Pricing the hedging factor in the cross-section of stock returns

We investigate the role of investors’ net hedging strategy (factor) in predicting stock returns and pricing the cross-section of individual stocks and equity portfolios. We estimate stock exposure to changes in the hedging factor and show that the hedging premium is driven by outperformance of stocks with large positive net hedging betas, which explains their higher average returns. We find the positive hedging premium indicates risk-averse investors demand extra compensation to hold stocks with higher equity risk premiums, and they are themselves willing to pay higher prices for stocks with positive hedging betas.     

Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

Relative risk aversion and the transmission of financial crises

We study how investor behavior affects the transmission of financial crises. If investors exhibit decreasing relative risk aversion, then negative wealth shocks increase the risk premium required to hold risky assets. We integrate this into a second generation model of currency crises which allows for contagion through changes in fundamentals. Investor behavior can be a transmission channel of financial crises, as changes in risk premia increase the coverage ratio and makes the defense of a peg less attractive for the policy maker. The feedback effect of the risk premia on the probability of devaluation also makes multiple equilibria more likely. The possible stabilization effects of capital controls and a Tobin tax on the international transmission of financial crises are also studied.     

Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network

This paper investigates the systemic risk spillovers and connectedness in the sectoral tail risk network of Chinese stock market, and explores the transmission mechanism of systemic risk spillovers by block models. Based on conditional value at risk (CoVaR) and single index model (SIM) quantile regression technique, we analyse the tail risk connectedness and find that during market crashes, stock market exposes to more systemic risk and more connectedness. Further, the orthogonal pulse function shows that Herfindahl-Hirschman Index (HHI) of edges has a significant positive effect on systemic risk, but the impact shows a certain lagging feature. Besides, the directional connectedness of sectors shows that systemic risk receivers and transmitters vary across time, and we adopt PageRank index to identify systemically important sector released by utilities and financial sectors. Finally, by block model we find that the tail risk network of Chinese sectors can be divided into four different spillover function blocks. The role of blocks and the spatial spillover transmission path between risk blocks are time-varying. Our results provide useful and positive implications for market participants and policy makers dealing with investment diversification and tracing the paths of risk shock transmission.     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.     

公司风险视角下上市国企管理层股权激励研究

在允许国有控股上市公司实施股权激励的背景下,考察了其不同种类风险与经营者股权激励强度的关系。先界定了风险的类型,再通过构建基于风险的两种股权激励模型,并进一步推导得出：若国有上市企业的管理层不能（可以）买卖公司以外的市场证券组合时,其最优股权激励强度与公司特别性风险成反向变化关系,而与公司整体性风险的相关关系不确定（无关）,这为正在实践中摸索的国有上市企业管理层股权激励合同的设计提供了进一步的理论建议。     

基于BAPM的企业权益资本成本研究

在行为资产定价模型（BAPM）,股票的权益资本成本和行为β相关。在非有效市场中,无风险利率、市场投资组合、行为β和市场风险溢价共同决定了权益资本成本。     

Predicting the portfolio risk of high-dimensional international stock indices with dynamic spatial dependence

The spatial dependence of assets, which relates to similarities in economic, political, or cultural systems and other aspects, has been confirmed through empirical research; however, spatial dependence has rarely been applied to financial risk measurement. To fill this gap in the literature, a dynamic spatial GARCH-copula (sGC) model is proposed in this paper to evaluate the portfolio risk of international stock indices. In this model, a spatial GARCH is used as the marginal distribution and vine copula is adopted as the joint distribution of indices. Then, the proposed model is applied empirically to assess portfolio risk. Results show that, first, the proposed risk prediction model with spatial dependence outperforms a model neglecting spatial effects per the Kupiec test, Z test and Christoffersen test. Risk prediction during periods of economic stability is also more accurate than during times of crisis. Second, risk measures for models with spatial dependence are higher than those without such dependence but lower than for vine copula models. Third, models including either spatial dependence or vine copulas alone exhibit relatively poor performance. Fourth, the model involving extreme value theory (EVT) generates the greatest value at risk to pass the Kupiec test, Z test and Christoffersen test; however, this model is not suitable for characterizing international indices with EVT based on negative values of the shape parameters of estimates. Findings offer important implications for personal investors, institutional investors, and national regulatory authorities.     

Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China

We develop a skewness-dependent multivariate conditional autoregressive value at risk model (SDMV-CAViaR) to detect the extreme risk transmission channels between the Chinese stock index futures and spot markets. The proposed SDMV-CAViaR model improves the forecast performance of extreme risk by introducing the high-frequency realized skewness. Specifically, the realized skewness has a significant impact on the spillovers, but the realized volatility and realized kurtosis do not, which implies that the jump component plays an important role in extreme risk spillovers. The empirical results indicate there are bidirectional extreme risk spillovers between the stock index futures and spot markets, the decline of one market has direct and indirect channels to exacerbate the extreme risk of the other market. Firstly, the market decline will directly increase the extreme risk of related markets by decreasing market returns. Besides, the decline will indirectly increase the extreme risk by increasing the negative realized skewness and extreme risk spillovers.     

Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China

This article uses the stock market regional indexes of 31 provinces (include Province-level municipalities and Minority Autonomous Regions) in mainland China as a sample, and constructs an inter-regional volatility spillover network of China’s stock market based on the GARCH-BEKK model. Through network centrality analysis, Diebold and Yilmaz's spillover index method and block model analysis, we comprehensively analyze the risk contagion effect among different regions in China’s stock market. The empirical results show that: (i) The risk contagion intensity (risk reception intensity) in various regions of China’s stock market has a typical “core-periphery” distribution characteristic due to regions’ different levels of economic development. (ii) There are obvious risk spillover effect in China’s stock market, among which the economically developed regions along the southeastern coast of China, such as Beijing, Shanghai, Zhejiang and Jiangsu, are the main risk transmitters, while the economically undeveloped regions in the Midwest of China, such as Xinjiang, Xizang, Gansu, Nei Menggu and Qinghai are the main risk receivers. (iii) Each region is divided into 4 blocks according to their respective roles in the risk spillover process in China’s stock market. Block 1 that is composed of the economically underdeveloped regions in the Midwest is the “main benefit block”, it acts as a “receiver”. Block 2 that is composed of regions with strong economic growth vitality in the Midwest is a “Bilateral spillover block”, it both plays the role of “receiver” and “transmitter”. Block 3 that is composed of developed regions along the southeast coast, it acts as a “transmitter”; Block 4 that is composed of the relatively fast-growing regions in the Southwest is the “brokers block”, it serves as a “bridge”. The results of this article can provide some reference for investors in financial institutions and decision makers in financial regulators.     

Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach

This paper uses a spatial econometrics approach to study the industry risks in China’s stock market. We comprehensively consider the real linkage and information risk transmission channels and analyze the risk spillovers of specific determinants. Our empirical results show the following: 1) The real linkage channel and information channel are both effective transmission channels for driving spillover effects, and the information channel is of the utmost importance. 2) The spillover effects of specific determinants exist and are persistent. The superposition of spillover effects may lead to extreme risk. 3) The transmission channels and spillover effects are asymmetric in different regimes.