本文關(guān)鍵詞： 證券交易異常 復(fù)雜事件處理 大數(shù)據(jù) 事件代數(shù) StreamInsight　出處：《浙江理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著經(jīng)濟(jì)全球化和資本市場(chǎng)的逐步開(kāi)放，我國(guó)的證券市場(chǎng)得到了很大的發(fā)展。證券作為一種特殊的商品，由于其虛擬性和特殊的效用和需求特性，使得證券市場(chǎng)存在很多的違法違規(guī)行為。建立一套開(kāi)發(fā)先進(jìn)的、實(shí)時(shí)的、快速響應(yīng)的證券市場(chǎng)交易異常事件監(jiān)測(cè)系統(tǒng)，，是對(duì)證券市場(chǎng)監(jiān)管、保證市場(chǎng)正常運(yùn)行的前提。 證券市場(chǎng)是個(gè)典型的“大數(shù)據(jù)”市場(chǎng)，具有數(shù)據(jù)量大、數(shù)據(jù)結(jié)構(gòu)復(fù)雜、流動(dòng)速度快、價(jià)值密度低等特點(diǎn)，此外，證券市場(chǎng)交易監(jiān)測(cè)還需要對(duì)事件進(jìn)行實(shí)時(shí)處理。復(fù)雜事件處理近年發(fā)展起來(lái)的一種新興事件處理技術(shù)，證券交易處理是復(fù)雜事件處理中一種重要的應(yīng)用領(lǐng)域。復(fù)雜事件處理平臺(tái)有其專門(mén)的事件描述語(yǔ)言以及強(qiáng)大的處理引擎，而且該處理引擎能夠獨(dú)立完成大規(guī)模數(shù)據(jù)的接收、分析和處理，能夠以組件的形式集成到系統(tǒng)中，具有低耦合、靈活性高等特點(diǎn)。 本文在分析研究復(fù)雜事件處理技術(shù)的基礎(chǔ)上，采用Visual Studio2010與微軟復(fù)雜事件處理引擎StreamInsight的平臺(tái)集成，開(kāi)發(fā)一個(gè)面向證券交易可疑事件監(jiān)測(cè)的控制臺(tái)應(yīng)用系統(tǒng)實(shí)例，實(shí)現(xiàn)了從交易數(shù)據(jù)流處理、復(fù)雜事件規(guī)則驗(yàn)證到證券交易事件判別等整個(gè)監(jiān)測(cè)過(guò)程。 論文首先對(duì)復(fù)雜事件處理以及大數(shù)據(jù)的研究現(xiàn)狀和相關(guān)技術(shù)進(jìn)行闡述，以及對(duì)復(fù)雜事件處理中的相關(guān)理論進(jìn)行研究。 其次，對(duì)證券交易中洗盤(pán)和對(duì)敲兩種重要可疑行為的幾種事件特征進(jìn)行總結(jié)，并通過(guò)事件代數(shù)以及XML語(yǔ)言的方式對(duì)其進(jìn)行描述和存儲(chǔ)，作為復(fù)雜事件模式，存儲(chǔ)于規(guī)則庫(kù)中，來(lái)作為可疑事件監(jiān)測(cè)規(guī)則。 最后，對(duì)基于對(duì)敲和洗盤(pán)兩類證券市場(chǎng)主要違法交易行為的代數(shù)定義和XML進(jìn)行描述，并將其轉(zhuǎn)化為StreamInsight應(yīng)用程序中的LINQ查詢語(yǔ)句，構(gòu)建相應(yīng)的StreamInsight復(fù)雜事件處理應(yīng)用程序。同時(shí)采用計(jì)算實(shí)驗(yàn)方法，將股票池中的歷史交易數(shù)據(jù)轉(zhuǎn)換為數(shù)據(jù)流，模擬數(shù)據(jù)流進(jìn)入應(yīng)用程序，利用復(fù)雜事件處理引擎StreamInsight對(duì)其分析判斷，查找出數(shù)據(jù)流中的異常行為事件。從而證實(shí)了復(fù)雜事件處理技術(shù)在處理證券市場(chǎng)“大數(shù)據(jù)”方面的優(yōu)勢(shì)。
[Abstract]:With the economic globalization and the gradual opening of the capital market, the securities market in China has been greatly developed. As a special commodity, the securities market is due to its virtual nature and special utility and demand characteristics. It makes the securities market have a lot of illegal behavior. To establish a set of advanced, real-time, rapid response securities market trading abnormal event monitoring system, is to monitor the securities market. The premise of ensuring the normal operation of the market. The securities market is a typical "big data" market, which has the characteristics of large amount of data, complex data structure, fast flow speed, low value density and so on. Stock market transaction monitoring also needs to deal with events in real time. Complex event processing is a new event processing technology developed in recent years. Securities transaction processing is an important application field in complex event processing. Complex event processing platform has its special event description language and powerful processing engine. Moreover, the engine can receive, analyze and process large-scale data independently, and can be integrated into the system in the form of components, which has the characteristics of low coupling, high flexibility and so on. Based on the analysis and research of complex event processing technology, the platform integration of Visual Studio2010 and Microsoft complex event processing engine StreamInsight is adopted in this paper. A console application system for monitoring suspicious events in securities transactions is developed, which realizes the whole monitoring process from transaction data flow processing, verification of complex event rules to discrimination of securities trading events. In this paper, the current research status and related technologies of complex event processing and big data, and the related theories of complex event processing are discussed. Secondly, it summarizes the event characteristics of two important suspicious behaviors in stock trading, and describes and stores them by means of event algebra and XML language. As a complex event pattern, it is stored in the rule base as a suspicious event monitoring rule. Finally, this paper describes the algebraic definition and XML of the main illegal trading behaviors in the securities market based on tapping and dishwashing. And turn it into a LINQ query statement in a StreamInsight application. The corresponding StreamInsight complex event processing application program is constructed, and the historical transaction data in stock pool is converted into data flow by using computational experiment method. The analog data stream enters the application program, and the complex event processing engine StreamInsight is used to analyze and judge it. The abnormal behavior events in the data flow are found, which proves the advantage of the complex event processing technology in dealing with "big data" in the securities market.
【學(xué)位授予單位】：浙江理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP274;F830.91

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