A new proposal for efficiency quantification of capital markets in the context of complex non-linear dynamics and chaos

The main purpose of this paper is efficiency analysis as well as its quantification in the case of emerging capital markets, by building a new measure of market efficiency. The basic assumption of such markets is the lack of correlation between returns, and therefore the existence of low entropy, the lack of randomness, manifestation of fractality and long-term memory, integrated into a single measure, will indicate the distancing from the state of efficient market. This paper proposes five different estimates (for informational entropy, run test, Hurst exponent, long-term correlation coefficient and fractal dimension) to construct a new measure of market efficiency based on a deviation from the ideal state (expressed by the efficient market). The Capital Market Efficiency Exponent is estimated for nine emerging capital markets and, for comparison, for three developed capital markets, at different stages of development over a 16-year time span.