本文關(guān)鍵詞：滬深300指數(shù)期貨與股指間的錯誤定價比率的門限效應(yīng)實證分析　出處：《西南財經(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： 期現(xiàn)套利 錯誤定價比率 誤差修正模型 門限效應(yīng)

【摘要】：滬深300股指是對滬深兩市具有代表性的300只股票進行加權(quán)而形成的綜合性指數(shù),股指期貨是以滬深300股指為標(biāo)的期貨合約。無論是對學(xué)術(shù)研究者還是投資者來說,他們都對期現(xiàn)套利的研究都有著強烈的興趣。 由于市場摩擦的影響,股指期貨的價格與理論價格的價差往往形成兩個門限,當(dāng)價差高于較大的門限時,套利者通過正向套利策略來進行套利：當(dāng)價差低于較小的門限時,套利者可通過反向套利策略進行套利；而當(dāng)價差在兩門限之間時,套利者不會進入市場。因此,對期現(xiàn)套利的門限進行研究對投資者有很大的參考價值。 在兩個門限以外的區(qū)域,期現(xiàn)價格調(diào)整速度一般要比在中間區(qū)域快,其調(diào)整速度為什么會有這種差別,主要原因在于兩門限外,有套利者的參與。套利者通過在兩個市場上同時進行交易,即可獲取無風(fēng)險利潤。 之所以有套利者進入,是因為市場摩擦,諸如稅收,沖擊成本,傭金成本等；構(gòu)建現(xiàn)貨組合時的對指數(shù)的跟蹤誤差等因素,造成期現(xiàn)價格偏離持有成本模型所決定的均衡狀態(tài),其錯誤定價比率形成兩個門限。由門限分割而成三個區(qū)域,使套利者在這三個區(qū)域的行為發(fā)生變化,從而也使得期現(xiàn)回復(fù)到均衡狀態(tài)的速度也不一樣。什么是門限效應(yīng)呢?當(dāng)價格處于無套利區(qū)間以外區(qū)域(即存在套利空間的極端區(qū)域)的時候,期指與滬深300股指的調(diào)整受到套利者套利行為的影響,其朝均衡狀態(tài)移動的速度更快；而在中間的無套利區(qū)間時,由于沒有套利者參與,其價格調(diào)整速度較慢。 本文著重研究期指與股指的錯誤定價比率的一種非線性性關(guān)系。首先對股指與期指進行平穩(wěn)性(單位根)和協(xié)整檢驗,然后對各交易合約利用偏自相關(guān)函數(shù)來估計AR模型的滯后階數(shù)p,進而為估計時間滯后參數(shù)d(d=p)提供可選集,然后利用Tsay的排列自回歸模型首先檢驗?zāi)Ｐ偷木�性性,即檢驗自激發(fā)門限自回歸模型的線性性,更進一步利用Hansen(1999)方法測試模型的線性性,門限的個數(shù)(或者區(qū)間的個數(shù)),最后利用自激發(fā)門限自回歸模型(SETAR)對樣本進行估計分析,并將其得出的門限值作為初始指定的門限值傳遞給下一步要分析的誤差修正模型(VECM),并就其中一個典型合約進行誤差修正模型的估計,并分析結(jié)果得出結(jié)論。本文的的目的就是要通過實證分析,觀察這個門限變量在中國的滬深300指數(shù)與期指之間是否存在門限效應(yīng),如果存在門限效應(yīng),那么其門限個數(shù)(或區(qū)域的個數(shù))又有幾個,套利者在各個區(qū)域的套利行為模式又是怎樣的,每個區(qū)間的期貨價格與現(xiàn)貨價格的調(diào)整速度又是不是一樣的?期貨價格對現(xiàn)貨價格有價格發(fā)現(xiàn)作用嗎?或者現(xiàn)貨價格對期貨價格有價格發(fā)現(xiàn)作用?最后投資者很關(guān)心的：在錯誤定價比率作為門限變量的情況下,門限的位置在哪里,套利者在什么情況下會進入市場? 本文研究的創(chuàng)新點：(1)采用滬深300期現(xiàn)的錯誤定價比率作為門限變量。用錯誤定價比率作為門限變量可以衡量期現(xiàn)套利的平均交易成本,因為在期現(xiàn)套利中,一般假設(shè)股指的一定比率為期現(xiàn)套利的成本。(2)采用了六個合約的一分鐘高頻數(shù)據(jù),并對其典型滬深300股指期貨合約用Tsay檢驗對setar模型線性性進行了檢驗,并用hansen檢驗確定了門限的個數(shù),克服了以往文獻中直接采用兩門限三區(qū)域模型缺乏理論依據(jù)的不足。 研究的不足：本文最考慮了套利交易的平均交易成本,然后套利者進入市場,還會考慮其面臨的風(fēng)險,這是本文沒有考慮到的,希望研究者在以后的研究中可以考慮將加入風(fēng)險的門限變量進行建模,比如考慮夏普比率,即套利的收益扣除套利成本后除以歷史波動率作為門限變量,這樣研究假設(shè)與實際套利者更為接近,得出的結(jié)論更具有實用價值。 文章的整體結(jié)構(gòu)安排如下： 第一章為引言,對研究的背景作簡要介紹,就此提出研究的問題,期貨價格與現(xiàn)貨價格往往偏離持有成本模型決定的均衡狀態(tài)而形成了多個區(qū)域,本文以mackinlay提出的錯誤定價比率作為門限變量來分析滬深300股指及期貨間是否存在門限效應(yīng),以及這樣的門限效應(yīng)特征。 第二章,門限產(chǎn)生的原因主要是各種市場摩擦造成的,套利者在選擇進入兩個市場進行套利的這種行為模式導(dǎo)致門限的產(chǎn)生,然后就期現(xiàn)套利的風(fēng)險做簡要概述。 第三章,首先介紹了數(shù)據(jù)的選取及處理,然后介紹了協(xié)整檢驗。要建立兩個時間序列的某種函數(shù)關(guān)系,首先要確定的是這兩個時間序列之間是否存在長期的均衡關(guān)系,如果不存在,那么建立就沒有意義。這一章主要就是介紹協(xié)整檢驗的方法與檢驗步驟及標(biāo)準。當(dāng)然協(xié)整檢驗的前提是對各時間序列進行平穩(wěn)性檢驗,典型的是ADF及PP的單位根檢驗。 第四章主要講的是門限效應(yīng)研究方法,首先我們用Tsay檢驗來檢驗?zāi)Ｐ偷木�性性,用偏自相關(guān)函數(shù)確定自回歸模型的滯后階數(shù)p,然后確定時間滯后階數(shù)d,其中dp,確定p后實際上可以確定的d的可選集,這樣就可以減少我們隨機估計的大工作量。其次,我們利用Hansen方法對構(gòu)建的自激發(fā)門限模型進行檢驗,其主要目標(biāo)是確定區(qū)域個數(shù),同時也就確定了模型的門限個數(shù)。hansen方法是一系列檢驗,先檢驗其線性性,原假設(shè)：自激發(fā)門限模型只有一個區(qū)域;備擇假設(shè)為：該模型不只一個區(qū)域。如果檢驗的結(jié)果是接受原假設(shè),那么該SETAR模型就是簡化為一個線性模型,如果拒絕該模型為線性模型的原假設(shè),那么模型的區(qū)域數(shù)就大于2。然后又給出SETAR模型是兩區(qū)域的假設(shè),其原假設(shè)：自激發(fā)門限模型只有兩個區(qū)域；備擇假設(shè)為：其區(qū)域數(shù)大于2,如果拒絕原假設(shè),說明該模型不只一個門限的SETAR模型,同理,對于SETAR(3)的原假設(shè)：自激發(fā)門限模型只有三個區(qū)域；備擇假設(shè)為：該模型有三個以上的區(qū)域。如果拒絕原假設(shè),說明該模型的門限數(shù)大于2；同樣的道理,對于有k個區(qū)域的檢驗,其原假設(shè)原假設(shè)：自激發(fā)門限模型只有k個區(qū)域；備擇假設(shè)為：該模型有k個以上的區(qū)域。我們測試的思想即是,從區(qū)域數(shù)小的SETAR模型開始,通過不斷的測試,拒絕原假設(shè),直到我們接受含有m個區(qū)域的SETAR模型的原假設(shè)為止,區(qū)域數(shù)m確定,其相應(yīng)的門限數(shù)為：m-1。然后將錯誤定價比率作為門限變量用誤差修正模型對結(jié)果進行估計。 第五章為實證部分,就滬深300期指與現(xiàn)貨指數(shù)價格序列動態(tài)變化的門限效應(yīng)進行實證研究,首先利用偏自相關(guān)函數(shù)來估計AR模型的滯后階數(shù)p,進而為估計時間滯后參數(shù)d(dp)提供可選集,然后利用Tsay的排列自回歸模型首先檢驗?zāi)Ｐ偷木�性性自激發(fā)門限自回歸模型檢驗門限的線性性,更進一步利用Hansen(1999)方法測試模型的線性性,門限的個數(shù)(或者區(qū)間的個數(shù)),然后以錯誤定價比率作為誤差修正項用誤差修正模型去估計參數(shù),并分析所得結(jié)果并得出結(jié)論。 本文采用2011年12月16日至2012年5月15日的這段時期的一分鐘高頻數(shù)據(jù),用錯誤定價比率作為門限變量,用Tsay方法以及Hansen方法以及誤差修正模型來研究滬深300股指與期指之間是否存在門限效應(yīng)以及該門限效應(yīng)的特征。主要有以下幾個方面的意義和結(jié)論： 對滬深300指數(shù)與滬深300期指價格序列采用以錯誤定價比率作為門限變量來進行門限效應(yīng)分析以及協(xié)整動態(tài)調(diào)整分析。 本文采用了六個當(dāng)月連續(xù)合約的一分鐘為頻率的高頻數(shù)據(jù)作為分析數(shù)據(jù),通過對六個樣本的估計對門限模型的非線性進行測試,用hansen方法對各個合約的門限數(shù)進行估計,最終得出兩門限的結(jié)論,這樣得出的兩門限的結(jié)果的更具說服力,得出的結(jié)論更可靠。 現(xiàn)貨價格序列服從一階單整過程,滬深300股指期貨組成的時間序列也服從一階單整過程,同時期指與滬深300指數(shù)存在協(xié)整關(guān)系,即存在長期的均衡關(guān)系。 在頻率為一分鐘的情況下,股指期貨對滬深300股指有價格發(fā)現(xiàn)作用。 較多觀測值落入無套利空間,說明期指與股指價格發(fā)現(xiàn)作用明顯,目前的金融市場較期指剛上市時比較變得成熟一些。 下門限的絕對值比上門限值要大,說明現(xiàn)貨市場中,中國特有的做空限制機制對在下區(qū)間的套利行為影響較大,主要表現(xiàn)在反向套利中套利者構(gòu)建現(xiàn)貨組合時比較困難,目前的金融市場還不是很完善,有進一步深化金融市場的空間。滬深300股指期貨間的錯誤定價比率存在門限效應(yīng),當(dāng)錯誤定價比率在[-0.002244323,0.001640752]區(qū)間時,套利者不會進入兩個市場,這個區(qū)間也就是無套利區(qū)間。
[Abstract]:Shanghai and Shenzhen 300 stock index is a comprehensive index of 300 stocks which are representative of the Shanghai and Shenzhen two were weighted and the formation of the stock index futures in Shanghai and Shenzhen 300 stock index futures contract. Both the academic researchers and investors, they are on the study of arbitrage will have a strong interest.
The influence of market friction, the price and the theoretical price of the stock index futures spreads tend to form the two threshold, when the spread is higher than the high threshold, through arbitrage arbitrage strategy for arbitrage: when the spread is lower than the small threshold, arbitrageurs can carry through the reverse arbitrage strategy; and when the spread in the two threshold between when arbitrageurs will not enter the market. Therefore, the arbitrage threshold study has great reference value for investors.
In addition to the two threshold region, the speed of price adjustment period than in the middle region of the adjustment of the speed quickly, why there is such a difference, the main reason is that the two threshold, there is arbitrage arbitrage by participation. At the same time the transaction in the two markets, can obtain risk-free profits.
The reason why there are arbitrage to enter, because the market friction, such as tax, the impact of the cost, the cost of the Construction Commission; on the spot portfolio index tracking error caused by other factors, the current price deviates from the equilibrium of holding cost model is decided by the ratio of mispricing to form two threshold by threshold segmentation and three. A region, make arbitrage change in the three areas of behavior, which also makes the return to equilibrium speed is not the same. What is the threshold effect? When the price is no arbitrage interval (other than regional extreme areas that exist arbitrage space) when the index and the Shanghai and Shenzhen 300 stock index the adjustment is affected by arbitrage arbitrage, towards the equilibrium state to move faster; and in the middle of the no arbitrage interval, because there is no arbitrage in the price adjustment speed is slow.
A nonlinear relationship between index futures and stock index this paper focuses on the error ratio. Firstly, pricing of Stock Index Futures (stationary and unit root and cointegration test), and then all of the contracts with the partial autocorrelation function to estimate the AR model lag order P, and to estimate the time delay parameter d (d=p) to provide can then use the Tsay collection, arrangement of autoregressive model first test of linear model, which is to check the self exciting threshold from linear regression model, and further using Hansen (1999) linear method test model, number threshold (number or interval), the self excitation threshold autoregressive model (SETAR) estimation analysis of samples, and the obtained threshold value as the initial specified threshold value passed to the next step to the analysis of the error correction model (VECM), which is one of the typical contract error correction mode The type of estimation, and the results of the analysis conclusion. The aim of this study is to through empirical analysis, to observe whether there is a threshold effect between the Shanghai and Shenzhen 300 index variables in China threshold and index futures, if there is a threshold effect, then the threshold number (number or area) there are a few arbitrage and how in various regions of the arbitrage model, adjust the speed of the spot price and futures price of each interval is not the same? The futures price on the spot price is the price discovery function? Or the spot price of the futures price is the price discovery role? Very concerned about investors: finally mispricing in the ratio as the threshold variable. Under the threshold where, arbitrageurs will enter the market in what circumstances?
The innovation of this paper: (1) the Shanghai and Shenzhen 300 current error pricing ratio as the threshold variable. The threshold variables can measure the arbitrage transaction cost with average mispricing ratio as, because in arbitrage, a certain percentage of the cost for the general assumption of stock index arbitrage. (2) the six contract one minute high frequency data, and the typical CSI 300 stock index futures contract with Tsay to test the linear SETAR model were tested, and determined the number threshold with Hansen test, to overcome the shortcomings of previous literature directly by the two threshold three region model of the lack of theoretical basis.
The lack of research: the consideration of arbitrage, the average transaction cost, then arbitrageurs enter the market, will also consider the risks, this paper does not consider, want to consider will join the risk threshold variable modeling can be studied in the future research, such as the SHARP ratio, less arbitrage the income arbitrage cost divided by the historical volatility as the threshold variable, so the research hypothesis and the actual arbitrage is more close, the conclusion has more practical value.
The overall structure of the article is as follows:
The first chapter is the introduction of research background briefly, puts forward the research question, the futures prices and spot prices tend to deviate from the equilibrium state holding cost model of decision and the formation of multiple regions, the paper presents a MacKinlay error pricing ratio as the threshold variable to analyze whether threshold effect exists between the Shanghai and Shenzhen 300 stock index and futures. And such a threshold effect.
The second chapter, the reason of the threshold is mainly caused by various market frictions. Arbitrage people choose to enter the two markets to carry out arbitrage. This behavior leads to the threshold generation. Then the risk of arbitrage is briefly outlined.
The third chapter first introduces the selection and processing of data, and then introduces a cointegration test. To establish the function relationship between the two time series, first to determine whether there is a long-term equilibrium relationship between the two time series, if not, then there is no established meaning. This chapter is introduce the method of Cointegration test and inspection procedures and standards. Of course, the premise of the cointegration test is a smooth test for the time series, the typical unit root ADF and PP test.
The fourth chapter is mainly about the research method of threshold effects, firstly we use Tsay test to test the linear model, the partial autocorrelation function to determine the lag order autoregressive model P, and then determine the time lag of the order of D, DP, P after determining can actually determine d can be selected, so you can to reduce the workload of our stochastic estimation. Secondly, we use Hansen method to test the self exciting threshold model is constructed, its main goal is to determine the number of regions, but also determine the threshold number of.Hansen model is a series of tests, the first test of its linearity, the original hypothesis: self excitation threshold model only one area; the alternative hypothesis is that the model is not only a region. If the test result is to accept the null hypothesis, then the SETAR model is simplified as a linear model, if the model is linear model to the original Assume, then the regional model number is greater than 2. and then given the SETAR model is two region hypothesis, the original hypothesis: self excitation threshold model only two areas; the alternative hypothesis is: the number of regions is greater than 2, if we reject the null hypothesis, which indicates that the SETAR model, this model is not only a threshold for the same SETAR (3) of the original hypothesis: self excitation threshold model only three areas; the alternative hypothesis is that the model has more than three areas. If we reject the null hypothesis, that the number of the threshold of the model is larger than 2; similarly, the K region of the test, the null hypothesis null hypothesis: the self excitation threshold model only K region; the alternative hypothesis is: the model has more than k area. We tested the idea that, starting from the SETAR model of regional small number, through continuous testing, reject the null hypothesis, until we accept containing m region SETAR The original number of the model is m, and the corresponding threshold is m-1.. Then the error pricing ratio is used as threshold variable, and the error correction model is used to estimate the result.
The fifth chapter is the empirical part, empirical research on the threshold effect of price changes in the Shanghai and Shenzhen 300 index with the sequence of dynamic stock index, the partial autocorrelation function to estimate the AR model lag order P, and to estimate the time delay parameter d (DP) can provide selections, and then use the Tsay order autoregressive model first test of linear threshold auto regression model to test the linear threshold model of self excitation, further use of Hansen (1999) linear method test model, number threshold (number or interval), then the error rate as the pricing error correction error correction model is used to estimate the parameters, and analyze the results and conclusion.
This paper uses the period from December 16, 2011 to May 15, 2012 one minute high frequency data, with the wrong pricing ratio as the threshold variable, using Tsay method and Hansen method, to study the Shanghai and Shenzhen whether there is a threshold effect and the threshold effect between the 300 stock index futures and the model error correction characteristics. Mainly has the following significance and conclusions:
The Shanghai and Shenzhen 300 index and the Shanghai and Shenzhen 300 index futures price series by mispricing ratio as the threshold variable for threshold effect analysis and cointegration analysis of dynamic adjustment.
The six month continuous contract for one minute frequency data as the analysis data, the estimation of six samples of nonlinear threshold model is tested by the number of each contract, threshold Hansen estimation method, finally obtains the conclusion of the two threshold, so that the two threshold results more persuasion, the conclusion is more reliable.
The spot price series is subject to a single whole process, time series of Shanghai and Shenzhen 300 stock index futures which also follow a single whole process, there is a cointegration relationship and the index and the Shanghai and Shenzhen 300 index, that there is a long-term equilibrium relationship.
In the case of a one minute frequency, stock index futures have a price discovery effect on the Shanghai and Shenzhen 300 stock index.
More observations fall into no arbitrage space, and stock index futures price discovery shows obvious effect, the current financial futures market than just listed more mature.
The absolute value of the threshold limit value than under the door to a large, indicating that the spot market, short Chinese unique restriction mechanism has great effect on arbitrage in the interval, mainly construction spot portfolio in the reverse arbitrage arbitrage is difficult, the financial market is not perfect, with further deepening of the financial market space Shanghai and Shenzhen 300 stock index futures. The error between the price ratio threshold effect, when the error rate in the range of [-0.002244323,0.001640752] pricing, arbitrage will not enter the two market, this interval is no arbitrage interval.

【學(xué)位授予單位】：西南財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.51;F224

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