This article analyses downside risk of Indian equity mutual funds from 1999 to 2014 using a value at risk (VaR)-based approach. We use weekly return data of a sample of 349 equity mutual funds during the said period to estimate their weekly VaRs on a rolling basis using some parametric and non-parametric models. Moving average (MA), exponentially weighted MA and GARCH (1, 1) are the parametric models and historical simulation (HS) is the non-parametric model. We also carry out backtesting of the models using three popular approaches—two under the unconditional coverage approach, namely Jorion’s ‘Failure Rate’ approach and Kupiec’s proportion of ‘failures’ (POF) test, and one under the conditional coverage approach, namely the Christoffersen’s Independence test—to test the robustness of the VaR models. Our results show that Indian equity mutual funds exhibit considerable downside risk during the chosen period, in terms of the magnitude of the projected VaRs. Moreover, significant proportions of the funds ‘fail’ the predicted VaRs, particularly during times of crisis for some of the models, raising questions about their robustness in an investment setting in India. On the whole, both from failure proportion as well as backtesting perspective, the GARCH (1,1) seems to be the most robust of the models. JEL codes: G32, G15, G23

中文翻译：

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全球金融危机之前和之后，基于VaR的印度股票共同基金的下行风险分析

本文使用基于风险价值（VaR）的方法分析了1999年至2014年印度股票共同基金的下行风险。在上述期间，我们使用349个股票共同基金样本的每周收益数据，使用一些参数和非参数模型，以滚动方式估算其每周VaR。移动平均（MA），指数加权MA和GARCH（1、1）是参数模型，历史模拟（HS）是非参数模型。我们还使用三种流行的方法对模型进行了回测-两种是在无条件覆盖方法下进行的，即Jorion的“失败率”方法和Kupiec的“失败”比例（POF）测试，另一种是在条件覆盖方法下进行的，即Christoffersen独立性测试-测试VaR模型的稳健性。我们的结果表明，就所选VaR的规模而言，印度股票共同基金在所选时期内表现出巨大的下行风险。此外，很大一部分资金“未达到”预期的风险价值，特别是在某些模型出现危机期间，这使人们质疑它们在印度投资环境中的稳健性。总体而言，无论是从失败比例还是从回测的角度来看，GARCH（1,1）似乎都是最强大的模型。JEL代码：G32，G15，G23 总体而言，无论是从失败比例还是从回测的角度来看，GARCH（1,1）似乎都是最强大的模型。JEL代码：G32，G15，G23 总体而言，无论是从失败比例还是从回测的角度来看，GARCH（1,1）似乎都是最强大的模型。JEL代码：G32，G15，G23