系統識別號 | U0002-2907202110064700 |
---|---|
DOI | 10.6846/TKU.2021.00821 |
論文名稱(中文) | 衍生性市場到期效果的移轉性分析 |
論文名稱(英文) | Analysis on Transferability of the Maturity Effects of Derivative Markets |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 財務金融學系博士班 |
系所名稱(英文) | Department of Banking and Finance |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 109 |
學期 | 2 |
出版年 | 110 |
研究生(中文) | 劉曾若 |
研究生(英文) | Tseng-Jou Liu |
學號 | 806530084 |
學位類別 | 博士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2021-07-04 |
論文頁數 | 59頁 |
口試委員 |
指導教授
-
邱 建 良
指導教授 - 黃 健 銘 委員 - 林忠機 委員 - 郭宗賢 委員 - 王譯賢 委員 - 姜淑美 委員 - 鄭東光 委員 - 邱建良 委員 - 張鼎煥 |
關鍵字(中) |
到期效果 向量自我迴歸模型 拔靴複製法 |
關鍵字(英) |
maturity effect Vector Autoregression model bootstrap copy method |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
本研究首先探討衍生性商品市場是否具有一致性的到期效果,並觀察本研究之標的商品是否經由彼此之交互作用,使到期效果移轉至其他商品市場,進而影響金融市場之運作;最後探討中美貿易關稅協議及美國期中選舉等事件對本研究之標的商品-指數股票型基金(Exchange Traded Funds, ETF)、股價指數及臺股期貨之市場價量結構的變化影響。本研究擷取臺灣經濟新報(Taiwan Economic Journal, TEJ)資料庫有關前揭商品高頻原始交易資料,樣本期間為2018年3月1日到2019年5月10日,並運用向量自我迴歸模型(Vector Autoregression model, VAR)、拔靴複製法等進行實證研究。 實證結果發現,首先以價格反轉比例結果發現,商品之到期效果與過往學者之證實結果未盡一致,亦即到期效果僅發生在市場平穩的情況下,若發生影響政經環境或社會之重大事件,無論是指數股票型基金、股價指數或臺股期貨都不會發生到期效果。再者,以向量自我迴歸模型檢定結果發現,臺股期貨對於股價指數具有價格領先的特性,此外,觀察樣本期間內,指數股票型基金、股價指數及臺股期貨等商品是否存有到期日效果,實證結果發現,指數股票型基金具有顯著之到期效果,股價指數及臺股期貨之到期效果則消逝,並未發現有到期效果之證據,到期效果全部移轉至指數股票型基金,此與學者Samuelson (1976), Stoll and Whaley (1987, 1991)及Edwards (1988)等人之研究,股票及期貨有到期效果之結果不同。其次,以拔靴複製法檢定之實證結果獲致與以向量自我迴歸模型法相同之結果。最後,本研究並進一步區分子樣本期間,以美國期中選舉分化後發現,當市場波動越大、市場越不穩定時,到期效果相對不明顯。 |
英文摘要 |
This research first explores whether consistent maturity effect exists in the derivative product markets, and observes whether the transfer of maturity effect to other commodity markets is caused by the interaction of the target commodities in this research, thereby affecting the operation of the financial market. The paper also discusses the impact of the Sino-US trade tariff agreement and the U.S. midterm elections on the changes in the price and volume market structure of the target commodities of this study, namely, Exchange Traded Funds (ETF), stock indices and Taiwan stock futures. This study extracts the high-frequency raw trading data of the previously disclosed commodities from the Taiwan Economic Journal (TEJ) database. Samples from March1, 2018 to May 10, 2019 are used, and a Vector Autoregression model (VAR), bootstrap copy method, etc. are employed for empirical research. The empirical results show that in terms of the price reversal ratio result, the maturity effect of commodities is not completely consistent with the results substantiated by previous scholars, that is, the maturity effect only occurs when the market is stable. However, if the occurrence of major events causes an impact on the political and economic environment or society, whether it is index stock funds, stock price indices or Taiwan stock futures, maturity effect is not likely to occur. Furthermore, the test result of the Vector Autoregression model indicates that Taiwan stock futures have the characteristics of leading price index for stock price indices. In addition, whether there is an maturity date effect for index stock funds, stock price indices, and Taiwan stock futures during the sample period, the empirical results show that index stock funds have a significant maturity effect, while the maturity effect of stock indices and Taiwan stock futures disappears. No evidence of maturity effect is found, and the maturity effect is all transferred to index stock type Funds. This is different from the research result of Samuelson (1976), Stoll and Whaley (1987, 1991) and Edwards (1988) which supports stocks and futures have maturity effects. Secondly, the empirical results obtained from the bootstrap copy method and the vector autoregressive model method are the same. Finally, this study further differentiates the sample period of the molecule. After the divided US midterm elections, it is found that when the market volatility increases and the market becomes unstable, the maturity effect is relatively insignificant. |
第三語言摘要 | |
論文目次 |
第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 4 第三節 研究目的 7 第四節 研究流程 10 第五節 研究架構與流程圖 12 第二章 文獻回顧 13 第一節 到期效果 13 第二節 到期效果之移轉性 16 第三節 事件研究 18 第三章 資料來源及研究方法 20 第一節 資料來源 20 第二節 變數定義 21 第三節 研究方法 24 第四章 實證結果與分析 32 第一節 樣本資料數據及處理 32 第二節 基本統計量分析 34 第三節 實證結果 39 第五章 結論 54 參考文獻 56 表目錄 表4.2.1 臺灣資本市場指數股票型基金、股價指數及臺股期貨之基本統計量 36 表4.2.2 臺灣資本市場指數股票型基金、股價指數及臺股期貨僅計算到期日之基本統計量 37 表4.2.3 臺灣資本市場指數股票型基金、股價指數及臺股期貨受中美貿易事件影響之基本統計量 38 表4.3.1 ADF單根檢定結果表 39 表4.3.2 向量自我迴歸模型落後期檢測結果表 40 表4.3.3 2018年4月至2019年4月到期效果之價格反轉比例表 42 表4.3.4 2018年4月至2019年4月指數股票型基金、股價指數及臺股期貨到期日效果之檢定結果表 44 表4.3.5 向量自我迴歸模型估計結果彙整表 46 表4.3.6 指數股票型基金報酬變異數分解結果表 49 表4.3.7 股價指數報酬變異數分解結果表 50 表4.3.8 臺股期貨報酬變異數分解結果表 50 圖目錄 圖1.1.1 2003年至2021年臺灣證券交易所發行指數股票型基金發行總檔數成長與資產規模變化 3 圖1.4.1 研究流程 12 圖4.3.1 衝擊反應分析 47 |
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