發(fā)布時(shí)間：2017-12-31 18:34

  本文關(guān)鍵詞：基于Copula理論的賣空交易策略研究　出處：《東北財(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： Copula理論 尾部相關(guān)性 投資策略 遺傳算法

【摘要】：20世紀(jì)70年代,量化投資開始在美國的資本市場(chǎng)興起,受益于量化投資的諸多優(yōu)點(diǎn),量化投資很快就成為美國主流的投資模式,在眾多的量化投資者中,以西蒙斯最為成功,他的大獎(jiǎng)?wù)禄�金�?0年內(nèi),持續(xù)而穩(wěn)定的獲得了每年平均35%的凈回報(bào),并且是在扣除費(fèi)用后的,這樣的成績堪比神話。而我國的量化投資還處于起步階段,但隨著我國資本市場(chǎng)的逐漸完善,量化投資的前景會(huì)越發(fā)明亮,同時(shí),量化投資的發(fā)展可以減少市場(chǎng)上的投機(jī)行為,減少市場(chǎng)泡沫,反過來促進(jìn)我國資本市場(chǎng)的發(fā)展和完善。 本文正是在此背景下,欲建立一種基于Copula理論的量化投資策略模型,運(yùn)用于我國的資本市場(chǎng)上。投資者一般習(xí)慣性做多,本文一反常態(tài)重點(diǎn)研究賣空方式的建立,期望使投資者在市場(chǎng)下跌時(shí)也能獲利,幫助投資者獲取超額收益。 本文選取豆油指數(shù)和棕櫚油指數(shù)2012年9月至12月共四個(gè)月的高頻數(shù)據(jù)作為研究對(duì)象。研究對(duì)象是由市場(chǎng)上的主力合約加權(quán)平均計(jì)算得到的,指數(shù)能體現(xiàn)研究對(duì)象的連續(xù)性,所以豆油指數(shù)和棕櫚油指數(shù)是非常合適的研究對(duì)象。 本文所設(shè)計(jì)的投資策略主要基于Copula函數(shù)刻畫的尾部相關(guān)性,即在下尾部相關(guān)性高的情況下,如果豆油指數(shù)下跌,那么棕櫚油指數(shù)下跌的概率是非常高的。假如現(xiàn)實(shí)中棕櫚油指數(shù)并沒有下跌,那么在Copula函數(shù)刻畫的尾部相關(guān)性下是“非正�！鼻闆r,我們相信棕櫚油指數(shù)將會(huì)下跌,此時(shí)就是投資的機(jī)會(huì)。由Copula函數(shù)的定義可知,Copula函數(shù)是兩隨機(jī)變量的邊際分布的連接函數(shù),為保證整個(gè)投資策略的成功,需要對(duì)兩組研究對(duì)象的邊際分布進(jìn)行精確的描述,邊際分布刻畫的越準(zhǔn)確,Copula函數(shù)擬合的越準(zhǔn)確,則可能出現(xiàn)的投資機(jī)會(huì)越準(zhǔn)確。由于金融資產(chǎn)的高頻數(shù)據(jù)的分布不具有正態(tài)性,一般有“尖峰肥尾”的性質(zhì),本文也放棄了傳統(tǒng)的假設(shè)收益率服從正態(tài)分布的方法,轉(zhuǎn)而采用核密度估計(jì)這種非參數(shù)估計(jì)的方法,以求能夠更精確的刻畫研究對(duì)象的邊際分布情況。 利用本文所研究的策略對(duì)實(shí)際數(shù)據(jù)進(jìn)行測(cè)試,本文得到了非常好的累積收益率,九月至十二月的累積收益率依次是17.70%、3.45%、8.97%、-0.82%,這在當(dāng)今的金融投資理論中已經(jīng)屬于超額收益率。交易次數(shù)分別為96、57、79、6,總次數(shù)達(dá)到了238次,屬于典型的高頻交易,九月至十二月四個(gè)月中單筆最大虧損依次為-1.4699%。顯然虧損幅度是我們能夠接受的。本文實(shí)證的結(jié)論表明本文的投資策略是具有一定的實(shí)際參考意義的。 本文的創(chuàng)新之處主要有三點(diǎn)：第一,本文打破投資者的慣性思維,重點(diǎn)進(jìn)行賣空交易；第二,創(chuàng)造性的基于Copula尾部相關(guān)性構(gòu)造程序化交易策略,傳統(tǒng)的資產(chǎn)配置思想要求資產(chǎn)之間的相關(guān)性要低,以分散風(fēng)險(xiǎn),本文則是利用尾部相關(guān)性高的資產(chǎn)來尋找交易時(shí)機(jī),這也是本文最突出的創(chuàng)新點(diǎn)；第三,由于數(shù)據(jù)多,計(jì)算量大,在參數(shù)擬合的過程中為得到最優(yōu)的參數(shù)組合,使用遺傳算法能夠避免窮舉算法費(fèi)時(shí)費(fèi)力的缺點(diǎn)。 本文的不足之處有兩點(diǎn)；第一,Copula函數(shù)描述下尾相關(guān)性的能力遠(yuǎn)遠(yuǎn)高于其描述上尾相關(guān)性的能力,因此,投資者可以得到的買入信號(hào)較差,因此喪失了一部分的利潤,而且由于上尾相關(guān)性刻畫的精度不夠,反而可能降低投資收益率；第二,雖然在實(shí)證過程中并沒有出現(xiàn)不可接受的虧損,但是過度的依賴程序化交易而考慮情況不夠細(xì)致的話,一旦極特殊的情況出現(xiàn),可能導(dǎo)致較大的虧損。
[Abstract]:In 1970s, quantitative investment began to rise in the U.S. capital market, to benefit many advantages of quantitative investment, quantitative investment soon became the mainstream mode of investment, many investors in the quantification, with Simmons's most successful, his Medallion fund in 20 years, sustained and stable won the annual average net return 35%, and after deducting expenses, this result is comparable to myth and quantitative investment in China is still in the initial stage, but with the development of China's capital market is gradually improving, quantitative investment prospects will be brighter, and at the same time, the development of quantitative investment can reduce market speculation, reduce the market bubble. In turn, promote the development and perfection of China's capital market.
Under this background, to establish a quantitative investment strategy model based on Copula theory, used in China's capital market. Investors generally used to do more, this paper focuses on the establishment of uncharacteristically selling short, so that investors expect the decline in the market can profit, help investors to obtain excess returns.
This paper selects the high frequency data of soybean oil and palm oil index index from September 2012 to December a total of four months as the research object. The research object is the main contract on the market by the weighted average calculated index, can continuously reflect the research object, and soybean oil and palm oil index index is the object of study is very appropriate.
The design of this investment strategy is mainly based on the Copula function to describe tail dependence, namely in the tail correlation is high, if the oil index fell, then the probability of palm oil fell is very high. If the palm oil index in reality did not fall, then described in the Copula function is the tail correlation non normal situation, we believe that the palm oil index would fall, this is the investment opportunity. By the definition of the Copula function, Copula function is the link function of marginal distribution of two random variables, in order to ensure the success of the investment strategy, to the marginal distribution of two groups of subjects were accurate description, marginal distribution more accurately, the Copula function fitting is more accurate, it may be more accurate investment opportunities. Due to the distribution of high-frequency data of financial assets is not normal, there are The nature of "spiking fat tail" also abandons the traditional assumption that yield is subject to normal distribution. Instead of using kernel density estimation, this method of nonparametric estimation can be used to depict the marginal distribution of research objects more accurately.
To test the actual data by using the strategy, this paper obtained the very good cumulative rate of return, from September to December the cumulative rate of return was 17.70%, 3.45%, 8.97%, -0.82%, which belongs to the excess rate of return in today's financial investment theory. The number of transactions were 96,57,79,6, the total number reached 238 second, belongs to the typical high frequency trading, September to December four months, the single largest loss in -1.4699%. obviously loss rate is acceptable to us. The empirical results show that this investment strategy is of practical significance to a certain.
The innovation of this paper has three main points: first, this paper break the inertia of thinking investors, focusing on short selling; second, Copula tail correlation program trading strategy based on the structure of creative thought, the traditional asset allocation requirements of the correlation between the assets to be low, to disperse the risk, this is the tail of the high correlation of assets to looking for the timing of the transaction, which is the most important innovation; third, because most of the data, a large amount of computation in the process parameter fitting to obtain the optimal combination of the parameters, using genetic algorithm can avoid the shortcomings of time-consuming exhaustive algorithm.
There are two shortcomings in this paper; first, Copula function to describe the ability of lower tail dependence is much higher than the upper tail dependence of the description ability, therefore, the poor buy signal that investors can get lost a part of the profits, but due to lack of characterization of upper tail dependence accuracy, but may reduce the rate of return on investment; second. Although in the empirical process and no unacceptable losses, but excessive reliance on program trading and consider the situation is not careful, once the very special circumstances, may lead to greater losses.

【學(xué)位授予單位】：東北財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51

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