本文選題：資產(chǎn)價格跳躍 + 市場微觀結(jié)構(gòu)�。� 參考：《天津大學(xué)》2012年博士論文

【摘要】：隨著資產(chǎn)價格行為研究的精細化和微觀化，資產(chǎn)價格跳躍行為已成為市場微觀結(jié)構(gòu)等金融研究領(lǐng)域的重點和難點問題之一。跳躍行為的研究深刻揭示了金融市場資產(chǎn)價格發(fā)現(xiàn)過程的微觀機理，直接影響資產(chǎn)價格波動率的估計和預(yù)測，繼而促使傳統(tǒng)的金融理論和計量方法必須進行深刻調(diào)整，并構(gòu)成資產(chǎn)動態(tài)配置、風險管理和金融衍生產(chǎn)品定價等諸多金融實踐領(lǐng)域的核心環(huán)節(jié)。在中國證券市場跳躍頻發(fā)的背景下，本文基于證券市場微觀結(jié)構(gòu)理論視角，沿用“已實現(xiàn)”波動理論的主流研究框架，對資產(chǎn)價格跳躍行為進行了系統(tǒng)全面的理論和實證研究。具體內(nèi)容如下： 1、跳躍行為的非參數(shù)辨識方法研究�；贐NS跳躍辨識理論框架，系統(tǒng)刻畫了中國證券市場跳躍行為分布特征，包括對跳躍頻度、久期、強度、方向、時刻分布、指數(shù)關(guān)聯(lián)性、波動貢獻等問題的完整討論，，初步研究了剝離跳躍性收益的日間收益率分布特征。得到結(jié)論：中國證券市場跳躍頻發(fā)，個股跳躍行為與市場整體狀態(tài)關(guān)聯(lián)緊密，不同方向的跳躍行為對日間收益率分布的作用機制存在顯著的差異，剝離跳躍性收益的日間收益率序列的平穩(wěn)性得到了明顯加強。 2、基于信息沖擊和流動性沖擊的跳躍行為引發(fā)機制研究。首先對跳躍前后非對稱信息與流動性分布特征進行了深入的刻畫，在此基礎(chǔ)上，構(gòu)建了結(jié)合信息沖擊和流動性沖擊的Probit模型，對不同類型股票跳躍行為的引發(fā)機制進行研究。實證結(jié)果表明，單一因素無法對跳躍行為產(chǎn)生的原因進行完整詮釋，并且對于不同類型股票，信息與流動性沖擊的作用模式也是不盡相同的。 3、基于跳躍行為的波動率預(yù)測研究。首先在傳統(tǒng)的HAR RV模型的基礎(chǔ)上發(fā)展了具有方向性變差以及杠桿效應(yīng)特征的HAR RS Leverage_(RV)模型，研究其對預(yù)期波動的作用機制。進一步，基于“已實現(xiàn)”半方差理論定義了方向性跳躍變差的概念，發(fā)展并構(gòu)造了HAR-RV-C△J-Leverage_(C,J)模型，分析方向性跳躍變差與連續(xù)性變差以及杠桿效應(yīng)因子對預(yù)期波動的作用機理。實證結(jié)果表明，HAR-RS-Leverage_(RV)模型適用于長期波動的預(yù)測，HAR-RV-C△J-Leverage_(C,J)模型對短期波動具有更好的預(yù)測效果。 4、基于有效波動率的市場一般性風險測度研究。首先依據(jù)魯棒跳躍波動率medRV估計量，給出了有效波動率的定義并構(gòu)建了有效波動率預(yù)測模型ARFIMA medR。V蒙特卡洛模擬實驗得出結(jié)論：有效波動率估計量medRV能較好的魯棒跳躍行為，能顯著提高對波動率預(yù)測的準確程度。在此基礎(chǔ)上進一步構(gòu)造了市場一般性風險測度VaR medRV，實證研究表明： 能有效摒除市場跳躍風險因子，對市場一般性風險進行有效測度。 5、證券市場跳躍性風險問題研究。首先對“已實現(xiàn)”貝塔系數(shù)β、“已實現(xiàn)”離散貝塔系數(shù)β~d、“已實現(xiàn)”連續(xù)貝塔系數(shù)β~c的分布特征及其內(nèi)在關(guān)系展開了理論和實證研究，以此構(gòu)成對市場跳躍風險系統(tǒng)性成分研究的技術(shù)基礎(chǔ)；進一步，從資產(chǎn)收益的不確定性角度構(gòu)造了市場日內(nèi)跳躍風險測度，對中國證券市場不同類型資產(chǎn)在不同市場狀態(tài)下的跳躍風險分布特征進行刻畫，揭示了中國證券市場跳躍風險存在的系統(tǒng)性問題，并從價格發(fā)現(xiàn)與投資者行為角度對實證結(jié)果的市場根源進行了深入討論。
[Abstract]:With the refinement and microrefinement of the research on asset price behavior, asset price jumping has become one of the key and difficult problems in the field of financial research, such as market microstructures. The study of jumping behavior profoundly reveals the microscopic mechanism of the asset price discovery process in the financial market, and directly affects the estimation and prediction of the volatility of asset prices. Then the traditional financial theory and measurement methods must be deeply adjusted, and the core links in many financial practice fields, such as the dynamic allocation of assets, risk management and the pricing of financial derivatives, have been used in the context of the securities market micro structure theory. The mainstream research framework of wave theory conducts a systematic and comprehensive theoretical and Empirical Study of asset price jump behavior.
1, study on the nonparametric identification method of jumping behavior. Based on the BNS jump identification theory framework, this paper systematically depicts the distribution characteristics of jumping behavior in China's securities market, including the complete discussion of jumping frequency, duration, intensity, direction, time distribution, exponential correlation, volatility contribution and so on, and preliminarily studies the daytime income of jumping income. It is concluded that the jump behavior of China's securities market is frequent, the jump behavior of the stock market is closely related to the overall state of the market. There is a significant difference in the mechanism of the interaction between different directions of jumping behavior on the distribution of daytime yield, and the smoothness of the daily yield sequence of peeling jumping income has been obviously strengthened.
2, the mechanism of jumping behavior based on the impact of information shock and liquidity shock is studied. First, the asymmetric information and the characteristics of the liquidity distribution before and after jumping are deeply depicted. On this basis, a Probit model combining information shock and liquidity shock is constructed, and the trigger mechanism of the jump behavior of different types of stocks is studied. The results show that the single factor can not complete the interpretation of the causes of jumping, and the modes of action of information and liquidity impact are not the same for different types of stocks.
3, the study of Volatility Prediction Based on jumping behavior. Firstly, based on the traditional HAR RV model, the HAR RS Leverage_ (RV) model with directional variation and leveraging effect is developed to study the mechanism of its effect on expected fluctuation. The HAR-RV-C Delta J-Leverage_ (C, J) model is developed and constructed to analyze the mechanism of the variation of directional jump and continuity and the effect of leveraged effect factors on expected fluctuation. The empirical results show that the HAR-RS-Leverage_ (RV) model is suitable for the prediction of long term fluctuations, and the HAR-RV-C Delta J-Leverage_ (C, J) model has a better prediction for short-term fluctuations. Effect.
4, based on the effective volatility of the market general risk measurement research. First, based on the robust jump volatility medRV estimates, the effective volatility is defined and the effective Volatility Prediction Model ARFIMA medR.V Monte Carlo simulation experiment results are concluded that the effective volatility estimation medRV can be better robust jumping behavior, can be shown to be significant. In order to improve the accuracy of Volatility Prediction, a general risk measure VaR medRV is further constructed.
It can effectively eliminate market jumping risk factors and effectively measure the general market risks.
5, the study of the jump risk in the securities market. First, the theoretical and empirical research on the "realized" beta coefficient beta, the "realized" beta coefficient beta ~d, the distribution characteristics of the "realized" beta coefficient beta ~c and its intrinsic relationship are carried out to form the technical basis for the systematic study of the market jump risk. Step, the market jump risk measure is constructed from the uncertainty of asset income, and the leaping risk distribution characteristics of different types of assets in different market states are depicted. The systematic problems of jumping risk in China's securities market are revealed, and the empirical analysis is made from the perspective of price discovery and investor behavior. The market roots of the results were discussed in depth.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2012
【分類號】：F224;F832.51

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