Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

Financial integration and the price of world covariance risk: Large- vs. small-cap stocks

We investigate whether recent country-level evidence of global pricing is particular to large-cap stocks. Specifically, we examine cross-country return correlations and conduct asset pricing tests on three size-based stock portfolios for nine developed countries over the period from 1980 to 2004. We find that large-cap stocks realize significant comovements across countries, whereas small-cap stocks realize smaller average correlations (relative to both large-cap stocks and small-cap stocks across countries). More important, asset pricing tests suggest that while large-cap stocks are priced globally, global pricing is rejected for most small-cap stocks. Finally, the evidence indicates that financial integration deepened in recent years primarily for large-cap stocks. Overall, the results suggest that the global pricing pertains chiefly to large-cap stocks.     

Asymptotic expansion of S-estimators of location and covariance

By means of a straightforward application of empirical process theory, we show that S-estimators of multivariate location and covariance are asymptotically equivalent to a sum of independent vector and matrix valued random elements respectively. This provides an alternative proof of asymptotic normality of S-estimators and clearly explains the limiting covariance structure. It also leads to a relatively simple proof of asymptotic normality of the length of the shortest α-fraction.     

弄另水电站1~#发电机定子铁损试验分析

大中型水轮发电机的定子,因外形尺寸大,受到运输条件的限制,其定子机座采用分瓣制造运输,在安装现场进行组装焊接、铁芯堆积及定子下线。定子铁损试验是在定子铁芯冲片叠装、压紧后进行,通过测量铁损、温升及温差的方法检查定子铁芯冲片的制造及叠装整体质量,定子铁芯制造及安装质量好坏关系着机组的长期安全运行。文章对弄令电站1#发电机定子铁损试验的实施进行了研究分析。     

灌区不同空间尺度显热通量测定方法的对比分析

摘要：本文利用安装在山东省位山灌区典型农田内的大孔径激光闪烁仪 （LAS） 和涡度相关系统 （EC） ,测定了不同空度尺度上的显热通量,对比分析了两个系统测定结果在不同作物条件下的相关关系,讨论了造成二者偏差的可能原因。结果显示,在研究区域的农田下垫面条件下LAS和EC系统测定的显热通量之间存在较好的一致性;LAS的测量结果略大于EC测量值,这可能是由下垫面不均匀性、二者源区不一致以及EC测量值偏小造成的。研究证明,LAS是测定区域平均显热通量较为可靠的方法。     

三方柱绕流的大涡模拟及频谱分析

高雷诺数条件下,无论来流是均匀还是非均匀,多方柱绕流情况下方柱受力及尾流的相互干扰都是相当复杂的.为了研究方柱受力及下游尾流的相互干扰,基于大涡模拟紊流模型对后品字等边布置的三方柱绕流进行了数值模拟,数值模拟结果表明,上游两个方柱的阻力系数要明显小于下游方柱,而上游两方柱升力系数远大于下游方柱,且下游方柱的升力系数基本...     

Multivariate Hill Estimators

We propose two classes of semi‐parametric estimators for the tail index of a regular varying elliptical random vector. The first one is based on the distance between a tail probability contour and the observations outside this contour. We denote it as the class of separating estimators. The second one is based on the norm of an arbitrary order. We denote it as the class of angular estimators. We show the asymptotic properties and the finite sample performances of both classes. We also illustrate the separating estimators with an empirical application to 21 worldwide financial market indexes.     

On Some Characteristics of Gaussian Covariance Functions

The concepts of isotropy/anisotropy and separability/non‐separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results concerning the Gaussian covariance model and its properties related to isotropy and separability are given, and moreover, some examples are provided. Finally, a discussion on asymmetric models, with Gaussian marginals, is furnished and the strictly positive definiteness condition is discussed.     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage,jumps, spillovers,and geopolitical risks

To forecast the covariance matrix for the returns of crude oil and gold futures, this paper examines the effects of leverage, jumps, spillovers, and geopolitical risks by using their respective realized covariance matrices. To guarantee the positive definiteness of the forecasts, we consider the full BEKK structure on the conditional Wishart model. By the specification, we can flexibly divide the direct and spillover effects of volatility feedback, negative returns, and jumps. The empirical analysis indicates the benefits of accommodating the spillover effects of negative returns, and the geopolitical risks indicator for modeling and forecasting the covariance matrix.