Modelling the short term herding behaviour of stock markets

Abstract

Modelling the behaviour of stock markets has been of major interest in the past century. The market can be treated as a network of many investors reacting in accordance to their group behaviour, as manifested by the index and effected by the flow of external information into the system. Here we devise a model that encapsulates the behaviour of stock markets. The model consists of two terms, demonstrating quantitatively the effect of the individual tendency to follow the group and the effect of the individual reaction to the available information. Using the above factors we were able to explain several key features of the stock market: the high correlations between the individual stocks and the index; the Epps effect; the high fluctuating nature of the market, which is similar to real market behaviour. Furthermore, intricate long term phenomena are also described by this model, such as bursts of synchronized average correlation and the dominance of the index as demonstrated through partial correlation.

Big data techniques in auditing research and practice: Current trends and future opportunities

“…Adopting a different approach,Sun, Shen, and Cheng (2014) use individual stock transaction data to create a trading network to characterize the trading behaviour of stocks investors. They show that trading networks can be used to predict individual stock returns Shapira, Berman, and Ben-Jacob (2014). model the stock market as a network of many investors, whileGui, Li, Cao, and Li (2014) model it as a network of communities of stocks.…”

Uncovering Discrete Non-Linear Dependence with Information Theory

“…The codependence between financial time series returns exhibits Epps effect, the phenomenon that the empirical correlation decreases as sampling frequency increases [20]. The phenomenon is caused by asynchronous trading, nonlinearity, discretisation and herding behavior [21,22]. Therefore, we find the event based framework and information theoretic measurement suitable for capturing codependence among financial time series.…”

Review of Stock Markets’ Reaction to New Events: Evidence from Brexit

“…Therefore, investors expect stock prices to react to some new information or events (Schweitzer, 1989). The starling nature of stock markets' reaction to new information is highlighted by (Fama et al, 1969;Woolridge & Snow, 1990;Rigobon & Sack, 2003;Vega, 2006;Shapira et al, 2014). This assertion is supported by (Swedroe, 2013) as the report reveals the existence of a significant body of literature measuring the speed and the efficiency of the market adjustment to new information.…”