذاری، 4 (16)، 125-146.

*      شایگان‌مهر، علی، زمانیان، غلامرضا و شهیکی‌تاش محمدنبی. (1394). ارزیابی عملکرد صندوق‌های سرمایه‌گذاری مشترک با استفاده از معیار غلبه تصادفی و مقایسه با نسبت شارپ و نسبت سورتینو. فصلنامه مدیریت دارایی و تأمین مالی، 3 (4)،  67-84.

*      کشاورز حداد، غلامرضا و اصفهانی، محمدرضا. (1392). معمای صرف سهام در بورس اوراق بهادار تهران در چارچوب آزمون‌های تسلط تصادفی. فصلنامه پژوهش‌های اقتصادی ایران، 18(56)، 1-40.

*      Abhyankar, A., Ho, K. Y., & Zhao, H. (2008). Value versus growth: stochastic dominance criteria. Quantitative Finance, 8(7), 693-704.

*      Abhyankar, A., Ho, K. Y., & Zhao, H. (2009). International value versus growth: evidence from stochastic dominance analysis. International Journal of Finance & Economics, 14(3), 222-232.

*      Abid, F., Leung, P. L., Mroua, M., & Wong, W. K. (2014). International diversification versus domestic diversification: mean-variance portfolio optimization and stochastic dominance approaches. Journal of Risk and Financial Management, 7(2), 45-66.

*      Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of financial markets, 5(1), 31-56.

*      Babbel, D. F., & Herce, M. (2007). A closer look at stable value funds performance. Wharton Financial Institutions Center, Working Paper No. 07-21.

*      Bawa, V. S. (1975). Optimal rules for ordering uncertain prospects. Journal of Financial Economics, 2(1), 95-121.

*      Bhootra, A. (2011). Are momentum profits driven by the cross-sectional dispersion in expected stock returns? Journal of Financial Markets, 14(3), 494-513.

*      Blackwell, D. (1951). Comparison of experiments. In Proceedings of the second Berkeley symposium on mathematical statistics and probability, 1, 93-102.

*      Blackwell, D. (1953). Equivalent comparisons of experiments. The annals of mathematical statistics, 24(2), 265-272.

*      Breen, W., & Savage, J. (1968). Portfolio distributions and tests of security selection models. The Journal of Finance, 23(5), 805-819.

*      Clark, E., & Kassimatis, K. (2014). Exploiting stochastic dominance to generate abnormal stock returns. Journal of Financial Markets, 20, 20-38.

*      Davidson, R., & Duclos, J. Y. (2000). Statistical inference for stochastic dominance and for the measurement of poverty and inequality. Econometrica: Journal of the Econometric Society, 68(6), 1435-1464.

*      Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of financial economics, 33(1), 3-56.

*      Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. The Journal of Political Economy, 607-636.

*      Fishburn, P. C. (1964). Decision and value theory. John Wiley and Sons, New York.

*      Fong, W. M., Lean, H. H., & Wong, W. K. (2008). Stochastic dominance and behavior towards risk: the market for internet stocks. Journal of Economic Behavior & Organization, 68(1), 194-208.

*      Gonzalo, J., & Olmo, J. (2014). Conditional stochastic dominance tests in dynamic settings. International Economic Review, 55(3), 819-838.

*      Hadar, J., & Russell, W. R. (1969). Rules for ordering uncertain prospects. The American Economic Review, 59(1), 25-34.

*      Hanoch, G., & Levy, H. (1969). The efficiency analysis of choices involving risk. The Review of Economic Studies, 36(3), 335-346.

*      Hardy, G. H., Littlewood, J. E., & Pólya, G. (1952). Inequalities. Cambridge university press.

*      Hsieh, C.S. (2016). Revisiting the monthly effect for the Chinese’ stock markets. Applied Economics and Finance, 3(2), 73-87.

*      Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of finance, 48(1), 65-91.

*      Jensen, M. C. (1978). Some anomalous evidence regarding market efficiency. Journal of financial economics, 6(2/3), 95-101.

*      Karamata, J. (1932). Sur une inégalité relative aux fonctions convexes. Publications de l'Institut mathematique, 1(1), 145-147.

*      Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. The journal of finance, 49(5), 1541-1578.

*      Lean, H. H., McAleer, M., & Wong, W. K. (2010). Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach. Energy Economics, 32(5), 979-986.

*      Lean, H. H., & McAleer, M. (2013). Risk-averse and risk-seeking investor preferences for oil spot and futures. Tinbergen Institute Discussion Paper, 13-132/III.

*      Lehmann, E. L. (1955). Ordered families of distributions. The Annals of Mathematical Statistics, 399-419.

*      Levy, H. (1992). Stochastic dominance and expected utility: survey and analysis. Management Science, 38(4), 555-593.

*      Levy, H. (2006, 2015). Stochastic dominance: Investment decision making under uncertainty. Springer Science & Business Media.

*      Linton, O., Maasoumi, E., & Whang, Y. J. (2005). Consistent testing for stochastic dominance under general sampling schemes. The Review of Economic Studies, 72(3), 735-765.

*      Malkiel, B. G., & Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The journal of Finance, 25(2), 383-417.

*      Malkiel, B. G. (2003). The efficient market hypothesis and its critics. The Journal of Economic Perspectives, 17(1), 59-82.

*      Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. The annals of mathematical statistics, 50-60.

*      Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.

*      Meyer, T. O., Xiao-Ming, L., & Rose, L. C. (2005). Comparing mean variance tests with stochastic dominance tests when assessing international portfolio diversification benefits. Financial Services Review, 14(2), 149-168.

*      Qiao, Z., Clark, E., & Wong, W. K. (2014). Investors’ preference towards risk: evidence from the Taiwan stock and stock index futures markets. Accounting & Finance, 54(1), 251-274.

*      Quirk, J. P., & Saposnik, R. (1962). Admissibility and measurable utility functions. The Review of Economic Studies, 29(2), 140-146.

*      Roman, D., & Mitra, G. (2009). Portfolio selection models: A review and new directions. Wilmott Journal, 1(2), 69-85.

*      Rothschild, M., & Stiglitz, J. E. (1970). Increasing risk: I. A definition. Journal of Economic theory, 2(3), 225-243.

*      Thompson, H. E., Wei, S., & Chow, Y. F. (2007). Do Winners Perform Better Than Losers?: A Stochastic Dominance Approach. Advances in Quantitative Analysis of Finance and Accounting. 4, 219–254.

*      Von Neumann, J., & Morgenstern, O. (1962). Theory of games and economic behavior. The Review of Economics Studies, 29, 140–146.

*      Whitmore, G. A. (1970). Third-degree stochastic dominance. The American Economic Review, 60(3), 457-459.

*      Xiong, J. X., & Idzorek, T. M. (2011). The impact of skewness and fat tails on the asset allocation decision. Financial Analysts Journal, 67(2), 23-35.