基于統(tǒng)計套利理論的股指期貨跨期套利研究
本文關(guān)鍵詞:基于統(tǒng)計套利理論的股指期貨跨期套利研究 出處:《東華大學》2012年碩士論文 論文類型:學位論文
更多相關(guān)文章: 股指期貨 跨期套利 統(tǒng)計套利
【摘要】:股票指數(shù)期貨是現(xiàn)代資本市場發(fā)展的產(chǎn)物。20世紀70年代,西方各國受石油危機的影響,經(jīng)濟發(fā)展十分不穩(wěn)定,利率波動劇烈導致股票市場價格大幅波動,股票投資者迫切需要一種能夠有效規(guī)避風險、實現(xiàn)資產(chǎn)保值的金融工具。于是,股票指數(shù)期貨應運而生。發(fā)展到今天,股指期貨已經(jīng)成為世界投資最為活躍的期貨交易品種。 股指期貨市場的套利交易在促使市場價格趨于理性、增加市場的活躍程度方面起著非常重要的作用,是期貨市場功能能夠得到有效發(fā)揮的重要保障。本文以我國推出滬深300股指期貨市場為研究背景,基于統(tǒng)計套利的思想研究了滬深300股指期貨市場推出初期的跨期套利機會。 文章選取滬深300股指期貨當月連續(xù)合約IFL0與下月連續(xù)合約IFL1的5分鐘高頻數(shù)據(jù)為研究對象,首先對兩合約間的關(guān)系進行了協(xié)整關(guān)系檢驗。接著檢驗了持有成本理論下無風險利率和股息率這兩個變量與合約間價差波動的關(guān)系。結(jié)果顯示,其對價差波動的解釋能力為35%,同時格蘭杰因果關(guān)系檢驗表明,其確實是價差波動的格蘭杰原因。 合約間價差的統(tǒng)計套利建立在價差均值回歸的前提條件下,但由于外部變量的變化導致價差均值回復的中樞也會隨之變化,文章選取加權(quán)移動均值(WMA)來對價差均值回復的中樞進行刻畫。同時和一般金融時間序列一樣,價差的波動表現(xiàn)為廣義自回歸條件異方差(GARCH)的特點,文章分別選用GARCH(1,1)與EWMA模型來刻畫條件異方差。在確定價差的均值與方差后,文章選用正態(tài)分布N(μ1,σ12)來刻畫每一時刻價差的分布狀態(tài)。最后在正態(tài)分布的基礎(chǔ)上結(jié)合Vidyamurthy (2004)的交易機制給出套利交易的開倉時點與平倉時點,建立套利交易策略。 文章最后分別應用樣本內(nèi)數(shù)據(jù)與樣本外數(shù)據(jù)實證檢驗了套利模型的交易效果。實證套利結(jié)果表明,在不考慮股指期貨杠桿交易提高資金使用效率的條件下,基于GARCH所刻畫的條件異方差,樣本內(nèi)數(shù)據(jù)累積年化收益率為11.79%,樣本外數(shù)據(jù)累積年化收益率為15.89%;基于EWMA所刻畫的條件異方差,樣本內(nèi)數(shù)據(jù)累積年化收益率為12.30%,樣本外數(shù)據(jù)累積年化收益率為21.33%?傊,取得了較好的收益水平:
[Abstract]:The stock index futures is the product of the development of the modern capital market. In 70s, the western countries were affected by the oil crisis, the economic development was very unstable, the fluctuation of interest rate caused the stock market price to fluctuate sharply. Stock investors are in urgent need of a financial tool that can effectively avoid risks and maintain the value of assets. Therefore, stock index futures emerge as the times require. Stock index futures have become the most active futures trading species in the world. Arbitrage trading in the stock index futures market plays a very important role in promoting rational market prices and increasing the active degree of the market. It is an important guarantee that the function of futures market can be effectively played. This paper takes the introduction of Shanghai and Shenzhen 300 stock index futures market as the research background. Based on the idea of statistical arbitrage, this paper studies the intertemporal arbitrage opportunities in the initial stage of Shanghai and Shenzhen 300 stock index futures market. This paper selects the 5-minute high frequency data of Shanghai and Shenzhen 300 stock index futures' continuous contract IFL0 and next month's continuous contract IFL1 as the research object. Firstly, the cointegration relationship between the two contracts is tested, and then the relationship between the risk-free interest rate and the dividend yield and the fluctuation of the price difference between the contracts under the holding cost theory is tested. Its ability to explain the fluctuation of the spread is 35 and the Granger causality test shows that it is the Granger cause of the fluctuation of the spread. The statistical arbitrage of the price difference between contracts is based on the premise of the price difference mean regression, but because of the change of external variables, the center of the average price difference return will also change. In this paper, the weighted moving mean (WMA) is chosen to describe the center of the average return of the spread. At the same time, it is the same as the general financial time series. The fluctuation of price difference is characterized by generalized autoregressive conditional heteroscedasticity (GARCH(1). 1) describe conditional heteroscedasticity with EWMA model. After determining the mean and variance of the spread, the normal distribution N (渭 1) is selected. 蟽 12) is used to describe the distribution of the price difference at each moment. Finally, based on the normal distribution, the distribution is combined with Vidyamurthy / 2004). The trading mechanism gives the opening point and closing point of arbitrage trade. Establish arbitrage trading strategy. At the end of the paper, we use the data inside the sample and the data outside the sample to test the effect of the arbitrage model. The empirical arbitrage results show that, without considering the leverage trading of stock index futures to improve the efficiency of the use of funds. Based on the conditional heteroscedasticity described by GARCH, the cumulative annualized rate of return of data in the sample is 11.79 and that of the data outside the sample is 15.89; Based on the conditional heteroscedasticity described by EWMA, the cumulative annualized rate of return of data in the sample is 12.30 and that of the data outside the sample is 21.33.
【學位授予單位】:東華大學
【學位級別】:碩士
【學位授予年份】:2012
【分類號】:F832.5;F224
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