An Empirical Research On The Demand Feedback Trading Of Chinese Securities Investment Fund

Recent years, securities investment fund is still in the stage of rapid development, and is playing a more and more important role on Chinese capital market because its collection of fiscal, risk diversification, professional financial management. The behavior of securities investment fund is always the hot research areas but existing document is mainly focus on herding and momentum trading. The main research issue in this paper is the demand feedback trading of Chinese securities investment fund.Basing on the 2005-2009 quarterly stock transaction data and adopts Sias's(2004) approach, this paper first measures the demand feedback trading of securities investment funds feedback trading; secondly, divide the demand feedback trading into following their own trades and following others' trades; finally, further divides following other's trades into following same type trades and following different type trades. The paper also made different classifications of stocks and funds for empirical research. The empirical results show that:(1)There are significant negative demand feedback trading(demand reversal) strategy, and there are significant following their own trades and following others' trades but the following other's trades is on dominant position; (2) According the investigative herding, following other's trades gets larger with the increase of the capital value of stocks, so homogenization and correlation of information is the main causes of following other's trades; (3)Further, both following same type trades and following different type trades are significant different from zero, but following different type trades play a main role;(4)The following other's trades of both stock-based and slant model fund are higher than the average level(30%) The prime cause can be fund classification and concern for reputation (reputation herding); (5)The demand reversal and its component part significant different among Beijing, Shanghai, Guangzhou and Shenzhen; Similar conclusions can be draw from the super nine asset management companies.