Using a genetic algorithm-based RAROC model for the performance and persistence of the funds

Shang-Ling Ou, Li-yu Daisy Liu and Yih-Chang Ou

Journal of Applied Statistics, 2014, vol. 41, issue 5, 929-943

Abstract: Assisting fund investors in making better investment decisions when faced with market climate change is an important subject. For this purpose, we adopt a genetic algorithm (GA) to search for an optimal decay factor for an exponential weighted moving average model, which is used to calculate the value at risk combined with risk-adjusted return on capital (RAROC). We then propose a GA-based RAROC model. Next, using the model we find the optimal decay factor and investigate the performance and persistence of 31 Taiwanese open-end equity mutual funds over the period from November 2006 to October 2009, divided into three periods: November 2006--October 2007, November 2007--October 2008, and November 2008--October 2009, which includes the global financial crisis. We find that for three periods, the optimal decay factors are 0.999, 0.951, and 0.990, respectively. The rankings of funds between bull and bear markets are quite different. Moreover, the proposed model improves performance persistence. That is, a fund's past performance will continue into the future.

Date: 2014
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DOI: 10.1080/02664763.2013.856870

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