Difference in nature of correlation between NASDAQ and BSE indices

Abstract

We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. We analyze daily price of NASDAQ composite index for a period of 20 years, and BSE sensex index, over a period of 15 years. It is found that the long-range correlation, as well as fractal behavior for both the stock index values differ from each other significantly. Strong non-statistical long-range correlation is observed in BSE index, whose removal revealed a Gaussian random noise character for the corresponding fluctuation. The NASDAQ index, on the other hand, showed a multifractal behavior with long-range statistical correlation.