A Deep Factor Model for Crop Yield Forecasting and Insurance Ratemaking

DOI10.1080/10920277.2023.2182792zbMATH Open1537.91277MaRDI QIDQ6549253

Wenjun Zhu

Publication date: 3 June 2024

Published in: North American Actuarial Journal (Search for Journal in Brave)

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Actuarial mathematics (91G05)

Cites Work

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• Insurance loss coverage and demand elasticities
• Geostatistical Model Averaging for Locally Calibrated Probabilistic Quantitative Precipitation Forecasting
• SPATIAL DEPENDENCE AND AGGREGATION IN WEATHER RISK HEDGING: A LÉVY SUBORDINATED HIERARCHICAL ARCHIMEDEAN COPULAS (LSHAC) APPROACH
• Time-series forecasting of mortality rates using deep learning
• Agricultural Insurance Ratemaking: Development of a New Premium Principle
• Deep Learning at the Interface of Agricultural Insurance Risk and Spatio-Temporal Uncertainty in Weather Extremes
• A Relational Data Matching Model for Enhancing Individual Loss Experience: An Example from Crop Insurance
• Regularization and Variable Selection Via the Elastic Net
• Impacts of Weather and Time Horizon Selection on Crop Insurance Ratemaking: A Conditional Distribution Approach
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

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