有實證研究表明，傳統的信貸風險結構模型顯著低估了違約概率以及信貸收益率差。傳統的結構模型有三個可能的問題：1. 因為正態假設，布朗模型在模擬公司資產價值的過程中未能捕捉到極端事件2. 市場微觀結構噪聲扭曲了股票價格所包含信息3. 在到期日前任何時間，標準BS 期權理論方法不足以描述任何破產的可能性。這些問題在過去的文獻中曾分別提及。而在本文中，在不同的信用風險結構模型的基礎上，我們提出了貝葉斯方法去估算公司價值的跳躍擴散過程和微觀結構噪聲。因為企業的資產淨值不能在市場上觀察，本文建議的貝葉斯方法可對隱藏變量和泊松衝擊作出一定的估算，並就後驗分佈進行財務分析。我們應用馬爾可夫鏈蒙特卡羅方法（MCMC）和吉布斯採樣計算每個參數的後驗分佈。以上的做法，允許我們檢查結構性信用風險模型的偏差主要是來自公司價值的分佈、期權理論方法或市場微觀結構噪聲。我們進行模擬研究以確定模型的表現。最後，我們以新興市場的數據實踐我們的模型。 / There is empirical evidence that structural models of credit risk significantly underestimate both the probability of default and credit yield spreads. There are three potential sources of the problems in traditional structural models. First, the Brownian model driving the firm asset value process may fail to capture extreme events because of the normality assumption. Second, the market micro-structure noise in trading may distort the information contained in equity prices within the estimation process. Third, the standard Black and Scholes option-theoretic approach may be inadequate to describe the consequences of bankruptcy at any time before maturity. These potential problems have been handled separately in the literature. In this paper, we propose a Bayesian approach to simultaneously estimate the jump-diffusion firm value process and micro-structure noise from equity prices based on different structural credit risk models. As the firm asset value is not observable but the equity price is, the proposed Bayesian approach is useful in the estimation with hidden variable and Poisson shocks, and produces posterior distributions for financial analysis. We demonstrate the application using the Markov chain Monte Carlo (MCMC) method to obtain the posterior distributions of parameters and latent variable. The proposed approach enables us to check whether the bias of the structural credit risk model is mainly caused by the firm value distribution, the option-theoretic method or the micro-structure noise of the market. A simulation study is conducted to ascertain the performance of our model. We also apply our model to the emerging market data. / Detailed summary in vernacular field only. / Chan, Sau Lung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 62-65). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / List of Tables --- p.vii / List of Figures --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background and Intuition --- p.5 / Chapter 2.1 --- Merton Model with Trading Noise --- p.7 / Chapter 2.2 --- Black-Cox Model with Default Barrier --- p.10 / Chapter 2.3 --- Double Exponential Jump Diffusion Model (KJD Model) --- p.11 / Chapter 2.4 --- Equity Value via Laplace Transforms --- p.13 / Chapter 2.5 --- KJD Model with Trading Noises --- p.15 / Chapter 3 --- Bayesian Analysis --- p.17 / Chapter 3.1 --- Gibbs Sampling and Metropolis-Hastings Method --- p.17 / Chapter 3.2 --- Merton Model with Trading Noises (M1) --- p.19 / Chapter 3.2.1 --- Prior Distribution for M1 --- p.19 / Chapter 3.2.2 --- Posterior Distribution for M1 --- p.20 / Chapter 3.3 --- Merton Model with Default Barrier (M2) --- p.22 / Chapter 3.3.1 --- Prior Distribution for M2 --- p.23 / Chapter 3.3.2 --- Posterior Distribution for M2 --- p.23 / Chapter 3.4 --- KJD Model with Trading Noises (M3) --- p.25 / Chapter 3.4.1 --- Prior Distribution for M3 --- p.26 / Chapter 3.4.2 --- Posterior Distribution for M3 --- p.27 / Chapter 3.5 --- KJD Model with Default Barrier (M4) --- p.33 / Chapter 3.5.1 --- Prior Distribution for M4 --- p.34 / Chapter 3.5.2 --- Posterior Distribution for M4 --- p.35 / Chapter 4 --- Numerical Examples --- p.42 / Chapter 4.1 --- Simulation Analysis --- p.42 / Chapter 4.2 --- Empirical Study --- p.46 / Chapter 4.2.1 --- BEA and DBS, 2003-2004 --- p.46 / Chapter 4.2.2 --- HSBC, 2008-2009 --- p.49 / Chapter 5 --- Conclusion --- p.60 / Bibliography --- p.62
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328092 |
| Date | January 2013 |
| Contributors | Chan, Sau Lung., Chinese University of Hong Kong Graduate School. Division of Risk Management Science. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (viii, 65 leaves) : ill. (some col.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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