Catastrophe bond spread and hurricane arrival frequency

Carolyn W. Chang, Yu-Jen Wang and Min-Teh Yu ()

The North American Journal of Economics and Finance, 2020, vol. 54, issue C

Abstract: 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 CO2 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.

Keywords: Catastrophe bonds; Price discovery function; Climate variables forecasting approach; Poisson regression; Negative binomial regression (search for similar items in EconPapers)
JEL-codes: G20 G22 G28 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:54:y:2020:i:c:s1062940818304406

DOI: 10.1016/j.najef.2019.01.003

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