本文選題：行為金融 + 動(dòng)量效應(yīng)��； 參考：《華東師范大學(xué)》2013年博士論文

【摘要】：量化投資作為一種新的投資方法,在海外的發(fā)展已有30多年的歷史,由于投資業(yè)績穩(wěn)定,其所占市場規(guī)模和份額不斷擴(kuò)大。在國內(nèi),量化投資雖仍處于起步階段,但其發(fā)展迅速,所受市場的重視程度也超過其他投資方法。交易策略是量化投資中的核心問題。一項(xiàng)投資是否成功,其效果如何,很大程度上由交易策略決定。鑒于投資策略的重要性,本文嘗試研究行為金融和高頻交易中的的幾種交易策略,并討論了它們在實(shí)際投資中的應(yīng)用。 在行為金融中,我們重點(diǎn)討論動(dòng)量策略的相關(guān)問題(可參考Wang,S.and Zheng, W.A.[93]).在實(shí)際金融市場中,有很多頻繁出現(xiàn)的金融現(xiàn)象無法用傳統(tǒng)金融給出解釋,人們把這些金融現(xiàn)象稱為金融異象。在這些金融異象中,動(dòng)量效應(yīng)、反轉(zhuǎn)效應(yīng)是兩類重要的現(xiàn)象。關(guān)于動(dòng)量效應(yīng),已經(jīng)有大量學(xué)者研究了它的存在性及來源。在關(guān)于它的來源中,Hong-Stein模型是典型的將動(dòng)量和反轉(zhuǎn)效應(yīng)組合在一起的模型。在Hong-Stein模型下,市場能產(chǎn)生動(dòng)量效應(yīng)及反轉(zhuǎn)效應(yīng)。然而,在其能解釋動(dòng)量效應(yīng)的同時(shí),該模型也易于產(chǎn)生兩種極端情形。一方面,基本均衡價(jià)格函數(shù)下的收益率序列中的自相關(guān)性過于顯著,使得價(jià)格變動(dòng)方向可以用最臨近時(shí)期的價(jià)格變動(dòng)方向預(yù)測；另一方面,在推廣的均衡模型中,收益率序列的自相關(guān)性過于不明顯,這使得收益率序列幾乎成為相互獨(dú)立序列。對于這兩種情形,我們構(gòu)造了相應(yīng)的檢驗(yàn)統(tǒng)計(jì)量,并在各國家指數(shù)上進(jìn)行了檢驗(yàn)。檢驗(yàn)結(jié)果標(biāo)明,這兩種極端情形均被拒絕。此外,我們還檢驗(yàn)了傳統(tǒng)動(dòng)量策略在A股市場及商品期貨市場上的有效性。檢驗(yàn)結(jié)果表明,在A股市場上,動(dòng)量策略不能產(chǎn)生顯著正收益；而在商品期貨市場上,動(dòng)量策略卻能帶來顯著的正收益�；趯ong-Stein模型的討論,我們構(gòu)建了隨機(jī)持有期動(dòng)量策略,并重新在A股市場及商品期貨市場上檢驗(yàn)其有效性。檢驗(yàn)結(jié)果表明,在A股市場及商品期貨市場上,隨機(jī)持有期動(dòng)量策略均能產(chǎn)生顯著的正收益。經(jīng)過風(fēng)險(xiǎn)分析,我們發(fā)現(xiàn)策略的收益無法用相關(guān)的風(fēng)險(xiǎn)因子進(jìn)行解釋,這也說明了中國證券市場非弱有效。 在對動(dòng)量策略的研究中,我們發(fā)現(xiàn),作為一種低頻交易策略,雖然動(dòng)量策略可以容納大量的資金在數(shù)量眾多的標(biāo)的資產(chǎn)進(jìn)行投資,也可以產(chǎn)生顯著的正收益,但動(dòng)量策略本身有無法克服的問題。這些問題主要包括：持倉時(shí)間長,占用資金成本高；在持倉過程中,賬面收益易出現(xiàn)大幅波動(dòng),其中較大的收益回撤會(huì)對投資者的心理產(chǎn)生很大的壓力；長時(shí)間持倉也使得收益率序列本身波動(dòng)率加大,這使得策略的夏普比率不高。此外,隨著交易所公布的數(shù)據(jù)越來越詳細(xì),高頻數(shù)據(jù)會(huì)提供低頻數(shù)據(jù)之外的很多信息,比如市場微觀結(jié)構(gòu)的信息,而這些信息在低頻交易策略中并沒有考慮到。因此,這啟發(fā)我們研究高頻交易策略,以克服低頻交易中的不足。 在高頻交易中,本文討論了基于一類技術(shù)指標(biāo)(拋物反轉(zhuǎn)指標(biāo),]Parabolic SAR)的交易策略的構(gòu)建,并討論了它的應(yīng)用(可參考Wang,S. and Zheng, W.A.[94])技術(shù)分析是高頻交易策略中的重要的組成部分,而技術(shù)指標(biāo)是技術(shù)分析的基礎(chǔ)。技術(shù)指標(biāo)多以價(jià)格為基礎(chǔ),而資產(chǎn)定價(jià)是數(shù)理金融的核心問題之一,因此,在數(shù)理金融的框架下討論基于技術(shù)指標(biāo)的交易策略是恰當(dāng)?shù)�。Parabolic SAR是一類重要的趨勢性技術(shù)指標(biāo),因其具備加速追趕趨勢的特點(diǎn)而與其他趨勢類指標(biāo)相異。根據(jù)SAR的定義,每個(gè)時(shí)間點(diǎn)上SAR的取值都依賴于初始值,這對于指標(biāo)計(jì)算是繁雜的。本文中,我們討論截?cái)郤AR指標(biāo)的新定義,并由此得到新的SAR指標(biāo)。因?yàn)镾AR指標(biāo)同樣圍繞價(jià)格走勢波動(dòng),因此我們構(gòu)造了價(jià)格序列與SAR之差作為新指標(biāo)Xt。在Black Scholes模型下,我們證明了Xt的平穩(wěn)性。模擬數(shù)據(jù)及基于模擬數(shù)據(jù)的檢驗(yàn)同樣支持指標(biāo)平穩(wěn)性的結(jié)論�；赬t,我們構(gòu)造出本文的交易策略。利用中國A股市場的高頻數(shù)據(jù),我們對該策略的有效性進(jìn)行檢驗(yàn)。在對策略有效性的檢驗(yàn)中,我們采用了傳統(tǒng)t檢驗(yàn)對策略收益的顯著性進(jìn)行檢驗(yàn)。對于在GARCH類模型下策略有效性的檢驗(yàn),我們采用殘差bootstrap方法。檢驗(yàn)結(jié)果表明,策略可以產(chǎn)生顯著的買入收益和賣出收益。由于現(xiàn)階段仍然是高頻交易的快速發(fā)展階段,高頻交易也在為投資機(jī)構(gòu)帶來巨大的收益,因此,許多高頻交易策略都處于保密狀態(tài),外界無法知道策略的具體內(nèi)容。本文則嘗試研究了一類具體的交易策略,并且經(jīng)在實(shí)際投資部門的檢驗(yàn),策略也具備有效性。因此,不論從實(shí)際操作層面還是理論研究層面,本文對于高頻交易的研究都很有意義。
[Abstract]:As a new investment method, quantitative investment has been developing abroad for more than 30 years. As the investment performance is stable, the scale and share of the market is expanding. In China, although the quantitative investment is still in its infancy, its development is rapid and the value of the market is more than the other investment methods. The trading strategy is quantified. At the core of the capital, the success of an investment is largely determined by the transaction strategy. In view of the importance of the investment strategy, this paper tries to study several trading strategies in behavioral finance and high frequency transactions, and discusses their use in real investment.
In behavioral finance, we focus on the related issues of momentum strategy (reference Wang, S.and Zheng, W.A.[93]). In real financial markets, many frequent financial phenomena can not be explained by traditional finance. These financial phenomena are called financial anomalies. In these financial anomalies, the momentum effect and reversal effect are two A large number of scholars have studied the existence and source of the momentum effect. In its source, the Hong-Stein model is a typical model that combines momentum and reversal effect. In the Hong-Stein model, the market can produce momentum effect and reversal effect. However, the momentum effect can be explained in the market. At the same time, the model is also easy to produce two extreme cases. On the one hand, the autocorrelation in the return sequence of the basic equilibrium price function is too obvious, making the price change direction can be predicted by the direction of the price change in the nearest period; on the other hand, the autocorrelation of the return sequence is too unknown in the extended equilibrium model. Obviously, this makes the return sequence almost independent sequence. For these two cases, we construct the corresponding test statistics and test the index in each country. The results indicate that these two extreme cases are rejected. In addition, we also test the traditional momentum strategy in the A stock market and the commodity futures market. The results show that momentum strategy can not produce significant positive returns in the A stock market, while momentum strategy can bring significant positive returns in the commodity futures market. Based on the discussion of the Hong-Stein model, we construct a random holding momentum strategy and check its effectiveness in the new A share market and commodity futures market. The results show that in the A stock market and the commodity futures market, the momentum strategy of the random holding period can produce significant positive returns. After the risk analysis, we find that the earnings of the strategy can not be explained by the related risk factors, which also shows that the Chinese securities market is not weak and effective.
In the study of momentum strategy, we find that as a low-frequency trading strategy, although momentum strategy can accommodate a large amount of funds to invest in a large number of standard assets, the momentum strategy can produce significant positive returns, but the momentum strategy itself has an insurmountable problem. These include the long holding time and the appropriation of funds. The cost is high; in the process of holding, there is a large fluctuation in the book income, of which a large return will have a great pressure on the investor's psychology; long holding also increases the volatility of the return sequence itself, which makes the SHARP ratio of the strategy not high. The data will provide a lot of information outside the low frequency data, such as the information of the market microstructures, which are not considered in the low-frequency trading strategy. Therefore, it inspires us to study high frequency trading strategies to overcome the shortcomings of low frequency transactions.
In the high frequency transaction, this paper discusses the construction of a transaction strategy based on a class of technical indicators (]Parabolic SAR), and discusses its application (reference Wang, S. and Zheng, W.A.[94]) is an important component of the high frequency trading strategy, and the technical index is the basis of technical analysis. Based on price, asset pricing is one of the core problems of mathematical finance. Therefore, under the framework of mathematical finance, the discussion of the trading strategy based on technical indicators is an appropriate.Parabolic SAR as an important trend technical indicator, which is different from other trend indicators because of its characteristics of accelerating the trend of catching up. According to the definition of SAR, The value of SAR at each time point is dependent on the initial value, which is complicated for the index calculation. In this paper, we discuss the new definition of the truncated SAR index and thus get a new SAR index. Because the SAR index also revolves in the fluctuation of the price trend, we construct the difference between the price sequence and SAR as the new index Xt. in the Black Scholes model We prove the smoothness of the Xt. The simulation data and the test based on the analog data also support the conclusion of the stability of the index. Based on Xt, we construct the trading strategy in this paper. We use the high frequency data of the Chinese A share market to test the effectiveness of the strategy. In the test of the strategy, we use the traditional t test. Test for the significance of policy gains. For the test of policy effectiveness under the GARCH class model, we use the residual bootstrap method. The results show that the strategy can produce significant buy returns and sell returns. As the current phase is still the rapid development stage of high frequency transactions, high frequency transactions are also brought to investment institutions. As a result, many high frequency trading strategies are in a state of secrecy, and the outside world can not know the specific content of the strategy. This paper tries to study a specific kind of transaction strategy, and the strategy is also valid in the actual investment department. The study of high frequency trading is of great significance.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F830.59

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本文編號(hào)：1936945