Research On Linkage Relationship And Quantitative Strategy Of China's Financial Marke

China’s financial markets are fast expanding as the Chinese economy continues to flourish.By exploring the links between China’s multiple financial markets with the Chinese stock market as the center,this article investigates the influence of interest rate variations in the bond market and institutional changes in the exchange rate market on the stock market.This study also presents a betting against volatility factor(BAV)to examine the origins of the Chinese stock market’s low-risk impact,as well as a marginal strategy of Value at Risk to decrease investment risk.To begin,this study examines the econometric relationship between the stock and bond markets and presents a semi-parametric multiplicative volatility model.Meanwhile,the speed of convergence and asymptotic normality of non-parametric estimators are demonstrated using the B-sample approach,and the correlation features of their consistent confidence bands are obtained.Finally,the article empirically proves that credit spread regressors influence the CSI 300 Index’s yield volatility and finds that the credit gap between 10-year government bonds and 10-year treasury bonds has the biggest impact on the CSI 300 Index’s yield.In the second part of the article,this paper combines the modeling theory of the Markov mechanism switching model with the multivariate time series analysis model VAR.It is applied to the analytical study of macroeconomic variable exchange rates and financial variable stock prices in order to jointly consider the dynamic structure of economic and financial markets.Meanwhile,this paper examines the relationship between the exchange rate market and the stock market,with the view to providing a new analytical perspective for solving economic and financial practical problems.It aims to provide a new analysis of the relationships between the two and how they relate to each other.This paper demonstrates that:whenever a state shift occurs,it is always the exchange rate market or the stock market that suffers a large external shock,such as a policy shock or a financial crisis.A bull market in the stock market causes a slowdown in RMB appreciation.There is no significant bootstrap or delayed relationship between the exchange rate market and the stock market when the stock market is in a bear market or a low-risk,low-return scenario.The results of this article are also highly verified by the direction of the financial markets in 2020-2022,offering a novel viewpoint on the pattern of China’s stock and exchange markets and their relationship.In order to investigate the source of the low-risk effect in the Chinese stock market,the third section of this study decomposes the betting against beta(BAB)into two elements in order to explore the source of the low-risk impact in the Chinese stock market:betting against volatility(BAV)and betting against correlation(BAC).Using Chinese equity market data and a twelve-month moving window,the BAV factor portfolio was built based on daily log returns,predicted volatility,and correlation coefficients to obtain considerable excess returns.Furthermore,this study reveals that the BAV factor is the key source of lowrisk effects in the Chinese stock market and that it is closely connected to behavioral characteristics.In this way,idiotic risk is the primary cause of low-risk anomalies in the Chinese stock market.Finally,this paper creates the SMAX factor based on volatility to capture short-term gambling desires and finds that the portfolio formed by this factor yields high excess returns as well,implying that the low-risk impact of the Chinese stock market and gambling preferences are related.In the last part of this paper,We introduce various marginal conditions into the framework of Constant Proportion Portfolio Insurance strategy,and give the marginal strategy M-CPPI based on the Value at Risk.We divide the trading volume into two parts:predictable and unpredictable,and introduce the predictable trading volume volatility rate into the price volatility model of risk assets.At the same time,we take the part that the actual volatility of risk assets exceeds the Value at Risk as the marginal increment to realize the dynamic adjustment of the bottom line of Strategic Safety(floor).We divide the close price series of Shanghai and Shenzhen 300 index into 24 different time periods in turn,and calculate the price performance path of portfolio assets under each strategy with a period of 3 years.The results show that the extended M-CPPI strategy is significantly better than the standard CPPI strategy.The improvement of this strategy enables us to reexamine the feasible design path of hedging financial products,in order to avoid the risk of gap which is widely criticized in the operation process of principal guaranteed and hedge funds,and at the same time to mitigate the risk of cash lock-in which may occur in the operation process of the strategy.