In this paper we study a new class of nonlinear GARCH models. Special interest is devoted to models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable is mainly motivated by the desire to find useful models for highly persistent volatility. The underlying idea is that high persistence in conditional variance is related to relatively infrequent changes in regime, which can be captured by a suitable specification of the new model. Using the theory of Markov chains, we provide sufficient conditions for the stationarity and existence of moments of various smooth transition GARC...
We present a novel GARCH model that accounts for time varying, state dependent, persistence in the v...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
textabstractIn this paper we examine the forecasting performance of five nonlinear GARCH(1,1) models...
In this paper a new GARCH–M type model, denoted the GARCH-AR, is proposed. In particular, it is show...
Many researchers use GARCH models to generate volatility forecasts. Using data on three major U.S. d...
This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two differen...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
We present a novel GARCH model that accounts for time varying, state dependent, persistence in the v...
GARCH-type models have been very successful in describing the volatility dynamics of financial retur...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
The paper considers a volatility model that includes a persistent, integrated or nearly integrated, ...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
A new multivariate volatility model that belongs to the family of conditional correlation GARCH mode...
We present a novel GARCH model that accounts for time varying, state dependent, persistence in the v...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
textabstractIn this paper we examine the forecasting performance of five nonlinear GARCH(1,1) models...
In this paper a new GARCH–M type model, denoted the GARCH-AR, is proposed. In particular, it is show...
Many researchers use GARCH models to generate volatility forecasts. Using data on three major U.S. d...
This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two differen...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
We present a novel GARCH model that accounts for time varying, state dependent, persistence in the v...
GARCH-type models have been very successful in describing the volatility dynamics of financial retur...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
The paper considers a volatility model that includes a persistent, integrated or nearly integrated, ...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
A new multivariate volatility model that belongs to the family of conditional correlation GARCH mode...
We present a novel GARCH model that accounts for time varying, state dependent, persistence in the v...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...
Abstract: We present a novel GARCH model that accounts for time varying, state dependent, persistenc...