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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Rechercher
21 août 2023
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. 2023
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. 2023
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 2023
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 2023
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 2023
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. 2023
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 2023
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 2023
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 2023
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. 2023
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. 2023
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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