Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on...

This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it...

The financial crisis that began in 2007 has brought to the fore the issues of excesses in lending, leverage, and risk-taking as some of the fundamental causes of this crisis. At the same time, in dealing with the financial crisis there have been large scale interventions by governments, often...

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative...

Within a unified theory for stocks and corporate bonds, based on dynamic optimization by investors, this paper derives analytical expressions for the momentary distributions of expected price, respectively known to approximate lognormal with systematic deviations (high peak, fat tail) and double...

This paper builds on recent research by Fender and Mitchell (2009) who show that if financial institutions securitize loans, retaining an interest in the equity tranche does not always induce the securitizer to diligently screen borrowers ex ante. We first determine the conditions under which...

This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior....

Building on the widely-used double-lognormal approach by Bahra (1997), this paper presents a multi-lognormal approach with restrictions to extract risk-neutral probability density functions (RNPs) for various asset classes. The contributions are twofold: first, on the technical side, the paper...

Decision analysis produces measures of value such as expected net present values or expected utilities and ranks alternatives by these value estimates. Other optimization-based processes operate in a similar manner. With uncertainty and limited resources, an analysis is never perfect, so these...

This research proposes primitive cognitive network process (P-CNP), which comprises five decision processes, as an alternative of analytic hierarchy process (AHP). Two published cases using AHP are revised by P-CNP, and the validity and applicability of P-CNP are demonstrated. The comparison...