 Predicting catastrophe risk: Evidence from catastrophe bond marketsYang Zhao and Min-Teh Yu () Journal of Banking & Finance, 2020, vol. 121, issue C Abstract: Compared to the past literature on prediction markets that uses small-scale observational field data or experiments, this present research examines the efficiency of such markets by studying catastrophe (CAT) bonds. We collect actual catastrophe loss data, match them with the defined trigger events of each CAT bond contract, and then employ an empirical pricing framework to obtain the excess CAT premiums in order to represent the market-based forecasts. Our results indeed show that market-based forecasts have more significant predictive content for future CAT losses than professional forecasts that use natural catastrophe risk models. Although the predictive information for CAT events is specialized and complex, our evidence supports that CAT bond markets are successful prediction markets that efficiently aggregate information about future CAT losses. Our resultsalso highlight that actual CAT losses in future periods can explain the excess CAT bond spreads in the primary market and provide support for market efficiency when pricing CAT risk. Keywords: Prediction markets; Catastrophe bonds; Market efficiency; Catastrophe risk; Market-based forecast (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:121:y:2020:i:c:s0378426620302442 DOI: 10.1016/j.jbankfin.2020.105982 Access Statistics for this article Journal of Banking & Finance is currently edited by Ike Mathur More articles in Journal of Banking & Finance from Elsevier |
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