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The computation of various risk metrics is essential to the quantitative risk management of variable annuity guaranteed … produce closed-form approximation of the risk measures for variable annuity guaranteed benefits. The techniques are further … developed in this paper to address in a systematic way risk measures for death benefits with the consideration of dynamic …
Persistent link: https://www.econbiz.de/10010464782
We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and …-year-ahead. The latter has recently attracted considerable attention due to the different properties of short term risk and long run … risk. The key insight behind our importance sampling based approach is the sequential construction of marginal and …
Persistent link: https://www.econbiz.de/10011979983
Economic problems such as large claims analysis in insurance and value-at-risk in finance, requireassessment of the …
Persistent link: https://www.econbiz.de/10010533207
An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the …
Persistent link: https://www.econbiz.de/10011301159
application is accurate prediction of financial risk measures, where the area of interest is the left tail of the predictive … introduced to further decrease the numerical standard errors of the Value-at-Risk and Expected Shortfall estimators. The third …
Persistent link: https://www.econbiz.de/10012057160
applied within a Bayesian analysisof a GARCH-mixture model which is used for the evaluation of theValue-at-Risk of the return …
Persistent link: https://www.econbiz.de/10011302625
This paper introduces a novel approach to simulation smoothing for nonlinear and non-Gaussian state space models. It allows for computing smoothed estimates of the states and nonlinear functions of the states, as well as visualizing the joint smoothing distribution. The approach combines...
Persistent link: https://www.econbiz.de/10015404318
The econometrics literature proposed several new causal machine learning methods (CML) in the past few years. These methods harness the strength of machine learning methods to flexibly model the relationship between the treatment, outcome and confounders, while providing valid inferential...
Persistent link: https://www.econbiz.de/10012650104
We extend the results of De Luca et al. (2021) to inference for linear regression models based on weighted-average least squares (WALS), a frequentist model averaging approach with a Bayesian flavor. We concentrate on inference about a single focus parameter, interpreted as the causal effect of...
Persistent link: https://www.econbiz.de/10012510747
Persistent link: https://www.econbiz.de/10003644178