We use a unique dataset of bond downgrades from a niche rating company that has been found to be reacting faster to publicly available information than its competitors. Using regime-switching models we propose risk measures to quantify stock return disturbances (distress costs) associated with...

We construct a model for pricing sovereign debt that accounts for the risks of both default and restructuring, and allows for compensation for illiquidity. Using a new and relatively efficient method, we estimate the model using Russian dollar-denominated bonds.(...)

This paper develops a model and estimate simultaneously the joint dynamics of default-free and defaultable bond term structures.

We investigate the evolution of health over the life-cycle. We allow for two sources of persistence: unobserved heterogeneity and state dependence. Estimation indicates that there is a large degree of heterogeneity. For half the population, there are modest degrees of state dependence...

We introduce a Nelson-Siegel type interest rate term structure model with the underlying yield factors following autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term structure and are associated with the time-varying...

In this paper we first investigate the validity of a general Value at Risk approach, which iswidely used for risk management in banking and insurance companies. We discuss and widely rejectthe conventional assumptions, e.g. independent identically distributed normal returns, and as...

Recently, Diebold and Li (2003) obtained good forecasting results foryield curves in a reparametrized Nelson-Siegel framework. We analyze similarmodeling approaches for price curves of variance swaps that serve nowadaysas hedging instruments for options on realized variance. We consider the...

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

Inspired by findings of lowdimensional nonlinearities and the Theorem of Takens (1983) forecasting models of financial time series are often built upon nonparametric, i.e. universal nonlinear, univariate relationships. Empirical investigations, however, are seriously contaminated by the problem...

Conventional time series analysis, focusing exclusively on a time series at a given scale, lacks the ability to explain the nature of the data generating process. A process equation that successfully explains daily price changes, for example, is unable to characterize the nature of hourly price...