Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

Limited information-processing capacity and asymmetric stock correlations

Through an orthogonalized impulse-response analysis, I studied the relationship between the variance risk premium, market variance and stock correlations in the French stock market from September 2002 through September 2006, using high-frequency data-based measures. Variance risk premium is estimated using realized variances and index options-implied variances and used as a state vector to proxy investors perceived uncertainty. I found that a shock to variance risk premium causes long-lasting increases in the market variance pointing to the limitedness of investors information-processing capacity. At the same time, the shock generates consecutive increases in realized correlations between individual stocks and the market portfolio. I propose this as a possible explanation for the asymmetric/counter-cyclic behaviour of stock correlations.     

An effective hybrid variance reduction method for pricing the Asian options and its variants

In this paper, we propose a variance reduction method that combines importance sampling and control variates to price European Arithmetic Asian options and its variants (i.e., Asian options plus knock-in or knock-out options) under the Black-Scholes model. The numerical results show that the proposed methods are especially efficient under the following scenarios: in the money, low volatility, more sampling dates, and higher barrier thresholds.     

Variance swaps valuation under non-affine GARCH models and their diffusion limits

In this article, we investigate the pricing and convergence of general non-affine non-Gaussian GARCH-based discretely sampled variance swaps. Explicit solutions for fair strike prices under two different sampling schemes are derived using the extended Girsanov principle as the pricing kernel candidate. Following standard assumptions on time-varying GARCH parameters, we show that these quantities converge respectively to fair strikes of discretely and continuously sampled variance swaps that are constructed based on the weak diffusion limit of the underlying GARCH model. An empirical study which relies on a joint estimation using both historical returns and VIX data indicates that an asymmetric heavier tailed distribution is more appropriate for modelling the GARCH innovations. Finally, we provide several numerical exercises to support our theoretical convergence results in which we further investigate the effect of the quadratic variation approximation for the realized variance, as well as the impact of discrete versus continuous-time modelling of asset returns.     

The market price of risk of the variance term structure

In this paper I examine the market price of risk of the variance term structure. To this end, the S&P 500 option implied variance term structure is used as a proxy for aggregate variance risk. Principal component analysis shows that time variation in the variance term structure over the 1996–2012 period can be explained mainly by two factors which capture changes in the level and slope. The market price of risk of each factor is estimated in the cross-section of stock returns. The slope of the variance term structure is the most significant factor in the cross-section of stocks returns and carries a negative risk premium. The slope factor has also some predictive ability over long horizon equity returns.     

How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns

We explore whether the market variance risk premium (VRP) can be predicted. We measure VRP by distinguishing the investment horizon from the variance swap’s maturity. We extract VRP from actual S&P 500 variance swap quotes and we test four classes of predictive models. We find that the best performing model is the one that conditions on trading activity. This relation is also economically significant. Volatility trading strategies which condition on trading activity outperform popular benchmark strategies, even once we consider transaction costs. Our finding implies that broker dealers command a greater VRP to continue holding short positions in index options in the case where trading conditions deteriorate.     

陕西省城乡关联发展与基础设施建设动态关系分析

以陕西省为例,在对近20年城乡关联度和基础设施建设水平测度的基础上,利用格兰杰因果检验、脉冲响应函数及方差分解模型,对其城乡关联发展与基础设施建设的关系进行了计量分析。研究显示：①1990年以来,陕西省城乡关联度和基础设施建设水平经历了同步发展到拮抗的演变过程;②陕西省道路、邮电通信、环保和教育卫生设施建设水平变化与城乡关联度变化互为格兰杰因果关系,而城乡关联度变化仅是能源给水设施建设水平变化的单向格兰杰因果关系;③陕西省城乡关联度变化一直受到自身及道路、邮电通信、环保和教育卫生设施建设水平的影响,且后者的方差贡献逐渐增大,其中道路设施建设水平的方差贡献率在第5期（即1994年）超过了其自身的贡献率。     

基于VAR模型的深圳保险发展与宏观经济增长关联机制研究

深圳特区建立30年以来,随着宏观经济的迅猛发展,深圳保险业也不断发展壮大,创造了诸多全国第一。本文通过建立VAR模型,借助脉冲响应函数、方差分解方法,揭示了深圳保险发展与宏观经济之间的关联机制,分析了金融危机对深圳保险业的影响路径,并在此基础上形成了一些结论和建议。     

中国人力资本水平与FDI技术溢出关系研究

针对1985-2009年间中国人力资本水平和FDI技术溢出进行VECM模型检验结果表明,我国人力资本水平与FDI技术溢出存在长期稳定关系,但短期关系不显著。从动态层面看,FDI技术溢出变化对我国人力资本水平有显著的正向影响,但我国人力资本水平变化对FDI技术溢出的正向影响程度较弱。     

西部欠发达地区FDI与经济增长的动态关系研究——以广西数据为例

以广西1986～2009年有关数据为基础,运用协整分析、脉冲响应函数和方差分解分析等方法,对外商直接投资和经济增长之间的动态关系进行实证分析.结果显示:广西的外商直接投资与经济增长之间具有长期均衡关系,而且FDI对GDP增长具有较弱的正效应,短期具有一定的波动性。最后,提出相关的政策措施。