1 PhD Research Scholar, School of Accounting, Dongbei University of Finance and Economics, Dalian
2 Professor, School of Accounting, Dongbei University of Finance and Economics, Dalian
3 Professor, International Business School, Dongbei University of Finance and Economics, Dalian
Returns predictability and cross autocorrelations is an important consideration in behavioral finance and is of considerable interest to investors and financial economists. This area gained much attention due to developments in behavioral finance during the last two decades. Previously, lead-lag patterns were supported by argument of rational expectations, however, it lacked much empirical evidence. According to behaviorists' views, it is human inability to process all sorts of information and thus, information moves diffuse slowly from one market to another. In this study, we tested this slow diffusion of information using an extensive set of data over a period from 2004-2013. We found that the market was led by industry returns up to a period of four weeks. This predictive power of industries decreased as the prediction horizon increased. These findings are robust, even if we control for industry size and trading volume. Thus, these findings add considerable support to the slow diffusion of information hypothesis.
Ajid ur Rehman, Man Wang, Sajal Kabiraj (2016). Do Chinese Industries Predict the Stock Market Due to Slow Diffusion of Information? Analysis of the Shanghai Stock Exchange. Indian Journal of Finance, 10(7), 7–21. https://doi.org/10.17010/ijf/2016/v10i7/97239