Сравнение методов

	DCC-GARCH модель с изменяющимися во времени параметрами (TVP-DCC-GARCH)	Модель стохастической волатильности (Хестон)
Область	Эконометрика	Финансы
Семейство	Regression model	Regression model
Год появления	2002 (DCC-GARCH); TVP extension 2010s	1993
Автор метода	Robert F. Engle (DCC-GARCH); TVP extension developed in applied finance literature	Steven L. Heston
Тип	Multivariate volatility model with time-varying correlation	Continuous-time stochastic volatility model
Основополагающий источник	Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350.	Heston, S. L. (1993). A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options. Review of Financial Studies, 6(2), 327-343.
Другие названия	TVP-DCC-GARCH, time-varying DCC-GARCH, dynamic conditional correlation GARCH with TVP, TVP dynamic conditional correlation model	Heston model, SV model, continuous-time stochastic volatility, Stokastik Volatilite Modeli (Heston, SV)
Связанные	4	5
Сводка	The TVP-DCC-GARCH model extends the Dynamic Conditional Correlation GARCH framework by allowing not only the pairwise correlations but also the underlying model parameters to evolve continuously over time. It captures structural shifts in volatility dynamics and cross-asset dependence, making it essential for financial risk modelling in non-stationary environments.	The stochastic volatility model is a continuous-time option-pricing and risk framework in which volatility follows its own random process rather than staying constant. The Heston model, introduced by Steven Heston in 1993, gives the variance a mean-reverting square-root (CIR) dynamic and yields a closed-form option price; it is the continuous-time counterpart of GARCH.