POINT AND INTERVAL FORECASTS OF DEATH RATES USING NEURAL NETWORKS

DOI10.1017/asb.2021.34zbMath1484.91404OpenAlexW4226454868MaRDI QIDQ5067895

Ralf Korn, Simon Schnürch

Publication date: 4 April 2022

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2021.34

zbMATH Keywords

neural networksprediction intervalsLee-Carter modeluncertainty quantificationmortality forecastingconvolutional neural networksmortality of multiple populations

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Mathematical geography and demography (91D20) Actuarial mathematics (91G05)

Related Items (5)

TREE-BASED MACHINE LEARNING METHODS FOR MODELING AND FORECASTING MORTALITY ⋮ EXTENDING THE LEE–CARTER MODEL WITH VARIATIONAL AUTOENCODER: A FUSION OF NEURAL NETWORK AND BAYESIAN APPROACH ⋮ A Neural Approach to Improve the Lee-Carter Mortality Density Forecasts ⋮ Time-series forecasting of mortality rates using transformer ⋮ Locally-coherent multi-population mortality modelling via neural networks

Uses Software

• ggplot2
• Keras
• RMSprop
• GitHub

Cites Work

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• Unnamed Item
• Bagging predictors
• Modeling and Forecasting U.S. Mortality
• A note on the validity of cross-validation for evaluating autoregressive time series prediction
• A Poisson log-bilinear regression approach to the construction of projected lifetables.
• Modelling dependent data for longevity projections
• A cohort-based extension to the Lee-Carter model for mortality reduction factors
• Evaluating and extending the Lee\,-\,Carter model for mortality forecasting: bootstrap confidence interval
• ggplot2
• Pricing Death: Frameworks for the Valuation and Securitization of Mortality Risk
• Parameter risk in time-series mortality forecasts
• Time-series forecasting of mortality rates using deep learning
• NEIGHBOURING PREDICTION FOR MORTALITY
• A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States
• Effective Statistical Learning Methods for Actuaries III

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