“Noise” in Ratings: Not Entirely Random I investigate the informational accuracy as opposed to informational content of credit ratings over time. The study presents an empirical analysis of the classification errors. Results suggest that greater the credit risk in the economy, the higher is the error rate. Of all binary classifications tested, classification error for dichotomous class of inves...

We present a multi-dimensional jump-diffusion version of a structural default model and show how to use it in order to value the credit value adjustment for a credit default swap. We develop novel analytical and numerical methods for solving the corresponding boundary value problem with a special emphasis on the role of negative asset value jumps. Using recent market data, we show that under re...

This paper presents the Loans Standard (LS) model as an example of a pure credit monetary system. The LS model clariies some en-dogenous credit money issues raised by Moore, Wray, Arestis, Good-hart and others in the Journal of Post Keynesian Economics. The LS model encapsulates the credit money characteristics which have been identiied in the present monetary system, but removes its extraneous...

The firm’s credit rating is an important communication tool and previous research has shown that many companies consider it important in capital structure decisions. This study examines the determinants of capital structure in MENA banks. In addition, it investigates the determinants of credit rating. Further, the impact of credit rating and capital structure on banks’ performance is examined. ...

Corporate credit default swap (CDS) premium is the market price of credit risk posed by a corporate obligor. Although corporate CDS are commonly used for risk benchmarking in accounting and credit risk management, liquid CDS are limited to less than 500 corporate names globally. CDS users must either confine their usage to this limited subset or resort to aggregates derived from the liquid CDS ...

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-...