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

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.     

体验、解析、会通——张岱年哲学方法论的综合创新

体验、解析、会通的有机统一,是张岱年《天人五论》所建构的哲学方法论。这种方法论排斥直觉法,因而不同于现代新儒家和清华学派的哲学家;同时,它把辩证法看成一般的学术方法而非独立的哲学方法,这又使其不同于当时的新唯物论者。这种方法论是在综合中西哲学方法以及近现代各派哲学方法基础上的一个综合创造。     

Demographic Differentials and Demographic Integration of Turkish and Kurdish Populations in Turkey

The objectives of the study are threefold: (1) to provide estimates of the total populations and spatial distributions of different language groups in Turkey, (2) to test whether the commonly held belief that Turkish-speaking and Kurdish-speaking populations are “actors” of different demographic regimes is true, and (3) to assess whether a process of integration, in the form of intermarriage of Turks and Kurds is under way in Turkey. Data come mainly from the 2003 Turkish Demographic and Health Survey (TDHS-2003). Based on the assumption that the mother tongue composition of women is also representative of that of the whole population, the results of the TDHS-2003 imply that of the population of Turkey, 83% are Turkish-speaking, 14% are Kurdish-speaking, 2% are Arabic-speaking and the remaining 1% belong to other language groups. Results show that despite intensive internal migration movements in the last 50 years, strong demographic differentials exist between Turkish and Kurdish-speaking populations, and that the convergence of the two groups does not appear to be a process under way. Turks and Kurds do indeed appear to be actors of different demographic regimes, at different stages of demographic and health transition processes.     

一类有理分式的积分

本文介绍了一类有理分式的积分,并得到了一组织分公式。     

Two Moments of the Logitnormal Distribution

We display the first two moment functions of the Logitnormal(μ, σ²) family of distributions, conveniently described in terms of the Normal mean, μ, and the Normal signal-to-noise ratio, μ/σ, parameters that generate the family. Long neglected on account of the numerical integrations required to compute them, awareness of these moment functions should aid the sensible interpretation of logistic regression statistics and the specification of “diffuse” prior distributions in hierarchical models, which can be deceiving. We also use numerical integration to compare the correlation between bivariate Logitnormal variables with the correlation between the bivariate Normal variables from which they are transformed.     

An algorithm to compute the cdf of the product of two normal random variables

This paper provides a fortran algorithm that can be used to compute the cdf of the product of two normal distribution random variables. We also give references that provide mathematical properties, tables, and applications of this distribution     

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.     

On square ordinal contingency tables: a comparison of social class and income mobility for the same individuals

Summary.  Square contingency tables with matching ordinal rows and columns arise in particular as empirical transition matrices and the paper considers these in the context of social class and income mobility tables. Such tables relate the socio-economic position of parents to the socio-economic position of their child in adulthood. The level of association between parental and child socio-economic position is taken as a measure of mobility. Several approaches to analysis are described and illustrated by UK data in which interest focuses on comparisons of social class and income mobility tables that are derived from the same individuals. Account is taken of the use of the same individuals in the two tables. Additionally comparisons over time are considered.     

A note on the non-negativity of continuous-time ARMA and GARCH processes

A general approach for modeling the volatility process in continuous-time is based on the convolution of a kernel with a non-decreasing Lévy process, which is non-negative if the kernel is non-negative. Within the framework of Continuous-time Auto-Regressive Moving-Average (CARMA) processes, we derive a necessary condition for the kernel to be non-negative, and propose a numerical method for checking the non-negativity of a kernel function. These results can be lifted to solving a similar problem with another approach to modeling volatility via the COntinuous-time Generalized Auto-Regressive Conditional Heteroscedastic (COGARCH) processes.