Refined Inference on Long Memory in Realized Volatility

There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter (d) around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about d by higher order theory. Standard asymptotic theory has an O(n^-1/2) error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of o(n^-1/2). The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary (d = 0.5) of nonstationary long memory, and generally confirms earlier findings.     

Issues in applying recent CPMP ‘Points to Consider’ and FDA guidance documents with biostatistical implications

The International Conference on Harmonisation guideline ‘Statistical Principles for Clinical Trials’ was adopted by the Committee for Proprietary Medicinal Products (CPMP) in March 1998, and consequently is operational in Europe. Since then more detailed guidance on selected topics has been issued by the CPMP in the form of ‘Points to Consider’ documents. The intent of these was to give guidance particularly to non‐statistical reviewers within regulatory authorities, although of course they also provide a good source of information for pharmaceutical industry statisticians. In addition, the Food and Drug Administration has recently issued a draft guideline on data monitoring committees. In November 2002 a one‐day discussion forum was held in London by Statisticians in the Pharmaceutical Industry (PSI). The aim of the meeting was to discuss how statisticians were responding to some of the issues covered in these new guidelines, and to document consensus views where they existed. The forum was attended by industry, academic and regulatory statisticians. This paper outlines the questions raised, resulting discussions and consensus views reached. It is clear from the guidelines and discussions at the workshop that the statistical analysis strategy must be planned during the design phase of a clinical trial and carefully documented. Once the study is complete the analysis strategy should be thoughtfully executed and the findings reported. Copyright © 2003 John Wiley & Sons, Ltd.     

Beyond recruitment: Predictors of differential participation in a national antihunger organization

Surprisingly little research has sought to explain differential participation after recruitment into social movement organizations (SMOs). This study examines the influence of several sets of predictors on participation by members of a national organization in the antihunger movement. The findings highlight the importance of incentive, ideological, and microstructural factors for differential participation and suggest that favorable perceptions of SMOs also promote participation. Final remarks address the implications of the findings for the social movement and voluntary organization literatures.     

The expressive and communicative functions of preschool children's smiles in an achievement-situation

Two studies examined how different social contexts determine whether preschoolers' smiles in an achievement-game serve an expressive function indicating success versus failure experiences and/or a communicative function. Facial behavior was coded with the Facial Action Coding System. Unexpectedly, in Study 1 children (N=19) smiled more often after failure than after success. Study 2 investigated the influence of face-to-face contact with the experimenter on preschoolers' smiles (N=20). However, there were no differences between success and failure, but with face-to-face contact subjects exhibited more smiles than without. Features of the social situation that are supposed to determine the predominance of the communicative or expressive function of a smile are discussed.We gratefully acknowledge the assistance of Detlef Friedrich and Katja Johann in the data collection and Signe Preuschoft in coding and analyzing the data.     

刻意创新

我们大多数人都认同创新是成长的关键途径。问题是如何创新?许多企业依靠突发机遇。也就是说,他们指望某个人提出产品或服务方面的点子,然后从中获利。然而有些时候,企业必须发掘比以往更多的创意,并先于竞争对手将创意化为切实可行的产品与服务。此时,企业便不能再依靠机缘巧合了。我们需要可持续、可重复的创新方法。     

＂Inspire Confidence, Stay Relevant＂

(Continued from the last issue)However,I did not feel I had made the right choice and the next time I saw her I apologized.She said to me I had done nothing wrong and said "it’s not your fault teacher,it’s my fault my English is too poor." But I still insisted that I had made a mistake.Yes,I had corrected her,but at what cost? The experience obviously embarrassed her,and her peers by the third time she repeated the word incorrectly had been shaking their heads.She may have left the classroom being able to pronounce the word correctly but what about the damage to her confidence? I thought about it for literally hours.I feared that perhaps next time she might not want to stand up,or shout out the answer in class in case she might be humiliated again.In her mind it was her own incompetence but for me it was my own ignorance.     

Improved bridge constructs for stochastic differential equations

We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion process satisfying an Itô stochastic differential equation conditional on an observation taken at a fixed future time-point. Such realisations are typically termed diffusion bridges. Since, in general, no closed form expression exists for the transition densities of the process of interest, a widely adopted solution works with the Euler–Maruyama approximation, by replacing the intractable transition densities with Gaussian approximations. However, the density of the conditioned discrete-time process remains intractable, necessitating the use of computationally intensive methods such as Markov chain Monte Carlo. Designing an efficient proposal mechanism which can be applied to a noisy and partially observed system that exhibits nonlinear dynamics is a challenging problem, and is the focus of this paper. By partitioning the process into two parts, one that accounts for nonlinear dynamics in a deterministic way, and another as a residual stochastic process, we develop a class of novel constructs that bridge the residual process via a linear approximation. In addition, we adapt a recently proposed construct to a partial and noisy observation regime. We compare the performance of each new construct with a number of existing approaches, using three applications.