發(fā)布時(shí)間：2018-01-02 18:00

  本文關(guān)鍵詞：超高頻期貨市場微觀結(jié)構(gòu)噪音實(shí)證研究　出處：《西南財(cái)經(jīng)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 期貨市場 微觀結(jié)構(gòu) 微觀結(jié)構(gòu)噪音 超高頻數(shù)據(jù) 已實(shí)現(xiàn)波動率(RV) 二尺度已實(shí)現(xiàn)波動率(TSRV)

【摘要】：期貨市場是金融市場和國民經(jīng)濟(jì)的重要組成部分,具有價(jià)格發(fā)現(xiàn)和套期保值兩大重要功能。不僅對股票市場、外匯市場等其他虛擬經(jīng)濟(jì)有巨大的影響,也與現(xiàn)貨市場直接關(guān)聯(lián),調(diào)控著實(shí)體經(jīng)濟(jì)的運(yùn)行。隨著近年來國際貿(mào)易和經(jīng)濟(jì)一體化的迅猛發(fā)展,期貨市場跨越國界配置資源的作用越發(fā)顯現(xiàn),成為搶奪國際資源定價(jià)權(quán)和話語權(quán)的重要陣地。期貨市場的地位在不斷增強(qiáng)。 因此,理解和研究我國期貨市場的微觀結(jié)構(gòu)及其運(yùn)作方式,對于揭示我國期貨產(chǎn)品價(jià)格形成規(guī)律,理解期貨市場波動率有重要的意義。認(rèn)識市場微觀構(gòu)件如何影響市場價(jià)格變動趨勢,可以直接運(yùn)用到實(shí)際期貨產(chǎn)品投資實(shí)踐,有助于我們評價(jià)期貨市場質(zhì)量和效率,促使我國期貨市場交易制度、規(guī)則的完善。 市場微觀結(jié)構(gòu)理論的出現(xiàn)和發(fā)展,為深入理解和研究期貨市場微觀結(jié)構(gòu)提供了方法和手段。莫琳·奧哈拉將市場微觀結(jié)構(gòu)的研究界定為“研究確定交易規(guī)則下資產(chǎn)交易的過程和結(jié)果”。強(qiáng)調(diào)從確定的交易機(jī)制之下的規(guī)則出發(fā),來分析價(jià)格決定過程。麥德哈文(Ananth Madhavan,2000)將市場微觀結(jié)構(gòu)定義為“一個(gè)研究投資者潛在的交易需求轉(zhuǎn)化為最終交易價(jià)格和交易量過程的金融學(xué)領(lǐng)域”。關(guān)注交易機(jī)制本身對價(jià)格形成的影響,是市場微觀結(jié)構(gòu)研究的一大特點(diǎn)。 微觀結(jié)構(gòu)噪音的相關(guān)研究正是這樣的背景提出和發(fā)展的。根據(jù)市場微觀結(jié)構(gòu)的相關(guān)理論,現(xiàn)實(shí)市場不同于完美信息市場,存在著交易成本、信息不對稱等市場摩擦,證券價(jià)格在交易過程會受到這些摩擦因素的影響而偏離完美市場下資產(chǎn)的均衡價(jià)格。在交易過程中導(dǎo)致證券價(jià)格偏離均衡價(jià)格的因素的總和即為微觀結(jié)構(gòu)噪音。微觀結(jié)構(gòu)噪音是產(chǎn)生于交易過程的一系列市場摩擦,包括買賣價(jià)差、價(jià)格的離散變化、非同步交易、信息不對稱、市場對大宗交易的逐漸反應(yīng)、訂單流的策略成分、市場參與者的流動性需要、市場參與者存貨控制效應(yīng)等。 高頻數(shù)據(jù)和超高頻數(shù)據(jù)記錄了市場所有的交易信息,其運(yùn)用促進(jìn)了微觀結(jié)構(gòu)噪音的研究,也為深入研究我國期貨市場提供了重要的實(shí)證數(shù)據(jù)。 傳統(tǒng)的資產(chǎn)價(jià)格波動研究主要以低頻數(shù)據(jù)為主,采樣頻率較低容易造成的信息流失,難以準(zhǔn)確的刻畫市場特征。高頻數(shù)據(jù)和超高頻數(shù)據(jù)包含了所有的交易信息,彌補(bǔ)了低頻研究的不足。但超高頻數(shù)據(jù)具有“采樣頻率高、不等的時(shí)間間隔、價(jià)格的離散變化、交易的周期模式、交易的多重性”等特性,使得低頻下的波動估計(jì)不再是無偏估計(jì)。事實(shí)上,當(dāng)采樣頻率越高,基于GARCH,SV模型不能取得較好的估計(jì)效果,RV模型的估計(jì)量的漸進(jìn)一致性受到的影響越嚴(yán)重。一個(gè)主要的原因就是存在著市場微觀結(jié)構(gòu)噪音的干擾,上述波動估計(jì)量將不再收斂于積分波動率。Zhang等(2005)提出了二尺度已實(shí)現(xiàn)波動率(TSRV),充分利用全樣本觀測數(shù)據(jù),將觀測價(jià)格的波動分解為來自真實(shí)價(jià)格的波動和微觀結(jié)構(gòu)噪音的波動,得出了市場波動的漸近一致估計(jì)量。 對市場微觀噪音的研究,可以充分揭示具體交易規(guī)則之下,證券市場的價(jià)格行為多大程度上偏離了完美市場假設(shè)下的均衡價(jià)格行為。可以排除觀測價(jià)格存在的非信息干擾,回歸資產(chǎn)正確的價(jià)格。其次,應(yīng)用微觀結(jié)構(gòu)噪音的的分離框架,可以有效估計(jì)價(jià)格過程的波動率狀況,為尋求市場交易機(jī)會和構(gòu)建投資組合提供幫助。應(yīng)用噪音的研究,也能夠形成對市場流動性和市場有效性的評價(jià),從而幫助構(gòu)建一個(gè)高效率、高質(zhì)量的證券期貨市場。 鑒于目前國內(nèi)在期貨市場微觀結(jié)構(gòu)方面的研究相對匱乏,對微觀結(jié)構(gòu)噪音的實(shí)證研究更是幾乎處于空白狀態(tài)。本文以500ms高頻采樣數(shù)據(jù)和處理之后的得到的超高頻交易數(shù)據(jù)為樣本,研究期貨市場價(jià)格波動狀況,成交量變動規(guī)律,以及期貨日內(nèi)交易的一些特征。同時(shí)將引入TSRV方法對期貨市場高頻采樣條件下的波動率進(jìn)行估計(jì),對微觀結(jié)構(gòu)噪音做出分離并分析其構(gòu)成因素。 本文的主要結(jié)構(gòu)和安排如下： 第一章是緒論部分。簡述了期貨市場微觀結(jié)構(gòu)噪音研究的研究背景和意義。第二章是相關(guān)理論和文獻(xiàn)綜述。第三章簡要介紹了我國期貨市場及其微觀結(jié)構(gòu)特征。第四章是文章的實(shí)證數(shù)據(jù)描述以及數(shù)據(jù)處理方法的介紹,包括了期貨交易的日歷效應(yīng)和日內(nèi)分時(shí)特征。 第五章是本文的一個(gè)重點(diǎn),介紹了微觀結(jié)構(gòu)噪音估計(jì)的原理和本文選取的TSRV噪音估計(jì)方法。然后基于逐筆交易數(shù)據(jù)對不同期貨品種價(jià)格波動率和市場噪音水平進(jìn)行了分離和估計(jì)。 第六章分析了微觀結(jié)構(gòu)噪音的影響因素,并基于超高頻數(shù)據(jù)實(shí)證回歸分析了相關(guān)因素對噪音的貢獻(xiàn)。第七章是本文的結(jié)語,總結(jié)了全文的研究和得出的結(jié)論,并就研究中存在的一些問題進(jìn)行了總結(jié),指出了未來可能的研究方向。最后是本文的參考文獻(xiàn),致謝和附錄。本文研究得出的一些圖表難以在正文中全部給出,可以在附錄中找到。 本文的研究主要得出了以下結(jié)論： 第一,滬深300股指期貨、天然橡膠、銅期貨日歷效應(yīng),各品種期貨不同合約之間價(jià)格存在高度相關(guān)性,表現(xiàn)出同向變動趨勢；股指成交量呈現(xiàn)當(dāng)月交易活躍,其他時(shí)間交易較為清淡。臨近交割日成交量先上升后下降的,類似于“M”型變化的趨勢。天然橡膠期貨日間成交量受現(xiàn)貨市場的影響,存在著季節(jié)性變化的趨勢。銅期貨成交量與是否是主力合約有關(guān)。 第二,本文分析了滬深300股指期貨、天然橡膠、銅期貨3個(gè)期貨品種日內(nèi)分時(shí)交易的特征。發(fā)現(xiàn)期貨日內(nèi)交易價(jià)格存在跳躍的行為,具有典型的離散變動特點(diǎn),不能視為一個(gè)連續(xù)的價(jià)格過程。股指、銅期貨的收益率在開盤和收盤附近具有類似“L”型或“倒L”型的特征,離開盤或收盤時(shí)點(diǎn)越近,收益率表現(xiàn)出較大幅度波動,隨著距這些時(shí)點(diǎn)的間隔增加,收益率波動減小相對較為平緩。成交量有類似收益率的變動趨勢。說明開盤和收盤附近存在較多的信息噪音交易。當(dāng)市場處于一致的行情走勢時(shí),市場信息分歧較低,交易行為表現(xiàn)一致變動,日內(nèi)分時(shí)特征將不明顯。 第三,利用已實(shí)現(xiàn)波動率RV、二尺度已實(shí)現(xiàn)波動率TSRV對市場的波動率進(jìn)行了估計(jì)和比較,并對微觀結(jié)構(gòu)噪音進(jìn)行了分離。發(fā)現(xiàn)以下結(jié)果：股指期貨RV大致在104級別,TSRV大致在10-5級別,微觀結(jié)構(gòu)噪音在10-8和10-9兩個(gè)級別變動。TSRV對市場噪音干擾的排除更優(yōu),是比RV更好的波動率估計(jì)量。微觀結(jié)構(gòu)噪音的變動趨勢與成交量變動有較大關(guān)系,當(dāng)成交量較低時(shí),市場流動性價(jià)差,微觀結(jié)構(gòu)噪音相對較高,當(dāng)交易變得活躍時(shí),微觀結(jié)構(gòu)噪音下降。天然橡膠期貨RV、TSRV都處于10-4水平,但顯然TSRV的值更小,而其微觀結(jié)構(gòu)噪音水平在10-5,噪音水平與成交量有類似于股指期貨的變化,成反向變動關(guān)系。銅期貨RV、TSRV、微觀結(jié)構(gòu)噪音分別處于10-4、10-5、10-6水平。同時(shí),微觀結(jié)構(gòu)噪音尖峰事件亦很好的解釋了銅期貨交易手續(xù)費(fèi)調(diào)整和異常交易的現(xiàn)象。 在本文的最后實(shí)證分析了微觀結(jié)構(gòu)噪音的影響因素,發(fā)現(xiàn)價(jià)差、交易規(guī)模對其有正的貢獻(xiàn),日內(nèi)交易次數(shù)對其有負(fù)的貢獻(xiàn),TSRV對其無明顯貢獻(xiàn),說明市場流動性與噪音有負(fù)相關(guān)關(guān)系。 本文的創(chuàng)新之處在于： 第一,首次運(yùn)用500毫秒處理得出超高頻數(shù)據(jù)分析了股指期貨、天然橡膠、銅的日內(nèi)分時(shí)交易特征。第二,首次引入了期貨市場資產(chǎn)價(jià)格波動率和微觀結(jié)構(gòu)噪音的分離框架,并運(yùn)用逐筆成交數(shù)據(jù)對股指期貨、天然橡膠、銅期貨三個(gè)品種的已實(shí)現(xiàn)波動率、二尺度已實(shí)現(xiàn)波動率、微觀結(jié)構(gòu)噪音水平分別作出了估計(jì)。第三,驗(yàn)證了TSRV模型在期貨市場應(yīng)用的穩(wěn)健性,實(shí)證結(jié)果表明TSRV估計(jì)波動優(yōu)于RV估計(jì)量。從而為高頻條件波動率估計(jì)提出了一個(gè)參考指標(biāo),有助于更深刻地認(rèn)識期貨市場波動特征,更準(zhǔn)備的構(gòu)建投資組合實(shí)現(xiàn)風(fēng)險(xiǎn)控制。第四,實(shí)證分析了期貨市場噪音的相關(guān)影響因素,驗(yàn)證價(jià)差、交易規(guī)模對微觀結(jié)構(gòu)噪音有正的影響,而日內(nèi)交易頻率與噪音負(fù)相關(guān)。第五,運(yùn)用微觀結(jié)構(gòu)噪音尖峰事件,成功的解釋了如市場微觀結(jié)構(gòu)調(diào)整(銅期貨交易費(fèi)率)、市場異常交易情況。 本文的研究可以彌補(bǔ)目前在國內(nèi)期貨市場微觀結(jié)構(gòu)噪音定量研究上的空白,為以后的相關(guān)研究鋪石墊瓦、拋磚引玉。
[Abstract]:The futures market is an important part of the financial market and the national economy, with the price discovery and hedging two important functions. Not only on the stock market, has great impact on the foreign exchange market and other virtual economy, and also directly related to the spot market, regulate the operation of the real economy. In recent years with the rapid development of international trade and economic integration the allocation of resources across borders, the role of the futures market is more and more, has become an important position to snatch international resource pricing and voice. The position in the futures market is growing.
Therefore, the understanding and research of China's futures market micro structure and mode of operation, to reveal China's futures price formation law, understand the futures market volatility has important significance. Know how to influence the market micro component market price movements, can be directly applied to the actual product futures investment practice, helps us to evaluate the futures market the quality and efficiency, promote China's futures market trading system, the perfection of rules.
The emergence of market microstructure theory and development, methods and means are provided for the in-depth understanding and study of futures market microstructure. Maureen O Hara will study the microscopic structure of the market is defined as "the process and results of" asset transactions to determine the transaction rules. Under the stress from the trading mechanism to determine the rules of price analysis in the decision process. Neil (Ananth Madhavan, 2000) will define the market microstructure for transforming a potential transaction demand for investors of finance "the final transaction price and transaction volume process. Pay attention to the influence of trading on the price formation mechanism itself, is a major feature of the market microstructure research.
The related research of microstructure noise is the background and development. According to the theory of market microstructure, the real market is different from the perfect information market, there is a transaction cost, information asymmetry and other market frictions, the equilibrium price of stock price will be affected by the friction factors and deviate from the perfect market assets in the transaction process. In the trading process, resulting in a total stock price deviates from the equilibrium price of the factors is the microstructure noise. The microstructure noise is a series of market frictions in the trading process, including the sale price, discrete changes in price, non synchronous trading, information asymmetry, market gradually in response to the bulk of the transaction, component order flow the liquidity needs of market participants, market participants inventory control effect.
High frequency data and ultra-high frequency data have recorded all trading information in the market, and their application has promoted the research of microstructure noise, and provided important empirical data for further study of China's futures market.
Study on the fluctuation of asset prices mainly in the traditional low frequency data, the sampling frequency is low easy to cause the loss of information, it is difficult to accurately describe the characteristics of the market. The high frequency data and high frequency data contains all of the transaction information, to make up for the lack of the low frequency. But the ultra high frequency data with high sampling frequency, unequal time interval, discrete changes in price, the transaction cycle mode, the characteristics of trading ", so that multiple low frequency fluctuation of the estimator is no longer the unbiased estimation. In fact, when the sampling frequency is high, based on GARCH, the SV model can not get good estimates of the effect, influence the progressive model by RV estimator the more serious. One of the main reasons is the existence of market microstructure noise interference, the fluctuation estimator will no longer converge to the integral fluctuation rate of.Zhang (2005) proposed two scale realized volatility (TSRV), we make full use of the whole sample observation data to decompose the fluctuation of observed price into the fluctuation of real price and microstructure noise, and obtain the asymptotic consistent estimator of market volatility.
Research on market microstructure noise, can fully reveal the specific transaction under the rules, the behavior of stock market prices of the extent to which deviates from the equilibrium price behavior under the perfect market assumption. You can exclude non interference observation price exists, the price return of assets right. Second, the separation framework of microstructure noise, can effective estimation of price process volatility, the market is looking for trading opportunities and portfolio construction help. Research and application of noise, but also to the formation of evaluation on the market liquidity and market efficiency, and help from the construction of a high efficient, high quality of the securities and futures market.
In view of the current domestic research in the futures market micro structure, the relative lack of empirical research on the microstructure noise is almost in a blank state. After taking the 500ms high frequency sampling data and processing the ultra high frequency trading data, research status of price fluctuation of futures market, change the volume, and some characteristics of futures in the deal. While the introduction of TSRV method on the futures market under the condition of high frequency sampling is used to estimate the volatility, make the separation and analysis of its constituent factors of microstructure noise.
The main structure and arrangement of this article are as follows:
The first chapter is the introduction part. The study of microstructure noise in the futures market research background and significance. The second chapter is the related theory and literature review. The third chapter briefly introduces the characteristics of China's futures market and its micro structure. The fourth chapter is the empirical data description and data processing methods in this paper are introduced, including the calendar effect of futures trading and the days when feature.
The fifth chapter is the emphasis of this paper, this paper introduces the TSRV noise principle and microstructure noise estimation method to estimate the selection. Then the separation and estimation of different futures price volatility and market transaction data based on the level of noise.
The sixth chapter analyzes the influencing factors of microstructure noise, and the empirical regression analysis based on the ultra high frequency data with related factors on noise. The seventh chapter is the conclusion of this thesis, summarizes and draws the research conclusion, and summarizes the problems existing in the research, pointed out the direction of future studies finally is this article references acknowledgements and appendix. Some charts are drawn in this paper it is hard to give all in the text, can be found in the appendix.
The main conclusions of this paper are as follows:
First, the Shanghai and Shenzhen 300 stock index futures, natural rubber, copper futures calendar effect, the futures contract between different prices are highly correlated, showed the same change trend; the stock volume presents the active transactions, other time relatively light trading. Near the settlement volume increased after the first drop, similar to the "M" type change trend natural rubber futures day trading volume. Affected by the stock market, there is a seasonal variation trend. Copper futures trading volume and is the main contract.
Second, this paper analyzes the CSI 300 stock index futures, natural rubber, copper futures trading features 3 days of time. It is found that the trading prices of futures intraday skipping behavior, has the typical characteristics of discrete changes, can not be regarded as a continuous process. The price of stock index futures, the rate of return has characteristics similar to "L" or "inverted L" type in the vicinity of the opening and closing of the left disc or closing point closer, yield showed a relatively large fluctuation, with the distance from the point of the interval is increased, the return volatility decreases relatively smooth. Volume change trend similar yields. It shows that there are more near the opening and closing the information of noise trading. When the market is in consistent with the market trend, the differences of market information is low, trading behavior changes consistent, days when feature is not obvious.
Third, the realized volatility of RV two scale realized volatility TSRV market volatility was estimated and compared, and the microstructure noise were separated. Find the following results: RV stock index futures at approximately 104 level, TSRV is at the 10-5 level, the microscopic structure of the noise interference of noise in the market 10-8 and 10-9 two level changes of.TSRV better, is a rate estimator is better than RV fluctuations. Have a greater relationship of microstructure noise change trend and volume changes, when the volume is low, market liquidity spreads, microstructure noise is relatively high, when the transaction becomes active when the microstructure noise decreased. Natural rubber futures RV, TSRV at 10-4 level, but obviously TSRV is smaller, and the microscopic structure of the noise level in the 10-5, the noise level and volume changes similar to the stock index futures, the reverse change relationship between copper futures of RV. , TSRV, microstructure noise respectively in the 10-4,10-5,10-6 level. At the same time, the microstructure noise spike event was also a good explanation of the copper futures transaction fee adjustment and abnormal trading phenomenon.
At the end of this paper, we empirically analyze the influencing factors of microstructure noise. We find that the price difference and the scale of transaction have positive contributions to it. The number of intra day trading has a negative contribution to it, and TSRV has no significant contribution to it, which indicates that market liquidity is negatively correlated with noise.
The innovation of this article lies in:
First, for the first time by 500 milliseconds that the ultra high frequency data analysis of stock index futures, natural rubber, copper within transaction characteristics. Second, first introduced the framework of separation of asset price volatility and futures market microstructure noise, and the use of transaction transaction data of stock index futures, natural rubber, copper has achieved three varieties of two scale volatility, realized volatility, microstructure noise levels were estimated. Third, to verify the robustness of the TSRV model application in the futures market, the empirical results show that TSRV is superior to RV estimation of volatility estimator. Thus rate estimation is proposed as a reference index for high frequency fluctuations, contribute to a more profound to understand the fluctuation characteristics of the futures market, build a portfolio to achieve risk control. Fourth, empirical analysis of the factors related to the effects of noise, the futures market price verification, trading rules Die has a positive impact on the microstructure noise, and the noise trading frequency and negative correlation. Fifth days, the microstructure noise spike event, such as the successful interpretation of market microstructure adjustment (copper futures rate), market abnormal trading.
The research of this paper can make up the blank of the quantitative research on the micro structure noise in the domestic futures market.

【學(xué)位授予單位】：西南財(cái)經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F724.5;F224

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