Catastrophe risk bonds with applications to earthquakes

Shao, Jia; Pantelous, Athanasios A.; Papaioannou, Apostolos D.

doi:10.1007/s13385-015-0104-9

Cited by 32 publications

(31 citation statements)

References 27 publications

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“…regardless of the actual physical distribution of the underlying catastrophe insurance risk (see, e.g., Zimbidis et al (2007) and Shao et al (2015)). Under certain circumstances, such a pricing scheme may be questionable since the resulting risk premiums for catastrophes at different levels will become indistinguishable.…”

Section: A Product Pricing Measurementioning

confidence: 99%

“…The normalizing constants c n and d n in (4.1) and the scale function a(•) in (4.3) are all explicitly expressed. For applications of EVT to insurance and finance in general, we refer the reader to Embrechts et al (1999), Bali (2007), Donnelly and Embrechts (2010), Kellner andGatzert (2013), andMcNeil et al (2015), among others, while for applications of EVT to pricing CAT bonds in particular, we refer the reader to Zimbidis et al (2007), Li et al (2008), Chen and Cummins (2010), Shao et al (2015), and Aviv (2018), among others.…”

Section: Highlights Of Evtmentioning

confidence: 99%

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Cat Bond Pricing Under a Product Probability Measure With Pot Risk Characterization

Tang¹,

Yuan²

2019

ASTIN Bull.

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Frequent large losses from recent catastrophes have caused great concerns among insurers/reinsurers, who then turn to seek mitigations of such catastrophe risks by issuing catastrophe (CAT) bonds and thereby transferring the risks to the bond market. Whereas, the pricing of CAT bonds remains a challenging task, mainly due to the facts that the CAT bond market is incomplete and that the pricing usually requires knowledge about the tail of the risks. In this paper, we propose a general pricing framework based on a product pricing measure, which combines a distorted probability measure that prices the catastrophe risks underlying the CAT bond with a risk-neutral probability measure that prices interest rate risk. We also demonstrate the use of the peaks over threshold (POT) method to uncover the tail risk. Finally, we conduct case studies using Mexico and California earthquake data to demonstrate the applicability of our pricing framework.

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Section: A Product Pricing Measurementioning

confidence: 99%

Section: Highlights Of Evtmentioning

confidence: 99%

Cat Bond Pricing Under a Product Probability Measure With Pot Risk Characterization

Tang¹,

Yuan²

2019

ASTIN Bull.

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“…where is a trigger point which is the interval of data, which follows the loss function distribution and affects the level of securitization of the bonds. Where each company must balance profits and selling power by analyzing historically the loss of natural disasters [9].…”

Section: Cash Value Model For Cat Bondmentioning

confidence: 99%

“…In previous studies regarding the calculation of CAT bond prices, as Shao at al. [9], Lai et al [10], and Mariani & Amoruso [7], using quantitative methods to estimate the factors needed in calculating CAT bond prices. Zimbidis et al [11] uses Extreme Value Theory to obtain a numerical result in the form of CAT bond prices, based on the stochastic interest rate in an incomplete market scope.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Catastrophe Bonds Price by using Risk Neutral Measurement

2019

IJRTE

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Catastrophe Bonds (CAT bonds) or disaster bonds are securities products that work by transferring risk in the form of natural disaster losses to the capital market, so that it is necessary to estimate CAT bond prices. This study intends to discuss the model to determine the price of CAT bonds in arbitrage-free scope based on the approach of risk neutral measurement. The data used is extreme data in the form of losses due to natural disasters in the range of 2000-2019. There are several stages carried out in this study. The first step is to calculate descriptive data statistics. Then, estimating the data parameters using the Maximum Likelihood Estimation (MLE) method assuming the data distributed Generalized Extreme Value (GEV). Next, determine the price of CAT bond using the formula of risk neutral measurement. From the results of the analysis carried out, the CAT bond price is USD98.63, and there is the effect of risk neutral measurement on the price of CAT bonds paid by investors.

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“…Moreover, they evaluated the CAT bond price using Monte Carlo simulation techniques and stochastic iterative equations. Shao et al [7] applied equilibrium pricing theory and EVT to construct a multiple-variable CAT bond for California earthquakes. Ma et al [8] employed a doubly stochastic Poisson and Peak over Threshold (POT) to price zero-coupon catastrophe bonds.…”

Section: Introductionmentioning

confidence: 99%

Multiple-Event Catastrophe Bond Pricing Based on CIR-Copula-POT Model

Chao

Zou

2018

Discrete Dynamics in Nature and Society

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Catastrophe events are attracting increased attention because of their devastating consequences. Aimed at the nonlinear dependency and tail characteristics of different triggered indexes of multiple-event catastrophe bonds, this paper applies Copula function and the extreme value theory to multiple-event catastrophe bond pricing. At the same time, floating coupon and principal payoff structures are adopted instead of fixed coupon and principal payoff structures, to reduce moral hazard and improve bond attractiveness. Furthermore, we develop a CIR-Copula-POT bond pricing model with CIR stochastic rate and estimate flood multiple-event triggered catastrophe bond price using Monte Carlo simulation method. Finally, we implement the sensitivity analysis to show how catastrophe intensity, maturity date, and the dependence affect the prices of catastrophe bonds.

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Catastrophe risk bonds with applications to earthquakes

Cited by 32 publications

References 27 publications

Cat Bond Pricing Under a Product Probability Measure With Pot Risk Characterization

Cat Bond Pricing Under a Product Probability Measure With Pot Risk Characterization

Estimation of the Catastrophe Bonds Price by using Risk Neutral Measurement

Multiple-Event Catastrophe Bond Pricing Based on CIR-Copula-POT Model

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