We investigate price duration variance estimators that have long been neglected in the literature. We show i) how price duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and ii) how they are affected by a)...

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

The main challenge of forecasting credit default risk in loan portfolios is forecasting the default probabilities and the default correlations. We derive a Merton-style threshold-value model for the default probability which treats the asset value of a firm as unknown and uses a factor model...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading...

This paper employs the parametric probit regression model, estimates the probability of default (PD) of Australian mortgages, and examines the nature of the relationships between the PD and some loan level variables such as loan-to-value ratio (LVR), loan documentation, loan type, loan purpose,...

We use a large panel dataset that includes nearly 31,000 Greek private firms to investigate which variables impact on the prediction of corporate financial distress. Based on a multi-period logit model that accounts for industry effects, we identify six firm-specific variables that best describe...

Credit ratings are ordinal predictions for the default risk of an obligor. To evaluate the accuracy of such predictions commonly used measures are the Accuracy Ratio or, equivalently, the Area under the ROC curve. The disadvantage of these measures is that they treat default as a binary variable...

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy....

Predictions of whether newly unemployed individuals will become long-term unemployed are important for the planning and policy mix of unemployment insurance agencies. We analyze unique data on three sources of information on the probability of re-employment within 6 months (RE6), for the same...