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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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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中文摘要：
这项工作致力于地球物理和金融时间序列建模的研究。提出了一类具有时变参数的波动率模型来预测平稳环境下时间序列的波动率。具有一致性质的平稳时间序列的建模有助于更确定的预测。利用GARCH和随机波动率模型，我们预测了一步领先的建议波动率，标准预测误差为+/-2，这是通过最大似然估计实现的。我们将条件波动率中使用的基于过滤技术的随机波动率模型与GARCH模型进行了比较。我们得出结论，随机波动率是一种比GARCH（1，1）更好的预测工具，因为它不受自回归过去信息的制约。
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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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