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This paper compares solvency capital requirements under Solvency I and Solvency II for a sample mid-size insurance portfolio. According to the results of a study, changing the solvency capital regime from Solvency I to Solvency II will lead to a substantial additional solvency capital requirement that might represent a heavy burden for the company's shareholders. One way to reduce the capital requirement under Solvency II is to increase reinsurance protection, which will reduce the net retained risk exposure and hence also the solvency capital requirement. Therefore, this paper proposes an extended reinsurance structure that, under Solvency II, brings the capital requirement back to the level of that required under Solvency I. In a step-by-step approach, the paper demonstrates the extent of solvency relief attained by the insurer by applying different possible adjustments in the reinsurance structure. To evaluate the efficiency of reinsurance as the solvency capital relief instrument, the authors introduce a cost-of-capital based approach, which puts the achieved capital relief in relation to the costs of extending the reinsurance protection. This approach allows a direct comparison of reinsurance as a capital relief instrument with debt instruments available in the capital market. With the help of the introduced approach, the authors show that the best capital relief efficiency under all examined reinsurance alternatives is achieved when a financial quota share contract is chosen for proportional reinsurance.
Banking Law --- Capital Requirement --- Debt Markets --- Finance and Financial Sector Development --- Hazard Risk Management --- Insurance & Risk Mitigation --- Insurance Law --- Insurance Portfolio --- Non-Life --- Private Sector Development --- Reinsurance --- Risk Management --- Solvency I --- Solvency II
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The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050. Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.
Stocks --- Financial crises --- Prices --- History. --- United States. --- Asia. --- Black Monday. --- Dow Jones Industrial Average. --- Hong Kong. --- Latin America. --- Louis Bachelier. --- Nasdaq index. --- Nasdaq. --- Nikkei. --- Russia. --- South Sea bubble. --- anti-imitation. --- antibubble. --- arbitrage opportunities. --- bubble. --- collapse. --- complex systems. --- computational methods. --- cooperative behavior. --- cooperative speculation. --- crash hazard. --- currency crash. --- derivatives. --- discrete scale invariance. --- drawdown. --- efficient market. --- emergent markets. --- extreme events. --- financial crashes. --- finite-time singularity. --- forward prediction. --- fractals. --- free lunch. --- gold. --- hazard rate. --- hedging. --- herding. --- imitation. --- insurance portfolio. --- log-periodicity. --- market failure. --- natural scientists. --- outlier. --- population dynamics. --- positive feedback. --- power law. --- prediction. --- price-driven model. --- random walk. --- rational agent. --- renormalization group. --- returns. --- risk-driven model. --- risk. --- self-organization. --- self-similarity. --- social network. --- social scientists. --- speculative bubble. --- stock market crash. --- stock market indices. --- stock market prices. --- stock market. --- superhumans. --- sustainability. --- tronics boom. --- tulip mania. --- world economy.
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