| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 戴育詳 | zh_TW |
| DC.creator | Yu-Hsiang Tai | en_US |
| dc.date.accessioned | 2021-1-18T07:39:07Z | |
| dc.date.available | 2021-1-18T07:39:07Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=107225022 | |
| dc.contributor.department | 統計研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 為了使用高頻資料做配對交易，這篇論文回顧了 Liu 、 Chang 、 Geman 在 2017 年提出的 ＂ 雙
重均值回歸過程 ＂ 模型。基於這個模型，我們使用台灣的股市資料去做回測。我們一共挑
選並記錄了 68 間台灣半導體公司的股票資料。同時為了更貼近實際情況，我們也在這篇論
文裡介紹了一些重要的交易規則和策略。對於 2019/03/18 至 2019/10/24 這段期間的回測結
果為30%的年化報酬率與4.37的年化夏普比率。 | zh_TW |
| dc.description.abstract | In order to execute pairs trading on high frequency data, this thesis reviews ’doubly
mean-reverting processes,’ which was introduced in Liu, Chang, and Geman (2017). Based on
this model, we consider the back-testing driven by the Taiwan stock market data. There are
68 companies in Taiwan semiconductor industry group selected and recorded from Taiwan
Stock Exchange (TWSE). Some specific important trading rules and the corresponding
trading strategies are introduced. In empirical studies, we show the efficiency of the modified
strategy in terms of 30% annualized return and 4.37 annualized Sharpe ratio over the period
from 2019/03/18 to 2019/10/24. | en_US |
| DC.subject | 配對交易 | zh_TW |
| DC.subject | 高頻資料 | zh_TW |
| DC.subject | 雙重均值回歸模型 | zh_TW |
| DC.subject | 年化報酬率 | zh_TW |
| DC.subject | 年化夏普比率 | zh_TW |
| DC.subject | Pairs trading | en_US |
| DC.subject | High frequency data | en_US |
| DC.subject | Doubly mean-reverting processes | en_US |
| DC.subject | Annualized return | en_US |
| DC.subject | Annualized Sharpe ratio | en_US |
| DC.title | Intraday Pairs Trading on Taiwan Semiconductor Companies through Mean Reverting Processes | en_US |
| dc.language.iso | en_US | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |