We study the implications of the value at risk concept for the bank's optimum amount of equity capital under credit risk. The market value of loans is risky and lognormally distributed. We show that the required equity capital depends upon managerial and market factors. Furthermore, the bank's...

The paper shows the ways of disclosing financial risks by IFRS 7 and certain types of sensitivity analysis. The different possibilities of preparing a sensitivity analysis, such as value at risk are illustrated and their suitability for reporting are faced critically. Following, the manner of...

[...] The objective of this study is to analyse - relying on 2006 data - FX settlement risk that may arise in the domestic banking system under its current operations, and to chart the changes which took place after 2000, covering improvements and, if necessary, formulating (new) recommendations...

Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. Thus, it serves to examine the robustness of numerical results with respect to input parameters, which is a...

This paper focuses on firm valuation for tax purposes of non-listed company shares and its sensitivity towards different market conditions. Since the value of a private company cannot be observed on the stock market the value has to be estimated. Due to uncertainty, expected future profits may...

The empirical economic growth literature is criticized for its lack ofrobustness. For different definitions of robustness, conclusions vary from 'almost everycorrelation is fragile' to 'a substantial number of explanatory variables are robust.' Were-analyze the empirical results of the economic...

Quantiles play an important role in modelling quality of service in the service industry and in modelling risk in the financial industry. Recently, Hong showed in his breakthrough papers that efficient simulation based estimators can be obtained for quantile sensitivities by means of sample path...

This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster...

Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly...