本研究探討「美國次級房貸」期間各國股票市場之間是否存在蔓延效果，本
研究採用Engle(2002) 所提出之動態條件相關(DCC) 搭配多變量
AR(1)-GJR-GARCH(1,1)模型估計「與時俱變--條件相關係數」。實證結果顯示美
國對其他國家股票市場存在蔓延效果且條件相關係數顯示為正向。
假如金融市場存在蔓延效果，則風暴期間各國股票市場也會面臨較大之系統
風險，因此本文延伸探討各股票市場之系統風險與下方風險。本文採用三個估計
方式來計算各國之系統風險與下方風險，分別為傳統公式、MV-DGP 架構與
DCC-GARCH(1,1)估計方式。研究結果發現美國、德國、法國與巴西等國存在較
高之系統風險與下方風險。相反地，中國的股票市場存在較低之系統風險與下方
風險，因此提供了投資人與基金經理人避險的投資選擇。最後，本研究結果顯示
採用 DCC-HW 方法所估計之下方系統風險較能俘獲市場投資組合與個別資產之
間的「下方風險」。相對地這是傳統CAPM β 所無法補捉的。

This study tests whether contagion effects existed during the “subprime
mortgage crisis” among the equity markets of the US, the EU, Asia and emerging
markets. The time-varying correlation coefficients are estimated by the dynamic
conditional correlation (DCC) of Engle (2002), using a multivariate GJR-GARCH
with AR (1) model. The empirical findings show that the conditional correlation
coefficients of stock returns between the U.S. and others countries were positive and
that the contagion effect exists among stock markets.
Financial markets displayed contagion effects, in that the global equity markets
were confronted with elevated systematic risk at the same time. Therefore, this study
further examines the role of systematic risk in the equity market of each country. I
used the rolling formulae, the MV-DGP, and DCC-GARCH (1, 1) models to estimate
the CAPM beta and downside betas. This study found higher systematic risk
(downside systematic risk) in the stock markets of the United States, Germany, France
and Brazil, which had beta values nearly above one, while the Chinese stock market
had the lowest systemic risk and served as a hedge for investors and fund managers.
Finally, the results demonstrate that DCC-HW beta can capture some downside
linkages between the market portfolios and expected stock returns, while these
linkages cannot likely be captured by the CAPM beta.

Table of Contents I
List of Figures III
List of Tables IV
摘要 V
Abstract VI

Chapter 1 Introduction 1
1.1 Motivation and contribution in the contagion effect 1
1.2 Motivation and contribution in the systematic risk 6

Chapter 2 Literature Review 10
2.1 Descriptive of Events 10
2.1.1 Subprime mortgage crisis 10
2.1.2 Bankruptcy of Lehman Brothers 12
2.2 Literature related to contagion effects 13
2.2.1 Traditional measures of contagion effects 14
2.2.2 Time-varying measures of contagion effect 16
2.3 Literature related to systematic risk and downside risk 18

Chapter 3 Model Framework and Econometric Methodology 21
3.1 CAPM model (beta) and downside beta 21
3.2 Derivation beta under MV-DGP 24
3.2.1 CAPM beta under MV-DGP 24
3.2.2 HW-beta under MV-DGP 26
3.2.3 HR-beta under MV-DGP 27
3.2.4 E-beta under MV-DGP 29
3.3 GARCH 31
3.3.1 Univariate GARCH 31
3.3.2 GJR-GARCH 33
3.3.3 Multivariate GARCH 35
3.4 Dynamic Conditional Correlation (DCC) 36
3.5 Conditional CAPM beta (Downside betas) 39

Chapter 4 Data and Empirical Results 41
4.1 Data and descriptive statistics 41
4.2 Contagion effect of various countries 51

4.3 Estimating the CAPM beta and downside beta (true beta) 64
4.4 Estimating the MV CAPM beta and MV downside beta 71
4.5 Estimating the DCC CAPM beta and DCC downside beta 77
4.6 Cross-sectional analysis of single factor pricing models 85

Chapter 5 Conclusion 89

Reference 92
Appendix I: Dynamic conditional correlations within countries 100

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