Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries

This paper examines the dynamic relationships between gold and stock markets using data for the BRICS counties. For this purpose, we estimate the Asymmetric DCC model for weekly stock and gold data. Our main objective is to examine the time-varying correlations between the two assets and to check the effectiveness of gold as a hedge for equity markets. The empirical results reveal that the dynamic conditional correlations switch between positive and negative values over the period under study. These correlations are low to negative during the major financial crises suggesting that gold can act as a safe haven against extreme market movements. We also evaluate the implications for portfolio diversification and hedging effectiveness for the gold/stock pairs. Our findings suggest that adding gold to a stock portfolio enhances its risk-adjusted return.     

Measuring large comovements in financial markets

A general, copula-based framework for measuring the dependence among financial time series is presented. Particular emphasis is placed on multivariate conditional Spearman's rho (MCS), a new measure of multivariate conditional dependence that describes the association between large or extreme negative returns—so-called tail dependence. We demonstrate that MCS has a number of advantages over conventional measures of tail dependence, both in theory and in practical applications. In the analysis of univariate financial series, data are filtered to remove temporal dependence as a matter of routine. We show that standard filtering procedures may strongly influence the conclusions drawn concerning tail dependence. We give empirical applications to two large data sets of high-frequency asset returns. Our results have immediate implications for portfolio risk management, derivative pricing and portfolio selection. In this context we address portfolio tail diversification and tail hedging. Amongst other aspects, it is shown that the proposed modeling framework improves the estimation of portfolio risk measures such as the value at risk.     

BookReview

We compare the bias in binomial trees against that in certain analytical/numerical valuation techniques with which they disagree. We consider the CRR tree, the COS method and the Leisen–Reimer as well as the Prekopa–Szantai exponentially smoothed method. We conclude that the binomial trees are unbiased and that the exponentially smoothed method is biased.     

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.     

铁路多经物流的规模经济研究及实例分析

随着物流被列为十大振兴产业革命之一,目前,我国铁路多经物流运输企业正面临着一个十分良好的发展机遇,近年来,不少企业通过各种方式扩大自己的生产经营规模,以取得更好的经营效果。通过运用多元线性回归模型来分析企业的规模经济,分别从理论和实例两个方面相结合进行研究,论证铁路多经物流存在着局部和总体的规模经济,结合此多元线性回归模型分析铁路多经物流由于规模扩大而出现经济的原因。     

Multivariate extremes for models with constant conditional correlations

Models with constant conditional correlations are versatile tools for describing the behavior of multivariate time series of financial returns. Mathematically speaking, they are solutions of a special class of stochastic recurrence equations (SRE). The extremal behavior of general solutions of SRE has been studied in detail by Kesten [Kesten, H., 1973. Random difference equations and renewal theory for products of random matrices. Acta Mathematica 131, 207–248] and Perfekt [Perfekt, R., 1997. Extreme value theory for a class of Markov chains with values in ^d. Advances in Applied Probability 29, 138–164]. The central concept to understanding the joint extremal behavior of such multivariate time series is the multivariate regular variation spectral measure. In this paper, we propose an estimator for the spectral measure associated with solutions of SRE and prove its consistency. Our estimator is the tail empirical measure of the multivariate time series. Successful use of the estimator depends on a good choice of k, the number of upper order statistics contributing to the empirical measure. We introduce a new criteria for the choice of k based on a scaling property of the spectral measure. We investigate the performance of our estimation technique on exchange rate time series from HFDF96 data set. The estimated spectral measure is used to calculate probabilities of joint extreme returns and probabilities of large movements in an exchange rate conditional on the occurrence of extreme returns in another exchange rate. We find a high level of dependence between the extreme movements of most of the currencies in the EU. We also investigate the changes in the level of dependence between the extreme returns of pairs of currencies as the sampling frequency decreases. When at least one return is extreme, a strong dependence between the components is present already at the 4-hour level for most of the European currencies.     

Seeing and Doing: the Concept of Causation

This note is an extended review of the book by Judea Pearl (2000) on causality, in which the basic concepts therein are explained in a form that statisticians will hopefully appreciate, including some comments on their relevance to inference and decision-making.     

高新技术上市公司资本结构影响因素研究--基于多元线性回归分析的实证检验

公司资本结构是否合理直接影响到公司经营业绩和长远发展,高新技术上市公司是中国企业的优秀代表,仍然存在背离资本结构优化理论的种种因素,因此找出影响资本结构的主要因素是实现中国高新技术上市公司资本结构优化目标的必要途径。     

Monitoring the cross-covariances of a multivariate time series

In this paper sequential procedures are proposed for jointly monitoring all elements of the covariance matrix at lag 0 of a multivariate time series. All control charts are based on exponential smoothing. As a measure of the distance between the target values and the actual values the Mahalanobis distance is used. It is distinguished between residual control schemes and modified control schemes. Several properties of these charts are proved assuming the target process to be a stationary Gaussian process. Within an extensive Monte Carlo study all procedures are compared with each other. As a measure of the performance of a control chart the average run length is used. An empirical example about Eastern European stock markets illustrates how the autocovariance and the cross-covariance structure of financial assets can be monitored by these methods.