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Title: A higher-order Markov chain-modulated model for electricity spot-price dynamics Authors:  Rogemar Mamon - University of Western Ontario (Canada) [presenting]
Abstract: Over the last three decades, the electricity sector worldwide underwent massive deregulation. As electricity is a non-storable commodity, its price is extremely sensitive to changes in supply and demand. The evolution of electricity prices exhibits pronounced mean reversion and cyclical patterns, possesses extreme volatility and relatively frequently occurring spikes, and manifests presence of state memory. We tackle the modelling and estimation problems under a new paradigm that integrates the deterministic calendar seasons and stochastic factors governing electricity prices. The de-seasonalised component of our proposed model has both the jump and mean-reverting properties to account for spikes and periodic cycles alternating between lower price returns and compensating periods of higher price returns. The parameters of the de-seasonalised model components are also modulated by a higher-order hidden Markov chain (HOHMC) in discrete time. The HOHMC's state is interpreted as the ``state of the world" resulting from the interaction of various forces impacting the electricity market. Filters are developed to generate optimal estimates of HOHMC-relevant quantities using the observation process, and these provide online estimates of model parameters. We provide empirical demonstrations using the daily electricity spot prices compiled by the Alberta Electric System Operator.