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| Title | 比特幣日內技術分析交易策略:以交易區間突破為例 Intraday Technical Analysis Trading Strategies in Bitcoin: A Focus on Trading Range Breakouts |
| Creator | 陳冠華 Chen, Guan-Hua |
| Contributor | 岳夢蘭 Yueh, Meng-Lan 陳冠華 Chen, Guan-Hua |
| Key Words | 比特幣 加密貨幣 日內交易 高頻交易 技術分析 交易區間突破 Bitcoin Cryptocurrency Intraday trading High-frequency trading Technical analysis Trading range breakouts |
| Date | 2024 |
| Date Issued | 5-Aug-2024 13:43:50 (UTC+8) |
| Summary | 近年來，加密貨幣市場引起了許多投資者的關注，許多學者也投入研究其中。然而，目前只有少數文章探討了日內技術分析策略在比特幣市場的預測能力與獲利能力。本文使用1分鐘高頻資料，對比特幣的日內交易區間突破策略進行了全面研究。我發現，當出現向上突破與向下突破訊號時，通常會產生顯著的正報酬。此外，研究顯示，當持有期間小於支撐阻力窗口長度的一半時，報酬率更傾向顯著異於無條件均值。自2017年以來，比特幣的日內交易區間突破策略的預測能力下降。我還檢驗了不同資料頻率的影響，發現隨著資料頻率降低，策略組合的報酬率顯著性也隨之降低，這表明比特幣市場的效率性隨著時間和資料頻率的降低而提高。最後，考慮到交易成本後，發現交易區間突破策略在比特幣日內市場中無法超越買進持有策略。 In recent years, the cryptocurrency market has attracted much attention from investors and scholars. However, only a handful of studies have looked at the predictive power and profitability of intraday technical analysis strategies in the Bitcoin market. This study examines intraday trading range breakout strategies using 1-minute high-frequency data. The results show that significant positive returns often occur after breakout signals. Shorter holding periods, less than half the support-resistance window, tend to produce returns that are different from the unconditional mean return. Since 2017, the strategy’s effectiveness has decreased. As data frequency decreases, the returns from trading range breakout strategy become insignificant. Finally, after accounting for transaction costs, the trading range breakout strategies do not outperform the buy-and-hold strategy. |
| 參考文獻 | Al-Yahyaee, K. H., Mensi, W., & Yoon, S. M. (2018). Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets. Finance Research Letters, 27, 228-234. Bariviera, A. F. (2017). The inefficiency of Bitcoin revisited: A dynamic approach. Economics Letters, 161, 1-4. Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets?. Journal of International Financial Markets, Institutions and Money, 54, 177-189. Bessembinder, H., & Chan, K. (1998). Market efficiency and the returns to technical analysis. Financial management, 5-17. Blau, B. M. (2017). Price dynamics and speculative trading in bitcoin. Research in international Business and Finance, 41, 493-499. Bouri, E., Gupta, R., Tiwari, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95. Bouri, E., Lau, C. K. M., Lucey, B., & Roubaud, D. (2019). Trading volume and the predictability of return and volatility in the cryptocurrency market. Finance Research Letters, 29, 340-346. Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?. Finance Research Letters, 20, 192-198. Brandvold, M., Molnár, P., Vagstad, K., & Valstad, O. C. A. (2015). Price discovery on Bitcoin exchanges. Journal of International Financial Markets, Institutions and Money, 36, 18-35. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of finance, 47(5), 1731-1764. Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics letters, 130, 32-36. Corbet, S., Eraslan, V., Lucey, B., & Sensoy, A. (2019). The effectiveness of technical trading rules in cryptocurrency markets. Finance Research Letters, 31, 32-37. Corbet, S., Lucey, B., & Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81-88. Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics letters, 165, 28-34. Detzel, A., Liu, H., Strauss, J., Zhou, G., & Zhu, Y. (2021). Learning and predictability via technical analysis: evidence from Bitcoin and stocks with hard‐to‐value fundamentals. Financial Management, 50(1), 107-137. Dwyer, G. P. (2015). The economics of Bitcoin and similar private digital currencies. Journal of financial stability, 17, 81-91. Dyhrberg, A. H. (2016). Hedging capabilities of bitcoin. Is it the virtual gold?. Finance Research Letters, 16, 139-144. Eross, A., McGroarty, F., Urquhart, A., & Wolfe, S. (2019). The intraday dynamics of bitcoin. Research in international business and finance, 49, 71-81. Glantz, M., & Kissell, R. (2013). Multi-asset risk modeling: techniques for a global economy in an electronic and algorithmic trading era. Academic Press. Grobys, K., Ahmed, S., & Sapkota, N. (2020). Technical trading rules in the cryptocurrency market. Finance Research Letters, 32, 101396. Hsu, P. H., Taylor, M. P., & Wang, Z. (2016). Technical trading: Is it still beating the foreign exchange market?. Journal of International Economics, 102, 188-208. Hu, B., McInish, T., Miller, J., & Zeng, L. (2019). Intraday price behavior of cryptocurrencies. Finance Research Letters, 28, 337-342. Hudson, R., & Urquhart, A. (2021). Technical trading and cryptocurrencies. Annals of Operations Research, 297(1), 191-220. Jiang, Y., Nie, H., & Ruan, W. (2018). Time-varying long-term memory in Bitcoin market. Finance Research Letters, 25, 280-284. Khairuddin, I. E., Sas, C., Clinch, S., & Davies, N. (2016, May). Exploring motivations for bitcoin technology usage. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2872-2878). Khuntia, S., & Pattanayak, J. K. (2018). Adaptive market hypothesis and evolving predictability of bitcoin. Economics Letters, 167, 26-28. Kristoufek, L. (2018). On Bitcoin markets (in) efficiency and its evolution. Physica A: statistical mechanics and its applications, 503, 257-262. Marshall, B. R., Cahan, R. H., & Cahan, J. M. (2008). Does intraday technical analysis in the US equity market have value?. Journal of Empirical Finance, 15(2), 199-210. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Olson, D. (2004). Have trading rule profits in the currency markets declined over time?. Journal of banking & Finance, 28(1), 85-105. Sensoy, A. (2019). The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies. Finance Research Letters, 28, 68-73. Su, F., Wang, X., & Yuan, Y. (2022). The intraday dynamics and intraday price discovery of bitcoin. Research in International Business and Finance, 60, 101625. Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80-82. Urquhart, A. (2017). Price clustering in Bitcoin. Economics letters, 159, 145-148. Urquhart, A., & Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, 49-57. Wyckoff, R. D. (1910). Studies in tape reading. Traders Press. Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In Handbook of digital currency (pp. 31-43). Academic Press. Zargar, F. N., & Kumar, D. (2019). Informational inefficiency of Bitcoin: A study based on high-frequency data. Research in International Business and Finance, 47, 344-353. Zhang, W., Wang, P., Li, X., & Shen, D. (2018). The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average. Physica A: Statistical Mechanics and its Applications, 510, 658-670. |
| Description | 碩士 國立政治大學 財務管理學系 111357028 |
| 資料來源 | http://thesis.lib.nccu.edu.tw/record/#G0111357028 |
| Type | thesis |
| dc.contributor.advisor | 岳夢蘭 | zh_TW |
| dc.contributor.advisor | Yueh, Meng-Lan | en_US |
| dc.contributor.author (Authors) | 陳冠華 | zh_TW |
| dc.contributor.author (Authors) | Chen, Guan-Hua | en_US |
| dc.creator (作者) | 陳冠華 | zh_TW |
| dc.creator (作者) | Chen, Guan-Hua | en_US |
| dc.date (日期) | 2024 | en_US |
| dc.date.accessioned | 5-Aug-2024 13:43:50 (UTC+8) | - |
| dc.date.available | 5-Aug-2024 13:43:50 (UTC+8) | - |
| dc.date.issued (上傳時間) | 5-Aug-2024 13:43:50 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0111357028 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/152729 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 財務管理學系 | zh_TW |
| dc.description (描述) | 111357028 | zh_TW |
| dc.description.abstract (摘要) | 近年來，加密貨幣市場引起了許多投資者的關注，許多學者也投入研究其中。然而，目前只有少數文章探討了日內技術分析策略在比特幣市場的預測能力與獲利能力。本文使用1分鐘高頻資料，對比特幣的日內交易區間突破策略進行了全面研究。我發現，當出現向上突破與向下突破訊號時，通常會產生顯著的正報酬。此外，研究顯示，當持有期間小於支撐阻力窗口長度的一半時，報酬率更傾向顯著異於無條件均值。自2017年以來，比特幣的日內交易區間突破策略的預測能力下降。我還檢驗了不同資料頻率的影響，發現隨著資料頻率降低，策略組合的報酬率顯著性也隨之降低，這表明比特幣市場的效率性隨著時間和資料頻率的降低而提高。最後，考慮到交易成本後，發現交易區間突破策略在比特幣日內市場中無法超越買進持有策略。 | zh_TW |
| dc.description.abstract (摘要) | In recent years, the cryptocurrency market has attracted much attention from investors and scholars. However, only a handful of studies have looked at the predictive power and profitability of intraday technical analysis strategies in the Bitcoin market. This study examines intraday trading range breakout strategies using 1-minute high-frequency data. The results show that significant positive returns often occur after breakout signals. Shorter holding periods, less than half the support-resistance window, tend to produce returns that are different from the unconditional mean return. Since 2017, the strategy’s effectiveness has decreased. As data frequency decreases, the returns from trading range breakout strategy become insignificant. Finally, after accounting for transaction costs, the trading range breakout strategies do not outperform the buy-and-hold strategy. | en_US |
| dc.description.tableofcontents | 1. Introduction 1 2. Literature Review. 3 2.1. Cryptocurrency literature 3 2.2. Cryptocurrency intraday literature 4 2.3. Technical analysis literature 5 3. Data and trading rules 6 3.1. Data 6 3.2. Trading rules 8 4. Empirical results 9 4.1. Main results 9 4.2. Sub-sample and different frequencies 10 4.3. Profitability considering transaction costs 11 5. Conclusion 12 Reference 14 Appendix 18 | zh_TW |
| dc.format.extent | 605753 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0111357028 | en_US |
| dc.subject (關鍵詞) | 比特幣 | zh_TW |
| dc.subject (關鍵詞) | 加密貨幣 | zh_TW |
| dc.subject (關鍵詞) | 日內交易 | zh_TW |
| dc.subject (關鍵詞) | 高頻交易 | zh_TW |
| dc.subject (關鍵詞) | 技術分析 | zh_TW |
| dc.subject (關鍵詞) | 交易區間突破 | zh_TW |
| dc.subject (關鍵詞) | Bitcoin | en_US |
| dc.subject (關鍵詞) | Cryptocurrency | en_US |
| dc.subject (關鍵詞) | Intraday trading | en_US |
| dc.subject (關鍵詞) | High-frequency trading | en_US |
| dc.subject (關鍵詞) | Technical analysis | en_US |
| dc.subject (關鍵詞) | Trading range breakouts | en_US |
| dc.title (題名) | 比特幣日內技術分析交易策略:以交易區間突破為例 | zh_TW |
| dc.title (題名) | Intraday Technical Analysis Trading Strategies in Bitcoin: A Focus on Trading Range Breakouts | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | Al-Yahyaee, K. H., Mensi, W., & Yoon, S. M. (2018). Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets. Finance Research Letters, 27, 228-234. Bariviera, A. F. (2017). The inefficiency of Bitcoin revisited: A dynamic approach. Economics Letters, 161, 1-4. Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets?. Journal of International Financial Markets, Institutions and Money, 54, 177-189. Bessembinder, H., & Chan, K. (1998). Market efficiency and the returns to technical analysis. Financial management, 5-17. Blau, B. M. (2017). Price dynamics and speculative trading in bitcoin. Research in international Business and Finance, 41, 493-499. Bouri, E., Gupta, R., Tiwari, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95. Bouri, E., Lau, C. K. M., Lucey, B., & Roubaud, D. (2019). Trading volume and the predictability of return and volatility in the cryptocurrency market. Finance Research Letters, 29, 340-346. Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?. Finance Research Letters, 20, 192-198. Brandvold, M., Molnár, P., Vagstad, K., & Valstad, O. C. A. (2015). Price discovery on Bitcoin exchanges. Journal of International Financial Markets, Institutions and Money, 36, 18-35. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of finance, 47(5), 1731-1764. Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics letters, 130, 32-36. Corbet, S., Eraslan, V., Lucey, B., & Sensoy, A. (2019). The effectiveness of technical trading rules in cryptocurrency markets. Finance Research Letters, 31, 32-37. Corbet, S., Lucey, B., & Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81-88. Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics letters, 165, 28-34. Detzel, A., Liu, H., Strauss, J., Zhou, G., & Zhu, Y. (2021). Learning and predictability via technical analysis: evidence from Bitcoin and stocks with hard‐to‐value fundamentals. Financial Management, 50(1), 107-137. Dwyer, G. P. (2015). The economics of Bitcoin and similar private digital currencies. Journal of financial stability, 17, 81-91. Dyhrberg, A. H. (2016). Hedging capabilities of bitcoin. Is it the virtual gold?. Finance Research Letters, 16, 139-144. Eross, A., McGroarty, F., Urquhart, A., & Wolfe, S. (2019). The intraday dynamics of bitcoin. Research in international business and finance, 49, 71-81. Glantz, M., & Kissell, R. (2013). Multi-asset risk modeling: techniques for a global economy in an electronic and algorithmic trading era. Academic Press. Grobys, K., Ahmed, S., & Sapkota, N. (2020). Technical trading rules in the cryptocurrency market. Finance Research Letters, 32, 101396. Hsu, P. H., Taylor, M. P., & Wang, Z. (2016). Technical trading: Is it still beating the foreign exchange market?. Journal of International Economics, 102, 188-208. Hu, B., McInish, T., Miller, J., & Zeng, L. (2019). Intraday price behavior of cryptocurrencies. Finance Research Letters, 28, 337-342. Hudson, R., & Urquhart, A. (2021). Technical trading and cryptocurrencies. Annals of Operations Research, 297(1), 191-220. Jiang, Y., Nie, H., & Ruan, W. (2018). Time-varying long-term memory in Bitcoin market. Finance Research Letters, 25, 280-284. Khairuddin, I. E., Sas, C., Clinch, S., & Davies, N. (2016, May). Exploring motivations for bitcoin technology usage. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2872-2878). Khuntia, S., & Pattanayak, J. K. (2018). Adaptive market hypothesis and evolving predictability of bitcoin. Economics Letters, 167, 26-28. Kristoufek, L. (2018). On Bitcoin markets (in) efficiency and its evolution. Physica A: statistical mechanics and its applications, 503, 257-262. Marshall, B. R., Cahan, R. H., & Cahan, J. M. (2008). Does intraday technical analysis in the US equity market have value?. Journal of Empirical Finance, 15(2), 199-210. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Olson, D. (2004). Have trading rule profits in the currency markets declined over time?. Journal of banking & Finance, 28(1), 85-105. Sensoy, A. (2019). The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies. Finance Research Letters, 28, 68-73. Su, F., Wang, X., & Yuan, Y. (2022). The intraday dynamics and intraday price discovery of bitcoin. Research in International Business and Finance, 60, 101625. Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80-82. Urquhart, A. (2017). Price clustering in Bitcoin. Economics letters, 159, 145-148. Urquhart, A., & Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, 49-57. Wyckoff, R. D. (1910). Studies in tape reading. Traders Press. Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In Handbook of digital currency (pp. 31-43). Academic Press. Zargar, F. N., & Kumar, D. (2019). Informational inefficiency of Bitcoin: A study based on high-frequency data. Research in International Business and Finance, 47, 344-353. Zhang, W., Wang, P., Li, X., & Shen, D. (2018). The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average. Physica A: Statistical Mechanics and its Applications, 510, 658-670. | zh_TW |