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An Empirical Study on the Solvency Prediction of Simulation Analysis, Scenario Analysis, and Risk-based Capital

風險基礎資本、情境分析及動態模擬破產預測模型之比較

摘要


保險公司的清償能力一向是保險監理的重心,而所有現行的制度中,風險基礎資本是監理上的一項重要工具。可是文獻指出動態現金流量分析模型相較於風險基礎資本能提供較佳的破產預測能力。有鑑於此,本文以模擬方式加上經濟模型來分析風險基礎資本、情境分析及模擬分析等方法對破產預測的精確性,其中風險基礎資本之資料來自於美國保險監理委員會的年報資料,情境分析及模擬分析則利用我們所設定的模型。我們的結果發現情境分析與模擬分析的預測能力皆優於風險基礎資本,且前二者之預測能力相近的原因可歸因於採用相同的模擬模型。

並列摘要


The solvency of the insurance company is the focal point of insurance regulation. One prevalent way to safeguard the insurer's financial strength is setting capital requirement. Although capital requirements have been transformed from constant ones to risk-based capital requirement (RBC), the literature finds that RBC is rather ineffective in rendering early warning. The literature to date further shows that scenario analysis done with dynamic cash flow models generates the best predicting results. Since a natural extension of scenario analysis is simulation analysis, this paper aims to investigate the effectiveness of simulation analysis in solvency/insolvency predictions. We find that simulation analysis as well as scenario analysis does dominate RBC in correctly classifying insurers' financial conditions. However, simulation analysis outperforms scenario analysis only by small or insignificant margins. Such a tie mainly results from the use of the same cash flow model.

參考文獻


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