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Long Memory in Stock Returns: A Study of Emerging Markets

Keywords: Long memory , Rescaled range , Fractional integration , Spectral regression.

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Abstract:

The present study aimed at investigating the existence of long memory properties in ten emerging stock markets across the globe. When return series exhibit long memory, it indicates that observed returns are not independent over time. If returns are not independent, past returns can help predict future returns, thereby violating the market efficiency hypothesis. It poses a serious challenge to the supporters of random walk behavior of the stock returns. Hurst-Mandelbrot's Classical R/S statistic, Lo’s statistic and semi parametric GPH statistic were computed as well as modified GPH statistic of Robinson (1995). The findings suggest existence of long memory in volatility as well as in absolute returns and random walk for asset return series in general for all the selected stock market indices. The study did not support existence of Taylor’s effect in the selected emerging markets.

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