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Exploring a Risk Adjusted Return on Capital Model for the Performance and Persistence of the Indian Equity Mutual Funds

机译:为印度股票共同基金的业绩和持续性探索风险调整后的资本回报率模型

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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.
机译:面对市场气候变化时,协助基金投资者做出更好的投资决策是重要的课题。为此,作者采用遗传算法(GA)来寻找指数加权移动平均模型的最佳衰减因子,该模型用于计算风险价值和风险调整后的资本回报率(RAROC)。然后作者提出了基于GA的RAROC模型。接下来,使用该模型找到最佳衰减因子,并研究2012年11月至2015年10月期间31种印度开放式股票共同基金的业绩和持续性,分为三个时期:2012年11月至2013年10月,2013年11月至2014年10月以及2014年11月至2015年10月,其中包括全球金融危机。作者发现,在三个周期中,最佳衰减因子分别为0.999、0.951和0.990。牛市和熊市之间的基金排名是完全不同的。此外,提出的模型提高了性能持久性。也就是说,基金的过去表现将持续到未来。

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