The Application of Spark and its Social Network Analysis in Trading Strategy
| Autor: | CHEN, YU-ZHEN, 陳禹蓁 |
|---|---|
| Jazyk: | zh-TW |
| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 Pair trading, also called as Spreading, is a trading strategy which can make two stocks whose prices are on a high correlation to be a pair based on the property of mean reversion in a stationary time series. Furthermore, it can be arbitraged through a portfolio with a long position and a short position as the value of the portfolio deviates from the historical mean. The thesis will apply the daily adjusted closing prices of publicly traded companies in 2016 from TEJ to test if an autoregressive model exists a unit root or not by augmented Dickey-Fuller Test of Said and Dickey (1984), and then test if any two stocks exist the property of cointegration by Cointegration Test of Engle and Granger (1987). If two stocks exist the property of cointegration, they will be assumed to be a pair. There are lots of pairs constitute a huge and complicated network system in the thesis. In fact, there are many effective algorithms in Spark to deal with complicated graphs, and that is why the thesis applies its tools, GraphFrames, to analyze the complex network by Social Network Analysis. Eventually, the thesis will use Label Propagation Algorithm to detect communities in the network, and then work on the further analysis of the result. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|