Bayesian analysis of moving average stochastic volatility models: modeling in-mean effects and leverage for financial time series

Dimitrakopoulos Stefanos; Kolossiatis Michalis

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Bayesian analysis of moving average stochastic volatility models: modeling in-mean effects and leverage for financial time series

机译：移动平均随机波动率模型的贝叶斯分析：均值效果与金融时序效果和杠杆效果

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摘要

We propose a moving average stochastic volatility in mean model and a moving average stochastic volatility model with leverage. For parameter estimation, we develop efficient Markov chain Monte Carlo algorithms and illustrate our methods, using simulated and real data sets. We compare the proposed specifications against several competing stochastic volatility models, using marginal likelihoods and the observed-data Deviance information criterion. We also perform a forecasting exercise, using predictive likelihoods, the root mean square forecast error and Kullback-Leibler divergence. We find that the moving average stochastic volatility model with leverage better fits the four empirical data sets used.

机译：我们提出了杠杆式模型中的平均随机波动率和移动平均随机挥发性模型。对于参数估计，我们使用模拟和实际数据集开发高效的Markov链Monte Carlo算法并说明了我们的方法。我们使用边缘似然和观察数据偏差信息标准对拟议的拟议规范进行比较若干竞争随机挥发性模型。我们还使用预测似然性进行预测锻炼，根均线预测误差和kullback-Leibler发散。我们发现，具有杠杆的移动平均随机波动率模型更好地适合使用的四种经验数据集。

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来源
《Econometric Reviews》 |2020年第5期|319-343|共25页
作者
Dimitrakopoulos Stefanos; Kolossiatis Michalis;
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作者单位

Univ Leeds Econ Div Leeds W Yorkshire England;

Univ Cyprus Dept Math & Stat Nicosia Cyprus;

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原文格式 PDF
正文语种 eng
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关键词
In-mean effects; leverage; Markov chain Monte Carlo; moving average; stochastic volatility;

机译：惯用效果;杠杆;马尔可夫链蒙特卡罗;移动平均值;随机波动性;

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专利

1. Modelling fluctuations of financial time series: from cascade process to stochastic volatility model [J] . J. F. Muzy, J. Delour, E. Bacry The European physical journal, B. Condensed matter physics . 2000,第3期

机译：金融时间序列波动建模：从级联过程到随机波动率模型
2. Simulation Methods for Levy-Driven Continuous-Time Autoregressive Moving Average (CARMA) Stochastic Volatility Models [J] . Viktor Todorov, George Tauchen Journal of business & economic statistics . 2006,第4期

机译：征费驱动的连续时间自回归移动平均（CARMA）随机波动率模型的仿真方法
3. HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES [J] . Cathy W. S. Chen, F. C. Liu, Mike K. P. So Australian & New Zealand journal of statistics . 2008,第1期

机译：金融时间序列中的重分布阈值随机波动率模型
4. Bayesian Analysis of Stochastic Volatility Models in Financial Time Series [C] . Zhengbo Jiang, rnJin Liu, rnLei Zhang, International conference on systems science, management science and system dynamics . 2007

机译：金融时间序列中的随机波动率模型的贝叶斯分析
5. AUTOREGRESSIVE MOVING-AVERAGE (ARMA) MODEL IDENTIFICATION FOR DEGENERATE TIME SERIES WITH APPLICATION TO MANEUVERING TARGET TRACKING (STOCHASTIC MODELING, KALMAN FILTER). [D] . SPEAKMAN, NORMAN OWEN. 1985

机译：退化时间序列的自动回归平均（ARMA）模型识别，应用于机动目标跟踪（随机建模，卡尔曼滤波器）。
6. Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution [O] . William L. Leão, Carlos A. Abanto-Valle, Ming-Hui Chen -1

机译：使用广义双曲斜学生t分布的具有杠杆和不对称重尾误差的随机均值波动模型的贝叶斯分析
7. Modelling fluctuations of financial time series: from cascade process to stochastic volatility model [O] . Muzy, J. F., Delour, J., Bacry, E. 2000

机译：金融时间序列的波动模型：从级联过程到随机波动率模型
8. Estimation of Parameters in Integrated Autoregressive-Moving Average Time Series Models. Part 2. Moving Average and Mixed Models [R] . Box, G. E. P., Jenkins, G. M. 1972

机译：综合自回归 - 移动平均时间序列模型中参数的估计。第2部分。移动平均线和混合模型

Bayesian analysis of moving average stochastic volatility models: modeling in-mean effects and leverage for financial time series

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