GARCH option pricing models have the advantage of a well-established econometric foundation. However, multiple states need to be introduced as single state GARCH and even Levy processes are unable to explain the term structure of the moments of financial data. We show that the continuous time version of the Markov switching GARCH(1,1) process is a stochastic model where the volatility follows a switching process. The continuous time switching GARCH model derived in this paper, where the variance process jumps between two or more GARCH volatility states, is able to capture the features of implied volatilities in an intuitive and tractable framework.GARCH, jumps, normal mixture, Markov switching, stochastic volatility, time aggregation
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
[[abstract]]The paper constructs a GARCH process with time-changed L?vy innovations from the economi...
We present a discrete time stochastic volatility model in which the conditional distribution of the ...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
Empirically the constant volatility model of Black & Scholes (1973) is found to suffer from a nu...
This paper considers the pricing of options when there are jumps in the pricing kernel and correlate...
This paper describes briefly about GARCH with regime switching (SW-GARCH) following Markov Chain pro...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
This paper introduces four models of conditional heteroskedasticity that contain markov switching pa...
In this paper we develop a method for pricing derivatives under a Markov switching version of the He...
This paper considers a model where there is a single state variable that drives the state of the wor...
Contrary to popular belief, the diffusion limit of a GARCH variance process is not a diffusion model...
Stochastic volatility models both in continuous and in discrete time have been successful in many fi...
This paper considers the pricing of options when there are jumps in the pricing kernel and correlate...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
[[abstract]]The paper constructs a GARCH process with time-changed L?vy innovations from the economi...
We present a discrete time stochastic volatility model in which the conditional distribution of the ...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
Empirically the constant volatility model of Black & Scholes (1973) is found to suffer from a nu...
This paper considers the pricing of options when there are jumps in the pricing kernel and correlate...
This paper describes briefly about GARCH with regime switching (SW-GARCH) following Markov Chain pro...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
This paper introduces four models of conditional heteroskedasticity that contain markov switching pa...
In this paper we develop a method for pricing derivatives under a Markov switching version of the He...
This paper considers a model where there is a single state variable that drives the state of the wor...
Contrary to popular belief, the diffusion limit of a GARCH variance process is not a diffusion model...
Stochastic volatility models both in continuous and in discrete time have been successful in many fi...
This paper considers the pricing of options when there are jumps in the pricing kernel and correlate...
Based on the fact that volatility is time varying in high frequency data and that periods of high vo...
[[abstract]]The paper constructs a GARCH process with time-changed L?vy innovations from the economi...
We present a discrete time stochastic volatility model in which the conditional distribution of the ...