臺灣博碩士論文加值系統

本論文探討國際原油價格波動性是否有助於預測台灣加權股價指數報酬率。除了以已實現波動 (realized volatility) 衡量西德州與布蘭特 (Brent) 原油價格波動性外，並依據 Xiao and Wang (2022) 而將其區分為好的油價波動與壞的油價波動。另一方面，本論文亦考慮Chen et al. (2022) 所建構的 RSJV油價波動變數。應用 36 年共 436 筆的月資料，本文分別探討這四種波動性指標針對臺灣加權股價指數報酬率的樣本內與樣本外預測表現。本研究在樣本內的預測表現部分的主要實證發現為，相較於Xiao and Wang (2022) 和 Chen et al. (2022) 的實證結果顯示國際原油價格波動性對美國股市報酬具有預測力，本研究的實證結果則顯示不論是否有考量其他控制變數，這四種波動性指標對台灣股市報酬皆無顯著的預測力。然而進一步將樣本期間以石油金融化的 2003 年作為分界後，本文發現在考量其他控制變數後僅有壞的油價波動在石油金融化之前具有顯著的預測力。至於樣本外的預測表現部分，本研究的實證結果則顯示，不論是否有考量其他控制變數、應用不同的樣本內資料占總資料之比例、與引入三倍股票報酬標準差做為經濟限制，在大部分的情況下，所有的油價波動性指標對台灣股市皆不具有顯著的預測力。

This paper explores whether the volatility of international crude oil prices helps predict the return rate of the Taiwan Weighted Stock Index (TAIEX). In addition to using realized volatility to measure the volatility of West Texas Intermediate (WTI) and Brent crude oil prices, this study also categorizes the volatility into good and bad oil price volatility based on Xiao and Wang (2022). Furthermore, this paper considers the RSJV oil price volatility variable constructed by Chen et al. (2022). Using 436 monthly data points over 36 years, this study investigates the in-sample and out-of-sample predictive performance of these four volatility indicators for the return rate of TAIEX.
The main empirical finding for in-sample predictive performance is that, unlike the empirical results of Xiao and Wang (2022) and Chen et al. (2022), which show that international crude oil price volatility has predictive power for U.S. stock market returns, this study's empirical results indicate that these four volatility indicators do not have significant predictive power for Taiwan's stock market returns, regardless of whether other control variables are considered. However, when the sample period is divided at the year 2003, marking the onset of oil financialization, this paper finds that only bad oil price volatility has significant predictive power before oil financialization, after considering other control variables.
As for out-of-sample predictive performance, the empirical results of this study show that, regardless of whether other control variables are considered, different proportions of in-sample data are used, or three times the standard deviation of stock returns is introduced as an economic constraint, none of the oil price volatility indicators have significant predictive power for Taiwan's stock market in most cases.

謝辭 I
摘要 II
表目錄 IV
圖目錄 V
1.前言 1
2.文獻回顧 3
3.研究方法 11
3.1油價波動性指標的建構 12
3.2樣本內預測表現 13
3.2.1無控制變數之迴歸模型 13
3.2.2加入控制變數之迴歸模型 14
3.3樣本外預測表現 15
3.3.1模型建立 15
3.3.2預測方法和ROS 15
3.3.3檢定方法及CW統計量 17
3.4經濟限制 17
4.實證資料敘述 18
5.實證結果與分析 22
5.1樣本內預測 23
5.1.1樣本內預測結果與分析 23
5.1.2 樣本內小結 31
5.2 樣本外預測 34
5.2.1樣本外預測結果與分析 34
5.2.2樣本外小結 40
6.結論 40
參考文獻 43
附錄 46

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