發(fā)布時(shí)間：2018-03-21 00:54

  本文選題：算法交易　切入點(diǎn)：WAP算法　出處：《西北大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著算法交易在金融領(lǐng)域的快速發(fā)展和廣泛運(yùn)用,對(duì)于交易算法的研究也日益活躍,而作為運(yùn)用最為廣泛的VWAP(交易量加權(quán)平均價(jià)格)算法交易策略也就成為了研究的熱點(diǎn)之一。在VWAP交易策略中,關(guān)鍵的問(wèn)題在于對(duì)交易量分布的預(yù)測(cè),預(yù)測(cè)的準(zhǔn)確性直接關(guān)系到交易策略的有效性。在歷史的VWAP交易策略中,是運(yùn)用靜態(tài)的方法,通過(guò)歷史數(shù)據(jù)來(lái)進(jìn)行交易量分布的預(yù)測(cè),其中并沒(méi)有將市場(chǎng)的實(shí)時(shí)信息反映到預(yù)測(cè)過(guò)程中去。本文則通過(guò)將股票的實(shí)時(shí)價(jià)格信息引入到交易量分布的預(yù)測(cè)中去,實(shí)現(xiàn)了對(duì)交易量分布的動(dòng)態(tài)預(yù)測(cè)。 根據(jù)單日內(nèi)股票交易量通常成“U”型分布的特征,本文首先運(yùn)用時(shí)間序列因素分解的方法,將交易量的歷史數(shù)據(jù)分解成周期因素、趨勢(shì)因素和波動(dòng)因素,然后再分別對(duì)這些分解出的因素進(jìn)行預(yù)測(cè)得到各因素的預(yù)測(cè)值,進(jìn)而再將各因素的預(yù)測(cè)值進(jìn)行組合得到交易量的預(yù)測(cè)值,最后再通過(guò)引入股票的實(shí)時(shí)價(jià)格信息,對(duì)交易量的預(yù)測(cè)值進(jìn)行動(dòng)態(tài)的調(diào)整,得到最終的交易量預(yù)測(cè)值。 通過(guò)數(shù)值實(shí)驗(yàn),本文的預(yù)測(cè)方法比歷史的靜態(tài)預(yù)測(cè)方法得到的交易量的分布更加接近于市場(chǎng)實(shí)際的交易量的分布,證實(shí)了本文預(yù)測(cè)方法的準(zhǔn)確性。 在交易量分布預(yù)測(cè)的基礎(chǔ)上,本文設(shè)計(jì)了基于動(dòng)態(tài)預(yù)測(cè)的VWAP算法交易策略。通過(guò)數(shù)值實(shí)驗(yàn),本文策略獲得的VWAP價(jià)格較歷史策略獲得的VWAP價(jià)格更接近于市場(chǎng)實(shí)際的VWAP價(jià)格；通過(guò)在交易相同股票數(shù)量的條件下對(duì)本文策略獲得的VWAP價(jià)格與歷史策略獲得的VWAP價(jià)格的差值進(jìn)行比較,得到了本文交易策略獲得的收益高于歷史交易策略收益的結(jié)果,證實(shí)了本文交易策略的有效性。
[Abstract]:With the rapid development and wide application of algorithmic transaction in the field of finance, the research on transaction algorithm is becoming more and more active. As one of the most widely used trading strategies of VWAP (transaction volume weighted average price) algorithm, the key problem in VWAP trading strategy is the prediction of trading volume distribution. The accuracy of prediction is directly related to the validity of trading strategy. In the historical VWAP trading strategy, the static method is used to predict the distribution of transaction volume through historical data. The real-time information of the market is not reflected in the forecasting process, and the dynamic forecasting of the trading volume distribution is realized by introducing the real-time price information of the stock into the forecasting of the trading volume distribution. According to the characteristics of "U" distribution of stock trading volume in a single day, this paper firstly uses the method of time series factor decomposition to decompose the historical data of trading volume into periodic factor, trend factor and fluctuation factor. Then the factors are predicted to get the predicted value of each factor, and then the forecast value of each factor is combined to get the forecast value of trading volume. Finally, the real-time price information of the stock is introduced. The forecast value of trading volume is adjusted dynamically, and the final forecast value of trading volume is obtained. Through numerical experiments, the distribution of trading volume obtained by this method is closer to that of the actual market volume, which proves the accuracy of this method. Based on the prediction of trading volume distribution, this paper designs the VWAP algorithm trading strategy based on dynamic prediction. Through the numerical experiment, the VWAP price obtained by this strategy is closer to the actual VWAP price than the VWAP price obtained by the historical strategy. By comparing the difference between the VWAP price obtained by the strategy and the VWAP price obtained by the historical strategy under the condition of the same number of shares traded, the result that the profit obtained by the trading strategy is higher than that obtained by the historical trading strategy is obtained by comparing the difference between the VWAP price obtained by this paper and the VWAP price obtained by the historical strategy. The validity of the trading strategy is verified.
【學(xué)位授予單位】：西北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F830.91;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 吳進(jìn)軍;時(shí)間序列分解預(yù)測(cè)法及周期因素的探討[J];數(shù)理統(tǒng)計(jì)與管理;1995年03期

2 劉逖;盧濤;;算法交易及在中國(guó)資本市場(chǎng)的應(yīng)用前景[J];上海金融;2012年01期

3 周仁才;陳曉雯;;基于瞬時(shí)交易量及收益率動(dòng)態(tài)調(diào)整的交易量加權(quán)平均價(jià)格策略[J];上海交通大學(xué)學(xué)報(bào);2013年03期

4 方兆本;鎮(zhèn)磊;;基于非對(duì)稱(chēng)效應(yīng)ACD模型和分時(shí)VWAP算法對(duì)A股市場(chǎng)算法交易的量化分析研究[J];中國(guó)科學(xué)技術(shù)大學(xué)學(xué)報(bào);2011年09期

5 陳夢(mèng)根;;算法交易的興起及最新研究進(jìn)展[J];證券市場(chǎng)導(dǎo)報(bào);2013年09期

相關(guān)博士學(xué)位論文 前1條

1 鎮(zhèn)磊;基于高頻數(shù)據(jù)處理方法對(duì)A股算法交易優(yōu)化決策的量化分析研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2010年

，

本文編號(hào)：1641550