An application of the information-adjusted noise model to the Shenzhen stock market

Abstract

Purpose – The purpose of this paper is to: first, test if information-adjusted noise model (IANM) can be applied in China; second, quantify noise trader risk, overreaction, underreaction and information pricing errors in that market; and third, explain the relationship between noise trader risk and return. Design/methodology/approach – The authors use a behavioural asset pricing model (BAPM), CAPM, the information-adjusted noise model and model proposed by Ramiah and Davidson (2010). Findings – The findings show that noise traders are active 99.7 per cent of the time on the Shenzhen A-share market. Furthermore, our results suggest that the Shenzhen market overreacts 41 per cent of the time, underreacts 18 per cent of the time and information pricing errors occur 40 per cent of the time. Originality/value – Various methods have been applied to the Chinese stock market in an effort to measure noise trading activities and all of them failed to account for information arrival. Our study uses a superior and alternative model to detect noise trader risk, overreaction and underreaction in China.

Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature

“…Xu et al (2015) apply the model to the Chinese market and report pronounced market inefficiency with overreaction (40 per cent), underreaction (18 per cent) and IPE (42 per cent). Both of these studies show that noise trader risk is priced to a certain degree.…”

An Overconfident Market Environment - A Place for Irrational Noise Trading

“…To further apply the model to empirical analysis of capital markets, two Australian financial economists, Ramiah and Davidson (2003) [14] , conducted research and analysis on the pricing model in terms of empirical methodology. Xu et al (2016) [15] conducted a quantitative noise analysis of the Chinese Shenzhen market through an adjusted behavioral asset pricing model, demonstrating that noisy trading is prevalence.…”

Noise Trader Risk: Evidence From Vietnam Stock Market

“…Scruggs utilizes two pairs of twins shares to research about the magnitude and nature of noise trader risk [26]. Other authors use behavior error as a raw proxy for noise trader risk [24,31]. According to Shefrin and Statman, the CAPM (capital asset pricing model) beta has a noise trader risk component and an efficient beta (BAPM -behavioral capital asset pricing model -beta) [27].…”