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A time series analysis of price formation in power markets

This study examines price formation in one of the largest wholesale electricity
markets in the world: the Pennsylvania Jersey Maryland Interconnection, which
serves 13 states and the District of Columbia with over 60 million consumers. The
contribution of this thesis is to apply a variety of time series models offered in the
literature to a large data set describing a single market, allowing for a comparison
of their performance as well as demonstrating their validity. A central question that
drives market deregulation is if it has created efficiency gains. To formalize this
notion of efficiency, we implement tests for stationarity to measure the degree of
randomness over time, finding that short run volatility can result in the outcomes
for these tests that are inconclusive. We explore this volatility structure using
Asymmetrical Power Autoregressive Conditional Heteroskedastic (APARCH)
framework which captures the asymmetric nature of price shocks, finding that this
behavior is unique to electricity returns, and that APARCH offers a better
modelling alternative than simpler representations. Additionally, we account for
long memory given the seasonal drivers of electricity prices which are persistent
using Autoregressive Fractionally Integrated Moving Averages (ARFIMA).
Temperature related market drivers are further modelled using Fourier based
seasonality functions which enable us to capture cycles over multiple frequencies.
Lastly, we provide an application of Markov Regime Switching models to account
for the possibility of multiple states. Although appealing from a theoretical
perspective, we find that the increased complexity of the model does not necessarily
translate to better performance over simpler non-switching alternatives. These
findings highlight the importance of establishing the features of the time series
before selecting an appropriate model, and motivating it with economic rationale. / Graduate

Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/9138
Date14 March 2018
CreatorsKhan, Ibrahim
ContributorsClarke, Judith A.
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsAvailable to the World Wide Web

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