| 研究生: |
邱芝螢 Chiu, Jhih-Ying |
|---|---|
| 論文名稱: |
是否有比歷史平均法更有效預測股票市場溢酬的方法?-以美國市場為例 Is there a way to predict the stock market risk premium better than historical average? Evidence from the US market stock market |
| 指導教授: |
顏佑銘
Yen, Yu-Min |
| 口試委員: |
顏佑銘
Yen, Yu-Min 謝淑貞 Shieh, Shwu-Jane 張子溥 Chang, Tzu-Pu |
| 學位類別: |
碩士
Master |
| 系所名稱: |
商學院 - 國際經營與貿易學系 Department of International Business |
| 論文出版年: | 2020 |
| 畢業學年度: | 108 |
| 語文別: | 中文 |
| 論文頁數: | 25 |
| 中文關鍵詞: | 股票市場溢酬 、樣本外測試 、模型平均法 |
| 外文關鍵詞: | Stock market premium, Out of sample test, Model averaging |
| DOI URL: | http://doi.org/10.6814/NCCU202001021 |
| 相關次數: | 點閱:248 下載:2 |
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本研究乃運用Welch and Goyal(2008)所提出的1945年至2018年的十二項經濟變數資料去預測股票市場溢酬。首先重新檢驗單一變數的樣本內測試(in-sample test)及樣本外測試(out-of-sample test)的結果,接著透過組合變數模型估計,最後再以模型平均法(Model Averaging)建構新的模型。希望藉由新的建構模型方法,比較不同預測模型的預測能力。實證結果發現,以上所建構的模型,皆無法打敗歷史平均法(historical average method)。
In this paper, I use the twelve economic variables of Welch and Goyal (2008) to predict the stock market premium. First of all, I reexamine the in-sample and out-of-sample test. After that, I establish the combination variable to predict the stock market. Finally, I use the model averaging to establish new models. Empirical results display that, the whole models fail to beat the historical average.
論文審定書 i
謝辭 ii
摘要 iii
Abstract iv
第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究架構(流程) 2
第二章 文獻回顧 3
第三章 研究方法 6
第一節 單一變數 6
第二節 組合變數 6
第三節 模型平均 6
第四節 預測結果評估 7
第四章 實證分析 9
第一節 樣本說明 9
第二節 單一變數 10
第三節 組合變數 17
第四節 模型平均 19
第五章 結論 23
參考文獻 24
中文參考文獻
1.陳旭昇(2009),"時間序列-總體經濟與財務金融與財務金融之應用”,台北:東華書局
英文參考文獻
1.Ang, Andrew Bekaert, Geert. (2007) “Stock return predictability: Is it there? “, Review of Financial Studies, 651-707
2.Baetje, FabianMenkhoff, Lukas.(2016) “Equity premium prediction: Are economic and technical indicators unstable?”, International Journal of Forecasting, 1193-1207
3.Campbell, John Y.Thompson, Samuel B.( 2008) “Predicting excess stock returns out of sample: Can anything beat the historical average? ”, Review of Financial Studies, 1509-1531
4.Cenesizoglu, Tolga Timmermann, Allan (2012) “Do return prediction models add economic value?”, Journal of Banking and Finance, 2974-2987
5.Cochrane, John H.(2008) “The dog that did not bark: A defense of return predictability”, Review of Financial Studies, 1533-1575
6.Cremers, K. J.Martijn (2002) “Stock Return Predictability: A Bayesian Model Selection Perspective”, Review of Financial Studies, 1223-1249
7.Hjalmarsson, Erik (2010) “Predicting global stock returns”, Journal of Financial and Quantitative Analysis, 49-80
8.Li, Jiahan Tsiakas, Ilias (2017) “Equity premium prediction: The role of economic and statistical constraints”, Journal of Financial Markets, 56-75
9.Neely, Christopher J. Rapach, David E. Tu, Jun Zhou, Guofu (2014) “Forecasting the equity risk premium: The role of technical indicators”, Management Science, 1772-1791
10.Pettenuzzo, Davide Timmermann, Allan Valkanov, Rossen (2014) “Forecasting stock returns under economic constraints” , Journal of Financial Economics, 517-553
11.Paye, Bradley S. Timmermann, Allan (2006) “Instability of return prediction models”, Journal of Empirical Finance, 274-315
12.Rapach, David E. Strauss, Jack K. Zhou, Guofu (2010) “Out-of-sample equity premium prediction: Combination forecasts and links to the real economy”, Review of Financial Studies, 821-862
13.Welch, Goyal (2008) “A Comprehensive Look at The Empirical Performance of Equity Premium Prediction”, The Review of Financial Studies, 1455-1508