An Econometric Model of Credit Spreads with Rebalance, ARCH, and Jump Effects In this paper, we examine the dynamic behavior of credit spreads on corporate bond portfolios. We propose an econometric model of credit spreads that incorporates portfolio rebalancing, the near unit root property of spreads, the autocorrelation in spread changes, the ARCH conditional heteroscedasticity, jumps, and la...

An Econometric Model of Credit Spreads with Rebalancing, ARCH, and Jump Effects In this paper, we examine the dynamic behavior of credit spreads on corporate bond portfolios. We propose an econometric model of credit spreads that incorporates portfolio rebalancing, the near unit root property of spreads, the autocorrelation in spread changes, the ARCH conditional heteroscedasticity, jumps, and ...

This paper describes an approach to user adaptation realized in a multiagent interface system for interaction with a virtual environment. The interface agency adapts to users' individual preferences by learning from direct feedback. The core idea is that agents that were successful in meeting the user's expectations are given credit while unsuccessful agents are \discredited." Communicating cre...

Many factors innuence the performance of a learned classiier. In this paper we study diier-ent methods of measuring performance based on a uniied set of cost models and the eeects of training class distribution with respect to these models. Observations from these eeects help us devise a distributed multi-classiier meta-learning approach to learn in domains with skewed class distributions, non-...

This paper studies limited commitment and adverse selection in an economy in which private liabilities (inside money) can be used as instruments of intertemporal trade. The results suggest that in conjunction with adverse selection, the limited commitment problem may affect the behavior of intrinsically higher quality debtors more severely than lower quality ones. Nonetheless, a credit economy ...

Association rules are considered to be the best studied models for data mining. In this article, we propose their use in order to extract knowledge so that normal behavior patterns may be obtained in unlawful transactions from transactional credit card databases in order to detect and prevent fraud. The proposed methodology has been applied on data about credit card fraud in some of the most im...