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Volatility Mean Reversion and Stock Market Efficiency

机译:波动率均值回归与股市效率

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Traditional econometric models, such as the ordinary least square method, are built on the assumption of constant variance. Financial time series, unlike other economic series, usually exhibit a set of peculiar characteristics i.e. mean reversion, volatility clustering, fat tails and long memory. The main purpose of this study was to study market efficiency through modeling one stylized facts of asset returns series i.e. mean reversion in the Indian stock market. To achieve this purpose, the study used ADF test and GARCH model. The study found that the underlying series is stationary and therefore mean reverting. Therefore, based on the results the study concluded that, the Indian stock market is informationally weak-inefficient.
机译:传统的计量经济学模型,例如普通最小二乘法,是建立在恒定方差的假设之上的。金融时间序列与其他经济序列不同,通常表现出一组独特的特征,即均值回归,波动性聚类,肥尾和长记忆。这项研究的主要目的是通过对资产收益系列的一个典型事实进行建模来研究市场效率,即印度股票市场的均值回归。为了达到这个目的,本研究使用了ADF测试和GARCH模型。研究发现底层序列是平稳的,因此意味着均值反转。因此,根据结果,研究得出的结论是,印度股票市场信息薄弱,效率低下。

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