本文關(guān)鍵詞： 算法交易 FLS 卡爾曼濾波 時變系數(shù) 在線估計　出處：《西南財經(jīng)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：算法交易也稱為程序化交易,是一種將投資策略邏輯程式化,然后借助計算機進行買賣決策的投資方式。在實際運用中,一個高效的交易系統(tǒng)需要實時的分析和處理海量數(shù)據(jù),然后給出交易信號。其中最為重要的一個任務(wù)便是在不施加任何概率先驗假設(shè)的條件下挖掘出各個數(shù)據(jù)流的相關(guān)關(guān)系以及其隨時間的演變情況。本文首先介紹了一種估計時變參數(shù)的有效算法——靈活最小二乘算法(flexible least squares,簡稱FLS),該算法是普通最小二乘的一種變形,它能夠在沒有概率假設(shè)的情況下快速的估計出隨時間演變的回歸系數(shù)。其次,為了能更好的理解該算法,本文還討論了FLS算法與卡爾曼濾波算法之間的內(nèi)在聯(lián)系以及給出了一些改進。最后,我們將FLS算法運用到了高頻統(tǒng)計套利之中,并且在此基礎(chǔ)上構(gòu)建了一套完整的程序化交易系統(tǒng),并取得了良好的業(yè)績表現(xiàn)。
[Abstract]:Algorithmic transaction, also known as programmed transaction, is an investment method that makes investment strategy logical and then makes trading decisions with the help of computer. In practice, an efficient trading system needs to analyze and process massive amounts of data in real time. Then the transaction signal is given. One of the most important tasks is to excavate the correlation of each data stream and its evolution over time without applying any probabilistic priori hypothesis. Flexible least squares, an efficient algorithm for estimating time-varying parameters, is a variant of ordinary least squares. It can estimate the regression coefficients over time quickly without the assumption of probability. Secondly, in order to better understand the algorithm, This paper also discusses the relationship between the FLS algorithm and the Kalman filter algorithm and gives some improvements. Finally, we apply the FLS algorithm to the high frequency statistical arbitrage. And on this basis, a complete set of program trading system, and achieved good performance.
【學(xué)位授予單位】：西南財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F830.59

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本文編號：1516000