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題名 以Probit模型預測美元指數循環
Forecasting the turning points of the US dollar index by using the probit model作者 黃文基
Huang, Wen-Chi貢獻者 徐士勛
Hsu, Shih-Hsun
黃文基
Huang, Wen-Chi關鍵詞 美元指數
動態 Probit 模型
轉折點預測日期 2021 上傳時間 4-Aug-2021 15:57:59 (UTC+8) 摘要 本文建構動態Probit 模型預測美元指數循環。首先,本文以 BBQ algorithm 認定美元指數的牛熊市狀態,再透過樣本內估計結果篩選出重要變數後,進行樣本外預測評析。實證結果發現影響美元指數較為顯著且穩健的變數為美元指數在過去18 個月排名的年增率、美元指數前一期的正負值、布蘭特原油價格、美國十年期公債與兩年期公債殖利率差四個變數。樣本外預測結果有65% 的正確率,而根據預測結果組成的投資組合也可以打敗長期持有美元、s&p500、MSCI 新興市場指數。此外,我們也發現量化寬鬆政策的實施並未對本文的樣本外預測結果造成明顯的影響。 參考文獻 Ahmed, J. and S. Straetmans (2015), “Predicting Exchange Rate Cycles utilizing Risk Factors,” Journal of Empirical Finance, 34, 112–130.Basher, S. A. , A. A Haug,and P. Sadorsky (2012), “Oil Prices, Exchange Rates and Emerging Stock Markets,” Energy Economics, 34, 227–240.Bry, G. and C. Boschan (1971), “Cyclical Analysis of Time Series: Selected Procedures and Computer Programs,” NBER.Chen, S. S. (2009), “Predicting the Bear Stock Market: Macroeconomic Variables as Leading Indicators,” Journal of Banking & Finance, 33, 211-223.Gonzalez, L. , J. G. Powell , J. Shi, and A. Wilson (2005), “Two Centuries of Bull and Bear Market Cycles,” International Review of Economics & Finance, 14, 469–486.Kauppi, H. and P. Saikkonen (2008), “Predicting U.S. Recessions with DynamicBinary Response Models,” The Review of Economics and Statistics, 90, 777–791.Mikhaylov, A. Y. (2018). “Pricing in Oil Market and Using Probit Model for Analysis of Stock Market Effects, ”International Journal of Energy Economics and Policy, 8, 69-73.Nissil¨a , W. (2020), “Probit Based Time Series Models in Recession Forecasting – A Survey with an Empirical Illustration for Finland, ”BoF Economics Review.Ntantamis, C. and J. Zhou (2015), “Bull and Bear Markets in Commodity Prices and Commodity Stocks: Is There a Relation?” Resources Policy,43, 61–81.Nyberg, H. (2011), “Forecasting the Direction of The US Stock Market with Dynamic Binary Probit Models,”International Journal of Forecasing, 27, 561-578.Nyberg, H. (2013), “Predicting Bear and Bull Stock markets with Dynamic Binary Time Series Models, ”Journal of Banking and Finance, 37, 3351–3363.Samanta, S. K. and A. H. Zadeh (2012). “Co-movements of Oil, Gold, the US Dollar, and Stocks,” Modern Economy, 3, 111-117.Sartore, D. , L. Trevisan, M. Trova, and F. Volo (2002) “US Dollar/Euro Exchange Rate: a Monthly Econometric model for Forecasting,” The European Journal of Finance, 8, 480-501. 描述 碩士
國立政治大學
經濟學系
108258009資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108258009 資料類型 thesis dc.contributor.advisor 徐士勛 zh_TW dc.contributor.advisor Hsu, Shih-Hsun en_US dc.contributor.author (Authors) 黃文基 zh_TW dc.contributor.author (Authors) Huang, Wen-Chi en_US dc.creator (作者) 黃文基 zh_TW dc.creator (作者) Huang, Wen-Chi en_US dc.date (日期) 2021 en_US dc.date.accessioned 4-Aug-2021 15:57:59 (UTC+8) - dc.date.available 4-Aug-2021 15:57:59 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2021 15:57:59 (UTC+8) - dc.identifier (Other Identifiers) G0108258009 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/136555 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 108258009 zh_TW dc.description.abstract (摘要) 本文建構動態Probit 模型預測美元指數循環。首先,本文以 BBQ algorithm 認定美元指數的牛熊市狀態,再透過樣本內估計結果篩選出重要變數後,進行樣本外預測評析。實證結果發現影響美元指數較為顯著且穩健的變數為美元指數在過去18 個月排名的年增率、美元指數前一期的正負值、布蘭特原油價格、美國十年期公債與兩年期公債殖利率差四個變數。樣本外預測結果有65% 的正確率,而根據預測結果組成的投資組合也可以打敗長期持有美元、s&p500、MSCI 新興市場指數。此外,我們也發現量化寬鬆政策的實施並未對本文的樣本外預測結果造成明顯的影響。 zh_TW dc.description.tableofcontents 目錄1 前言 12 文獻回顧 13 研究方法與計量模型 33.1 Probit 模型 33.2 靜態Probit 模型與動態Probit 模型 43.3 參數估計 53.4 預測過程 53.4.1 所有變數都可取得 63.4.2 應變數落後項資料仍無法取得 63.5 ROC 與AUC 介紹 84 資料處理與基本統計性質 84.1 資料來源 84.2 應變數yt 說明 94.3 資料說明 124.4 敘述統計 134.5 資料處理 165 實證結果 165.1 變數篩選的重要性 165.2 樣本內結果與變數挑選 185.3 LASSO 方法的嘗試 225.4 樣本外結果 226 結論 297 參考文獻 30圖目錄1 兩種認列與美元指數 112 樣本內ROC 曲線243 樣本內獲利率 244 樣本外ROC 曲線255 樣本外獲利率 256 獲利圖 267 全期長週期樣本內外預測圖 27表目錄1 混淆矩陣 82 BBQ 認列的轉折點 103 變數全名對照表144 敘述統計155 ADF 檢定 176 樣本內單一變數pseudo R2 197 多變數樣本內結果(係數與P-value)8 四種情況比較圖28 zh_TW dc.format.extent 1435019 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108258009 en_US dc.subject (關鍵詞) 美元指數 zh_TW dc.subject (關鍵詞) 動態 Probit 模型 zh_TW dc.subject (關鍵詞) 轉折點預測 zh_TW dc.title (題名) 以Probit模型預測美元指數循環 zh_TW dc.title (題名) Forecasting the turning points of the US dollar index by using the probit model en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Ahmed, J. and S. Straetmans (2015), “Predicting Exchange Rate Cycles utilizing Risk Factors,” Journal of Empirical Finance, 34, 112–130.Basher, S. A. , A. A Haug,and P. Sadorsky (2012), “Oil Prices, Exchange Rates and Emerging Stock Markets,” Energy Economics, 34, 227–240.Bry, G. and C. Boschan (1971), “Cyclical Analysis of Time Series: Selected Procedures and Computer Programs,” NBER.Chen, S. S. (2009), “Predicting the Bear Stock Market: Macroeconomic Variables as Leading Indicators,” Journal of Banking & Finance, 33, 211-223.Gonzalez, L. , J. G. Powell , J. Shi, and A. Wilson (2005), “Two Centuries of Bull and Bear Market Cycles,” International Review of Economics & Finance, 14, 469–486.Kauppi, H. and P. Saikkonen (2008), “Predicting U.S. Recessions with DynamicBinary Response Models,” The Review of Economics and Statistics, 90, 777–791.Mikhaylov, A. Y. (2018). “Pricing in Oil Market and Using Probit Model for Analysis of Stock Market Effects, ”International Journal of Energy Economics and Policy, 8, 69-73.Nissil¨a , W. (2020), “Probit Based Time Series Models in Recession Forecasting – A Survey with an Empirical Illustration for Finland, ”BoF Economics Review.Ntantamis, C. and J. Zhou (2015), “Bull and Bear Markets in Commodity Prices and Commodity Stocks: Is There a Relation?” Resources Policy,43, 61–81.Nyberg, H. (2011), “Forecasting the Direction of The US Stock Market with Dynamic Binary Probit Models,”International Journal of Forecasing, 27, 561-578.Nyberg, H. (2013), “Predicting Bear and Bull Stock markets with Dynamic Binary Time Series Models, ”Journal of Banking and Finance, 37, 3351–3363.Samanta, S. K. and A. H. Zadeh (2012). “Co-movements of Oil, Gold, the US Dollar, and Stocks,” Modern Economy, 3, 111-117.Sartore, D. , L. Trevisan, M. Trova, and F. Volo (2002) “US Dollar/Euro Exchange Rate: a Monthly Econometric model for Forecasting,” The European Journal of Finance, 8, 480-501. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202100753 en_US