Managing Basis Risks in Weather Parametric Insurance: A Quantitative Study of Diversification and Key Influencing Factors

TL;DR

This study uses Monte Carlo simulations to analyze how diversification and spatial factors can reduce basis risk in weather parametric insurance, showing that increasing contracts and understanding spatial relationships improve risk management.

Contribution

It introduces an empirical approach to managing basis risk through diversification and spatial analysis, providing new insights into risk mitigation strategies for weather parametric insurance.

Findings

Portfolio basis risk decreases with more contracts

Spatial relationships significantly influence basis risk

Event severity has minimal impact on basis risk

Abstract

Weather parametric insurance relies on weather indices rather than actual loss assessments, enhancing claims efficiency, reducing moral hazard, and improving fairness. In the context of increasing climate change risks, despite growing interest and demand,, weather parametric insurance's market share remains limited due to inherent basis risk, which is the mismatch between actual loss and payout, leading to loss without payout or payout without loss. This paper proposes a novel empirical research using Monte Carlo simulations to test whether basis risk can be managed through diversification and hedged like other risks. Key findings include: Firstly, portfolio basis risk and volatility decrease as the number of contracts increases. Secondly, spatial relationships significantly impact basis risk, with risk levels correlating with the ratio between insured location, weather station, and disaster footprint radius, and thirdly, event severity does not significantly impact basis risk, suggesting that catastrophic disaster severity should not hinder parametric insurance development.