Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models
نویسندگان
چکیده
In this paper, we propose a new method for estimating and forecasting asymmetric stochastic volatility models. The proposal is based on dynamic linear models with Markov switching written as state space Then, the likelihood calculated through Kalman filter outputs estimates are obtained by maximum method. Monte Carlo experiments performed to assess quality of estimation. addition, backtesting exercise real-life time series illustrates that proposed quick accurate alternative value-at-risk.
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ژورنال
عنوان ژورنال: Econometrics
سال: 2022
ISSN: ['2225-1146']
DOI: https://doi.org/10.3390/econometrics11010001