Falling and explosive, dormant, and rising markets via multi-regime financial time series models. (English) Zbl 1224.91185
In this paper, the authors propose a multi-regime threshold nonlinear double threshold GARCH model, with a fat-tailed error distribution, to capture mean and volatility asymmetries in financial markets. The main features of the model are that the authors allow more than two regimes, including an explosive regime in the volatility equation. It is performed Markov chain Monte carlo sampling to estimate the threshold values, the delay lag, and all other parameters simultaneously, while also performing diagnostic checking for the proposed multi-regime model via importance sampling methods. Simulation results showed that the proposed Bayesian approach could provide accurate estimates and inference for all unknown parameters in a three-regime model. An empirical study using eight daily closing indices for oil and gas index markets found that all market returns responded asymmetrically to past information, when compared with two threshold values, in mean, volatility and volatility persistence at a delay lag of 1 day. Three distinct regime behaviours were found: falling/explosive, dormant and rising markets.
Reviewer: A. D. Borisenko (Kyïv)
MSC:
| 91G70 | Statistical methods; risk measures |
| 91B84 | Economic time series analysis |
| 62P05 | Applications of statistics to actuarial sciences and financial mathematics |
| 65C05 | Monte Carlo methods |
| 65C40 | Numerical analysis or methods applied to Markov chains |
Keywords:
Markov chain Monte Carlo method; model selection; multi-regime financial time series modelsReferences:
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