The comparison of range-based volatility estimators and an application of TVP-VARbased connectedness
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Kaynakça
- ANTONAKAKIS, N., & GABAUER, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR. MPRA Paper No. 78282.
- ANTONAKAKIS, N., CHATZIANTONIOU, I., & GABAUER, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4), 84. MDPI AG. Retrieved from http://dx.doi.org/10.3390/jrfm13040084
- ARNERIĆ, J., MATKOVIĆ, M., & SORIĆ, P. (2019). Comparison of range-based volatility estimators against integrated volatility in European emerging markets. Finance Research Letters, 28, 118-124.
- BALI, T. G., & WEINBAUM, D. (2005). A comparative study of alternative extreme‐value volatility estimators. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 25(9), 873-892.
- BAYRACI, S., & UNAL, G. (2014). Stochastic interest rate volatility modeling with a continuous time
- GARCH(1, 1) model. Journal of Computational and Applied Mathematics, 259, 464–473. doi:10.1016/j.cam.2013.10.017
- BOLLEN, B. (2014). What should the value of lambda be in the exponentially weighted moving average volatility model? Applied Economics, 47(8), 853–860. doi:10.1080/00036846.2014.98285
- CHOU, R. Y. (2005). Forecasting financial volatilities with extreme values: the conditional autoregressive range (CARR) model. Journal of Money, Credit and Banking, Vol. 37, 561-582.
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Bu kişi benim
0000-0002-5666-5365
Türkiye
Yayımlanma Tarihi
7 Ağustos 2022
Gönderilme Tarihi
11 Haziran 2022
Kabul Tarihi
20 Temmuz 2022
Yayımlandığı Sayı
Yıl 2022 Cilt: 9 Sayı: 3