A regime switching long memory model for electricity prices
电价的状态转换长记忆模型AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要明确研究状态转换长记忆时间序列,并评估电价预测。
电价的状态转换长记忆模型AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
In this paper we develop a regime switching model which can generate long memory (fractional integration) in each of the regime states. This property is relevant in a number of cases. For instance, the deregulated market for electricity power in the Nordic countries is characterized by electricity spot prices with a high degree of long memory. It occurs that in some time periods bilateral prices are identical whereas in other periods the prices differ. The latter occurs when a capacity congestion exists across regions and multiple price areas will result. If the price series are fractionally integrated this means that in some regimes, an extreme form of fractional cointegration amongst prices will exist. We define a Markov switching fractional integration model from which the fractional orders of integration in separate states can be estimated using Maximum Likelihood techniques. The model is adapted to data for the Nordic electricity spot market, and we find that regime swithing and long memory are empirically relevant to co-exist. In particular, we find that the price behaviour for single markets can be very different depending upon the presence or absence of bottlenecks in electricity transmission. Using Monte Carlo forecasting we find that the regime switching model appears to be especially attractive in forecasting relative prices.