The Analysis Of The Global Correlations Of Catastrophe Losses -Based On The Application Of Copula Theory

Since the end of last century, the degree of openness of the insurance market continues to deepen, the globalization of insurance and reinsurance industry has become a common phenomenon. That means the insurance policies between countries have lots of interaction and coordination and the insurance and reinsurance industry all over the world may become a whole one.The globalization of the insurance industry has led to a rapid transfer of risk on a global scale. Various risks in the global insurance market re-combine and have greatly changed the operating mode of the global insurance market and risk performance. The globalization of the insurance industry has greatly enhanced the interdependence between the world’s major insurance markets and reinsurance markets. The cooperative motion between the insurance markets makes a local market fluctuations will quickly spread to; other markets. The risks that the company and the government bear are becoming increasingly complex. Along with the worldwide reinsurance market continues to expand, the catastrophe risk also increases with the development trend of the globalization of the insurance industry in the greater scope of the market, with its stronger ability to affect the development of world economy.Accompanied by rapid economic development, more and more stringent requirements for risk analysis are badly needed. The various means of risk analysis used in the early age has been unable to adapt to changes, which also contributed to the innovation of theoretical methods and techniques of statistical analysis, including important breakthrough in the correlation measure indicators. Because of such needs, Copula came into being as a new measurement tool. The function can help with characterizing the relationship between the joint distribution of random variables and their univariate marginal distribution. The portfolio risk is decomposed into multiple marginal risks which can not only help us to solve the financial serial correlation problem, but also help us understand the market structure. Copula function is a flexible, robust analysis tools. It has a lot of advantages in the analysis of the correlation structure between variables. Copula functions will not change under strictly monotonic increment transformation when applied to measure the correlation. Copula will not be affected by the theoretical assumptions of selected marginal distributions.Our paper contributes to the literature in the following ways. First, we investigate the dependence structure between insurance companies’equity returns in three globally disconnected regions (America, Europe, Asia and Australia) to study potential problems for the global reinsurance market brought about by catastrophic losses. Second, in contrast to earlier literature on this subject, we try to disentangle the causes of dependence stemming from the asset side and those from the liability side by conditioning insurers’equity returns on general market conditions. As a measure of dependence, we use both correlation and tail dependence coefficients. Finally, we investigate whether the extremal dependence structure between regions changes over time using the dynamic copula approach and the test for possible breakpoints for copula parameters.To summarize, large insurance losses indeed play the role of the "globalizing" factor, especially for Europe and America. This means that insured losses observed during the last two decades is associated with increased dependence of the geographically distant insurance markets, and thus the scope for international diversification of catastrophic losses is limited. In particular, the most severely affected reinsurance schemes may be retrocession or catastrophe risk swaps. In addition, the increased dependence of geographically distant insurance markets may undermine portfolio diversification benefits of catastrophe bonds, because different issues of such bonds may be subject to increasingly strong dependence, thus limiting their cross-regional diversification benefits. As a possible way to cope with these unfavorable developments, we suggest to look at diversification possibilities in Australasia, which in our analysis revealed the least codependence with the other markets.