摘要翻译：
本工作致力于地球物理和金融时间序列建模的研究。针对平稳环境下时间序列的波动性，提出了一类参数随时间变化的波动性模型。具有一致性质的平稳时间序列的建模使预测具有更大的确定性。利用GARCH模型和随机波动率模型，采用最大似然估计法，在标准预测误差为+/-2的情况下，预测了提前一步的建议波动率。我们将基于过滤技术的随机波动率模型与GARCH模型进行了比较。我们的结论是，随机波动率比GARCH(1,1）更好，因为它受自回归过去信息的影响更小。
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英文标题：
《Volatility Models Applied to Geophysics and High Frequency Financial
  Market Data》
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作者：
Maria C Mariani, Md Al Masum Bhuiyan, Osei K Tweneboah, Hector
  Gonzalez-Huizar, Ionut Florescu
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最新提交年份：
2019
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  This work is devoted to the study of modeling geophysical and financial time series. A class of volatility models with time-varying parameters is presented to forecast the volatility of time series in a stationary environment. The modeling of stationary time series with consistent properties facilitates prediction with much certainty. Using the GARCH and stochastic volatility model, we forecast one-step-ahead suggested volatility with +/- 2 standard prediction errors, which is enacted via Maximum Likelihood Estimation. We compare the stochastic volatility model relying on the filtering technique as used in the conditional volatility with the GARCH model. We conclude that the stochastic volatility is a better forecasting tool than GARCH (1, 1), since it is less conditioned by autoregressive past information.
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PDF链接：
https://arxiv.org/pdf/1901.09145