A threshold stochastic volatility model with explanatory variables

In this paper, we introduce a threshold stochastic volatility model with explanatory variables. The Bayesian method is considered in estimating the parameters of the proposed model via the Markov chain Monte Carlo (MCMC) algorithm. Gibbs sampling and Metropolis–Hastings sampling methods are used for drawing the posterior samples of the parameters and the latent variables. In the simulation study, the accuracy of the MCMC algorithm, the sensitivity of the algorithm for model assumptions, and the robustness of the posterior distribution under different priors are considered. Simulation results indicate that our MCMC algorithm converges fast and that the posterior distribution is robust under different priors and model assumptions. A real data example was analyzed to explain the asymmetric behavior of stock markets.     

基于灰色优势分析的中国农业现代化水平测度与波动趋势分析

灰色优势分析能在排除主观因素干扰的情况下对各评价指标进行赋权,提升了评价体系的可信度.农业现代化产出指标和投入指标的关联序分别表征了各评价指标在衡量农业现代化发展水平时的代表性强弱.结果显示:1981-2010年中国农业现代化进程已先后走出“高效益、低水平”和“高水平、低效益”的非良性状态,逐步趋向“高效益、高水平”的良性发展.随着资源、环境、人力等因素对农业的约束日渐趋紧,未来中国农业现代化水平的提升不能单纯依靠农业投入产出的规模扩张,必须注重提高农业投入产出的效益水平.     

Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables

In this study, we revisit the oil–stock nexus by accounting for the role of macroeconomic variables and testing their in-sample and out-of-sample predictive powers. We follow the approaches of Lewellen (2004) and Westerlund and Narayan (2015), which were formulated into a linear multi-predictive form by Makin et al. (2014) and Salisu et al. (2018) and a nonlinear multi-predictive model by Salisu and Isah (2018). Thereafter, we extend the multi-predictive model to account for structural breaks and asymmetries. Our analyses are conducted on aggregate and sectoral stock price indexes for the US stock market. Our proposed predictive model, which accounts for macroeconomic variables, outperforms the oil-based single-factor variant as well as the constant returns (historical average) model for both in-sample and out-of-sample forecasts. We find that it is important to account for structural breaks in our proposed predictive model, although asymmetries do not seem to improve predictability. In addition, we show that it is important to pre-test the predictors for persistence, endogeneity, and conditional heteroscedasticity, particularly when modeling with high-frequency series. Our results are robust to different forecast measures and forecast horizons and are useful for making effective hedging decisions in the US stock market.     

Expectations Hypothesis of the Term Structure of Implied Volatility: Evidence from Foreign Currency and Stock Index Options

Using a stochastic volatility option pricing model, we showthat the implied volatilities of at-the-money options are notnecessarily unbiased and that the fixed interval time-seriescan produce misleading results. Our results do not support theexpectations hypothesis: long-term volatilities rise relativeto short-term volatilities, but the increases are not matchedas predicted by the expectations hypothesis. In addition, anincrease in the current long-term volatility relative to thecurrent short-term volatility is followed by a subsequent decline.The results are similar for both foreign currency and the S&P500 stock index options.     

我国股市波动的阶段性特征研究——基于ARCH模型族的实证研究

以上证综合指数为代表,根据我国股市交易制度的两次转变,把我国股市自1991年至2006年的15年发展历程分为三个阶段,利用ARCH族模型,从股市波动的集聚性、持续性、"杠杆效应"几个方面,研究了我国股市15年间的波动特征的变迁,得出了一些富有现实意义的结论。     

Volatility dependences of stock markets with structural breaks

We develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.     

Mass at zero in the uncorrelated SABR model and implied volatility asymptotics

We study the mass at the origin in the uncorrelated stochastic alpha, beta, rho stochastic volatility model and derive several tractable expressions, in particular when time becomes small or large. As an application—in fact the original motivation for this paper—we derive small-strike expansions for the implied volatility when the maturity becomes short or large. These formulae, by definition arbitrage free, allow us to quantify the impact of the mass at zero on existing implied volatility approximations, and in particular how correct/erroneous these approximations become.     

结构变动、要素产出弹性与中国潜在经济增长率

构建了一个结构型时变弹性生产函数,将劳动投入结构、资本投入结构和人力资本结构纳入经济增长分析框架,运用1997-2012的省级面板数据估计了这一时期要素产出弹性的动态特征,并估算出中国潜在经济增长率的变化。研究结果表明：近年来潜在增长率下降,主要由资本存量增速下降所导致,但人力资本结构升级减缓了这一趋势。近10年来实际增长率变化主要是受潜在增长率变化影响,2010年以来的经济增速减缓,是由于潜在增长率下降导致,未来政策重心应当从需求管理过度到供给管理,着力开发经济增长的潜力,保证经济增长的可持续性。     

现券市场做市报价点差的微观特征分析

交易机制与价格发现的关系一直是金融市场微观结构的重要研究方向,其目的是为了发现金融市场如何借由微观行为的不均衡实现市场层面的价格均衡过程。事实上,交易机制、交易习惯和市场均衡过程三者之间是相互影响的关系。分析和研究这三者的内在联系可以加深我们对市场的理解,并找到提高市场资源配置效率的途径。文章以做市报价收益率点差作为研究对象,详细分析了其时间分布、相关性、波动性及时间持续性等微观特征,为深入研究做市商报价和交易行为提供各种可能的切入点。     

股票日内流动性度量及其风险调整--基于上海股票市场高频数据的实证研究

流动性是股票市场的重要属性,但对流动性进行准确的定义和度量却是一件困难的事情。本文给出了股票流动性度量的三个指标,并对这些指标进行了风险调整。最后利用风险调整后的指标对上海股票市场的样本股票进行了截面相关分析,得出风险调整后的流动性指标逻辑关系更加紧密的结论。