코풀라 이론의 금융위험 관리 적용 : 중국 상하이 증권거래소 : A주중심으로 = Application of Copula Theory to Financial Risk Control with Multivariate Financial Time Series Analysis in Chinese Security Market: The Case of SSE A-Shares

국문 초록 (Abstract)

요약
지난 30년 간 국제금융시장은 경제 세계화와 같은 거대한 변화를 겪었다. 이러한 변화는 급격한 경제 개발과 함께 국제시장과 국내시장 간 상호 연결하는 금융 혁신이 점점 더 이루어졌다 . 또한 복잡한 시장의 관계가 통화 시장의 변동성을 부추겼고 금융 위험을 증가시켰다. 상관분석은 포트폴리오 분석 투자, 자산 가격 결정, 부작용, 금융 위험 관리가 긴밀하게 연결되는 금융 연구 분야에서 중요한 역할을 한다.

GARCH 와 벡터 SV 모델은 금융시장의 상관관계분석에 사용될 수 있다. 그러나 파라미터 추정과 같이 해결해야 할 많은 문제들이 여전히 있다. 코풀라는 효과적인 상관분석과 다변량 통계 도구로써 비선형 변수와 비대칭 상관관계, 특히 테일 상관관계를 인해 발생한 문제를 잘 해결할 수 있다. 금융위기는 위험 관리 분야에서 중요한 문제이다. 따라서 다양한 변동성 수준을 가지는 금융시장을 잘 파악할 수 있는 코풀라 모델로 진행된 심층적 연구가 필요하다.

다국어 초록 (Multilingual Abstract)

Abstract
During the past three decades, international financial markets have undergone tremendous changes such as economic globalization. With the rapid development of economy, there has been more and more financial innovation which deep the interconnection between international and domestic market, consequently more and more complex markets’ correlations heighten monetary markets’ volatilities and increase financial risk. Correlation analysis plays an important role in financial studying field, which is closely related to investment portfolio analysis, asset pricing, spillover effect, and financial risk management.
The GARCH and Vector SV models can be used in financial markets’ correlation analysis, but there are still many problems needed to be solved such as parameters estimation. As an efficient correlation analysis and multivariate statistics tool, Copula can accurately capture variables’ nonlinear and asymmetric correlation, especially the tail correlation. Financial crisis cognation is an important problem in risk management field, which is deserved deep research through by adopting Copula model to capture the movements of financial markets under different volatility levels.

목차 (Table of Contents)

• Chapter 1 Introduction 1
• 1.1 Research Background 1
• 1.1.1 Rapid development of international financial market 1
• 1.1.2 Significance of Econometrics Theory 2
• 1.1.3 Development of Econometrics and Financial Volatility Model 2
• 1.2 Problem Introduction 5
• 1.2.1 Limitations of Correlation Coefficient and Traditional Analysis Methods 5
• 1.2.2 Copula Theory 6
• 1.2.3 Correlation Analysis and Modeling Research of Multivariate Time Series Based on Copula Theory 7
• 1.2.4 Application of Copula Model in Financial Risk Management 7
• 1.3 Structure of Thesis 8
• Chapter 2 Copula Theory and Copula’s Application in Analytical Finance 9
• 2.1 Brief Introduction of Copula Function 9
• 2.2 Construction of Copula Model 11
• 2.2.1 Marginal Distribution of Financial Time Series 11
• 2.2.2 Copula Function and Correlation Analysis 15
• 2.3 Multivariate Financial Time Series Model Based on Copula Theory 23
• 2.4 Chapter Summary 26
• Chapter 3 Application of Copula Model in Financial Risk Management 26
• 3.1 Asset Portfolio Simulation and VaR Calculation 27
• 3.1.1 Selection of Asset Portfolio and VaR Risk Model 27
• 3.1.2 Simulation and VaR Calculation of A portfolio with Two Assets 28
• 3.1.3 Simulation and VaR Calculation of A portfolio with Multi Assets 31
• 3.2 Copula Model and Financial Market Contagion Analysis 34
• 3.2.1 Financial Market Contagion Effects 34
• 3.2.2 Application of Copula Model in Financial Contagion Analysis 35
• 3.3 Empirical Research 37
• 3.3.1 Selection of Samples and Copula Model 37
• 3.3.2 Estimated Results of Copula Model 37
• 3.3.3 Selection and VaR Calculation of Investment Portfolio 39
• 3.4 Chapter Summary 45
• Chapter 4 Summary and Prospect 46
• 4.1 Summaries of the Thesis 46
• 4.1.1 Copula Theory and Application Review 46
• 4.1.2 Research on Multivariate Financial Time Series’ Modeling Based on Copula Theory 47
• 4.1.3 Research on Copula Model’s Application in Financial Risk Management 47
• 4.2 Research Prospect 47
• 4.2.1 Further Research and Application of Copula-SV Model 47
• 4.2.2 Further Research on Leverage Effect of SV-Cpula in Financial Market 48
• 4.2.3 Further Research on Multivariate and Dynamic Copula Model 48
• 4.2.4 Other Problems 49
• 4.3 Conclusion 49
• References: 50
• Abstract 52