Pricing synthetic CDO with MGB2 distribution

Cui, Qiurong; Ma, Yong

doi:10.4310/sii.2014.v7.n3.a1

Cited by 2 publications

(1 citation statement)

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“…The results presented that how the option price was highly sensitive to the changes in the tail shape, which was distinct to its sensitivity to the variance of the return distribution. Cui and Ma [39] studied the pricing synthetic CDO with MGB2 distribution. Ma et al [40] evaluated the default risk of bond portfolios with extreme value theory.…”

Section: Introductionmentioning

confidence: 99%

Valuation of Guaranteed Unitized Participating Life Insurance under MEGB2 Distribution

Zheng

Hao

Bai

et al. 2019

Discrete Dynamics in Nature and Society

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Crisis events have significantly changed the view that extreme events in financial markets have negligible probability. Especially in the life insurance market, the price of guaranteed participating life insurance contract will be affected by a change in asset volatility which leads to the fluctuations in embedded option value. Considering the correlation of different asset prices, MEGB2 (multivariate exponential generalized beta of the second kind) distribution is proposed to price guaranteed participating life insurance contract which can effectively describe the dependence structure of assets under some extreme risks. Assuming the returns of two different assets follow the MEGB2 distribution, a multifactor fair valuation pricing model of insurance contract is split into four components: the basic contract, the annual dividend option, the terminal dividend option, and the surrender option. This paper studies the effect of death rate, minimum guaranteed yield rate, annual dividend ratio, terminal dividend ratio, and surrender on the embedded option values and calculates the single premium of the insurance contract under different influence factors. The Least-Squares Monte Carlo simulation method is used to simulate the pricing model. This article makes a comparison in the sensitivity of the pricing parameters under the MEGB2 distribution and Multivariate Normal distribution asset returns. Finally, an optimal hedging strategy is designed to cover the possible risks of the underlying assets, which can effectively hedge the risks of portfolio.

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Section: Introductionmentioning

confidence: 99%