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題名 金融海嘯及海嘯後之台美匯率預測
Exchange rate forecasting during and after the financial crisis in Taiwan作者 謝仲
Hsieh, Chung貢獻者 林建秀
謝仲
Hsieh, Chung關鍵詞 匯率
泰勒法則模型
樣本外預測
台美匯率
exchange rate
Taylor rule models
out-of-sample
USD/NTD日期 2015 上傳時間 13-七月-2015 11:08:57 (UTC+8) 摘要 本篇論文使用out-of-sample之匯率預測方法，並使用泰勒法則模型及基礎模型，來比較各模型的預測能力，樣本為金融海嘯期間2007/4-2012/6之台美匯率及金融海嘯後2012/7-2014/8之台美匯率，為了更有效捕捉台美政府的政策變動，我們將失業率缺口也加入模型中，但研究結果發現泰勒法則模型仍較適用產出缺口，使用產出缺口的模型較能打敗隨機預測模型在金融海嘯期間以及金融海嘯後期間。而Taylor rule fundamental models在金融海嘯期間表現較好，Taylor rule differential models則在金融海嘯後期間表現較好，除此之外，購買力平價模型也有相當好的表現。
This thesis evaluates out-of-sample exchange rate predictability of Taylor rule models and fundamental models, such as Purchasing Power Parity models, monetary models and interest rate differential models, using the USD/NTD exchange rate with real-time data during, and after the financial crisis. To capture the policy of the central bank’s policies, we use the output or the unemployment gap in Taylor rule models. While Taylor rule models with output gap outperformed the random walk model during and after financial crisis, Taylor rule models with unemployment gap rarely beat the random walk model. Purchasing Power Parity model’s predictability was also better than the random walk model during and after financial crisis. The performance of Taylor rule fundamental models was better during the financial crisis and the performance of Taylor rule differential models was better after the financial crisis.參考文獻 1. Blinder, Alan S. and Ricardo Reis (2005), “Understanding the Greenspan Standard”, The Greenspan Era: Lessons for the Future, Federal Reserve Bank of Kansas City, 2005, pp. 11-96.\n2. Chinn, Menzie D. (2006), “A Primer on Real Effective Exchange Rates: Determinants, Overvaluation, Trade Flows and Competitive Devaluation”, Open economies review 17.pp. 115–143.\n3. Campbell, John Y., and Thompson, Samuel B. (2008), “Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?” , Review of Financial Studies. 21(4).pp. 1509-1531..\n4. Clark, Todd E., and West, Kenneth D. (2006), “Approximately normal tests for equal predictive accuracy in nested models”, NBER Technical Working Paper No. 326.\n5. Clark, Todd E., and West Kenneth D. (2006), “Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis”, Journal of Econometrics 135, pp. 155-186.\n6. Diebold, Francis X. , and Mariano ,Roberto S. (1995), “Comparing Predictive Accuracy”, Journal of Business and Economic Statistics 13, pp. 253-265.\n7. Diebold, Francis X. (2013), “Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests”, Journal of Business and Economic Statistics, Published online: 26 Jan 2015\n8. Engel, Charles, Nelson C. Mark, and Kenneth D. West (2008), “Exchange Rate Models Are Not as Bad as You Think”, NBER Macroeconomics Annual 2007, University of Chicago Press, pp. 381-441\n9. Mark, Nelson (1995), “Exchange Rate and Fundamentals: Evidence on Long-Horizon Predictability”, American Economic Review 85, pp. 201-218.\n10. Meese, Richard A. and Kenneth Rogoff (1983), “Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?”, Journal of International Economics 14, pp.3-24.\n11. Molodtsova, Tanya, and David H. Papell, David (2009),”Exchange Rate Predictability with Taylor Rule Fundamentals”, Journal of International Economics 77, pp.167-180.\n12. Molodtsova, Tanya, and David H. Papell (2012), “Taylor Rule Exchange Rate Forecasting During The Financial Crisis”, NBER Working Paper No. 18330.\n13. Nikolsko-Rzhevskyy, Alex, and Papell, David H. (2012), “Taylor’s Rule versus Taylor Rules”, International Finance Volume 16, Issue 1, pp. 71–93.\n14. Pasquale Della Corte, and Ilias Tsiakas (2012), “Statistical and Economic Methods for Evaluating Exchange Rate Predictability”, Handbook of exchange rates 2012.\n15. Rudebusch, Glenn (2010), “The Fed’s Exit Strategy for Monetary Policy”, Federal Reserve Bank of San Francisco Economic Letter 18, pp. 1-5.\n16. Taylor, John B. (1993), “Discretion versus policy rules in practice”, Carnegie-Rochester conference series on public policy 39, pp. 195-214.\n17. Woodford, Michael (2001), “The Taylor Rule and Optimal Monetary Policy”, The American Economic Review. pp. 232-237.\n18. Welch, Ivo and Goyal, Amit (2008), “A Comprehensive Look at The Empirical Performance of Equity Premium Prediction”. Review of Financial Studies. 21(4).pp. 1455-1508. 描述 碩士
國立政治大學
金融研究所
102352029
103資料來源 http://thesis.lib.nccu.edu.tw/record/#G0102352029 資料類型 thesis dc.contributor.advisor 林建秀 zh_TW dc.contributor.author (作者) 謝仲 zh_TW dc.contributor.author (作者) Hsieh, Chung en_US dc.creator (作者) 謝仲 zh_TW dc.creator (作者) Hsieh, Chung en_US dc.date (日期) 2015 en_US dc.date.accessioned 13-七月-2015 11:08:57 (UTC+8) - dc.date.available 13-七月-2015 11:08:57 (UTC+8) - dc.date.issued (上傳時間) 13-七月-2015 11:08:57 (UTC+8) - dc.identifier (其他 識別碼) G0102352029 en_US dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=85265 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 金融研究所 zh_TW dc.description (描述) 102352029 zh_TW dc.description (描述) 103 zh_TW dc.description.abstract (摘要) 本篇論文使用out-of-sample之匯率預測方法，並使用泰勒法則模型及基礎模型，來比較各模型的預測能力，樣本為金融海嘯期間2007/4-2012/6之台美匯率及金融海嘯後2012/7-2014/8之台美匯率，為了更有效捕捉台美政府的政策變動，我們將失業率缺口也加入模型中，但研究結果發現泰勒法則模型仍較適用產出缺口，使用產出缺口的模型較能打敗隨機預測模型在金融海嘯期間以及金融海嘯後期間。而Taylor rule fundamental models在金融海嘯期間表現較好，Taylor rule differential models則在金融海嘯後期間表現較好，除此之外，購買力平價模型也有相當好的表現。 zh_TW dc.description.abstract (摘要) This thesis evaluates out-of-sample exchange rate predictability of Taylor rule models and fundamental models, such as Purchasing Power Parity models, monetary models and interest rate differential models, using the USD/NTD exchange rate with real-time data during, and after the financial crisis. To capture the policy of the central bank’s policies, we use the output or the unemployment gap in Taylor rule models. While Taylor rule models with output gap outperformed the random walk model during and after financial crisis, Taylor rule models with unemployment gap rarely beat the random walk model. Purchasing Power Parity model’s predictability was also better than the random walk model during and after financial crisis. The performance of Taylor rule fundamental models was better during the financial crisis and the performance of Taylor rule differential models was better after the financial crisis. en_US dc.description.tableofcontents 1.Introduction\n1.1 Research motivation 2\n2.Literature Review\n2.1 Exchange rate forecasting models 5\n2.2 Performance evaluation 6\n3. Methodology\n3.1 Exchange rate forecasting model 7\n3.2 Statistical Evaluation of Exchange Rate Predictability 14\n4. Results\n4.1 Real-Time Data 17\n4.2 Descriptive Statistics 20\n4.3 Empirical results 21\n4.4 Summary of results 25\n5. Conclusion 28 zh_TW dc.format.extent 918195 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0102352029 en_US dc.subject (關鍵詞) 匯率 zh_TW dc.subject (關鍵詞) 泰勒法則模型 zh_TW dc.subject (關鍵詞) 樣本外預測 zh_TW dc.subject (關鍵詞) 台美匯率 zh_TW dc.subject (關鍵詞) exchange rate en_US dc.subject (關鍵詞) Taylor rule models en_US dc.subject (關鍵詞) out-of-sample en_US dc.subject (關鍵詞) USD/NTD en_US dc.title (題名) 金融海嘯及海嘯後之台美匯率預測 zh_TW dc.title (題名) Exchange rate forecasting during and after the financial crisis in Taiwan en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 1. Blinder, Alan S. and Ricardo Reis (2005), “Understanding the Greenspan Standard”, The Greenspan Era: Lessons for the Future, Federal Reserve Bank of Kansas City, 2005, pp. 11-96.\n2. Chinn, Menzie D. (2006), “A Primer on Real Effective Exchange Rates: Determinants, Overvaluation, Trade Flows and Competitive Devaluation”, Open economies review 17.pp. 115–143.\n3. Campbell, John Y., and Thompson, Samuel B. (2008), “Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?” , Review of Financial Studies. 21(4).pp. 1509-1531..\n4. Clark, Todd E., and West, Kenneth D. (2006), “Approximately normal tests for equal predictive accuracy in nested models”, NBER Technical Working Paper No. 326.\n5. Clark, Todd E., and West Kenneth D. (2006), “Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis”, Journal of Econometrics 135, pp. 155-186.\n6. Diebold, Francis X. , and Mariano ,Roberto S. (1995), “Comparing Predictive Accuracy”, Journal of Business and Economic Statistics 13, pp. 253-265.\n7. Diebold, Francis X. (2013), “Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests”, Journal of Business and Economic Statistics, Published online: 26 Jan 2015\n8. Engel, Charles, Nelson C. Mark, and Kenneth D. West (2008), “Exchange Rate Models Are Not as Bad as You Think”, NBER Macroeconomics Annual 2007, University of Chicago Press, pp. 381-441\n9. Mark, Nelson (1995), “Exchange Rate and Fundamentals: Evidence on Long-Horizon Predictability”, American Economic Review 85, pp. 201-218.\n10. Meese, Richard A. and Kenneth Rogoff (1983), “Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?”, Journal of International Economics 14, pp.3-24.\n11. Molodtsova, Tanya, and David H. Papell, David (2009),”Exchange Rate Predictability with Taylor Rule Fundamentals”, Journal of International Economics 77, pp.167-180.\n12. Molodtsova, Tanya, and David H. Papell (2012), “Taylor Rule Exchange Rate Forecasting During The Financial Crisis”, NBER Working Paper No. 18330.\n13. Nikolsko-Rzhevskyy, Alex, and Papell, David H. (2012), “Taylor’s Rule versus Taylor Rules”, International Finance Volume 16, Issue 1, pp. 71–93.\n14. Pasquale Della Corte, and Ilias Tsiakas (2012), “Statistical and Economic Methods for Evaluating Exchange Rate Predictability”, Handbook of exchange rates 2012.\n15. Rudebusch, Glenn (2010), “The Fed’s Exit Strategy for Monetary Policy”, Federal Reserve Bank of San Francisco Economic Letter 18, pp. 1-5.\n16. Taylor, John B. (1993), “Discretion versus policy rules in practice”, Carnegie-Rochester conference series on public policy 39, pp. 195-214.\n17. Woodford, Michael (2001), “The Taylor Rule and Optimal Monetary Policy”, The American Economic Review. pp. 232-237.\n18. Welch, Ivo and Goyal, Amit (2008), “A Comprehensive Look at The Empirical Performance of Equity Premium Prediction”. Review of Financial Studies. 21(4).pp. 1455-1508. zh_TW
