When estimating Loss Given Default (LGD) parameters using a workout approach, i.e. discounting cash flows over the workout period, the problem arises of how to take into account partial recoveries from incomplete work-outs. The simplest approach would see LGD based on complete recovery profiles...

This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...

This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The approach is flexible as it requires no assumptions on the form of return distributions. A monotonized double kernel local linear estimator is applied to estimate moderate (1%)...

The catastrophic failures of risk management systems in 2008 bring to the forefront the need for accurate and flexible estimators of market risk. Despite advances in the theory and practice of evaluating risk, existing measures are notoriously poor predictors of loss in high-quantile events. To...

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional...

This paper develops new inference methods for testing the expectations hypothesis in a general econometric framework. In particular, we consider nonparametric tests of the predictability of excess returns in the presence of MA disturbances. We discuss several alternatives of aggregation and...

This paper proposes a test for the conditional superior predictive ability (CSPA) of a family of forecast methods with respect to a benchmark. The test is functional in nature: Under the null hypothesis, the benchmark's conditional expected loss is no more than those of the competitors,...

This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all – or a subset – of the variables may be fractionally integrated and the...

Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...

The Diebold-Mariano-Test has become a common tool to compare the accuracy of macroeconomic forecasts. Since these are typically model-free forecasts, distribution free tests might be a good alternative to the Diebold-Mariano-Test. This paper suggests a permutation test. Stochastic simulations...