Information Efficiency Measuring And Asset Pricing For Stocks Trading In Shanghai,Shenzhen And Hong Kong Stock Markets Based On The Group Factor Structure

Adhering to a high level of opening up to the outside world is the only way to achieve high-quality development,and it is also an essential task for comprehensively building a modern socialist country.China has continuously adjusted the basic rhythm of opening up the capital market.The opening-up system of the capital market in Chinese mainland is inseparable from the capital market in Hong Kong.Up to now,Chinese mainland and Hong Kong have formed a basic pattern of multi-channel and multi-standard opening-up with qualified institutional investors,direct investment in the inter-bank bond market,interconnection mechanism,and bond connect.The increasingly close relationship between the Shanghai,Shenzhen,and Hong Kong stock markets also affects the participant structure and information function of the Shanghai,Shenzhen,and Hong Kong stock markets.Empirical research shows that after 2006,the Shanghai and Shenzhen stock markets showed different degrees of linkage and information spillover effects with major global stock markets.During the same period,the level of linkage and information spillover between the Shanghai and Shenzhen stock markets and the Hong Kong stock market was much higher than that of the Shanghai and Shenzhen stock markets and the other international stock markets.However,many existing studies have studied the characteristics of the linkage between the Shanghai and Shenzhen markets and the international stock market based on the linkage and spillover effects between market indexes.There is little discussion on the micro linkage structure and linkage sources between stock assets.Thus,in-depth discussions on the micro linkage structure of stock assets in the Shanghai,Shenzhen,and Hong Kong markets are needed.The micro linkage structure of stock assets describes the information structure and risk structure that affect the change of asset return,and its characteristics and changing trends have a profound impact on the stock price information efficiency and risk pricing of stock assets in the open stock market.Stock price information efficiency and risk pricing are important research objects of empirical financial research.The former is the basis for the stock market to realize the primary function of resource allocation,and the latter reveals the behavioral rules of stock asset price changes.There are two problems in the existing empirical research on the stock price information efficiency and risk pricing in the Shanghai,Shenzhen,and Hong Kong stock markets.On the one hand,the opening of the capital market has significantly affected the common information structure between the Shanghai,Shenzhen,and Hong Kong markets.Ignoring the micro linkage structure between stock assets and only considering the information decomposition model of the local market index and industry index cannot accurately estimate the stock price information efficiency of stock assets in Shanghai,Shenzhen,and Hong Kong markets.On the other hand,changes in the micro linkage structure of stock assets have triggered changes in the risk structure.From the perspective of econometric models,when there is an unobservable micro linkage structure among stock assets,ignoring the structure will lead to the wrong setting of the model,and it is impossible to obtain a consistent estimate of the risk structure;from the perspective of empirical research,the wrong risk structure setting will make the pricing test fail.In order to solve the above problems,we first summarize previous studies on information spillover effects,stock price information efficiency,and group factor models.Under the policy background of the continuous opening of China’s capital market,the micro linkage structure between stock assets in Shanghai,Shenzhen,and Hong Kong markets characteristics and time-varying trends are the main line of research.We use the micro linkage structure to describe stock asset information and risk structures in the Shanghai,Shenzhen,and Hong Kong markets.Carry research on the stock price information efficiency and risk pricing of stock assets in the Shanghai,Shenzhen,and Hong Kong markets.The specific research content of This research is as follows:(1)Based on the data-driven estimation method,under the condition of no prior information,the group factor model is used to identify and estimate the micro linkage structure of stock assets in Shanghai,Shenzhen,and Hong Kong stock markets during different capital opening periods.This section’s research is the basis for the following two parts of the research content.Based on the static group factor model,this section estimates the micro linkage structure of stock assets in the Shanghai,Shenzhen,and Hong Kong markets during each capital market opening period.Then we discuss the essential characteristics and time-varying trends of the group factor structure in different policy periods.Combined with observable style factors,we further discuss the economic implications of unobservable risk structures and examine pricing levels for unobservable risk structures.(2)We use the micro linkage structure to describe the common information structure and measure the price information efficiency of the stock assets in Shanghai,Shenzhen,and Hong Kong markets.Based on the research content(1),the essential characteristics of the micro linkage structure of unobservable stock assets are estimated.We propose the common information concept of the open stock market.Then,combined with the observable and unobservable common information structure,we propose the information decomposition model of stock assets in the open market.The model could estimate the stock price synchronicity index and measure the stock price information efficiency of stock assets in the Shanghai,Shenzhen,and Hong Kong markets.The empirical research comprehensively and systematically discusses the distribution characteristics of information efficiency for stock assets in the Shanghai,Shenzhen,and Hong Kong markets and their trends over time.We also examine the period,market,and industry differences in information efficiency;identifies common information sources,and examine information structure spillover effects.The price information efficiency index for stock assets in Shanghai,Shenzhen,and Hong Kong markets estimated in this section is one of the characteristic variables of stock assets in research(3).(3)We construct a time-varying factor loading group factor(TVL-GF)model that combines the risk structure characteristics and asset characteristics of stock assets in the Shanghai,Shenzhen,and Hong Kong markets,give the model setting and parameter estimation methods and use simulation research to test the estimator finite sample properties.Based on the TVL-GF model,we conduct a pricing test for the factor structure with time-varying factor loadings and analyze the influence path of the characteristic variables of stock assets in the Shanghai,Shenzhen,and Hong Kong markets is studied.Then we test the significance of the influence of the characteristic variables on the time-varying factor loadings.This research studies the correlation between characteristic asset variables and risk factors in the Shanghai,Shenzhen,and Hong Kong markets.We further discuss the sources of risk premiums for Shanghai,Shenzhen,and Hong Kong stock assets with different combinations of characteristic variables and the economic connotation of risk factors.Based on the above research content,the main innovations of This research are as follows:(1)Based on the group factor structure,using the data-driven method to identify and estimate the micro linkage structure of stock assets in Shanghai,Shenzhen,and Hong Kong markets in different periods of capital market opening in Chinese mainland,which enriches the empirical research on the microcosmic linkage of stock assets in Shanghai,Shenzhen and Hong Kong markets.Existing research on information spillover and linkage between Shanghai,Shenzhen,and Hong Kong markets is mainly based on the market level and lacks the identification and estimation of the micro linkage structure between stock assets in Shanghai,Shenzhen,and Hong Kong markets.Based on the static group factor model,This research describes the micro linkage structure of stock assets in Shanghai,Shenzhen,and Hong Kong markets in different policy periods.In each period,we use datadriven methods to identify and estimate stock asset groups and factor structures in Shanghai,Shenzhen,and Hong Kong markets.The research conclusions prove that the stock assets in the Shanghai,Shenzhen,and Hong Kong markets have an unobservable time-varying micro linkage structure with the market characteristics and industry to which the stock assets belong.The source of stock asset linkage in the Shanghai-Shenzhen-Hong Kong market has a linear correlation with the observable style factors.The micro linkage structure can describe the source of risk within the system and the group.Therefore,a structural description of information and risk structures provides an empirical basis.(2)We define common information in the open stock market and propose a price information decomposition model that combines observable and unobservable information structures and measures the stock price information of stock assets in the Shanghai,Shenzhen,and Hong Kong markets based on the common information structure.The existing research does not consider the information spillover structure between stock assets when measuring the stock price information efficiency in the open market.Hence,the stock price information efficiency based on the stock price synchronicity measurement is higher than the actual level.This research builds a price information decomposition model to estimate the stock asset information efficiency of the Shanghai,Shenzhen,and Hong Kong markets.On the one hand,the group factor structure can fully capture the common information spillover effect of stock assets;on the other hand,it combines the information of observable and unobservable common information.Decomposition models enhance the interpretability of information sources.The empirical research found that: first,there is a significant common information spillover effect between the stock assets in the Shanghai,Shenzhen,and Hong Kong markets,which explains the rationality of building an information decomposition model with an information structure;second,the information efficiency of stock prices in the Shanghai,Shenzhen and Hong Kong markets has significant time-varying characteristics,the stock price information efficiency in the Shanghai and Shenzhen stock markets fluctuates and rises.The research conclusion further enriches the measurement method and empirical research on the information efficiency of the open stock market.(3)Combining structural characteristics and asset characteristics to construct a time-varying load group factor model,breaking through the limitations of the existing group factor pricing model of "non-time-varying factor loading" and "weak economic interpretation ability." This research constructs a time-varying load group factor(TVL-GF)model based on the micro linkage structure and asset characteristics of stock assets in the Shanghai,Shenzhen,and Hong Kong markets.On the one hand,expanding the traditional non-time-varying factor loading to timevarying factor loading is more in line with empirical facts;On the one hand,the setting of time-varying factor loading combined with asset characteristics enhances the economic explanatory power of the unobservable factor model.This research enriches the theoretical research on group factor models by studying model settings,estimation methods,and model testing methods.On the one hand,the empirical research reveals the significance of the influence path and level of the characteristic variables of stock assets in the Shanghai,Shenzhen,and Hong Kong markets on the return rate through the model setting test.On the other hand,the research finds that the mapping matrix of the TVL-GF model depicts the factor exposure level of the combined stock assets on different style factor combinations has good economic explanatory power and high application value.