基于收益率视角的中国股市联动性研究

运用向量自回归模型、格兰杰因果关系检验、脉冲响应、方差分解及协整分析对我国创业板市场、主板市场及中小板市场联动性进行研究。研究结果表明:创业板市场与主板市场存在联动性,主板市场对创业板市场、中小板市场具有先行引导作用;沪深300指数市场波动受创业板市场波动的影响较大,而创业板市场波动的原因主要来自于其自身;沪深300指数与中小板指数存在协整效应,表明二者存在长期均衡关系。上述实证结论对研究者探讨新兴资本市场与传统资本市场之间的关系,监管当局厘清三资本市场的定位,投资者制定合理的投资策略具有重要的现实意义。     

Equilibrium asset pricing: with non-Gaussian factors and exponential utilities

We analyse the equilibrium asset pricing implications for an economy with single period return exposures to explicit non-Gaussian systematic factors, that may be both skewed and long-tailed, and Gaussian idiosyncratic components. Investors maximize expected exponential utility and equilibrium factor prices are shown to reflect exponentially tilted prices for non-Gaussian factor risk exposures. It is shown that these prices may be directly estimated from the univariate probability law of the factor exposure, given an estimate of average risk aversion in the economy. In addition, a residual form of the capital asset pricing model continues to hold and prices the idiosyncratic or Gaussian risks. The theory is illustrated on data for the US economy using independent components analysis to identify the factors and the variance gamma model to describe the probability law of the non-Gaussian factors. It is shown that the residual CAPM accounts for no more than 1% of the pricing of risky assets, while the exponentially tilted systematic factor risk exposures account for the bulk of risky asset pricing.     

Marginal consistent dependence modelling using weak subordination for Brownian motions

We present an approach for modelling dependencies in exponential Lévy market models with arbitrary margins originated from time changed Brownian motions. Using weak subordination of Buchmann et al. [Bernoulli, 2017], we face a new layer of dependencies, superior to traditional approaches based on pathwise subordination, since weakly subordinated processes are not required to have independent components considering multivariate stochastic time changes. We apply a subordinator being able to incorporate any joint or idiosyncratic information arrivals. We emphasize multivariate variance gamma and normal inverse Gaussian processes and state explicit formulae for the Lévy characteristics. Using maximum likelihood, we estimate multivariate variance gamma models on various market data and show that these models are highly preferable to traditional approaches. Consistent values of basket-options under given marginal pricing models are achieved using the Esscher transform, generating a non-flat implied correlation surface.     

Turbocharging Monte Carlo pricing for the rough Bergomi model

The rough Bergomi model, introduced by Bayer et al. [Quant. Finance, 2016, 16(6), 887–904], is one of the recent rough volatility models that are consistent with the stylised fact of implied volatility surfaces being essentially time-invariant, and are able to capture the term structure of skew observed in equity markets. In the absence of analytical European option pricing methods for the model, we focus on reducing the runtime-adjusted variance of Monte Carlo implied volatilities, thereby contributing to the model’s calibration by simulation. We employ a novel composition of variance reduction methods, immediately applicable to any conditionally log-normal stochastic volatility model. Assuming one targets implied volatility estimates with a given degree of confidence, thus calibration RMSE, the results we demonstrate equate to significant runtime reductions—roughly 20 times on average, across different correlation regimes.     

Dynamic credit default swap curves in a network topology

Systemically important banks are connected and their default probabilities have dynamic dependencies. An extraction of default factors from cross-sectional credit default swap (CDS) curves allows us to analyze the shape and the dynamics of default probabilities. In extending the Dynamic Nelson Siegel (DNS) model to an across firm multivariate setting, and employing the generalized variance decomposition of Diebold and Yilmaz [On the network topology of variance decompositions: Measuring the connectedness of financial firms. J. Econom., 2014, 182(1), 119–134], we are able to establish a DNS network topology. Its geometry yields a platform to analyze the interconnectedness of long-, middle- and short-term default factors in a dynamic fashion and to forecast the CDS curves. Our analysis concentrates on 10 financial institutions with CDS curves comprising of a wide range of time-to-maturities. The extracted level factor representing long-term default risk shows a higher level of total connectedness than those derived for short-term and middle-term default risk, respectively. US banks contributed more to the long-term default spillover before 2012, whereas European banks were major default transmitters during and after the European debt crisis, both in the long-term and short-term. The comparison of the network DNS model with alternatives proposed in the literature indicates that our approach yields superior forecast properties of CDS curves.     

Inconsistency of estimate of the degree of freedom of multivariate student-t disturbances in linear regression models

A moment estimator for the degree of freedom of the jointly multivariate student-t distribution of the disturbances in a linear regression model has been suggested by Singh [Economic letters (1988) 27, 47–53]. In this paper we will show that the distribution of the moment estimate is independent of the true value of the degree of freedom and the estimate converges to infinite in probability as the sample size goes to infinite. Our results show that the moment estimate does not provide any information on the degree of freedom.     

Further evidence on the efficiency of the Chinese stock markets: A note

This paper examines the efficiency of the Chinese A-share and B-share markets following the deregulation of the B-share market which widened ownership to include domestic investors. Applying parametric and non-parametric variance ratio tests to the daily data of 370 shares over 1996–2005, the paper finds that A-shares are more efficient than B-shares, although the efficiency of both markets has improved following the regulatory change. Overall, the results suggest that the Chinese stock markets are characterised by information asymmetry, although the timely access to high quality information that domestic investors enjoy has improved the efficiency of the B-share market.     

Hot deck插补和插补后数据的方差模拟研究

在抽样调查中，经常会遇到调查问卷中没有回答或者是某些题目没有回答的情况，这就是缺失数据的问题。处理项目无回答的缺失数据，常用的方法是插补。根据Rao和J．Shao的结果采用普通的jackknife方差会低估插补后数据的方差。如果有严重的方差低估，那就会对统计量的区间估计造成很大的影响。本文采用Montecarlo模拟的方法对这一问题进行了实证的研究，并且给出了普通的jackknife方差低估插补后数据方差的实际证据，同时支持了Rao和J．Shao提出的调整的jackknife方差。     

A Case Study of a Variance Analysis Framework for Managing Distribution Costs*

Managing the distribution function as part of an overall supply‐chain management strategy has become increasingly important given rising fuel costs in recent years. This paper presents a comprehensive variance analysis framework developed by supply‐chain managers at Catalyst Paper Corporation as a tool for reporting and controlling distribution costs. The model decomposes the overall static‐budget variance into four primary variance categories: volume, customer mix, distribution mix, and carrier charges. The framework addresses key limitations in the coverage of variance analysis contained in many management accounting textbooks. Specifically, Catalyst's framework incorporates: (a) mix variance calculations where there is more than one mix factor within a single cost element; (b) the impact of unplanned and unrealized activities; and (c) multiple nested mix variance calculations. Although developed in the context of distribution costs, the framework can be applied to the analysis of other manufacturing and non‐manufacturing costs where multiple mix factors exist. L'importance de la gestion de la fonction de distribution dans le cadre de la stratégie globale de gestion de la chaîne d'approvisionnement s'est accrue avec la hausse des coûts du carburant des dernières années. Les auteurs présentent un cadre complet d'analyse des écarts, élaboré par les gestionnaires de la chaîne d'approvisionnement chez Catalyst Paper Corporation aux fins de la présentation et du contrôle des coûts de distribution. Le modèle décompose l'écart global du budget fixe en quatre grandes catégories d'écarts: les écarts sur volume, les écarts sur composition de la clientèle, les écarts sur composition de la distribution et les écarts sur frais de transport. Le cadre résout les principales limites de la couverture de l'analyse des écarts évoquées dans de nombreux manuels de comptabilité de management. Le cadre d'analyse de Catalyst Paper Corporation englobe: a) les calculs de l'écart sur composition lorsqu'il existe plus d'un facteur de composition dans un même élément de coût; b) l'incidence des activités non planifiées et non réalisées; et c) les calculs de l'écart sur composition à multiples critères de classification. Bien qu'il ait été élaboré dans le contexte des coûts de distribution, ce cadre peut être appliqué à l'analyse d'autres coûts liés ou non à la fabrication, lorsque les facteurs de composition sont multiples.