An Insight Towards a More Comprehensive Approach to Measure Market Efficiency

Abstract

One of the burning issues of the contemporary world of Financial Management centers on the effective measure of volatility in a high-speed and highly oscillatory movement of financial data. In short, ‘volatility’ captures the extent of errors encountered in structuring returns of financial assets that fundamentally occurs as the market normally behaves under asymmetric information. It has found plenty of financial applications starting from Efficient Capital Market Hypothesis to valuation of derivatives and may also be as a tool towards risk – management. Existing literature suggests that, to a considerable extent the mean size of volatility dose not remain constant but varies with time and can be predictable in a stochastic sense. The precision of such forecasting definitely depends upon a number of combinations of factors, which are not always controllable. Apart from stochastic volatility models, two fundamental econometric tools, namely ARCH and GARCH models are often being regularly applied to forecast the volatility-clustering and thereby arrive at a measure of efficiency of financial market. This paper will try to throw a small insight as to how the different variants of ARCH and GARCH systems can be effectively utilized to forecast the variance – covariance trade off in financial portfolio, taking preferably an Indian context and to arrive at time-based efficiency index of the high-frequency financial data.