KOREYA FOND BOZORIDA TINCH VA NOTINCH SHAROITLARDA RISKKA DUCHOR BO‘LGAN QIYMAT (VAR) BASHORATINING NAMUNADAN TASHQARI SAMARADORLIGI
DOI:
https://doi.org/10.5281/zenodo.23834931Annotatsiya
Xavf modellari odatda uzoq davr bo‘yicha o‘rtacha samaradorlik asosida baholanadi, biroq moliya bozorlari tinch va notinch holatlar o‘rtasida almashinib turadi, bu esa turli modellashtirish yondashuvlarini talab qilishi mumkin. Ushbu maqolada Koreya fond bozori (KOSPI) misolida alohida volatillik rejimlarini aniqlash ayrim volatillik modellarining bozor notinch holatga o‘tganda nima sababdan boshqalariga nisbatan ishonchliroq bashorat berishini tushuntirishga yordam berish-bermasligi o‘rganiladi.Kalit soʻzlar
rejim almashinuvi, KOSPI, GARCH, riskka duchor bo‘lgan qiymat (VaR), orqaga qaytish testi (backtesting), bozor notinchligiFoydalanilgan adabiyotlar roʻyxati
Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. https://doi.org/10.1109/TAC.1974.1100705
Basel Committee on Banking Supervision. Minimum capital requirements for market risk. — Basel: Bank for International Settlements, 2016.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
Choi, K. (2015). -H., Yoon S.-M. The effect of money supply on the volatility of Korean stock market. Modern Economy, 6(5), 535–543. https://doi.org/10.4236/me.2015.65052
Christoffersen P., F. (1998). Evaluating interval forecasts. International Economic Review, 39(4), 841–862. https://doi.org/10.2307/2527341
Engle R., F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. https://doi.org/10.2307/1912773
Eom, C., Kaizoji, T., & Scalas, E. (2019). Fat tails in financial return distributions revisited: Evidence from the Korean stock market. Physica A: Statistical Mechanics and its Applications, 526. https://doi.org/10.1016/j
Ghalanos, A. (2022). rugarch: Univariate GARCH Models [Electronic resource]: R package, version 1.4-9. https://cran.r-project.org/package=rugarch (accessed: 06.09.
Glosten L., R., Jagannathan, R., & Runkle D., E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779–1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
Gray S., F. (1996). Modeling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics, 42(1), 27–62. https://doi.org/10.1016/0304-405X(96)00875-6
Haas, M., Mittnik, S., & Paolella M., S. (2004). A new approach to Markov-switching GARCH models. Journal of Financial Econometrics, 2(4), 493–530. https://doi.org/10.1093/jjfinec/nbh020
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
Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill.
Kim, C. (1999). -J., Nelson C. R. Has the U.S. economy become more stable? A Bayesian approach based on a Markovswitching model of the business cycle. The Review of Economics and Statistics, 81(4), 608–616. https://doi.org/10.1162/003465399558472
Kupiec P., H. (1995). Techniques for verifying the accuracy of risk measurement models. The Journal of Derivatives, 3(2), 73–84. https://doi.org/10.3905/jod.1995.407942
Nelson D., B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59.
— P. 347–370. — DOI: 10.2307/2938260.
Pyo, D. (2021). -J. The COVID-19 and stock return volatility: Evidence from South Korea. East Asian Economic Review, 25(2), 205–230. https://doi.org/10.11644/KIEP.EAER.2021.25.2.396
Roh T., H. (2007). Forecasting the volatility of stock price index. Expert Systems with Applications, 33.
— P. 916–922. — DOI: 10.1016/j.eswa.2006.08.001.
Sánchez-Espigares J., A., & López-Moreno, A. (2021). MSwM: Fitting Markov Switching Models [Electronic resource]: R package, version 1.5. https://cran.r-project.org/package=MSwM (accessed: 06.09.
Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. https://doi.org/10.1214/aos/1176344136
Tsay R., S. (2010). Analysis of Financial Time Series. John Wiley & Sons.
Zakoïan, J. (1994). -M. Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. https://doi.org/10.1016/0165-1889(94)90039-6
Yuklab olishlar
Nashr etilgan
Qanday iqtibos keltirish kerak
Son
Boʻlim
Litsenziya
Mualliflik huquqi (c) 2026 Gulchehraxon Farhodjon qizi Ortig‘aliyeva

Ushbu asar Creative Commons Attribution 4.0 International litsenziyasi asosida tarqatiladi.
