A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries

By Michael Mcaleer, Marcelo C. Medeiros. 2008

199 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/58f14dfa13d1f5f05cc48cbd5fa8f1e5d0c636e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Marcelo C. Medeiros
2. Michael Mcaleer
3. Asger Lunde
4. P. R. Hansen
5. Ricardo P. Masini
6. Eduardo F. Mendes
7. Andrew J. Patton
8. Jiti Gao

In Finance

1. Marcelo C. Medeiros
2. Michael Mcaleer
3. Asger Lunde
4. P. R. Hansen
5. Andrew J. Patton
6. Tim Bollerslev
7. Eduardo F. Mendes
8. Ricardo P. Masini

Citations in the corpus

• Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models (2018, result): “McAleer and Medeiros (2008) provided an excellent literature review and compared the performance of the HAR with that of the latent GARCH-type and stochastic volatility models.”
• HAR Modeling for Realized Volatility Forecasting (2012, unknown): “…c j , α The regimes are characterized by partition cells R j of the relevant predictor space G of X pred t : 7 The drastic 0-1 rule to define regime-switches can be relaxed to allow for more smooth regime transitions using, for example, a logistic function instead of the identity function; see [65].”
• Forecasting Volatility Using High-Frequency Data (2011, methodology): “4 High Frequency Data to Facilitate Estimation of Volatility Models Continuous time stochastic volatility (SV) models were introduced by Taylor (1982), and high frequency data has been used to facilitate and improve the estimation of SV models.”
• Machine Learning Advances for Time Series Forecasting (2020, background): “…solution is to restrict the function space, as for instance, imposing linearity or specific forms of parametric nonlinear models as in, for example, Teräsvirta (1994), Suarez-Fariñas et al. (2004), or McAleer and Medeiros (2008); see also Teräsvirta et al. (2010) for a recent review of such models.”
• Realized Volatility: A Review (2008, methodology): “McAleer and Medeiros (2006) extended the HAR-RV model by proposing a flexible multiple regime smooth transition model to capture nonlinearities and long-range dependence in the time series dynamics.”
• Time series forecasting for nonlinear and non-stationary processes: a review and comparative study (2015, background): “McAleer and Medeiros (2008) investigated heterogeneous AR models with multi-regime smooth transition for financial time series forecasting.”