管理工程学报2012，Vol.26Issue(2)：156-161,6.
基金交易行为与市场波动——基于小波与互谱分析的数据挖掘
Mutual Funds' Trading Behavior and Stock Market Volatility
摘要
Abstract
Institulionalization of investors is the trend of the international stock market. With the rapid growth of China's securities market, mutual funds, represented as institutional investors, have accounted for 40% ~ 50% of market capitalization and are having growing impact on the market. Influenced by the macro-economic cycle fluctuations and the global financial crisis, China's stock market has experienced a rapid alternation between super "bull market" and "bear market". With the market emotion changing from "frenzy" to "panic", the stock market is experiencing volatile fluctuation. In this volatile market environment, will the funds intensify or stabilize the market? Is Market volatility derived from systemic shocks or the adjustment of funds portfolio? Does the stock volatility caused by buying behavior of the funds have any relationships with the volatility of the stock market? How are these relationships established and whether they are predictable? These problems currently faced by China's securities market are good representative of institutional investors.This paper selected the top ten heavily holding mutual funds between 2007 and 2009 as our samples. The sample is representative because it includes different industries and has different attributes. At the same time, we provide descriptive statistics of the sample according to the proportion of the funds recording the buying or selling behaviors in different stages.In this paper, the empirical study includes two parts. In the first part, we use wavelet analysis to study the volatility of samples' features at different stages from the micro-level. Empirical results show that the stock's volatility will decline when the fund9 increase or maintain a ware-house stock rate but increase when the funds decrease in the non-symmetric market. Specifically, heavy-weight stocks, such as China Vanke Co. Ltd, are influenced by the fund severely, adding more in the portfolio stabilized fluctuations with less noise trading. On the other hand, introducing herding behaviors to a certain degree can still interfere the market sentiment, increase volatility, and create noise in the training process.Although the volatility of the counter-cyclical stocks, such as the Hei Longjiang Agriculture Co. , Ltd, increases when the funds reduce proportion, noise will increase even when the funds add proportion, which is mainly due to its agricultural characteristics. This condition makes these kinds of stocks susceptible to weather factors, which can cause noise trading frequently throughout the year. As for the small-cap growth stocks, such as Beijng Gehua CATV Netwok Co. , Ltd, it is vulnerable to the impact of large trading volume. In addition investors' different opinions on its future growth can lead to the valuation bias. Thus, volatility will increase regardless whether the funds increase or decrease. In addition, the growth uncertainty can cause low participation of small and medium investors and result in relatively small noise trading. All of our samples can be attributed to these three kinds of stocks. In the second part, we analyze the financial market's level. Firstly we test the spillover effect by applying the regression equation between two time-series variables. The results show that there is a certain relationship between the volatility of the stocks and the stock market, even though the effect is not significant ( R2 is low). Thus we consider using of cross-spectral analysis, which is also very effective on the high-frequency data and can lest the inter-relation of time series from a wave aspect. The finding indicates that there is a weak relationship between data (Coherency Spectrum coefficient is low), suggesting that the adjustment of the funds' portfolio may cause the volatility, and the market volatility has little effect on stocks' volatility.关键词
基金行为/市场波动/小波分解/互谱分析/溢出效应Key words
mutual funds' behavior/ market volatility/ Wavelet analysis/ cross-spectral analysis/ test of spillover effects分类
管理科学引用本文复制引用
张宗新,张雪娇..基金交易行为与市场波动——基于小波与互谱分析的数据挖掘[J].管理工程学报,2012,26(2):156-161,6.基金项目
国家自然科学基金资助项目(70973023) （70973023）
