Essential Aspects to Bayesian Data Imputation
#bayesian data imputation holds significant importance in a variety of fields including #riskmanagement. Incomplete or missing data can...
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- 21 août
Optimal Premium Pricing in a Competitive Stochastic Insurance Market with Incomplete Information
"This paper examines a #stochastic one-period #insurancemarket with incomplete information. The aggregate amount of #claims follows a...
- 28 juil.
Bayesian and Classical Approaches to Structural Estimation of Risk Attitudes
This study examines interpersonal heterogeneity in #risk attitudes in #decisionmaking experiments. The use of #bayesian and classical...
- 20 juil.
Introduction to Bayesian Data Imputation
#bayesian data imputation is a technique used to fill in missing data in a variety of fields, including #riskmanagement. By employing...
- 7 juin
Bayesian backtesting for counterparty risk models
"... we find that the #bayesian approach outperforms the classical [#counterparty #risk #model] in identifying whether a model is...
- 2 juin
Do Finance Researchers Address Sample Size Issues? – A Bayesian Inquiry in the AI Era.
Traditional #statistical and #algorithm-based methods used to analyze #bigdata often overlook small but significant evidence. #bayesian...
- 5 mai
Understanding Uncertainty Shocks and the Role of Black Swans
We offer a #datadriven theory of #belief formation that explains sudden surges in economic #uncertainty and their consequences. It argues...
- 25 avr.
Particle MCMC in forecasting frailty correlated default models with expert opinion
This paper focuses on predicting #corporate #default #risk using frailty correlated default #models with subjective judgments. The study...
- 24 mars
Uncertainty in Systemic Risks Rankings: Bayesian and Frequentist Analysis
"In this paper we propose efficient #bayesian Hamiltonian #montecarlo method for estimation of #systemicrisk#measures , LRMES, SRISK and...
- 15 mars
Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting Tail Risks of Monthly Us GDP
This paper proposes a novel mixed-frequency quantile vector autoregression (MF-QVAR) model that uses a #bayesian framework and...
- 7 mars
Bayesian Cart Models for Insurance Claims Frequency
This paper focuses on the development of #bayesian classification and regression tree (#cart) models for claims frequency modeling in...
- 13 févr.
A Dirichlet Process Mixture Regression Model for the Analysis of Competing Risk Events
"We address the problem of sharing risk among agents with preferences modelled by a general class of comonotonic additive and law-based...
- 26 janv.
Bayesian Model Selection and Prior Calibration for Structural Models in Economic Experiments
"Bayesian estimates from experimental data can be influenced by highly diffuse or "uninformative" priors. This paper discusses how...
- 6 juin 2022
Multi-Population Mortality Modelling: A Bayesian Approach
"An efficient Bayesian Markov Chain Monte-Carlo method is developed to estimate the unknown parameters to address the computational...
- 11 mai 2022
A Unified Bayesian Framework for Pricing Catastrophe Bond Derivatives
"The primary contribution of this paper is to present a unified Bayesian CAT bond pricing framework based on uncertainty quantification...
- 8 avr. 2022
A Generalized Linear Mixed Model for Data Breaches and its Application in Cyber Insurance
"Estimations of model parameters are presented under Bayesian framework using a combination of Gibbs sampler and Metropolis-Hastings...
- 13 janv. 2022
Pandemic Risk Assessment and Management in a Bayesian Framework
"This work presents a Bayesian-based semi-mechanistic model for a short-term forecast of pandemic risk." LIRE
- 27 déc. 2021
A Bayesian-Loss Function Model for Assessing Marine Liability Regime for Ship-Source Spills
"The model is a comprehensive template for assessing loss and subsequently the insurance for activities in the Arctic and sub-Arctic...
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