房地产市场波动溢出效应与风险传染机制研究

发布时间：2018-01-20 11:08

  本文关键词： 波动溢出效应 风险传染机制 杠杆效应 动态条件相关 多元GARCH模型 空间计量经济学　出处：《华中科技大学》2016年博士论文　论文类型：学位论文

【摘要】：随着经济全球化进程的加速,全球各金融市场间的空间交互作用和波动溢出变得愈加强烈和显著。深入分析各金融市场,尤其是各房地产市场间的依赖结构形式和异质性特征对金融专家、监管层和学者均有重要意义。鉴此,多市场间的依赖结构是什么,影响多市场间联动性的因素有哪些,以及如何刻画跨市场间的波动溢出特征并探究其蕴含的风险传染机制是当前学术界研究的热点和难点。本文在较为系统地梳理和归纳经典空间计量经济分析技术和多元GARCH模型在金融市场方面应用的文献的基础上,以多市场间的联动现象为出发点,提出两种新的有效融合空间计量模型和多元GARCH模型的途径,进而详细探讨两种融合模型的结构特征、参数平稳性条件和模型参数估计方法,并分别运用所提模型深入分析各房地产市场、各股票市场、各外汇市场以及跨市场间的波动溢出效应形式,进一步探究其蕴含的风险传染机制。首先,本文基于空间DCC-GARCH模型深入探讨了全球房地产市场间、全球股票市场间、全球外汇市场间以及跨市场间的价格联动性、波动溢出效应及蕴含的风险传染机制。研究发现各个国家的房地产市场间、股票市场间、外汇市场间以及跨市场间的动态条件相关性结构均具有时变特征。全球房地产市场、股票市场、外汇市场间以及跨市场间存在明显的波动溢出效应和风险传染,但各市场间的风险传染机制略有差异。另外,就研究区域而言,欧洲地区国家的金融市场彼此间的联动强度要强于亚太地区和拉美地区国家的金融市场彼此间的联动强度。其次,本文基于ARMA (1,1)-GJR-AGARCH (1,1)模型实证检验了2007-2009全球金融危机事件对全球房地产市场、股票市场和外汇市场间的依赖结构的影响。研究发现在全球金融危机阶段无论是房地产市场,股票市场还是外汇市场的波动强度均明显增大。房地产市场和股票市场中存在显著的“杠杆效应”,而外汇市场却不存在“杠杆效应”。再次,本文探讨了美元指数价格的波动对各国的房地产市场、股票市场和外汇市场的影响。实证结果表明,美元指数走强能够在一定程度上影响上述三个市场间的动态条件相关性结构。就房地产市场而言,美元指数走强会在一定程度上遏制亚太地区国家的房地产市场的价格的提升,但会在一定程度上拉升欧洲和拉美地区的国家的房地产市场价格。对股票市场而言,美元指数走强会促使各国的股票市场指数价格的走高,而欧洲和拉美地区国家的股票市场似乎与美元指数间的联动性更强。对外汇市场而言,美元指数与欧元、日元、英镑等成分股间的联动强度明显强于其与非成分股如人民币、港元和澳元间的联动强度。此外,本文考虑由两个资产所构成的最小方差策略和对冲策略,并采用样本内评估框架来评价策略的有效性。研究结果表明,两种投资组合策略均能够减小投资组合的策略方差,并且两种策略在金融危机阶段的策略方差要大于非危机时期的策略方差。相比传统模型而言,空间DCC-GARCH模型与传统模型的差异性并不明显。本文还发现最小方差策略更适用于房地产市场和混合资产的投资组合策略的构建；而对冲策略则更适用于股票市场和外汇市场中的资产最优配置。最后,本文将动态空间面板数据模型和多元GARCH模型加以融合,探讨了融合模型的平稳性条件及参数极大似然估计方法的实现方式,给出了设定空间权重矩阵的相关准则,实证分析了2005-2014年期间我国各区域住房市场间的价格联动与波动溢出效应问题。研究结果表明,地理位置相邻或者地理位置较远但经济发展状况相似的区域住房市场之间存在较强的联动性和波动溢出效应。基本面因素如人口、收入和国家宏观经济环境是决定区域住房市场价格的重要因素。在国务院历年颁布的房地产市场宏观调控政策中,仅有2006年5月颁布的“国六条”政策对住房市场回报和波动产生显著影响,而其他时期的宏观调控政策均未发现有显著影响。一线城市和二线城市之间的分化现象自2014年开始变得愈发明显。此外,我国各区域住房市场中存在较强的“杠杆效应”,其存在说明投资者对住房市场利空消息的反应程度要大于利好消息的反应程度。
[Abstract]:With the acceleration of economic globalization and world financial markets between spatial interaction and volatility spillover become more intense and significant. The thorough analysis of the financial market, especially the real estate market between the dependent structure and heterogeneity of financial experts, regulators and academics have important significance. In view of this, what is the dependence the structure of multi market, what are the factors that influence the market linkage between the cross and how to describe the characteristics of the market volatility spillover between and explore its risk contagion mechanism is the focus of academic research and difficult point. This paper analysis and multivariate GARCH model in the financial market literature in a system to sort out and summarize the classical spatial econometrics, the linkage between phenomenon in the multi market as the starting point, this paper proposes two new effective integration of spatial econometric models and multivariate GARCH The model approach, and a detailed discussion of two kinds of fusion model structure, parameter estimation method of stationary conditions and model parameters, and then use the model to analyze the real estate market, the stock market, the foreign exchange market and cross market volatility spillover effect, further explore its inherent mechanism of risk contagion. First, this paper discusses the spatial DCC-GARCH model based on the global real estate market, the global stock market, the global foreign exchange market and cross market between the price linkage, the volatility spillover effect and risk contagion mechanism. The study found that each country's real estate market, stock market, foreign exchange market and dynamic conditions cross market correlation between structure of time-varying characteristics. The global real estate market, stock market, volatility spillover exists obviously between foreign exchange market and cross market Effect and risk of infection, but the market risk contagion mechanism is slightly different. In addition, the research area, the strength between the strength of linkage linkage between European countries stronger financial markets in countries in the Asia Pacific region and Latin America financial market. Secondly, based on the ARMA (1,1) -GJR-AGARCH (1,1) model the empirical test of the 2007-2009 global financial crisis events on the global real estate market, affect the dependency structure of the stock market and foreign exchange market. The study found that in the stage of the global financial crisis, whether the real estate market, stock market and foreign exchange market volatility intensity were significantly increased. The real estate market and the stock market there is a significant "leverage effect" but the foreign exchange market does not exist leverage effect. Thirdly, this paper discusses the volatility of the dollar index price of the real estate market, the stock market and The impact of foreign exchange market. The empirical results show that the dollar index can affect the structure of the dynamic conditional correlation between the three markets to a certain extent. On the real estate market, the U.S. dollar index will curb the countries of the Asia Pacific region of the real estate market to a certain extent, the price increase, but will move up in Europe and Latin America the countries of the region's real estate market prices to a certain extent. On the stock market, the dollar index index of stock market prices will lead to the strong rise, and a stronger linkage between countries in Europe and Latin America stock market and the dollar index seems to be between. On the foreign exchange market, the dollar index and the euro, yen the strength of sterling, the linkage between stocks was stronger than its non stocks such as the renminbi, Hong Kong dollar and Australian dollar strength linkage between. In addition, we consider consists of two minimum assets Variance strategy and hedging strategy, and the sample evaluation framework to evaluate the effectiveness of the strategy. The results show that the two strategy variance portfolio strategy can reduce the portfolio strategy, and variance in the phase of the financial crisis two strategies should be greater than the variance of non crisis period strategy. Compared with the traditional model, difference the spatial DCC-GARCH model and traditional model is not obvious. This paper also finds that the construction of the portfolio strategy of minimum variance strategy is more suitable for the real estate market and mixed assets; while the hedging strategy is more suitable for optimal asset allocation in the stock market and foreign exchange market. Finally, the dynamic spatial panel data model and multiple GARCH the model integrates them, discusses the maximum likelihood stationary condition fusion model and parameter estimation methods to achieve, given the spatial weight matrix. Close the criterion, an empirical analysis of the price linkage and the volatility spillover effect between China's regional housing market during the period of 2005-2014. The results show that the geographic location or adjacent geographical distance but between economic development regions similar to the housing market there is a strong combination of liquidity and volatility spillover effect. The fundamental factors such as population. The macro economic environment and national income is an important factor in determining regional housing market prices. The State Council promulgated the macro-control policy in real estate market, only in May 2006 promulgated the "six countries" policies of the housing market returns and volatility have a significant impact, and other periods of macro-control policies were not found to have a significant impact. Differentiation between first-tier cities and second tier city began to become increasingly obvious since 2014. In addition, there is a strong bar regional housing market in China The existence of rod effect indicates that the extent to which investors respond to the niche news of the housing market is greater than the degree of good news.

【学位授予单位】：华中科技大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F299.1;F831.51;F224
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本文编号：1447971