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題名 比特幣與匯率、股市及景氣關聯性之研究
The research of the relationship among Bitcoin, exchange rates, stock markets and economy
作者 洪詩婷
Hung, Shih-Ting
貢獻者 鄭宇庭
Cheng, Yu-Ting
洪詩婷
Hung, Shih-Ting
關鍵詞 比特幣
單根檢定
共整合檢定
Granger因果關係檢定
Bitcoin
Unit test
Co-integration test
Granger causality test
日期 2018
上傳時間 3-七月-2018 17:38:35 (UTC+8)
摘要 2008年金融海嘯為全球帶來衝擊，比特幣的出現解決人民不信任政府之問題，但其暴漲暴跌之特性卻為投資人帶來極大的風險及不安定感，虛擬貨幣正逐漸改變我們既有的貨幣體系及支付系統，如何看待虛擬貨幣已是不容忽視之議題。本研究目的為分析比特幣議題在台灣之發展情況，並探討在研究期間美元兌比特幣與重要經濟變數間之關聯性，以期提供投資人擬定投資決策的參考準則。
     本研究之研究期間為2013年1月1日至2017年12月31日，採用單根檢定、共整合檢定與Granger因果關係檢定等研究方法，針對美元兌比特幣與重要經濟變數等資料進行實證分析。單根檢定結果顯示，所有研究變數均呈現非定態之隨機漫步走勢，經一階差分後，即成為定態時間序列；藉由Johansen共整合檢定，發現美元兌比特幣與美元兌日圓、美國道瓊工業指數、50檔高級葡萄酒指數具有長期均衡關係，表示短期可能產生偏離，但長期會往均衡方向調整，針對短期之動態關係，本研究建構向量誤差修正模型（VECM）進行修正；再透過Granger因果關係檢定探討變數間之領先落後關係，分析結果得知美元兌比特幣與標準普爾全球奢侈品指數、日經平均指數存在單向因果關係，即美元兌比特幣為標準普爾全球奢侈品指數、日經平均指數的因。
A financial crisis exploded around the world in 2008. At the same time, the Bitcoin was launched by Satoshi Nakamoto and solved the problem that people distrusted the government. However, price instability brings risks and uncertainty to investors. Virtual currencies have been transforming the existing monetary systems and payment methods. Consequently, we should place importance on the issue about how to treat virtual currencies. The purpose of this research isn’t only to analyze the development of the Bitcoin in Taiwan but investigate the relationships between Bitcoin and economic variables. We expect to help investors develop appropriate investment strategies.
     The research period is from 2013 to 2017. In our empirical analysis, we apply unit test, co-integration test and Granger causality test to examine the relationships. The result of unit test shows that all research variables are nonstationary and become stationary after first difference. Through co-integration test, we find that the Bitcoin price bears the long-run equilibrium relationship with the exchange rate of Japanese yen, Dow Jones Industrial Average and the Liv-ex 50 Fine Wine Index. Moreover, we build the VECM to evaluate the short-run dynamic relationships. Granger causality test is used to investigate whether the Bitcoin price bears the lead-lag relations to other variables. The result shows that the Bitcoin price has the causality between NK225 and S&P Global Luxury Index.
參考文獻 一、 中文文獻
     1. 王柏雅（2017）。虛擬貨幣兌美元價格指數兩階段預測模型 –以比特幣為例。天主教輔仁大學應用統計研究所碩士論文，新北市。
     2. 李庭安（2017）。比特幣與主要使用國家貨幣之匯率關係。淡江大學國際企業管理研究所碩士論文，新北市。
     3. 張紹勳（2012）。計量經濟及高等研究法。五南圖書出版股份有限公司。
     4. 莊秋欣（2017）。三種虛擬貨幣之比較與股市關聯性之研究。中原大學企業管理研究所碩士論文，桃園市。
     5. 陳旭昇（2013）。時間序列分析–總體經濟與財務金融之應用。臺灣東華書局股份有限公司。
     6. 黃宣凱（2017）。事件因素對比特幣價格之影響。國立台北大學國際財務金融碩士在職專班碩士論文，新北市。
     7. 楊馥安（2015）。虛擬貨幣的可投資性研究–以比特幣為例。中原大學企業管理研究所碩士論文，桃園市。
     8. 謝邦昌、鄭宇庭、謝邦彥（2017）。玩轉社群：文字大數據實作。五南圖書出版股份有限公司。
     9. 鍾惠民、周賓凰、孫而音（2009）。財務計量：E-views的運用。新陸書局股份有限公司。
      
     二、 英文文獻
     1. Bouoiyour, J. & Selmi, R. (2015). What does Bitcoin look like?. Annals of Economics & Finance, 16(2).
     2. Brière, M., Oosterlinck, K. & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with bitcoin. Journal of Asset Management, 16(6), 365-373.
     3. Batchelor, R., Alizadeh, A. & Visvikis, I. (2007). Forecasting spot and forward prices in the international freight market. International Journal of Forecasting, 23(1), 101-114.
     4. Commodity Futures Trading Commission (2018). Customer Advisory: Understand the Risks of Virtual Currency Trading.
     5. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.
     6. European Central Bank (2015). Virtual Currency Schemes-a Further Analysis, Feb.
     7. Engle, R. F. & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
     8. Enders, W. (2008). Applied econometric time series. John Wiley & Sons.
     9. European Commission (2016). Proposal for amending Directive (EU) 2015/849 on the prevention of the use of the financial system for the purposes of money laundering or terrorist financing.
     10. Granger, C. W. & Newbold, P. (1974). Spurious regressions in econometrics. Journal of econometrics, 2(2), 111-120.
     11. Gonzalo, J. (1994). Five alternative methods of estimating long-run equilibrium relationships. Journal of econometrics, 60(1-2), 203-233.
     12. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438.
     13. Gandal, N. & Halaburda, H. (2014). Competition in the cryptocurrency market.
     14. Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of economic dynamics and control, 12(2-3), 231-254.
     15. Johansen, S. & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and statistics, 52(2), 169-210.
     16. Kristoufek, L. (2013). BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Report, 3, 3415.
     17. Kaminski, J. (2016). Nowcasting the bitcoin market with twitter signals. arXiv preprint arXiv:1406.7577.
     18. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.
     19. Nelson, C. R. & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series: some evidence and implications. Journal of monetary economics, 10(2), 139-162.
     20. Pavel C., Miroslava R. & d’Artis K. (2015). The economics of BitCoin price formation, Applied Economics, 48:19, 1799-1815.
     21. Phillips, P. C. & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
     22. Said, S. E. & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
     23. Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 1-48.
     24. Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In Handbook of digital currency (pp. 31-43).
     三、 網路資源
     1. Bitcoin price and volume, from https://bitcoinity.org/
     2. Federal Reserve Economic Data, from https://fred.stlouisfed.org/
     3. Financial, Economic and Alternative Data, from https://www.quandl.com/
     4. S&P Dow Jones Indices, from https://us.spindices.com/
     5. Yahoo Finance–Business Finance, Stock Market, Quotes, News, from https://finance.yahoo.com/
描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
105363080
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105363080
資料類型 thesis
dc.contributor.advisor 鄭宇庭zh_TW
dc.contributor.advisor Cheng, Yu-Tingen_US
dc.contributor.author (作者) 洪詩婷zh_TW
dc.contributor.author (作者) Hung, Shih-Tingen_US
dc.creator (作者) 洪詩婷zh_TW
dc.creator (作者) Hung, Shih-Tingen_US
dc.date (日期) 2018en_US
dc.date.accessioned 3-七月-2018 17:38:35 (UTC+8)-
dc.date.available 3-七月-2018 17:38:35 (UTC+8)-
dc.date.issued (上傳時間) 3-七月-2018 17:38:35 (UTC+8)-
dc.identifier (其他 識別碼) G0105363080en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/118315-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所(MBA學位學程)zh_TW
dc.description (描述) 105363080zh_TW
dc.description.abstract (摘要) 2008年金融海嘯為全球帶來衝擊，比特幣的出現解決人民不信任政府之問題，但其暴漲暴跌之特性卻為投資人帶來極大的風險及不安定感，虛擬貨幣正逐漸改變我們既有的貨幣體系及支付系統，如何看待虛擬貨幣已是不容忽視之議題。本研究目的為分析比特幣議題在台灣之發展情況，並探討在研究期間美元兌比特幣與重要經濟變數間之關聯性，以期提供投資人擬定投資決策的參考準則。
     本研究之研究期間為2013年1月1日至2017年12月31日，採用單根檢定、共整合檢定與Granger因果關係檢定等研究方法，針對美元兌比特幣與重要經濟變數等資料進行實證分析。單根檢定結果顯示，所有研究變數均呈現非定態之隨機漫步走勢，經一階差分後，即成為定態時間序列；藉由Johansen共整合檢定，發現美元兌比特幣與美元兌日圓、美國道瓊工業指數、50檔高級葡萄酒指數具有長期均衡關係，表示短期可能產生偏離，但長期會往均衡方向調整，針對短期之動態關係，本研究建構向量誤差修正模型（VECM）進行修正；再透過Granger因果關係檢定探討變數間之領先落後關係，分析結果得知美元兌比特幣與標準普爾全球奢侈品指數、日經平均指數存在單向因果關係，即美元兌比特幣為標準普爾全球奢侈品指數、日經平均指數的因。		zh_TW
dc.description.abstract (摘要) A financial crisis exploded around the world in 2008. At the same time, the Bitcoin was launched by Satoshi Nakamoto and solved the problem that people distrusted the government. However, price instability brings risks and uncertainty to investors. Virtual currencies have been transforming the existing monetary systems and payment methods. Consequently, we should place importance on the issue about how to treat virtual currencies. The purpose of this research isn’t only to analyze the development of the Bitcoin in Taiwan but investigate the relationships between Bitcoin and economic variables. We expect to help investors develop appropriate investment strategies.
     The research period is from 2013 to 2017. In our empirical analysis, we apply unit test, co-integration test and Granger causality test to examine the relationships. The result of unit test shows that all research variables are nonstationary and become stationary after first difference. Through co-integration test, we find that the Bitcoin price bears the long-run equilibrium relationship with the exchange rate of Japanese yen, Dow Jones Industrial Average and the Liv-ex 50 Fine Wine Index. Moreover, we build the VECM to evaluate the short-run dynamic relationships. Granger causality test is used to investigate whether the Bitcoin price bears the lead-lag relations to other variables. The result shows that the Bitcoin price has the causality between NK225 and S&P Global Luxury Index.		en_US
dc.description.tableofcontents 摘要 I
     ABSTRACT II
     目 錄 III
     表目錄 V
     圖目錄 VII
     第一章 緒論 1
     第一節 研究背景 1
     第二節 研究動機及目的 2
     第三節 研究架構與流程 3
     第二章 文獻探討 5
     第一節 虛擬貨幣 5
     第二節 比特幣 6
     第三節 比特幣相關研究 7
     第三章 研究方法 19
     第一節 研究流程 19
     第二節 單根檢定 21
     第三節 共整合檢定 24
     第四節 向量自我迴歸模型（VAR）與向量誤差修正模型（VECM） 25
     第五節 GRANGER因果關係檢定 27
     第四章 實證研究 29
     第一節 研究對象與資料來源 29
     第二節 經濟變數之敘述性統計 31
     第三節 文字探勘分析 33
     第四節 單根檢定結果 43
     第五節 共整合檢定結果 45
     第六節 向量自我迴歸模型（VAR）與向量誤差修正模型（VECM） 47
     第七節 GRANGER因果關係檢定結果 59
     第五章 結論與建議 62
     第一節 結論 62
     第二節 後續研究建議 63
     參考文獻 65		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105363080en_US
dc.subject (關鍵詞) 比特幣zh_TW
dc.subject (關鍵詞) 單根檢定zh_TW
dc.subject (關鍵詞) 共整合檢定zh_TW
dc.subject (關鍵詞) Granger因果關係檢定zh_TW
dc.subject (關鍵詞) Bitcoinen_US
dc.subject (關鍵詞) Unit testen_US
dc.subject (關鍵詞) Co-integration testen_US
dc.subject (關鍵詞) Granger causality testen_US
dc.title (題名) 比特幣與匯率、股市及景氣關聯性之研究zh_TW
dc.title (題名) The research of the relationship among Bitcoin, exchange rates, stock markets and economyen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 一、 中文文獻
     1. 王柏雅（2017）。虛擬貨幣兌美元價格指數兩階段預測模型 –以比特幣為例。天主教輔仁大學應用統計研究所碩士論文，新北市。
     2. 李庭安（2017）。比特幣與主要使用國家貨幣之匯率關係。淡江大學國際企業管理研究所碩士論文，新北市。
     3. 張紹勳（2012）。計量經濟及高等研究法。五南圖書出版股份有限公司。
     4. 莊秋欣（2017）。三種虛擬貨幣之比較與股市關聯性之研究。中原大學企業管理研究所碩士論文，桃園市。
     5. 陳旭昇（2013）。時間序列分析–總體經濟與財務金融之應用。臺灣東華書局股份有限公司。
     6. 黃宣凱（2017）。事件因素對比特幣價格之影響。國立台北大學國際財務金融碩士在職專班碩士論文，新北市。
     7. 楊馥安（2015）。虛擬貨幣的可投資性研究–以比特幣為例。中原大學企業管理研究所碩士論文，桃園市。
     8. 謝邦昌、鄭宇庭、謝邦彥（2017）。玩轉社群：文字大數據實作。五南圖書出版股份有限公司。
     9. 鍾惠民、周賓凰、孫而音（2009）。財務計量：E-views的運用。新陸書局股份有限公司。
      
     二、 英文文獻
     1. Bouoiyour, J. & Selmi, R. (2015). What does Bitcoin look like?. Annals of Economics & Finance, 16(2).
     2. Brière, M., Oosterlinck, K. & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with bitcoin. Journal of Asset Management, 16(6), 365-373.
     3. Batchelor, R., Alizadeh, A. & Visvikis, I. (2007). Forecasting spot and forward prices in the international freight market. International Journal of Forecasting, 23(1), 101-114.
     4. Commodity Futures Trading Commission (2018). Customer Advisory: Understand the Risks of Virtual Currency Trading.
     5. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.
     6. European Central Bank (2015). Virtual Currency Schemes-a Further Analysis, Feb.
     7. Engle, R. F. & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
     8. Enders, W. (2008). Applied econometric time series. John Wiley & Sons.
     9. European Commission (2016). Proposal for amending Directive (EU) 2015/849 on the prevention of the use of the financial system for the purposes of money laundering or terrorist financing.
     10. Granger, C. W. & Newbold, P. (1974). Spurious regressions in econometrics. Journal of econometrics, 2(2), 111-120.
     11. Gonzalo, J. (1994). Five alternative methods of estimating long-run equilibrium relationships. Journal of econometrics, 60(1-2), 203-233.
     12. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438.
     13. Gandal, N. & Halaburda, H. (2014). Competition in the cryptocurrency market.
     14. Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of economic dynamics and control, 12(2-3), 231-254.
     15. Johansen, S. & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and statistics, 52(2), 169-210.
     16. Kristoufek, L. (2013). BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Report, 3, 3415.
     17. Kaminski, J. (2016). Nowcasting the bitcoin market with twitter signals. arXiv preprint arXiv:1406.7577.
     18. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.
     19. Nelson, C. R. & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series: some evidence and implications. Journal of monetary economics, 10(2), 139-162.
     20. Pavel C., Miroslava R. & d’Artis K. (2015). The economics of BitCoin price formation, Applied Economics, 48:19, 1799-1815.
     21. Phillips, P. C. & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
     22. Said, S. E. & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
     23. Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 1-48.
     24. Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In Handbook of digital currency (pp. 31-43).
     三、 網路資源
     1. Bitcoin price and volume, from https://bitcoinity.org/
     2. Federal Reserve Economic Data, from https://fred.stlouisfed.org/
     3. Financial, Economic and Alternative Data, from https://www.quandl.com/
     4. S&P Dow Jones Indices, from https://us.spindices.com/
     5. Yahoo Finance–Business Finance, Stock Market, Quotes, News, from https://finance.yahoo.com/		zh_TW
dc.identifier.doi (DOI) 10.6814/THE.NCCU.MBA.002.2018.F08-