Market Microstructure Noise, Intraday Stock Market Returns, and Adaptive Learning: Indian Evidence

Abstract

What drives intraday traders’ sentiments in the stock markets: information or noise? This paper argues that the market microstructure noise (MMN) manifests intraday traders’ aggregate sentiments depicted by chaotic and noisy market returns. It examines if intraday stock market returns, returns’ variances and higher order moments are erratic, noisy and nonnormal. It shows that the intraday Bombay Stock Exchange (BSE) Sensex and National Stock Exchange (NSE) Nifty index returns approximate to zero-mean, zero-variance but skewed and leptokurtic in distributions. In exploring the intraday market index returns, standardisation process reveals noises in the BSE market, but it is evened up in the NSE market. Since intraday traders’ market sentiments and decision choices are behavioural, noisy but adaptive, their decision choices need strategies given that those strategies have numerical “attractions” that determine choice probabilities. We explore the adaptive Experience Weighted Attraction (EWA) learning parameters to show persistent MMN in intraday traders’ adaptive learning behaviours