本文關(guān)鍵詞： 波動(dòng)溢出效應(yīng) 風(fēng)險(xiǎn)傳染機(jī)制 杠桿效應(yīng) 動(dòng)態(tài)條件相關(guān) 多元GARCH模型 空間計(jì)量經(jīng)濟(jì)學(xué)　出處：《華中科技大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：隨著經(jīng)濟(jì)全球化進(jìn)程的加速,全球各金融市場(chǎng)間的空間交互作用和波動(dòng)溢出變得愈加強(qiáng)烈和顯著。深入分析各金融市場(chǎng),尤其是各房地產(chǎn)市場(chǎng)間的依賴結(jié)構(gòu)形式和異質(zhì)性特征對(duì)金融專家、監(jiān)管層和學(xué)者均有重要意義。鑒此,多市場(chǎng)間的依賴結(jié)構(gòu)是什么,影響多市場(chǎng)間聯(lián)動(dòng)性的因素有哪些,以及如何刻畫跨市場(chǎng)間的波動(dòng)溢出特征并探究其蘊(yùn)含的風(fēng)險(xiǎn)傳染機(jī)制是當(dāng)前學(xué)術(shù)界研究的熱點(diǎn)和難點(diǎn)。本文在較為系統(tǒng)地梳理和歸納經(jīng)典空間計(jì)量經(jīng)濟(jì)分析技術(shù)和多元GARCH模型在金融市場(chǎng)方面應(yīng)用的文獻(xiàn)的基礎(chǔ)上,以多市場(chǎng)間的聯(lián)動(dòng)現(xiàn)象為出發(fā)點(diǎn),提出兩種新的有效融合空間計(jì)量模型和多元GARCH模型的途徑,進(jìn)而詳細(xì)探討兩種融合模型的結(jié)構(gòu)特征、參數(shù)平穩(wěn)性條件和模型參數(shù)估計(jì)方法,并分別運(yùn)用所提模型深入分析各房地產(chǎn)市場(chǎng)、各股票市場(chǎng)、各外匯市場(chǎng)以及跨市場(chǎng)間的波動(dòng)溢出效應(yīng)形式,進(jìn)一步探究其蘊(yùn)含的風(fēng)險(xiǎn)傳染機(jī)制。首先,本文基于空間DCC-GARCH模型深入探討了全球房地產(chǎn)市場(chǎng)間、全球股票市場(chǎng)間、全球外匯市場(chǎng)間以及跨市場(chǎng)間的價(jià)格聯(lián)動(dòng)性、波動(dòng)溢出效應(yīng)及蘊(yùn)含的風(fēng)險(xiǎn)傳染機(jī)制。研究發(fā)現(xiàn)各個(gè)國(guó)家的房地產(chǎn)市場(chǎng)間、股票市場(chǎng)間、外匯市場(chǎng)間以及跨市場(chǎng)間的動(dòng)態(tài)條件相關(guān)性結(jié)構(gòu)均具有時(shí)變特征。全球房地產(chǎn)市場(chǎng)、股票市場(chǎng)、外匯市場(chǎng)間以及跨市場(chǎng)間存在明顯的波動(dòng)溢出效應(yīng)和風(fēng)險(xiǎn)傳染,但各市場(chǎng)間的風(fēng)險(xiǎn)傳染機(jī)制略有差異。另外,就研究區(qū)域而言,歐洲地區(qū)國(guó)家的金融市場(chǎng)彼此間的聯(lián)動(dòng)強(qiáng)度要強(qiáng)于亞太地區(qū)和拉美地區(qū)國(guó)家的金融市場(chǎng)彼此間的聯(lián)動(dòng)強(qiáng)度。其次,本文基于ARMA (1,1)-GJR-AGARCH (1,1)模型實(shí)證檢驗(yàn)了2007-2009全球金融危機(jī)事件對(duì)全球房地產(chǎn)市場(chǎng)、股票市場(chǎng)和外匯市場(chǎng)間的依賴結(jié)構(gòu)的影響。研究發(fā)現(xiàn)在全球金融危機(jī)階段無論是房地產(chǎn)市場(chǎng),股票市場(chǎng)還是外匯市場(chǎng)的波動(dòng)強(qiáng)度均明顯增大。房地產(chǎn)市場(chǎng)和股票市場(chǎng)中存在顯著的“杠桿效應(yīng)”,而外匯市場(chǎng)卻不存在“杠桿效應(yīng)”。再次,本文探討了美元指數(shù)價(jià)格的波動(dòng)對(duì)各國(guó)的房地產(chǎn)市場(chǎng)、股票市場(chǎng)和外匯市場(chǎng)的影響。實(shí)證結(jié)果表明,美元指數(shù)走強(qiáng)能夠在一定程度上影響上述三個(gè)市場(chǎng)間的動(dòng)態(tài)條件相關(guān)性結(jié)構(gòu)。就房地產(chǎn)市場(chǎng)而言,美元指數(shù)走強(qiáng)會(huì)在一定程度上遏制亞太地區(qū)國(guó)家的房地產(chǎn)市場(chǎng)的價(jià)格的提升,但會(huì)在一定程度上拉升歐洲和拉美地區(qū)的國(guó)家的房地產(chǎn)市場(chǎng)價(jià)格。對(duì)股票市場(chǎng)而言,美元指數(shù)走強(qiáng)會(huì)促使各國(guó)的股票市場(chǎng)指數(shù)價(jià)格的走高,而歐洲和拉美地區(qū)國(guó)家的股票市場(chǎng)似乎與美元指數(shù)間的聯(lián)動(dòng)性更強(qiáng)。對(duì)外匯市場(chǎng)而言,美元指數(shù)與歐元、日元、英鎊等成分股間的聯(lián)動(dòng)強(qiáng)度明顯強(qiáng)于其與非成分股如人民幣、港元和澳元間的聯(lián)動(dòng)強(qiáng)度。此外,本文考慮由兩個(gè)資產(chǎn)所構(gòu)成的最小方差策略和對(duì)沖策略,并采用樣本內(nèi)評(píng)估框架來評(píng)價(jià)策略的有效性。研究結(jié)果表明,兩種投資組合策略均能夠減小投資組合的策略方差,并且兩種策略在金融危機(jī)階段的策略方差要大于非危機(jī)時(shí)期的策略方差。相比傳統(tǒng)模型而言,空間DCC-GARCH模型與傳統(tǒng)模型的差異性并不明顯。本文還發(fā)現(xiàn)最小方差策略更適用于房地產(chǎn)市場(chǎng)和混合資產(chǎn)的投資組合策略的構(gòu)建；而對(duì)沖策略則更適用于股票市場(chǎng)和外匯市場(chǎng)中的資產(chǎn)最優(yōu)配置。最后,本文將動(dòng)態(tài)空間面板數(shù)據(jù)模型和多元GARCH模型加以融合,探討了融合模型的平穩(wěn)性條件及參數(shù)極大似然估計(jì)方法的實(shí)現(xiàn)方式,給出了設(shè)定空間權(quán)重矩陣的相關(guān)準(zhǔn)則,實(shí)證分析了2005-2014年期間我國(guó)各區(qū)域住房市場(chǎng)間的價(jià)格聯(lián)動(dòng)與波動(dòng)溢出效應(yīng)問題。研究結(jié)果表明,地理位置相鄰或者地理位置較遠(yuǎn)但經(jīng)濟(jì)發(fā)展?fàn)顩r相似的區(qū)域住房市場(chǎng)之間存在較強(qiáng)的聯(lián)動(dòng)性和波動(dòng)溢出效應(yīng)�；久嬉蛩厝缛丝凇⑹杖牒蛧�(guó)家宏觀經(jīng)濟(jì)環(huán)境是決定區(qū)域住房市場(chǎng)價(jià)格的重要因素。在國(guó)務(wù)院歷年頒布的房地產(chǎn)市場(chǎng)宏觀調(diào)控政策中,僅有2006年5月頒布的“國(guó)六條”政策對(duì)住房市場(chǎng)回報(bào)和波動(dòng)產(chǎn)生顯著影響,而其他時(shí)期的宏觀調(diào)控政策均未發(fā)現(xiàn)有顯著影響。一線城市和二線城市之間的分化現(xiàn)象自2014年開始變得愈發(fā)明顯。此外,我國(guó)各區(qū)域住房市場(chǎng)中存在較強(qiáng)的“杠桿效應(yīng)”,其存在說明投資者對(duì)住房市場(chǎng)利空消息的反應(yīng)程度要大于利好消息的反應(yīng)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.

【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：F299.1;F831.51;F224
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本文編號(hào)：1447971