Default correlation is a critical concept in risk management for fixed income investment, bank management, and insurance industry, working capital management, among many. We extend the Leland-Toft term structure model into a two-firm environment and predict the default correlation between two...

A financial market can be expressed in a network structure where the stocks resides as nodes and the links account for returns correlation. Centrality measure in the financial network structure captures firms' embeddedness and connectivity in the capital market structure. This paper investigates...

A financial distress of company should be able anticipated smartly by its management to rerun the business without having any loss due to business failure. Thus, we need a model which could provide an early signal to company the probability of financial distress so that remedial efforts can be...

This study investigates the determinants of bank default probability and the predictive performance of the logit and the hazard models. Using accounting and market price information in the Taiwan bank sector for the period 1999 to 2010, the result shows both models provides adequate default...

Reviews on financial distress prediction models indicate that these techniques give highly reliable estimates of probabilities of default (PDs) and loss given default (LGD) only for relatively short horizons, rarely beyond two years. Major stakeholders, e.g. investors and bank risk and capital...

This paper offers a joint estimation approach for forecasting probabilities of default and loss rates given default in the presence of selection. The approach accommodates fixed and random risk factors. An empirical analysis identifies bond ratings, borrower characteristics and macroeconomic...

We analyse the impact of soft information on US mortgages for default prediction and provide a new measure for lender soft information that is based on the interest rates offered to borrowers and incremental to public hard information. Hard and soft information provide for a variation in annual...

The paper develops an early-warning model for predicting vulnerabilities leading to distress in European banks using both bank and country-level data. As outright bank failures have been rare in Europe, the paper introduces a novel dataset that complements bankruptcies and defaults with state...