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Semi‐parametric Forecasting of Spikes in Electricity Prices
Author(s) -
Clements Adam,
Fuller Joanne,
Hurn Stan
Publication year - 2013
Publication title -
economic record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 42
eISSN - 1475-4932
pISSN - 0013-0249
DOI - 10.1111/1475-4932.12072
Subject(s) - electricity , econometrics , range (aeronautics) , parametric statistics , economics , electricity market , electricity price , spot contract , parametric model , series (stratigraphy) , computer science , financial economics , mathematics , statistics , engineering , aerospace engineering , electrical engineering , futures contract , paleontology , biology
The occurrence of extreme movements in the spot price of electricity represents a significant source of risk to retailers. A range of approaches have been considered with respect to modelling electricity prices; these models, however, have relied on time‐series approaches, which typically use restrictive decay schemes placing greater weight on more recent observations. This study develops an alternative, semi‐parametric method for forecasting, which uses state‐dependent weights derived from a kernel function. The forecasts that are obtained using this method are accurate and therefore potentially useful to electricity retailers in terms of risk management.