论文标题
小型实用程序的投资组合管理，具有结构性向量自回归模型的德国电力市场
A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets
论文作者
论文摘要
电力市场的变化使Res生产商和电力交易员面临各种风险，其中价格和数量风险起着非常重要的作用。在这项研究中，提出了一项投资组合建筑策略，该策略可以动态选择在不同的电力市场（日前和盘中）交易的电力的比例，从而优化了公用事业的行为。考虑了两种类型的方法：简单，假设比例是固定的，并且数据驱动，从而允许其波动。为了探索市场信息，采用结构向量自动回归（SVAR）模型，该模型允许估计感兴趣的变量之间的关系并模拟其未来分布。呈现的方法通过来自德国电力市场的数据进行评估。结果表明，数据驱动的交易策略允许增加公用事业收入，同时降低了交易风险，这是通过第二天收入的可预测性和风险的收入价值来衡量的。事实证明，基于尖锐比率的方法提供了最强大的结果。
The changes in electricity markets expose RES producers and electricity traders to various risks, among which the price and the volume risk play a very important role. In this research, a portfolio building strategies are presented, which allow to dynamically choose a proportion of electricity traded in different electricity markets (day-ahead and intraday) and hence to optimize the behavior of an utility. Two types of approaches are considered: simple, assuming that the proportions are fixed, and data driven, which allows for thier fluctuation. In order to explore the market information, Structural Vector Autoregressive (SVAR) model is applied, which allows to estimate the relationship between variables of interest and to simulate their future distribution. The presented methods are evaluated with data coming from German electricity market. The results indicate that data driven trading strategies allow to increase the utility revenue and at the same time reduce the trading risk, measured by the predictability of the next day income and the revenue Value at Risk. It turns out that the approach based on Sharp Ratio provides the most robust results.
