We present a new model for the electricity spot price dynamics, which is able to capture
seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual
purely deterministic trend we introduce a non-stationary independent increments process
for the low-frequency dynamics, and model the large
uctuations by a non-Gaussian stable
CARMA process. The model allows for analytic forward prices, and we apply these to model
and estimate the whole market consistently. An estimation procedure is suggested, where we
fit the non-stationary trend using forward data with long time until delivery, and a robust
L1-Filter to and the states of the CARMA process. The estimation is based on minimizing
the distance between the empirical and theoretical risk premiums, and applied to data from
the German electricity exchange EEX. Our empirical analysis is split into base load and peak
load prices. We find an overall negative risk premium for the base load forward contracts,
except for contracts close to delivery, where a small positive risk premium is detected. The
peak load contracts, on the other hand, show a clear positive risk premium, when they are
close to delivery, while the contracts in the longer end also have a negative premium.
«
We present a new model for the electricity spot price dynamics, which is able to capture
seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual
purely deterministic trend we introduce a non-stationary independent increments process
for the low-frequency dynamics, and model the large
uctuations by a non-Gaussian stable
CARMA process. The model allows for analytic forward prices, and we apply these to model
and estimate the whole market consistently....
»