Compară metode

	Modelul HAR-RV al volatilității realizate	Modelul Markov cu Schimbări de Regim pentru Serii Financiare
Domeniu	Finanțe	Finanțe
Familie	Regression model	Regression model
Anul apariției	2009	1989
Autorul original	Fulvio Corsi	James D. Hamilton
Tip	Linear time-series regression for volatility	Markov regime-switching time-series model
Sursa seminală	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.
Denumiri alternative	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
Înrudite	5	1
Rezumat	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.