A Theory of Conflicts of Interest in Banking Relationships

Abstract

This paper highlights a dark side of banking relationships by elucidating the conditions under which a pre-existing relationship between a lending bank and a borrower can be detrimental to positive valuation effects of loan announcements. The effect of a pre-existing relationship is more likely to be negative when the pre-existing loans are large and firms' screening costs are low. A theoretical model shows that loan announcement's positive effect on borrowers' value due to the standard information advantage can be more than offset by the bank's conflict of interest when the bank's asset quality reputation is poor, i.e. when the probability of the bank holding a bad loan is large.     

Properties of a distribution-free two-stage two-sample median test

Abstract  In this paper we consider a class of distribution-free two-stage two-sample median tests. These procedures are based on a fixed size sample from one population, while the observations from the second population are collected in a truncated sequential fashion. Necessary tables are provided enabling us to select a particular member from the class such that arbitrarily preset power levels are approximately obtained. We also present asymptotic expressions and tables for the expected number of observations from the second population. Finally, comparisons between the asymptotic version of this two-stage median test and the binomial sequential probability ratio test due to W ald (1947) are discussed.     

Random variables generated by ranks in dependent schemes

Some nonstationary sequences having independent vector of ranks and vector of order statistics are under consideration. We extend some characterizations in a class of independent r.v.'s to a class of Archimedean copula processes and construct the interpretation which gives us a simple way for simulating Archimedean copula processes. Received November 1997     

品牌进入次序优势的经济解释

作者利用品牌经济学理论和其“选择成本范式”的分析框架研究品牌进入次序的优势及其产生的原因。通过对一个简单模型的分析表明,“趋利避害”的消费者的选择行为将给第一个进入市场的品牌以持久的优势,原因在于该品牌降低了消费者选择行为的局限条件—选择成本,而后进入市场的品牌,由于转换成本的存在,将使其选择成本高于先进入市场的品牌,从而使其处于劣势的地位,因此后进入市场品牌的品类模仿成功的可能性大大降低。     

Sequential estimation of a linear function of normal means under asymmetric loss function

The problem of estimating a linear function of k normal means with unknown variances is considered under an asymmetric loss function such that the associated risk is bounded from above by a known quantity. In the absence of a fixed sample size rule, sequential stopping rules satisfying a general set of assumptions are considered. Two estimators are proposed and second-order asymptotic expansions of their risk functions are derived. It is shown that the usual estimator, namely the linear function of the sample means, is asymptotically inadmissible, being dominated by a shrinkage-type estimator. An example illustrates the use of different multistage sampling schemes and provides asymptotic expansions of the risk functions. Received: August 1999     

The Effect of Sequential Structure in Charity Advertising on Message Elaboration and Donation Intention: The Mediating Role of Empathy

Abstract

This study examines how a sadness-happiness sequential structure affects how individuals process a charity advertisement. Cognitive elaboration is measured by capturing eye-movement. A negative-positive sequential structure in the charity advertisement induces individuals to focus on the incoming messages, thus evoking positive emotions and empathy for the needy person. Empathy plays a mediating role by mitigating the negative emotions induced by the negative element of the advertisement. The study’s results demonstrate that a negative-positive sequence in a charity advertisement enhances message elaboration, thus increasing individuals’ receptivity to charity advertising messages.     

The impact of the US stock market opening on price discovery of government bond futures

We examine price discovery in sequential markets for the 10-year US Treasury note, German bund, and UK gilt futures over the period 2010–2017. We find that price discovery increases after the opening of the US stock market. Order flows in the bond futures markets are more informative for permanent price changes in the 30-min period after the US stock market opens. A placebo test using US statutory holidays confirms our findings. A cross-market analysis suggests that the increased price discovery in the bond futures is related to returns and net order flows of the US stock market.     

Gaussian models for Euro high grade government yields

This paper tests affine, quadratic and Black-type Gaussian models on Euro area triple A Government bond yields for maturities up to 30 years. Quadratic Gaussian models beat affine Gaussian models both in-sample and out-of-sample. A Black-type model best fits the shortest maturities and the extremely low yields since 2013, but worst fits the longest maturities. Even for quadratic models we can infer the latent factors from some yields observed without errors, which makes quasi-maximum likelihood (QML) estimation feasible. New specifications of quadratic models fit the longest maturities better than does the ‘classic’ specification of Ahn et al. [2002. ‘Quadratic Term Structure Models: Theory and Evidence.’ The Review of Financial Studies 15 (1): 243–288], but the opposite is true for the shortest maturities. These new specifications are more suitable to QML estimation. Overall quadratic models seem preferable to affine Gaussian models, because of superior empirical performance, and to Black-type models, because of superior tractability. This paper also proposes the vertical method of lines (MOL) to solve numerically partial differential equations (PDEs) for pricing bonds under multiple non-independent stochastic factors. ‘Splitting’ the PDE drastically reduces computations. Vertical MOL can be considerably faster and more accurate than finite difference methods.     

基于SVM的虹膜识别技术

文章主要阐述了基于支持向量机方法进行虹膜识别,首先利用虹膜处理系统对采集到的虹膜图象预处理,得到条形图象,然后利用主元分析方法(即PCA方法)进行特征提取,以达到降维的目的,得到的一个训练样本对应一个40维的向量,最后利用支持向量机使用序列最小优化算法进行虹膜识别。平均识别率达到了94.3%,结果表明本文的方法取得了较好的效果,降低了训练时间,提高了训练效率。