Modelling Day Ahead Nord Pool Forward Price Volatility: Realized Volatility versus GARCH Models

摘要

Traditionally, and still within electricity futures/forward markets, daily data has been utilized as the unit of analyses when modelling and making predictions of volatility. However, over the recent past it is argued that better volatility estimates can be obtained by using standard time series techniques on non-parametric volatility measures constructed from high-frequency intradaily returns. Liquidity in financial electricity markets has increased rapidly over the recent years, which make it possible to apply these relatively new methods for measuring market volatility. In this paper high-frequency data and the concept of realized volatility is utilized to make day ahead predictions of Nord Pool forward price volatility. Such short term volatility predictions are especially important for operators and other participants in the electricity sector. We compare the results obtained from standard time-series techniques with the more traditional GARCH-framework which utilizes daily returns. Additionally, we examine whether different approaches of decomposing the total variation into a continuous - and jump measure improves the model fit or not. The paper provides new insights to how the financial electricity market at Nord Pool works, and how we efficiently can model and make predictions of the price movements in this market.