Araştırma Makalesi

Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin

Cilt: 8 7 Ekim 2026
PDF İndir
EN TR

Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin

Öz

Cryptocurrency prices often experience substantial changes in volatility over time, which may limit the usefulness of stochastic models based on a constant-volatility assumption. This study examines whether accounting for structural changes can improve the stochastic modeling of Bitcoin volatility. Daily Bitcoin prices from January 2020 to December 2025 are used to calculate log returns. A standard one-regime Geometric Brownian Motion (GBM) is first estimated as a benchmark, followed by a likelihood-based change-point analysis and a regime-dependent GBM. Model selection using the Bayesian Information Criterion favors the three-regime specification over the one- and two-regime alternatives. The estimated daily return volatility decreases across the training regimes, from 0.0446 to 0.0353 and then to 0.0248. The model is further evaluated using 2025 as an out-of-sample period. The change-point-aware GBM produces substantially lower forecasting errors than the standard GBM, with RMSE decreasing by 51.6% and MAE by 54.7%. These results suggest that allowing volatility to change at empirically identified points can provide a more useful stochastic representation of Bitcoin volatility than a single-regime GBM.

Anahtar Kelimeler

Bitcoin, cryptocurrency volatility, Geometric Brownian motion, change-point analysis, stochastic modelling, volatility forecasting

Kaynakça

  1. Ardia, D., Bluteau, K., & Rüede, M. (2019). Regime changes in Bitcoin GARCH volatility dynamics. Finance Research Letters, 29, 266–271. https://doi.org/10.1016/j.frl.2018.08.009
  2. Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637–654. https://doi.org/10.1086/260062
  3. Bouri, E., Gil-Alana, L. A., Gupta, R., & Roubaud, D. (2019). Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks. International Journal of Finance & Economics, 24(1), 412–426. https://doi.org/10.1002/ijfe.1670
  4. Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357–384. https://doi.org/10.2307/1912559
  5. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. https://doi.org/10.1214/aos/1176344136
  6. Shen, D., Urquhart, A., & Wang, P. (2020). Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks. European Financial Management, 26(5), 1294–1323. https://doi.org/10.1111/eufm.12254
  7. Thies, S., & Molnár, P. (2018). Bayesian change point analysis of Bitcoin returns. Finance Research Letters, 27, 223–227. https://doi.org/10.1016/j.frl.2018.03.018

Kaynak Göster

APA
Şamcı Karadeniz, R. (2026). Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin. BİLTÜRK Journal of Economics and Related Studies, 8, 410-423. https://doi.org/10.47103/bilturk.2055625
AMA
1.Şamcı Karadeniz R. Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin. BILTURK. 2026;8:410-423. doi:10.47103/bilturk.2055625
Chicago
Şamcı Karadeniz, Rukiye. 2026. “Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin”. BİLTÜRK Journal of Economics and Related Studies 8 (Ekim): 410-23. https://doi.org/10.47103/bilturk.2055625.
EndNote
Şamcı Karadeniz R (01 Ekim 2026) Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin. BİLTÜRK Journal of Economics and Related Studies 8 410–423.
IEEE
[1]R. Şamcı Karadeniz, “Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin”, BILTURK, c. 8, ss. 410–423, Eki. 2026, doi: 10.47103/bilturk.2055625.
ISNAD
Şamcı Karadeniz, Rukiye. “Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin”. BİLTÜRK Journal of Economics and Related Studies 8 (01 Ekim 2026): 410-423. https://doi.org/10.47103/bilturk.2055625.
JAMA
1.Şamcı Karadeniz R. Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin. BILTURK. 2026;8:410–423.
MLA
Şamcı Karadeniz, Rukiye. “Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin”. BİLTÜRK Journal of Economics and Related Studies, c. 8, Ekim 2026, ss. 410-23, doi:10.47103/bilturk.2055625.
Vancouver
1.Rukiye Şamcı Karadeniz. Change-Point-Aware Stochastic Modeling of Cryptocurrency Volatility: Evidence from Bitcoin. BILTURK. 01 Ekim 2026;8:410-23. doi:10.47103/bilturk.2055625