Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/152467
|
| Title: | 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 |
| Authors: | 張宏圖
Chang, Hung-Tu |
| Contributors: | 林士貴
Lin, Shih-Kuei
張宏圖
Chang, Hung-Tu |
| Keywords: | 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 |
| Date: | 2024 |
| Issue Date: | 2024-08-05 12:17:59 (UTC+8) |
| Abstract: | 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. |
| Reference: | 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. |
| Description: | 碩士
國立政治大學
金融學系
111352016 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111352016 |
| Data Type: | thesis |
| Appears in Collections: | [金融學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 201601.pdf | | 1480Kb | Adobe PDF | 0 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
