A lagrange multiplier test for the error components model with incomplete panels

This Paper extends the Breusch and Pagan(1980) lagrange Multiplier test for the random effects model to the incomplete panel data case. It is shown that this test retains the simple additive structure observed in the complete panel data case. It should prove useful for practitioners facing incomplete panel data applications.     

基于VaR收益率约束的贷款组合优化决策模型

本文以贷款的收益率为金融资产的收益,以贷款收益率的波动为标准反映贷款风险,在VaR约束下,以拉格朗日乘子法为工具求二次规划,建立了在既定组合收益范围内,组合风险最小的贷款组合优化决策模型。该模型的特点一是以收益率最大损失的形式、而不是收益额的形式来反应VaR,使组合决策分析更为方便。二是考虑了风险之间的相关性,用组合VaR的收益率最大损失来控制贷款收益率的风险限额;使贷款的分配直接反映了商业银行的风险承受能力。三是在合理的目标收益范围内,给定任意一个决策者期望的收益率,总能找到对应的风险最小的贷款组合,由此模型求出的有效边界,为组合贷款的优化决策提供了科学的方法。     

Extremal dependence tests for contagion

A new test for financial market contagion based on changes in extremal dependence defined as co-kurtosis and co-volatility is developed to identify the propagation mechanism of shocks across international financial markets. The proposed approach captures changes in various aspects of the asset return relationships such as cross-market mean and skewness (co-kurtosis) as well as cross-market volatilities (co-volatility). Monte Carlo experiments show that the tests perform well except for when crisis periods are short in duration. Small crisis sample critical values are calculated for use in this case. In an empirical application involving the global financial crisis of 2008–2009, the results show that significant contagion effects are widespread from the US banking sector to global equity markets and banking sectors through either the co-kurtosis or the co-volatility channels, reinforcing that higher order moments matter during crises.     

基于回归的时变偏度和时变峰度识别检验

资产收益率时变高阶矩建模的首要前提是资产收益率的偏度和峰度具有时变性,即资产收益率存在类似于异方差性的异偏度和异峰度特征。目前文献中的时变偏度和时变峰度识别检验存在适用性较差且检验功效较低等不足。本文提出基于回归的检验方法识别资产收益率偏度和峰度的时变性。该检验一方面利用概率积分变换缓解了拉格朗日乘数检验对资产收益率序列的高阶矩存在性的限制,另一方面考虑了检验统计量中参数估计的不确定性对其统计性质的影响,具有良好的渐近统计性质且适用性更广。蒙特卡洛模拟表明该检验具有良好的有限样本性质,具有合适的检验水平和较高的检验功效。最后,将基于回归的检验运用于上证综指和深圳成指收益率的时变建模研究中。     

固定效应模型基于个体LM的新可混合性检验

对固定效应模型,本文基于拉格朗日乘数（LM）原理提出了一种新的可混合性检验。不同于已有的LM型可混合性检验,这里使用每个截面个体的LM统计量构建可混合性检验统计量。数理分析表明,本文所提的方法有着渐进正态性,对于扰动项的异方差和非正态均稳健,且与PY检验（Pesaran&Yamagata,2008）渐近等价。Monte Carlo模拟实验表明,相对于PY检验及另外两种LM型的可混合性检验,对于不同大小的 ,本文提出的方法有着良好的水平表现和更优越的检验势。     

Double-length regressions for linear and log-linear regressions with AR(1) disturbances

This paper derives Lagrange Multiplier tests based on double-length artificial regressions (DLR) for testing linear and log-linear regressions with AR(1) disturbances against Box-Cox alternatives These DLR tests are easier to compute than the corresponding likelihood ratio tests, and are easily generalized to test jointly for functional form and serial correlation. Two illustrative examples are given to show the importance of jointly testing for functional form and serial correlation.     

The multiplier method in constrained estimation of covariance structure models

Based on the multiplier method of constrained minimization, an algorithm is developed to handle the constrained estimation problem in covariance structure analysis. In the context of a general model which has wide applicability in multivariate medical and behavioural researches, computer programs are implemented to produce the weighted least squares estimates and the maximum likelihood estimates. The multiplier method is compared with the penalty function method in terms of computer time, number of iterations and number of unconstrained minimizations. The indication is that the multiplier method is substantially better.     

Real and Spurious Long-Memory Properties of Stock-Market Data

We test for the presence of long memory in daily stock returns and their squares using a robust semiparametric procedure of Lobato and Robinson. Spurious results can be produced by nonstationarity and aggregation. We address these problems by analyzing subperiods of returns and using individual stocks. The test results show no evidence of long memory in the returns. By contrast, there is strong evidence in the squared returns.     

Approximations to the p-values of tests for a change-point under non-standard conditions

Three test statistics for a change-point in a linear model, variants of those considered by Andrews and Ploberger [Optimal tests when a nusiance parameter is present only under the alternative. Econometrica. 1994;62:1383–1414]: the sup-likelihood ratio (LR) statistic; a weighted average of the exponential of LR-statistics and a weighted average of LR-statistics, are studied. Critical values for the statistics with time trend regressors, obtained via simulation, are found to vary considerably, depending on conditions on the error terms. The performance of the bootstrap in approximating p-values of the distributions is assessed in a simulation study. A sample approximation to asymptotic analytical expressions extending those of Kim and Siegmund [The likelihood ratio test for a change-point in simple linear regression. Biometrika. 1989;76:409–423] in the case of the sup-LR test is also assessed. The approximations and bootstrap are applied to the Quandt data [The estimation of a parameter of a linear regression system obeying two separate regimes. J Amer Statist Assoc. 1958;53:873–880] and real data concerning a change-point in oxygen uptake during incremental exercise testing and the bootstrap gives reasonable results.