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題名 建模加密貨幣中的相互激發跳躍過程:來自比特幣和以太幣的證據
Modeling Mutually Exciting Jump Processes in Cryptocurrency:Evidence from BTC and ETH
作者 張宏圖
Chang, Hung-Tu
貢獻者 林士貴
Lin, Shih-Kuei
張宏圖
Chang, Hung-Tu
關鍵詞 相互激發跳躍過程
傳染效應
加密貨幣
交易策略
Mutually-Exciting Jump Processes
Contagion Effect
Cryptocurrency
Trading Strategy
日期 2024
上傳時間 5-Aug-2024 12:17:59 (UTC+8)
摘要 本文旨在利用相互激發跳躍過程（Mutually-Exciting Jump Processes）來驗證加密貨幣市場中的傳染效應（Contagion Effect）。為了測試模型的有效性，我們還構建了相關的交易策略。研究資料涵蓋了2020和2021年的資金狂熱時期、2022年的市場低迷，以及2023和2024年市場復甦的階段。這種多變的市場環境使得模型的成功更具說服力。研究結果顯示，相互激發模型能更準確地捕捉市場情緒，不論從統計上的結果或是交易策略在樣本外的表現，我們論文所提出的相互激勵模型都比自我激勵模型表現得更加優良。在未來的研究中，可以使用更高頻率的時間架構來探討更微觀的市場結構。
This paper aims to utilize mutually-exciting jump processes to verify the contagion effect in the cryptocurrency market. To test the effectiveness of the model, we also constructed relevant trading strategies. The study data encompasses the financial frenzy of 2020 and 2021, the market downturn of 2022, and the recovery phases of 2023 and 2024. This diverse market environment enhances the persuasiveness of the model's success. The results indicate that the mutually exciting model can more accurately capture market sentiment. Both the statistical results and the out-of-sample performance of the trading strategies demonstrate that the mutually exciting model outperforms the self-exciting model proposed in our paper. In future research, higher frequency time frameworks can be employed to explore more microscopic market structures.
參考文獻 Aït-Sahalia, Y., J. Cacho-Diaz, and R. J. Laeven (2015). Modeling financial contagion using mutually exciting jump processes. Journal of Financial Economics 117(3), 585–606. Arteaga-Garavito, M. J., M. M. Croce, P. Farroni, and I. Wolfskeil (2024). When the mar kets get co. vid: Contagion, viruses, and information diffusion. Journal of Financial Economics 157, 103850. Bates, D. S. (1996). Jumps and stochastic volatility: Exchange rate processes implicit in deutsche mark options. The Review of Financial Studies 9(1), 69–107. Bouri, E., D. Roubaud, and S. J. H. Shahzad (2020). Do bitcoin and other cryptocurrencies jump together? The Quarterly Review of Economics and Finance 76, 396–409. Chaim, P. and M. P. Laurini (2018). Volatility and return jumps in bitcoin. Economics Let ters 173, 158–163. Chen, J. (2022). Forecasting bitcoin. Working Paper. da GamaSilva, P.V.J., M.C.Klotzle, A.C.F.Pinto, andL.L.Gomes(2019). Herdingbehavior and contagion in the cryptocurrency market. Journal of Behavioral and Experimental Finance 22, 41–50. Duffie, D., J. Pan, and K. Singleton (2000). Transform analysis and asset pricing for affine jump-diffusions. Econometrica 68(6), 1343–1376. Eraker, B. (2004). Do stock prices and volatility jump? reconciling evidence from spot and option prices. The Journal of Finance 59(3), 1367–1403. 30 Ferreira, P. and É. Pereira (2019). Contagion effect in cryptocurrency market. Journal of Risk and Financial Management 12(3), 115. Hawkes, A. G. (1971a). Point spectra of some mutually exciting point processes. Journal of the Royal Statistical Society Series B: Statistical Methodology 33(3), 438–443. Hawkes, A. G. (1971b). Spectra of some self-exciting and mutually exciting point processes. Biometrika 58(1), 83–90. Hu, Y., X. Li, and D. Shen (2020). Attention allocation and international stock return co movement: evidence from the bitcoin market. Research in International Business and Finance 54, 101286. Klein, T., H. P. Thu, and T. Walther (2018). Bitcoin is not the new gold–a comparison of volatil ity, correlation, and portfolio performance. International Review of Financial Analy sis 59, 105–116. Lee, K. and B. K. Seo (2023). Modeling bid and ask price dynamics with an extended hawkes process and its empirical applications for high-frequency stock market data. Journal of Financial Econometrics 21(4), 1099–1142. Merton, R. C. (1976). Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics 3(1-2), 125–144. Scaillet, O., A. Treccani, and C. Trevisan (2020). High-frequency jump analysis of the bitcoin market. Journal of Financial Econometrics 18(2), 209–232. Shen, D., A.Urquhart, andP.Wang(2020). Forecastingthevolatilityofbitcoin: Theimportance of jumps and structural breaks. European Financial Management 26(5), 1294–1323. Trimborn, S. and W.K.Härdle(2018). Crixanindexforcryptocurrencies. Journal of Empirical Finance 49, 107–122. Yen, K.-C. and H.-P. Cheng (2021). Economic policy uncertainty and cryptocurrency volatility. Finance Research Letters 38, 101428.
描述 碩士
國立政治大學
金融學系
111352016
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111352016
資料類型 thesis
dc.contributor.advisor 林士貴zh_TW
dc.contributor.advisor Lin, Shih-Kueien_US
dc.contributor.author (Authors) 張宏圖zh_TW
dc.contributor.author (Authors) Chang, Hung-Tuen_US
dc.creator (作者) 張宏圖zh_TW
dc.creator (作者) Chang, Hung-Tuen_US
dc.date (日期) 2024en_US
dc.date.accessioned 5-Aug-2024 12:17:59 (UTC+8)-
dc.date.available 5-Aug-2024 12:17:59 (UTC+8)-
dc.date.issued (上傳時間) 5-Aug-2024 12:17:59 (UTC+8)-
dc.identifier (Other Identifiers) G0111352016en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152467-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 金融學系zh_TW
dc.description (描述) 111352016zh_TW
dc.description.abstract (摘要) 本文旨在利用相互激發跳躍過程（Mutually-Exciting Jump Processes）來驗證加密貨幣市場中的傳染效應（Contagion Effect）。為了測試模型的有效性，我們還構建了相關的交易策略。研究資料涵蓋了2020和2021年的資金狂熱時期、2022年的市場低迷，以及2023和2024年市場復甦的階段。這種多變的市場環境使得模型的成功更具說服力。研究結果顯示，相互激發模型能更準確地捕捉市場情緒，不論從統計上的結果或是交易策略在樣本外的表現，我們論文所提出的相互激勵模型都比自我激勵模型表現得更加優良。在未來的研究中，可以使用更高頻率的時間架構來探討更微觀的市場結構。zh_TW
dc.description.abstract (摘要) This paper aims to utilize mutually-exciting jump processes to verify the contagion effect in the cryptocurrency market. To test the effectiveness of the model, we also constructed relevant trading strategies. The study data encompasses the financial frenzy of 2020 and 2021, the market downturn of 2022, and the recovery phases of 2023 and 2024. This diverse market environment enhances the persuasiveness of the model's success. The results indicate that the mutually exciting model can more accurately capture market sentiment. Both the statistical results and the out-of-sample performance of the trading strategies demonstrate that the mutually exciting model outperforms the self-exciting model proposed in our paper. In future research, higher frequency time frameworks can be employed to explore more microscopic market structures.en_US
dc.description.tableofcontents 1 Introduction .. . . . . 1 2 LiteratureReview . . . . 6 3 Methodologies. . . . . . . 8 4 EmpiricalResults . . . 16 5 ConclusionandFutureWork . .. . 28 References. . .. . . 30zh_TW
dc.format.extent 1516364 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111352016en_US
dc.subject (關鍵詞) 相互激發跳躍過程zh_TW
dc.subject (關鍵詞) 傳染效應zh_TW
dc.subject (關鍵詞) 加密貨幣zh_TW
dc.subject (關鍵詞) 交易策略zh_TW
dc.subject (關鍵詞) Mutually-Exciting Jump Processesen_US
dc.subject (關鍵詞) Contagion Effecten_US
dc.subject (關鍵詞) Cryptocurrencyen_US
dc.subject (關鍵詞) Trading Strategyen_US
dc.title (題名) 建模加密貨幣中的相互激發跳躍過程:來自比特幣和以太幣的證據zh_TW
dc.title (題名) Modeling Mutually Exciting Jump Processes in Cryptocurrency:Evidence from BTC and ETHen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Aït-Sahalia, Y., J. Cacho-Diaz, and R. J. Laeven (2015). Modeling financial contagion using mutually exciting jump processes. Journal of Financial Economics 117(3), 585–606. Arteaga-Garavito, M. J., M. M. Croce, P. Farroni, and I. Wolfskeil (2024). When the mar kets get co. vid: Contagion, viruses, and information diffusion. Journal of Financial Economics 157, 103850. Bates, D. S. (1996). Jumps and stochastic volatility: Exchange rate processes implicit in deutsche mark options. The Review of Financial Studies 9(1), 69–107. Bouri, E., D. Roubaud, and S. J. H. Shahzad (2020). Do bitcoin and other cryptocurrencies jump together? The Quarterly Review of Economics and Finance 76, 396–409. Chaim, P. and M. P. Laurini (2018). Volatility and return jumps in bitcoin. Economics Let ters 173, 158–163. Chen, J. (2022). Forecasting bitcoin. Working Paper. da GamaSilva, P.V.J., M.C.Klotzle, A.C.F.Pinto, andL.L.Gomes(2019). Herdingbehavior and contagion in the cryptocurrency market. Journal of Behavioral and Experimental Finance 22, 41–50. Duffie, D., J. Pan, and K. Singleton (2000). Transform analysis and asset pricing for affine jump-diffusions. Econometrica 68(6), 1343–1376. Eraker, B. (2004). Do stock prices and volatility jump? reconciling evidence from spot and option prices. The Journal of Finance 59(3), 1367–1403. 30 Ferreira, P. and É. Pereira (2019). Contagion effect in cryptocurrency market. Journal of Risk and Financial Management 12(3), 115. Hawkes, A. G. (1971a). Point spectra of some mutually exciting point processes. Journal of the Royal Statistical Society Series B: Statistical Methodology 33(3), 438–443. Hawkes, A. G. (1971b). Spectra of some self-exciting and mutually exciting point processes. Biometrika 58(1), 83–90. Hu, Y., X. Li, and D. Shen (2020). Attention allocation and international stock return co movement: evidence from the bitcoin market. Research in International Business and Finance 54, 101286. Klein, T., H. P. Thu, and T. Walther (2018). Bitcoin is not the new gold–a comparison of volatil ity, correlation, and portfolio performance. International Review of Financial Analy sis 59, 105–116. Lee, K. and B. K. Seo (2023). Modeling bid and ask price dynamics with an extended hawkes process and its empirical applications for high-frequency stock market data. Journal of Financial Econometrics 21(4), 1099–1142. Merton, R. C. (1976). Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics 3(1-2), 125–144. Scaillet, O., A. Treccani, and C. Trevisan (2020). High-frequency jump analysis of the bitcoin market. Journal of Financial Econometrics 18(2), 209–232. Shen, D., A.Urquhart, andP.Wang(2020). Forecastingthevolatilityofbitcoin: Theimportance of jumps and structural breaks. European Financial Management 26(5), 1294–1323. Trimborn, S. and W.K.Härdle(2018). Crixanindexforcryptocurrencies. Journal of Empirical Finance 49, 107–122. Yen, K.-C. and H.-P. Cheng (2021). Economic policy uncertainty and cryptocurrency volatility. Finance Research Letters 38, 101428.zh_TW