Rescaled Range Analysis – A Comparative Study on Bombay Stock Exchange and National Stock Exchange

Dr. L. Vijaya Kumar, Dr. R. Balaguru
2019 Emperor International Journal of Finance and Management Research  
The present study is an attempt to find out the long range persistence of selected sample listed in BSE and NSE Sectoral Indices. To analyze the comparative study on Bombay Stock Exchange and National Stock Exchange (Special Reference with BSE Auto, Bankex & NSE Auto, Bankex ), Augmented Dickey Fuller Test, Phillips Perron Test for Stationarity, Autocorrelation, Normality test using Kolmogorov-Smirnov and Shapiro -Wilk Test, ARCH and GARCH model and Rescaled Range Analysis during the study
more » ... d 01st April 2005 to 31st March 2017 of selected Sectoral Indices listed in Bombay Stock Exchange and National Stock Exchanges.. The findings of the study indicated that there is a persistence of long range memory in selected sample return of BSE and NSE during the study period. (2010) , analyzed the presence of R/S were significantly higher than an asymptotic limit of 0.5 of random time series, using Hurst exponent H Estimation -Rescaled range analysis and de-trended fluctuation analysis on different types of financial assets. The findings indicated the R/S was useful and robust method when compared to newer method of DFA. II. Review of literature "Rescaled Range Analysis and De-trended Fluctuation Analysis: Finite sample properties and Confidence Intervals " by Ladislav Kristoufek In the paper "Long Memory in Eastern European Financial Markets Returns", by Cipriannecula and Alina Nicoleta Radu (2012), analyzed the long memory property of stock returns of Eight CEE emerging markets, namely Czech Republic, , using ARFIMA and FIGARCH model. It was found that there existed persistence of long memory in the returns of selected CEE emerging markets. Ladislav Kristoufek (2012), in the paper entitled "How are Re-scaled Range Analyses affected by different memory and distributional properties? A Monte Carlo Study" analyzed the effect of different distributional properties and the ability of the methods to efficiently distinguish between short term and long term memory, using classical and modified R/S analysis, ARFIMA and Monte Carlo simulation Techniques. It was concluded that the R/S exhibited biased results upwards for short range dependent process and M-R/S exhibited strong biased results downwards for long range dependency.
doi:10.35337/eijfmr.2019.5408 fatcat:3wticzvd5vbmjia4lasfmzhuoq