MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

Advertising to the masses: the effects of crowding on the attention to place-based advertising

Advertising situated in environments where people congregate or pass through on their way to somewhere else benefit from being placed in such high traffic areas. However, these strategically placed ads also suffer from conditions of human crowding that prevents them from being noticed and processed. We undertake a study of place-based advertising in a shopping mall using facial recognition software to determine the effect of human density on the attention directed to advertising. We find that as human density increases, attention to advertising decreases, but only to a point where it begins to increase again. Our research also finds that human density plays a moderating role on the motivation to process advertising.     

A Dynamic Analysis of Fixed- and Adjustable-Rate Mortgage Terminations

This paper provides a side-by-side comparison of loan-level statistical models for fixed- and adjustable-rate mortgages. Multinomial logit models for quarterly conditional probabilities of default and prepayment are estimated. We find that the estimated impacts of embedded option values for prepayment and default are generally quite similar across both FRM and ARM loans, providing additional empirical support for the basic predictions of the options theory. We also find that differences in estimates of conditional probabilities of prepayment and default associated with mortgage age, origination period, original LTV, and relative loan size, indicate the continued significance of these other economic and demographic factors for empirical models of mortgage terminations.     

无限缓存下自相似网络通信量复用策略

研究了自相似网络通信量的统计复用策略。首先讨论了在采用FIFO(First In First Out)服务策略且缓存趋于无限大时，满足一定溢出概率要求的统计复用带宽要求，然后对这种情况进行了仿真分析。研究表明网络通信量的自相似特性对复用增益有较大的影响，并且自相似性越强、复用通信量数量越大，所取得的复用增益越大，这对于网络设计是很重要的。     

Construct measurement in strategic management research: illusion or reality?

Strategic management research has been characterized as placing less emphasis on construct measurement than other management subfields. In this work, we document the state of the art of measurement in strategic management research, and discuss the implications for interpreting the results of research in this field. To assess the breadth of measurement issues in the discipline, we conducted a content analysis of empirical strategic management articles published in leading journals in the period of 1998–2000. We found that few studies discuss reliability and validity issues, and empirical research in the field commonly relies on single‐indicator measures. Additionally, studies rarely address the problems of attenuation due to measurement error. We close with a discussion of the implications for future research and for interpreting prior work in strategic management. Copyright © 2004 John Wiley & Sons, Ltd.     

An investigation of transformation-based prediction interval for the Weibull median life

Statistical inference based on the Weibull distribution, a distribution widely used in reliability and survival analysis, is usually difficult as it often involves numerical computation and approximation. However, this distribution can be transformed to near-normality by a simple power transformation. Based on this transformation, a prediction interval (PI) for its median can be easily constructed through an inverse transformation. The procedure for selecting the best power transformation through minimizing Kullback-Leibler information is described. The property of this transformation-based PI is investigated. Simple correction factors are also proposed. It is shown that the transformation-based PI with corrections performs well, irrespective of the sample size and parameter values. Simulation results show that the new PI generally outperforms the existing PI. Numerical examples are given for illustration.     

Generalized piecewise linear histograms

We extend the concept of piecewise linear histogram introduced recently by Beirlant, Berlinet and Györfi. The disadvantage of that histogram is that in many models it takes on negative values with probability close to 1. We show that for a wide set of models, the extended class of estimates contains a bona fide density with probability tending to 1 as the sample size n increases to infinity. The mean integrated absolute error in the extended class of estimators decreases with the same rate n^–2/5 as in the original narrower class.     

Conditioning as disintegration

Conditional probability distributions seem to have a bad reputation when it comes to rigorous treatment of conditioning. Technical arguments are published as manipulations of Radon–Nikodym derivatives, although we all secretly perform heuristic calculations using elementary definitions of conditional probabilities. In print, measurability and averaging properties substitute for intuitive ideas about random variables behaving like constants given particular conditioning information.
One way to engage in rigorous, guilt-free manipulation of conditional distributions is to treat them as disintegrating measures—families of probability measures concentrating on the level sets of a conditioning statistic. In this paper we present a little theory and a range of examples—from EM algorithms and the Neyman factorization, through Bayes theory and marginalization paradoxes—to suggest that disintegrations have both intuitive appeal and the rigor needed for many problems in mathematical statistics.     

The market’s view on the probability of banking sector failure: cross-country comparisons

Hall and Miles (1990) suggest an approach of estimating default probabilities of banks using stock market information, and in this paper we apply an aggregated version of their approach to banking sectors around the world in both developed and emerging economies. We study the market’s assessment of the probability of systemic banking crises world wide over the last decade, including the Asian crisis 1997–1998. In addition, we investigate whether there is a relationship between the failure probability and institutional features of the actual banking sector. The quality of governance and the degree of law and order in a country is found to be significantly negatively related to the market based failure probabilities as is an explicit deposit insurance during periods of crisis.