Measuring the Dependence between Non-Gaussian Financial Assets Using Copulae: Risk Management, Option Pricing and Default Risk

Author(s):  
Eric Bouyé ◽  
Mark Howard Salmon
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Fumin Zhu ◽  
Michele Leonardo Bianchi ◽  
Young Shin Kim ◽  
Frank J. Fabozzi ◽  
Hengyu Wu

AbstractThis paper studies the option valuation problem of non-Gaussian and asymmetric GARCH models from a state-space structure perspective. Assuming innovations following an infinitely divisible distribution, we apply different estimation methods including filtering and learning approaches. We then investigate the performance in pricing S&P 500 index short-term options after obtaining a proper change of measure. We find that the sequential Bayesian learning approach (SBLA) significantly and robustly decreases the option pricing errors. Our theoretical and empirical findings also suggest that, when stock returns are non-Gaussian distributed, their innovations under the risk-neutral measure may present more non-normality, exhibit higher volatility, and have a stronger leverage effect than under the physical measure.


Author(s):  
Tobias Götze ◽  
Marc Gürtler

AbstractReinsurance and CAT bonds are two alternative risk management instruments used by insurance companies. Insurers should be indifferent between the two instruments in a perfect capital market. However, the theoretical literature suggests that insured risk characteristics and market imperfections may influence the effectiveness and efficiency of reinsurance relative to CAT bonds. CAT bonds may add value to insurers’ risk management strategies and may therefore substitute for reinsurance. Our study is the first to empirically analyse if and under what circumstances CAT bonds can substitute for traditional reinsurance. Our analysis of a comprehensive data set comprising U.S. P&C insurers’ financial statements and CAT bond use shows that insurance companies’ choice of risk management instruments is not arbitrary. We find that the added value of CAT bonds mainly stems from non-indemnity bonds and reveal that (non-indemnity) CAT bonds are valuable under high reinsurer default risk, low basis risk and in high-risk layers.


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