程序化交易算法模型的研究
[Abstract]:With the continuous development and improvement of the securities market and the procedural trading platform in recent years, the programmed trading plays an increasingly important role in the securities trading market. A programmed transaction is the process of executing a set program through a computer. The computer program is the trading thought and model of traders. Therefore, programmed transactions depend on computer trading platforms and trading models. Since the development and development of the domestic procedural trading platform has been relatively perfect, the research and analysis of the transaction model has become the key factor affecting the procedural trading. The biggest advantage of programmed trading is that it is completely independent of traders' subjective emotions. The computer strictly executes the trading policy code without any hesitation, greed, or panic. Traders are inevitably influenced by their own subjective emotions, thus missing the best time to stop loss or profit. In the course of trading, the speed of the traders is also very strict requirements. The market is rapidly changing, and if orders are placed at a slower pace than others, the best trading opportunities are likely to be lost. Programmed transactions are very fast and can work 24 hours a day. For short-term trading or high-frequency trading investors, program trading is very attractive. Algorithmic transaction means that a transaction order with specified trading volume, transaction time interval and price interval constraints is completed by a computer program. The algorithm is used to determine the delivery time, price, quantity and type of the order. Algorithmic transaction can be regarded as a branch of programmed transaction. Therefore, integrating the idea of algorithm into programmed transaction can not only optimize the allocation of resources, but also reduce the transaction cost and obtain higher income. Starting from the origin of programmed trading, this paper first appeared in the American stock market in 1975. Secondly, the NYSE definition of programmed trading is given. Due to the development of programmed trading for more than 30 years, it redefines programmed trading according to the current market environment, which is closer to the usage habits of traders. More suitable for the development of market-oriented significance. Then it introduces the development situation of the domestic and foreign programmed transactions, and can understand the domestic development trend, which has a certain reference role for investors to carry out the programmed trading. By analyzing the advantages and applications of programmed trading, we can find out the reasons why programmed trading is popular with traders. At the same time, this paper mainly introduces the transaction model of programmed transaction. The principle of each model, the application rules and the shortcomings of the model are introduced and analyzed, which lays the groundwork for adding the idea of algorithm model to the following. Then, this paper introduces the idea of algorithm model and the commonly used algorithm transaction model. By introducing the definition and application field of algorithmic trading, we can help investors to know more about algorithmic transactions. The last part is the innovation of this paper. Based on the improvement of the commonly used algorithm transaction model, a program algorithm model is obtained by adding it to the program transaction model. This model is an improvement on the programmed transaction model, which can capture the market information and price better and obtain higher profit.
【學(xué)位授予單位】:山東大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:F224;F830.91
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 熊熊;袁海亮;張維;張永杰;;程序化交易及其風(fēng)險(xiǎn)分析[J];電子科技大學(xué)學(xué)報(bào)(社科版);2011年03期
2 韋丁源;;股市大盤指數(shù)的馬爾科夫鏈預(yù)測(cè)法[J];廣西廣播電視大學(xué)學(xué)報(bào);2008年03期
3 劉紅梅;;ARIMA模型在股票價(jià)格預(yù)測(cè)中的應(yīng)用[J];廣西輕工業(yè);2008年06期
4 郭國(guó)雄,陳玲,欒長(zhǎng)福,陸子強(qiáng);回歸分析在新股股價(jià)預(yù)測(cè)建模中的應(yīng)用[J];華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2003年03期
5 章晨;;基于馬爾科夫鏈的股票價(jià)格漲跌幅的預(yù)測(cè)[J];商業(yè)經(jīng)濟(jì);2010年21期
6 李春林;梁艷;;上市銀行股票市場(chǎng)分形特征的實(shí)證研究[J];價(jià)值工程;2012年01期
7 孟凡卉;;R/S分析[J];科技信息(學(xué)術(shù)研究);2008年19期
8 王寶森;王旭智;;期貨價(jià)格的馬爾科夫鏈改進(jìn)模型[J];青島大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年03期
9 方啟東;溫鑫;蔣佳靜;丁攀攀;沈友紅;王琰;;基于時(shí)間序列分析的股價(jià)預(yù)測(cè)[J];宿州學(xué)院學(xué)報(bào);2010年08期
10 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
相關(guān)碩士學(xué)位論文 前3條
1 何成剛;馬爾科夫模型預(yù)測(cè)方法的研究及其應(yīng)用[D];安徽大學(xué);2011年
2 彭濟(jì)敏;程序化交易方式在股票交易中的應(yīng)用[D];吉林大學(xué);2004年
3 彭蕾;中國(guó)證券市場(chǎng)程序化交易研究[D];西南財(cái)經(jīng)大學(xué);2005年
,本文編號(hào):2342294
本文鏈接:http://sikaile.net/guanlilunwen/zhqtouz/2342294.html