英文标题：
《Quantifying Volatility Reduction in German Day-ahead Spot Market in the
  Period 2006 through 2016》
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作者：
Abdolrahman Khoshrou and Eric J. Pauwels
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最新提交年份：
2018
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英文摘要：
  In Europe, Germany is taking the lead in the switch from the conventional to renewable energy. This poses new challenges as wind and solar energy are fundamentally intermittent, weather-dependent and less predictable. It is therefore of considerable interest to investigate the evolution of price volatility in this post-transition era. There are a number of reasons, however, that makes the practical studies difficult. For instance, EPEX prices can be zero or negative. Consequently, the standard approach in financial time series analysis to switch to logarithmic measures is inapplicable. Furthermore, in contrast to the stock market prices which are only available for trading days, EPEX prices cover the whole year, including weekends and holidays. Accordingly, there is a lot of underlying variability in the data which has nothing to do with volatility, but simply reflects diurnal activity patterns. An important distinction of the present work is the application of matrix decomposition techniques, namely the singular value decomposition (SVD), for defining an alternative notion of volatility. This approach is systematically more robust toward outliers and also the diurnal patterns. Our observations show that the day-ahead market is becoming less volatile in recent years.
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中文摘要：
在欧洲，德国正在率先从传统能源转向可再生能源。这带来了新的挑战，因为风能和太阳能基本上是间歇性的，依赖天气，不太可预测。因此，研究后过渡时期价格波动的演变具有相当大的意义。然而，有许多原因使实践研究变得困难。例如，EPEX价格可以是零或负。因此，金融时间序列分析中转换为对数度量的标准方法不适用。此外，与仅在交易日可用的股票市场价格相比，EPEX价格涵盖全年，包括周末和节假日。因此，数据中存在大量与波动性无关的潜在可变性，而只是反映了日活动模式。目前工作的一个重要区别是矩阵分解技术的应用，即奇异值分解（SVD），用于定义波动性的替代概念。这种方法对异常值和日变化模式系统性地更加稳健。我们的观察表明，近几年来，日前市场的波动性越来越小。
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分类信息：

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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一级分类：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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