LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

ABSTRACT

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

浅谈基层部队思想政治教育方法创新

随着社会主义市场经济和大众传媒的深人发展，部队官兵的价值观念日趋多元化，国内外敌对势力以现代传媒为手段加紧在意识形态领域与我争夺广大官兵。我军广大政工干部必须清醒认识到基层部队思想政治教育方法创新的必要性，认真分析制约当前部队思想政治教育方法创新的主要因素，采取可行措施促进基层部队思想政治教育方法不断创新。     

Vulnerability Assessment of Mining Subsidence Hazards

Between 1996 and 1999, five mining subsidence events occurred in the iron-ore field in Lorraine, France, and damaged several hundred buildings. Because of the thousand hectares of undermined areas, an assessment of the vulnerability of buildings and land is necessary for risk management. Risk assessment methods changed from initial risk management decisions that took place immediately after the mining subsidence to the risk assessment studies that are currently under consideration. These changes reveal much about the complexity of the vulnerability concept and about difficulties in developing simple and relevant methods for its assessment. The objective of this article is to present this process, suggest improvements on the basis of theoretical definitions of the vulnerability, and give an operational example of vulnerability assessment in the seismic field. The vulnerability is divided into three components: weakness, stakes value, and resilience. Final improvements take into account these three components and constitute an original method of assessing the vulnerability of a city to subsidence.     

2012年镇江赛珍珠国际学术研讨会综述

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Some small-sample results on a bounded influence rank regression method

Naranjo and HeUmansperger (1994) recently derved a bounded influence rank regression method and suggested how hypotheses about the regression coefficients might be tested. This brief note reports some simulation results on how their procedure performs when there is one predictor. Even when the error term is highly skewed, good control over the Type I error probability is obtained Power can be high relative to least squares regression when the error term has a heavy tailed distribution .and the predictor has a symmetric distribution However, if the predictor has a skewed distribution, power can be relatively low even when the distribution of the error term is heavy tailed. Despite this, it is argued that their method provides an important and useful alternative to ordinary least squares as well as other robust regression methods.     

浅议党委会应制定正确的工作方法

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The robustness of the systemwise breusch-godfrey autocorrelation test for non-normal distributed error terms

Using Monte Carlo methods, the properties of systemwise generalisations of the Breusch-Godfrey test for autocorrelated errors are studied in situations when the error terms follow either normal or non-normal distributions, and when these errors follow either AR(1) or MA(1) processes. Edgerton and Shukur (1999) studied the properties of the test using normally distributed error terms and when these errors follow an AR(1) process. When the errors follow a non-normal distribution, the performances of the tests deteriorate especially when the tails are very heavy. The performances of the tests become better (as in the case when the errors are generated by the normal distribution) when the errors are less heavy tailed.     

医学统计学教学改革刍议

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Block and Basu bivariate lifetime distribution in the presence of cure fraction

This paper presents estimates for the parameters included in the Block and Basu bivariate lifetime distributions in the presence of covariates and cure fraction, applied to analyze survival data when some individuals may never experience the event of interest and two lifetimes are associated with each unit. A Bayesian procedure is used to get point and confidence intervals for the unknown parameters. Posterior summaries of interest are obtained using standard Markov Chain Monte Carlo methods in rjags package for R software. An illustration of the proposed methodology is given for a Diabetic Retinopathy Study data set.