Comparer des méthodes

	Modèle HAR-RV de la volatilité réalisée	Modèle Markovien à Changement de Régime pour Séries Financières
Domaine	Finance	Finance
Famille	Regression model	Regression model
Année d'origine	2009	1989
Auteur d'origine	Fulvio Corsi	James D. Hamilton
Type	Linear time-series regression for volatility	Markov regime-switching time-series model
Source fondatrice	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.
Alias	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
Apparentées	5	1
Résumé	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.