Stock Indices of BRIC economies: Explored for Non Linear Dynamics and Volatility

Abstract

The current global scenario is a vulnerable one with crisis affecting the global markets. The speed, the magnitude and the frequency of changes has made markets more volatile than ever before. The reports of ECRI (Economic Cycle Research Institute) We are in an era of frequent recession ring true to ears. Predictability in financial markets has long been rejected by the conventional theories of finance. The implicit assumption in these theories that the investors are rational and the financial markets do not possess non linear dynamics has been falsified in many researches. Lately, the tools of Econophysics have proved to successfully overcome this shortcoming. Concepts of Hurst Exponent (Rescaled range analysis) and Shannon Entropy (Symbolic Time Series Analysis) borrowed from Physics and applied in Economics have opened novel dimensions for researchers, policy makers and investors. This paper is an attempt to explore the dynamics of the major stock indices of BRIC economies with these tools. An investigation into existence of the predictability (Hurst Exponent analysis) in these emerging markets coupled with a new volatility measure (Shannon entropy) hint towards non linear dynamics. The findings provide a substantial evidence of foretelling trend reversals in Russian, Indian and Chinese markets. Also, the Indian market was found to be the least volatile amongst the 4 economies. The study would encapsulate wide implications ranging from market efficiency interpretations, to facilitating investors on deciding on their exit and entry into the market and also, to regulators on when to intervene.