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研究生： 張家璇
Chang, Chia-Hsuan
論文名稱： Importance Sampling Estimation of Loss Density Function under Structural-Form Models
在結構式模型下以重點抽樣法估計損失密度函數
指導教授： 韓傳祥
Han, Chung-Hsiang
口試委員:
學位類別： 碩士
Master
系所名稱： 科技管理學院 - 計量財務金融學系
Department of Quantitative Finance
論文出版年： 2009
畢業學年度： 97
語文別： 英文
論文頁數： 52
中文關鍵詞： 重點抽樣法 、損失密度函數 、結構式模型 、信用違約交換
外文關鍵詞： Efficient Importance sampling, Loss density function, Structural form model, Credit default swap
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    • The loss density function is useful for pricing credit derivatives and risk management of credit portfolio. The loss density function concludes estimating the joint default probability and survival probability. Under the structural-form model, computation of the loss density function relies on the estimates of some mixture of joint default probability and joint survival probability. We provide several efficient importance sampling methods to estimate the probability of defaultable and/or survival event. We also provide an empirical study of a correlated hedging for CDS spread.

    1 Introduction and Problem Formulation 1.1 Loss Density Function Estimation 2 Structural-Form Models 2.1 Compound Poisson Process} 2.2 Jump-Diffusion Model 2.3 Probability of Default 2.3.1 Default at Maturity 2.3.2 Default before Maturity: First-Passage Time Problem 3 Variance Reduction Method 3.1 Monte Carlo Simulations 3.2 Importance Sampling 4 Importance Sampling and Its Efficiency 4.1 Efficient Importance Sampling on Diffusion model 4.1.1 Default Probability 4.1.2 Survival Probability 4.2 Efficient Importance Sampling on Jump-Diffusion Model 5 Numerical Results 5.1 Single-Name Case 5.1.1 Diffusion Model: Default Probability 5.1.2 Diffusion Model: Survival Probability 5.1.3 Jump Diffusion Model: First-Passage Time Problem 5.2 Multi-Dimension 5.2.1 Diffusion Model: Default Probability 5.2.2 Diffusion Model: Survival Probability 5.2.3 Jump Diffusion Model: First-Passage Time Problem 6 Loss Density Function 6.1 Diffusion model 6.2 Jump Diffusion Model 7 Hedging Credit Derivative

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