Default Estimation and Expert Information

Default is a rare event, even in segments in the midrange of a bank’s portfolio. Inference about default rates is essential for risk management and for compliance with the requirements of Basel II. Most commercial loans are in the middle-risk categories and are to unrated companies. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using a prior distribution assessed from an industry expert. The binomial model, most common in applications, is extended to allow correlated defaults. A check of robustness is illustrated with an ε-mixture of priors.     

“理工融合”理念下北邮信息与计算科学专业培养方案的制订和实践

本文论述了信息与计算科学专业理工融合的必要性,叙述了在理工融合的培养方案下,北邮在以下方面的做法: (1)课程体现; (2)实践贯彻; (3)师资保证.     

信息透明度对B2B交易场作用的博弈分析

传统理论认为,低的信息透明度不利于买卖双方之间达成交易,无法实现资源在市场中的最优化配置,而提高信息的透明度将有利于改变这一局面。本文通过博弈论方法分析低信息透明度和高信息透明度分别对传统交易场和B2B交易场的负面影响作用,认为,高信息透明度对于在线交易并非完全是一件有益之事。在此基础上,本文提出了降低高信息透明度负面影响作用的方法。     

Patent portfolios for strategic R&D planning

Empirical research has found a discrepancy between the perceived importance and the actual level of information on competitor's R&D strategies. It has been argued in the literature that patent information might be used to overcome this information deficit. However, empirical research further reveals that patent information is rarely used in strategic R&D planning. The present paper explores this issue and introduces two types of patent portfolios for strategic R&D planning. In patent portfolios on the company level, patenting strategies are identified and the quality of overall technological positions is benchmarked against relevant competitors. In addition, we present a patent portfolio on the technological level, which, as it is known from various technology portfolios, helps companies to manage the allocation of R&D resources effectively. Based on patent data from 21 German, European and Japanese mechanical engineering companies we show the application of both patent portfolios for strategic R&D planning purposes. The patent portfolios prove to be a very valuable tool for R&D decision makers in companies. Based on the experiences made in the case study, recommendation for the effective use of patent portfolios are formulated.     

Interpolation models with multiple hyperparameters

A traditional interpolation model is characterized by the choice of regularizer applied to the interpolant, and the choice of noise model. Typically, the regularizer has a single regularization constant , and the noise model has a single parameter . The ratio / alone is responsible for determining globally all these attributes of the interpolant: its complexity, flexibility, smoothness, characteristic scale length, and characteristic amplitude. We suggest that interpolation models should be able to capture more than just one flavour of simplicity and complexity. We describe Bayesian models in which the interpolant has a smoothness that varies spatially. We emphasize the importance, in practical implementation, of the concept of conditional convexity when designing models with many hyperparameters. We apply the new models to the interpolation of neuronal spike data and demonstrate a substantial improvement in generalization error.     

Quantitative refinements for comparisons of institutional performance

In the context of the data and issues discussed by Goldstein and Spiegelhalter, we suggest refinements which can be used by decision makers when confronted with ranking problems associated with 'league tables'. Two ranking criteria are defined and their performance illustrated for one of the studies reported by Goldstein and Spiegelhalter.     

Time series forecasting with neural networks: a comparative study using the air line data

This case-study fits a variety of neural network (NN) models to the well-known air line data and compares the resulting forecasts with those obtained from the Box–Jenkins and Holt–Winters methods. Many potential problems in fitting NN models were revealed such as the possibility that the fitting routine may not converge or may converge to a local minimum. Moreover it was found that an NN model which fits well may give poor out-of-sample forecasts. Thus we think it is unwise to apply NN models blindly in 'black box' mode as has sometimes been suggested. Rather, the wise analyst needs to use traditional modelling skills to select a good NN model, e.g. to select appropriate lagged variables as the 'inputs'. The Bayesian information criterion is preferred to Akaike's information criterion for comparing different models. Methods of examining the response surface implied by an NN model are examined and compared with the results of alternative nonparametric procedures using generalized additive models and projection pursuit regression. The latter imposes less structure on the model and is arguably easier to understand.     

Updating Uncertainty in an Integrated Risk Assessment: Conceptual Framework and Methods

Bayesian methods are presented for updating the uncertainty in the predictions of an integrated Environmental Health Risk Assessment (EHRA) model. The methods allow the estimation of posterior uncertainty distributions based on the observation of different model outputs along the chain of the linked assessment framework. Analytical equations are derived for the case of the multiplicative lognormal risk model where the sequential log outputs (log ambient concentration, log applied dose, log delivered dose, and log risk) are each normally distributed. Given observations of a log output made with a normally distributed measurement error, the posterior distributions of the log outputs remain normal, but with modified means and variances, and induced correlations between successive log outputs and log inputs. The analytical equations for forward and backward propagation of the updates are generally applicable to sums of normally distributed variables. The Bayesian Monte-Carlo (BMC) procedure is presented to provide an approximate, but more broadly applicable method for numerically updating uncertainty with concurrent backward and forward propagation. Illustrative examples, presented for the multiplicative lognormal model, demonstrate agreement between the analytical and BMC methods, and show how uncertainty updates can propagate through a linked EHRA. The Bayesian updating methods facilitate the pooling of knowledge encoded in predictive models with that transmitted by research outcomes (e.g., field measurements), and thereby support the practice of iterative risk assessment and value of information appraisals.     

Ethnic and class factors affecting mental health clinic service

Service delivery by a mental health clinic to clients from an older suburban catchment area containing both lower and middle class blacks and whites was studied. The epidemiologic method was employed, relating service delivery to the characteristics of the various population groups within the catchment. The findings indicate that low service rates for blacks were not related to ethnicity alone, but to the combination of black ethnicity and low social status; however, middle class blacks and middle class whites who entered treatment received similar service. Poor blacks had higher admission rates than poor whites with similar need indicators. In continued treatment, poor blacks received lowest service rates while minority status poor whites living in a predominantly black area received highest service rates. Social class mediated black service utilization. Severity of illness, interacting with social class and minority status mediated white service utilization. Outreach is suggested not only for poor blacks but also for poor whites, especially those living in areas in which they represent an ethnic minority.     

Is there early take-off phenomenon in diffusion of IP-based telecommunications services?

Traditionally, the diffusion of telecommunications services has been considerably affected by the presence of critical mass and network externalities, and thus has shown the so-called “late take-off” phenomenon. However, as telecommunications networks evolve from circuit switching to packet switching, especially IP networks, and thus enabling diverse new services, it seems these traditional telecommunications diffusion patterns are changing. By comparing the diffusion of IP-based services with those of circuit-based services and durable goods, we have found the late take-off phenomenon is not involved in the diffusion of newly introduced IP-based services. Moreover, we concluded that the diffusion of IP-based services is much faster than that of durable goods, thus showing an “early take-off” phenomenon. Based on this empirical result, we suggest that telcos (telecommunications companies) and (ISPs) Internet service providers should pay as much attention to the growth stage as the introduction stage in their development, in order for their IP-based services to be successful in the market.