Сравнение методов

	Модель HAR-RV реализованной волатильности	Модель Марковских переключений режимов для финансовых временных рядов
Область	Финансы	Финансы
Семейство	Regression model	Regression model
Год появления	2009	1989
Автор метода	Fulvio Corsi	James D. Hamilton
Тип	Linear time-series regression for volatility	Markov regime-switching time-series model
Основополагающий источник	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196.	Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
Другие названия	HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)	Markov switching model, Hamilton regime-switching model, MS-AR, hidden Markov regime model
Связанные	5	1
Сводка	The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility.	The Markov regime-switching model, introduced by James D. Hamilton in 1989, is a hidden-state time-series model in which financial series such as returns or volatility behave with different parameters across distinct economic regimes (bull/bear or high/low volatility). It is the financial application of Hamilton's MS-AR model, where an unobserved Markov state governs which parameter set is active at each point in time.