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Catastrophe bond spread and hurricane arrival frequency
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Catastrophe bond spread and hurricane arrival frequency

Carolyn W. Chang, Yu-Jen WangMin-Teh Yu
North American Journal of Economics and Finance
2020

摘要

Catastrophe bonds;Climate variables forecasting approach;Negative binomial regression;Poisson regression;Price discovery function Finance Economics and Econometrics

Catastrophe bonds are the most successful alternative risk transfer tools in transferring catastrophic insurance risk to capital markets. This research provides empirical insights about the predictive power of catastrophe bond spreads in forecasting catastrophe arrival frequency as a test of the catastrophe bond market's price discovery efficacy. Primary-market data for cat bonds, catastrophe arrival frequency data for hurricanes and windstorms, and climate variable data for Atlantic Multidecadal Oscillation, North Atlantic Oscillation and CO change rate are collected over June 1997 to March 2013 to examine this power. The calibration results show that cat bond spreads convey valuable incremental information as measured by the Akaike Information Criterion. Furthermore, in an out-sample test for hurricanes prediction, merging the conventional climate variables approach with our market-based forward-looking predictions reduces prediction errors by about 3% over the sample period. As the catastrophe bond market continues to grow with increasing trading volume, a needed ingredient to enhance market efficiency, we would expect this measure of improvement to accentuate.

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