Model risk as part of the operational risk is a serious problem for financial institutions. As the pricing of derivatives as well as the computation of the market or credit risk of an institution depend on statistical models the application of a wrong model can lead to a serious over- or...

This paper analyzes and quantifies the idea of model risk in the environment of internal model building. We define various types of model risk including estimation risk, model risk in distribution and model risk in functional form. By the quantification of these concepts we analyze the impact of...

Als Teil des operationellen Risikos stellt das Modellrisiko eine wichtige Komponente für die Risikoermittlung bei Finanzinstitutionen dar. Da letztere z.B. bei der Tarifierung und Bepreisung von Derivaten bzw. Portfolien oder bei der Markt- und Kreditrisikoberechnung auf stochastische Modelle...

Under the Basel II regulatory framework non-negligible statistical problems arise when backtesting risk measures. In this setting backtests often become infeasible due to a low number of violations leading to heavy size distortions. According to Escanciano and Olmo (2010, 2011) these problems...

This paper proposes simple Hausman-type tests to check for bias in the log-periodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the null hypothesis that no bias is present, and the tests are consistent. The use of the tests in...

We show that the power of the KPSS-test against integration, as measured by divergence rates of the test statistic under the alternative, remains the same when residuals from an OLS-regression rather than true observations are used. The divergence rate is independent of the order of integration...

In this paper, we propose Phillips-Perron type, semiparametric testing procedures to distinguish a unit root process from a mean-reverting exponential smooth transition autoregressive one. The limiting nonstandard distributions are derived under very general conditions and simulation evidence...

In this paper, we introduce the concept of fractional integration for spatial autoregressive models. We show that the range of the dependence can be spatially extended or diminished by introducing a further fractional integration parameter to spatial autoregressive moving average models (SARMA)....

This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely...