Empirical Exploration Of The Volatility Decomposition Of Individual Stock Based On CAPM Two-factor Model

The volatility of securities market has long been a core topic of financial economics,and also received attention as a concerned measure by the regulatory authorities of every country,it reflects the risk and health status of a country's securities market in a certain time. Campell,Lettau,Malkiel and Xu(2001) used disaggregated approach to decompose the volatility of individual stock return into market volatility,industry volatility and idiosyncratic volatility,they studied the volatility from a brand new perspective,and opened up a new study field.In China's current market enviroment ,it is commen that the price of individual stock goes up and down at the same time, and shows synchronization.Moreover,our stock market also fluctuates too severely,and the volatility level is much higher than other countries.Therefore,it is urgent to analyse the intrinsic composition of the stock volatility of our country in order to make clear the reasons of phenomenons mentioned aboved.This paper decomposes the volatility of individual stock based on CAPM two-factor model by using the disaggregated approach of Campell,Lettau,Malkiel and Xu(2001).After decomposing the volatility of individual,we study the monthly and quarterly volatility characteristics of market,industry,and firm ,describe the changing trend of each time series in the entire sample period,and test the correlation and stationarity of each volatility series.Then we shift to study the explanatory power of these three levels volatility series to FF three-factor model.In the end,we analyze the relationship between volatility and characteristics of variables on firm and industry level by empirical test.Our research achievements can be summarized as follows:(1) Monthly volatilities market,industry,and firm show stage characteristics,in the three periods given in the sample time,three levels of monthly volatilities display downward trend in the beginning and then go up.The performance of monthly volatilities differs in each month.Specifically,in the beginning of the year(January and February)or in the middle of the year(May and July) the averages of monthly volatilities are much higher,while other monthes a little lower;monthly volatilities show obvious relationship with the quarter which the month belongs to.Moreover,this paper also studies the effects of quarter,the beginning and the end of calender year,lunar new year to volatilities.According to our research,the beginnings of quarter,calender year have significant impacts to volatilities and the end has no impact.On the contrary, the end of the lunar new year has great effct to volatilities while the beginning has not.(2) The market volatility of our country has increased gradually since 2005,and the market stability have been worsening day by day.As for the industry volatility,it had been stable before 2006,but increased quickly since 2006 which shows serious differentiation of industry. Idiosyncratic volatility has been decreasing gradually and stable since 2000,but increased step by step since 2005 ,it shows that differentiation exsits among individual stocks.(3) This paper also studies the explanatory power on market volatility,industry volatility and idiosyncratic volatility to FF three factors .The result shows that market volatility,industry volatility and idiosyncratic volatility has no explanatory power to market factor and book value to market value ratio factor,but has obvious explanatory power to firm scale factor which shows positive relationship to it.These results demonstrate that China's securities market is far from than efficient and it can not differentiate between bad listed companies and the good one.In the market volatility and industry volatility increasing periods,market speculations on small-value stocks are even more fiercely which lead to the good explanatory power to firm scale factor. (4) On the study of industry volatility to characteristics of industry variables,we find that industry volatility shows positive relationship to size difference,financial leverage ratio,flow ratio,and listing time but negative relationship to number,ROA,book value to net value ratio of the listing company in the industry.It reflects that certain industries include the same profitability and valuation tend to have higher volatility but those industries include a large number of companies always have lower volatility.(5)On the study of idiosyncratic volatility to characteristics of firm-level variables,we find that idiosyncratic volatility has negative relationship to ROA but positive relationship to the book value to net value ratio,price,financial leverage ratio and listing time of the individual stock.As for the size and flow ratio,the positive relationship isn't obvious. It reflects that individual stock which owns good financial performance always has low idiosyncratic volatility while those which own high book value to net value ratio,high price,high financial leverage ratio and long listing time tend to has large idiosyncratic volatility.According to the thought of the whole paper, there are six chapters as follows: Chapter 1: introduction; Chapter 2:literature review; Chapter 3:introduction of approach to decompose the volatility; Chapter 4; explanatory power study on idiosyncratic volatility to returns of factors; Chapter 5; analysis of the relationship between idiosyncratic volatility and characteristics of variables. Chapter 6;summary and policy recommendations.