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Spectral density of Markov switching models: Derivation, simulation studies and application

机译:马尔可夫切换模型的光谱密度:推导,仿真研究与应用

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This paper is concerned with frequency domain analysis of Markov mean-switching autoregressive (MMSAR) models, linear Markov switching autoregressive (LMSAR) model and transitional Markov switching autoregressive (TMSAR) model. We derive the general expressions of autocovariance functions and spectra for these three models. Simulation studies of theoretical spectral density functions of these three models are presented. The results show that Markov chain seems to be the most important determinants of the frequency distribution of the volatility. A time series is analysed and both smoothed periodogram and theoretical spectra (of LMSAR and TMSAR models) show similar pattern and give clear ideas of business cycle.
机译:本文涉及马尔可夫均值切换自回归(MMSAR)模型,线性马尔可夫切换自回归(LMSAR)模型和过渡马尔可夫切换自回归(TMSAR)模型的频域分析。我们推导了这三个模型的自协方差函数和谱的一般表达式。给出了这三个模型的理论光谱密度函数的仿真研究。结果表明,马尔可夫链似乎是波动率频率分布的最重要决定因素。分析了一个时间序列,平滑的周期图和(LMSAR和TMSAR模型的)理论频谱都显示出相似的模式,并给出了清晰的商业周期构想。

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