High‐Frequency Positive Feedback Trading and Market Quality: Evidence from China's Stock Market

Abstract

This paper managed to measure the positive feedback trading intensity and its asymmetry with high‐frequency transaction data of China's individual stocks. The intraday positive feedback trading is found to be heterogeneous, and buying‐winners effect is significantly stronger than selling‐losers effect. In general, the high‐frequency asymmetric positive feedback trading's impact on market quality is mixed: The intraday positive feedback trades contribute to a liquid and active‐trading market but at the same time slow down the price discovery process and reduce the price efficiency.

Feedback trading: a review of theory and empirical evidence

“…Drawing on a set of 423 listed stocks from the UK market for the 2007–2012 window, Gębka and Wohar (2013) demonstrated using a quantile regression framework that daily autocorrelation varied across different performance quantiles, with negative feedback trading being a key candidate in explaining the positive autocorrelations observed among lower-return quantiles. Wan and Yang (2017) use the Sentana and Wadhwani (1992) model and report positive feedback trading among the constituent stocks of the SZ300P index (which includes the 300 largest stocks listed on the Shenzhen stock exchange) during the 2010–2013 period for various high frequencies (5/10/30 min), with its presence found to amplify return-autocorrelation.…”

Asymmetric responses to Purchasing Managers' Index announcements in China's stock returns

“…‘Rise‐chasing and down‐freezing’ 2 behaviours have been observed in individual investors in the Chinese stock market (Wan et al, 2016). That is to say, the ‘buying‐winners’ effect is significantly stronger than the ‘selling‐losers’ effect (Wan et al, 2017; Wan & Yang, 2017). Therefore, individual investors are encouraged by positive news, and may pay little attention to negative news, showing there is a predominance for positive news‐excitement in investor behaviour.…”

“…Both the ‘buying‐winners’ effect and the asymmetry of ‘buying‐winners’ and ‘selling‐losers’ contribute to high price volatility, high return autocorrelations, high variance ratios and low‐price discovery speed. So, aggregately, results show ‘rise‐chasing and down‐freezing’ not only leads to a less efficient market but also facilitates an active‐trading market (Wan & Yang, 2017). Additionally, if this rise‐chasing asymmetry has asset pricing power are tested with Fama–French three factor model, that is, reversal factor, positive feedback factor and rise‐chasing asymmetry factor.…”

How does regret affect investor behaviour? Evidence from Chinese stock markets

“…Differing from existing studies that examine investor trading behaviour and stock returns using public data (e.g., Sharif et al , 2014; Wan and Yang, 2017; Li et al , 2018; Lv and Wu, 2018), our proprietary data possess some unique features that enable tests of regret theory. Our dataset consists of all orders submitted in 161 stocks by investors on the SSE for the period from October 2003 to September 2004.…”