| Stock price always fluctuates, and the volatility is one of the most important concepts as well. Recently, foreign researchers transfer their attention from volatility persistence and volatility cluster to volatility asymmetry. Domestic researchers have found asymmetric volatility exists in China's stock market, which the impacts show asymmetric property from good news and bad one.Foreign researches find the volatility of developed countries' and development countries' stock market is asymmetric. All researchers define the volatility asymmetry as the impact of bad news is larger than good news and suggest leverage hypothesis and volatility feedback story to explain the asymmetry, and create asymmetric Garch model and asymmetric SV model to detect volatility asymmetry effect. Domestic researchers begin to study the phenomena, but most people just have empirically studied whether our own stock market had volatility asymmetry effect and almost no one investigates the character and reason of this effect. I believe this definition is not correct, and these two hypotheses couldn't well explain all the reasons of volatility's asymmetry, and few people puts interest into the study what kind of suggestion could get from the phenomena.This article focuses on volatility asymmetry of China's stock market, investigates the character of the asymmetry, and finally makes a more correct definition and deeper research of it and its origin.First of all, after empirical examination I find the impact of bad news is larger than good news in China's stock market at most of time while these exists specially opposite case. Besides stock market, volatility asymmetry also appears in bond market and future market. Therefore, volatility asymmetry is not a leverage effect, and it can't be simply defined as the impact that bad news is larger than good news. And so I think volatility asymmetry should be defined as the significant difference between the impact of good news and bad one. In this article I also probe into the financial economic meanings of volatility asymmetry and find the information impact curve could be either in V shape or in S shape. And I cite some indices to measure the asymmetric degree of volatility as well.Secondly, I examine leverage hypothesis and volatility feedback story whether explain the volatility asymmetry phenomena in the following two ways: (1) I find leverage hypothesis cann't explain why the impact of good news sometimes is larger than bad news and make empirical analysis on the section data and time series data of our stock market, and find the correlation between leverage ratios and volatility asymmetry is not significant and the precondition of leverage hypothesis is not fulfilled. And I conclude that this hypothesis can not explain the asymmetry. (2) After analyzing the logic of the volatility feedback story, I find it could not explain the asymmetry at firm level and the reason why sometimes the impact of good news is larger than bad news. I compare the asymmetric degree of high beta stocks with low beta stocks to find only in bearish market the correlation is significant and positive. And it indicates the necessary conditions of this theory can not be satisfied. Totally, this story can not explain the asymmetry of China's stock market.Thirdly, I start my study on whether stock style, market status and character of investor influence the asymmetry and find the influence is relatively significant in the following three aspects: (1) Empirical studies show the asymmetry is positive in bullish market and negative in bearish one. By behavioral finance analysis, we find market status influences investor's mood, causes understanding of information and reacting to its irrationality and results in volatility asymmetry. And so I recommend the market status hypothesis to explain the asymmetry and support three cases to prove, such as interest rate adjustment, stock circulating institution reform, and IPO and refinance,. (2) We find the asymmetric degree of volatility of growth stocks is larger than value stocks in bullish market, but in bearish they have no significant difference. Also I have analyzed the correlation between market value and the asymmetric degree, but results show they are not significant. (3) Empirical studies indicate there is significant difference between A shares and B shares of the same company. The asymmetric degree of overweight stock of institutional investors does not differentiate with personal investors' in bullish, while the volatility and asymmetry of overweight stock of institutional investors is less than personal investors in bearish.Finally, if considering volatility asymmetry we can estimate the statistical characteristics of stock return, forecast the volatility of stock and calculate the dynamic value at risk (VaR) accurately. Studies on the asymmetry can promote the regulator to carry out new polices and disclose new information in appropriate time, such it could enhance the stability of the market and financial efficiency of company, and improve investors to manage portfolio and risk more efficiently.Four contributions are made in this article: (1) make a more accurate definition of volatility asymmetry. (2) firstly investigate the reasons of the asymmetry of China's stock market in several angles including leverage ratios, volatility feedback, stock style, market status and character of investors. (3) construct a new model with market status hypothesis to explain the asymmetry in behavioral finance angle. (4) discuss the meaning of volatility asymmetry to regulators, investors and listed company. |
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