| Experiencing several ups and downs, Chinese stock market now has become the fourth largest stock market of the world which has been established in 1990.It not only assumes the responsibility of important functions on fund-raising and financing in the Chinese economic operation, but also plays a critical role in the processes of resource allocation and financial risk management, and significantly promotes the economic development. Although the establishment of Chinese securities business is not long, so far, only a period of about 15 years, and its developing process has experienced dramatic changes and fluctuations, the whole world still pays attention to its fast development and remarkable success we gained. At the same time, they carried out a large number of theoretical explorations and concrete practices towards its characteristics and rules and got some important theoretical research results and empirical discoveries.The purpose of the stock market investment is getting the largest investment return, which comes with risk, and it's difficult to make a decision between them. The traditional theory of the stock investment supports that the stock market is effective and equilibrious; the return is a linear function of the risk, whose volatility is according to Brown Motion, and it is independent with the same distribution, moreover the mean and variance is stable. However, the facts are that the influencing factors of stock market and their interaction are complicated, and obviously influenced by the psychological factors of individuals and groups; the volatility and relationship between return and risk are usually non-linear and non-equilibrium; the variance and mean of return are autocorrelation and unstable; the volatility of return is according to fractional Brownian Motion, which presents the characteristic of fraction and chaos. Because of the faster updating of stock market data,and the larger content of data information, and the existence of numerous dynamic measurement characteristic in financial time series, they went deep into the measurement analysis about stock market data and got lots of empirical evidences, based on which they reported a lot of theoretic hypothesizes and propositions. By describing and testing the time-series characteristic of the stock return series and the dynamic attributes of the process of mean and volatility rate, we can not only reveal the basic characteristic of stock market, but also judge the relationship between the operation of stock market and macroeconomic, thus provides the important reference for the judgment of economic situation and the establishment of the economic policy.Based on economic and financial extend theoretical models, This paper make use of the experiential data to confirm the theoretical models. Conditions hypothetical, theoretical inferred and experoential testify between each other improve, all the while has been the gradual and orderly progress from the fragment, typifying facts and found rule etc. The drivation abstract hypothetical of securities market theoretical has been proved in the specific empirical studies and research experience, also a number of empirical facts have been solid based for securities theory abstract and sublimation. This study started from the following aspects: First, we focused between statistical features of the stock market return rate series and volatility rate and the dynamic properties of the mean value process to detailed explain, and we conclude and review related research progress at home and abroad; Second, we discuss begin statistical model of assets return, then gradually discussions with the economic structure of the stock assets model and given about the stock price and the proceeds of measure and scale. Third, Studies show that a large number of foreign stock markets to the economic operation as"barometer". For this reason, this paper try test and analyze the relatedness of the stock market and macroeconomic volatility; Fourth, based on the hypothesis of effective market and long memory model of time series, This paper makes a serious attempt to explore whether there exists the long memory of the Shanghai and Shenzhen stock markets return rate series and volatility. Fifth, alike macroeconomic variable, much studies show that stock market volatility has been shown evidence nonlinear features. This paper attempt to explore used Markov model district transfer model to empirical study; Sixth, The stock market is closely related with the macroeconomic operation, nominal interest rates and the rate of inflation change impact the level of stock prices, based on "Fisher effect" hypothesis, this paper attempt to explore the dynamic relate between china stock price and inflation; Last, we discuss all kinds of methods of risk measure, and we colligate measure, decompose, evaluation and manage for a Portfolio investment.According to the research ideas, paper is divided into seven chapters and specifically organized as follows: Chapter 1 is about the evolution of yield and volatility of the stock market and Literature Review. First, we discussed the statistical characteristics of the stock yield series and the dynamic attributes of its mean, and reviewed the basic CAPM and related research progress of Markowitz (1959), the predictability of stock yield, non-normality of the asset yield series. Secondly, we discussed the statistical characteristics of the stock yield series and the dynamic attributes of its mean. Here, we recalled research progress of the yield and volatility in stock market during the latest 20 years, specific discussed the autoregressive conditional heteroskedasticity (ARCH) model, random volatility (SV) model,"Implied"volatility model, and"realized"volatility model of progress. Recall the four major characteristics of the stock market fluctuations, including time-varying fluctuations, volatility variable concentration, long-term memory, and the existence of spillover effect and leverage effect between different assets or different markets fluctuations.Chapter 2 take the stock yield series for example, under basic conditions of the uncertainty, we analysis the dynamic nature of stock market pricing behavior and yield series, and description the randomness and uncertainty impact to investors and the stock market. We mainly describe the stock pricing and investment return. During the uncertain conditions, we predict and infer the behavior characteristics of the stock market and investor. Since many aspects of economic behavior are not linear, causal inference and experimental evidence consider that investors'attitude to the risk and expected return is non-linear. So, this chapter briefly discussed the non-linear econometric methods of the stock yield series. Take Shanghai and Shenzhen stock market as an example, the empirical and testing the time-series features and some "typically facts" of the stock price yield series in Shanghai and Shenzhen stock markets. Chapter 3 investigate the relationship between the fluctuations of China's stock price and the macroeconomic variables, to seek in the higher level whether the stock market can be treat as a "barometer" function during the economic operation. Some foreign scholars use the data of United States or other countries find the existence of varying degrees correlation between stock returns and many macro factors. Some scholars'research suggests that there have significantly long-term relationship between stock returns and macroeconomic variables or financial variables. This chapter using multivariable cointegration model, description and testing the overall economic indicators including the actual stock prices and real GDP, real private investment and real money supply, weather existence of long-term cointegration relationship, and inspected the short-term deviation and the dynamic changes of actual macroeconomic behavior between the stock yields and long-term balanced relationship.Chapter 4 discusses volatility measurement of Chinese stock price and double long-term memory test. First, as the capital yield rate sequence variance itself may exist certain relevance, it first presented descriptions and characteristic of the relevant methods that is for the yield of random fluctuations, mainly autoregressive conditional heteroskedasticity (ARCH) group model. Secondly it save some methods for description and testing yield rate sequence and its fluctuations of long-term memory, these methods include the R / S test statistics and its analysis Hurst index, GPH (Geweke and Porter-Hudak, 1983) which is based on the frequency-domain spectrum regression estimation, ARFIMA model, FIGARCH model and Die ARFIMA- FIGARCH model. Finally based on China's Shanghai and Shenzhen stock markets yield rate date, empirical research was conducted, and detailed discussions of the average yield sequence process and the process of long-term memory fluctuations.Chapter 5 discusses the conditions volatility of the china stock market in the nonlinearity and non-symmetry. According to the gains size of the stock market volatility, we have a division of the volatility's state, such as the division of high volatility and low volatility, the division of High Medium and Low volatility. Through introducing the nature of the transfer zone system of conditions volatile in GARCH model, Chapter 5 describes and analyzes the dynamic features of China's stock market conditions volatility yield. Researching the yield conditions variance in China's Shanghai stock market is whether exists a significant district of area and the district transfer system phenomenon, this indicates that the risk characteristics in China's stock market is not only a significant short-term changes, it also demonstrated the relative stability in certain areas, which is the typical characteristic in China's securities market which is in a period of development and adjustment. The district and the district system transfer of stock yield volatility will provided the important reference of correct analysis and investment decision-making.Chapter 6 discusses the relevance between the stock price yield and the inflation rate. "Fisher hypothesis" basic content that changes in the level of stock prices is impacted by nominal interest rates and inflation rates. First, using wavelet analysis method describes and tests "Fisher hypothesis", and building up the correspondence between stocks yield sequence and the inflation rate. Secondly, by the use of state-space model of the district-state division to describe the relationship of stock return to the inflation rate to seeking the "threshold effect" of the dependence between them. Finally, further describing the relationship between the volatility of stock return and uncertainty of inflation rate, and extending the relevance of level series of them to the second-order moment situation, thus analysis the testing of relationship between the volatility of market price and stock price.Chapter 7 mainly measures the risk of Chinese stock market. Traditionally using variance and Beta coefficient to measure risk can only reflect the fluctuation of markets (or assets), but can't reflect the risk characteristic more roundly and dynamically. The present way is value risk (VaR) method which has been widely used. This chapter firstly introduces the basic concept of VaR and the main measuring method. Then we take in the concepts of marginal VaR (or M-VaR), component VaR (or C-VaR) and incremental VaR (or I-VaR) and some other types of VaR. As the heteroscedasticity characteristics of financial time series, we will again bring the GARCH (1, 1) model into the calculations of VaR to reflect the dynamic impact on risk measurement which is resulting from the achievement of new information and the presence of new stocks. The empirical analysis in the part 4 carries on the risk measurement, division, assessment and management towards the securities portfolio by using the method mentioned above. |
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