Abstract
Assisting fund investors in making better investment decisions when faced with market climate change is an important subject. For this purpose, the author adopts 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). The author then proposed a GA-based RAROC model. Next, using the model to find the optimal decay factor and investigate the performance and persistence of 31 Indian open-end equity mutual funds over the period from November 2012 to October 2015, divided into three periods: November 2012- October 2013, November 2013- October 2014, and November 2014- October 2015, which includes the global financial crisis. The author finds 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.
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