Equity market neutral hedge funds and the stock market: an application of score-driven copula models

In this article, we study the time-varying market neutrality of equity market neutral hedge funds. We use data from the Hedge Fund Research? Equity Market Neutral Index (HFRX EH), which represents the performance of a portfolio of individual equity market neutral hedge funds. For each day, we measure different levels of association of the Standard and Poor’s 500 (S&;P 500) index and the HFRX EH. We use non-linear dynamic conditional score models of location, scale and copula that, to the best of our knowledge, have not yet been applied in the body of literature on hedge funds. We study whether the neutrality of the HFRX EH that is evidenced in the body of literature for the period of April 1993–April 2003 also holds for the following decade, for the period of May 2003–December 2016. We estimate different average levels of association for the pre-, during- and post-periods of the US financial crisis of 2008. We find that the association of the S&;P 500 and the HFRX EH, on average, is significantly positive for the pre- and post-periods of the financial crisis, and it is significantly negative for the period during the financial crisis.     

担保债务凭证(CDO)定价研究——基于正态与学生氏copula法的比较

利用蒙特卡罗模拟技术,研究担保债务凭证(CDO)的定价问题,对于不同的相关系数,使用正态Copula以及学生氏Copula计算各级分类证券的公平价差,并对正态Copula以及学生氏Copula产生的结果进行比较分析。研究表明,在担保债务凭证(CDO)的定价中,学生氏Copula的性能更好。     

国际原油价格波动是否增加了国内CPI通胀率的不确定性?

本文选取2001年1月至2011年10月的月度统计数据,基于二阶矩意义的Granger因果检验方法,在多元GARCH模型框架下,运用残差向量的方差-协方差矩阵所包含的信息,构建非对称的BEKK模型,对国际油价波动与国内消费者价格指数(CPI)通胀率不确定性的因果关系进行了检验。结论表明,国际油价波动会向国内CPI输出不确定性因素,且短期油价上涨更容易增加国内CPI的不确定性;但国内CPI变动无法向国际油价输出不确定性。     

On the structure and estimation of hierarchical Archimedean copulas

In this paper we provide a method for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general, the true structure of the hierarchy is unknown, but we develop a computationally efficient technique to determine it from the data. For this purpose we introduce a hierarchical estimation procedure for the parameters and provide an asymptotic analysis. We consider both parametric and nonparametric estimation of the marginal distributions. A simulation study and an empirical application show the effectiveness of the grouping procedure in the sense of structure selection.     

我国财产保险公司承保业务线经济资本的度量

承保风险是保险公司面临的主要风险之一,合理地计量其经济资本有助于提高公司的资本管理能力。采用多元Copula理论对我国某财险公司主要业务线的相依结构进行建模,选择拟合较好的GaussCopula,在此基础上,使用凹扭曲风险度量测度主要业务线的经济资本。结果显示:凹扭曲风险度量中的Wang风险度量能够根据风险的整体水平灵活地调整所需的经济资本。     

Can channel pattern trading be profitably automated?

Financial markets, such as the global foreign exchange (FX) market, often exhibit trending behaviour. Within such trends, the market level oscillates with changes in market consensus. Continued oscillations of this type result in the formation of wave patterns within the underlying trend known as channels, which are used by technical analysts as trade entry signals. A sample space of such channels has been constructed from a set of US dollar/British pound Spot FX tick data from 1989–1997 using pattern recognition algorithms and the profitability of trading using such patterns has been estimated. A number of attributes of the resulting collection of channels has been subjected to statistical analysis with the aim of classifying patterns that can be traded profitably using a number of simple trading rules. Results of this analysis show that there exist statistically significant links between the channels' attributes and profitability.     

A multivariate Lévy process model with linear correlation

In this paper, we develop a multivariate risk-neutral Lévy process model and discuss its applicability in the context of the volatility smile of multiple assets. Our formulation is based upon a linear combination of independent univariate Lévy processes and can easily be calibrated to a set of one-dimensional marginal distributions and a given linear correlation matrix. We derive conditions for our formulation and the associated calibration procedure to be well-defined and provide some examples associated with particular Lévy processes permitting a closed-form characteristic function. Numerical results of the option premiums on three currencies are presented to illustrate the effectiveness of our formulation with different linear correlation structures.     

Evaluating portfolio Value-at-Risk using semi-parametric GARCH models

In this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes. Examining the within-sample VaRs of a set of given portfolios shows that the semi-parametric model performs uniformly well, while parametric models in several cases have unacceptable failure rates. Interestingly, distributional assumptions appear to have a much larger impact on the performance of the VaR estimates than the particular parametric specification chosen for the GARCH equations.     

The t copula with multiple parameters of degrees of freedom: bivariate characteristics and application to risk management

The t copula is often used in risk management as it allows for modeling the tail dependence between risks and it is simple to simulate and calibrate. However, the use of a standard t copula is often criticized due to its restriction of having a single parameter for the degrees of freedom (dof) that may limit its capability to model the tail dependence structure in a multivariate case. To overcome this problem, the grouped t copula was proposed recently, where risks are grouped a priori in such a way that each group has a standard t copula with its specific dof parameter. In this paper we propose the use of a generalized grouped t copula, where each group consists of one risk factor only, so that a priori grouping is not required. The copula characteristics in the bivariate case are studied. We explain simulation and calibration procedures, including a simulation study on the finite sample properties of the maximum likelihood estimators and Kendall's tau approximation. This new copula is significantly different from the standard t copula in terms of risk measures such as tail dependence, value at risk and expected shortfall.