本文關鍵詞： 統計套利策略 協整 主成分分析 證券市場　出處：《山東財經大學》2012年碩士論文　論文類型：學位論文

【摘要】：2011年在中國金融史上是不平凡的一年，，融資融券的正式推出不僅為中國證券市場帶來了做空機制，也使得中國證券市場徹底告別了單邊市的時代。中國的證券市場也將進入機會更多、更有效率和市場化程度更高的新時期。很多以前在發(fā)達國家得到廣泛應用的投資理念和策略，也將在中國落地生根大放異彩。這其中就包括統計套利的投資策略和技術應用。 本文正是在這種大背景下，通過借鑒金融發(fā)達國家的統計套利投資理念，針對中國內地證券市場做實證分析，也算是統計套利中國化的初步探索。 通過長期的證券投資實踐，人們總結出很多規(guī)律和投資策略，這其中就包括了利用股票與股票價格之間的長期均衡關系和在短時間內打破這種均衡關系的“異象”之間進行套利的統計套利策略。本文通過對統計套利技術的介紹、分析和實證檢驗，證實了這種投資策略在中國內地證券市場上應用的可行性。 統計套利策略有很多具體的方法，本文采用了應用最為廣泛的協整策略和主成分分析策略。通過對這兩種方法的對比得出了主成分分析方法效率更高，在國內市場更加實用的一般性結論。在實證分析中，我們使用了很多殘差處理模型和樣本期外時間窗口外推方法。經過對比分析我們得出了使用正態(tài)分布和均值回歸模型處理殘差序列，使用每日平移時間窗口外推方法收益率最高的結論。
[Abstract]:2011 was an extraordinary year in China's financial history. The formal introduction of margin financing not only brought about a short selling mechanism for China's securities market, It also made China's securities market bid farewell to the era of one-sided market. China's securities market will also have more opportunities. Many of the investment ideas and strategies that were widely used in developed countries will also take root in China. This includes the investment strategy and technology application of statistical arbitrage. It is under this background that this paper makes an empirical analysis on the securities market in the mainland of China by referring to the statistical arbitrage investment concept of the developed financial countries. It is also a preliminary exploration of statistical arbitrage in China. Through long-term securities investment practice, people have summed up a lot of laws and investment strategies. This includes the statistical arbitrage strategy which uses the long-term equilibrium relationship between stock and stock price and breaks the "vision" of the equilibrium relationship in a short time. The analysis and empirical test confirm the feasibility of applying this investment strategy to the securities market in mainland China. There are many specific methods for statistical arbitrage strategy. This paper adopts the most widely used cointegration strategy and principal component analysis strategy. By comparing these two methods, it is concluded that the principal component analysis method is more efficient. A more practical general conclusion in the domestic market. In empirical analysis, We use a lot of residual processing models and extrapolation methods of time window outside the sample period. Through comparison and analysis, we get that we use normal distribution and mean regression model to deal with residual sequences. Use the daily translation time window extrapolation method to get the highest rate of return.
【學位授予單位】：山東財經大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F832.51

【引證文獻】

相關期刊論文 前1條

1 杜夏筠;;基于協整理論的統計套利方法及實證[J];市場研究;2013年09期

本文編號：1522045