Abstract
In this article we present downside risk measures such as: Value-at-Risk - VaR and Conditional Value-at-Risk - CVaR. We established these measures based on the principal components analysis. The principal components analysis is usually applied to complex systems that depend on a large number of factors where one wishes to identify the smallest number of new variables that explain as much of the variability in the system as possible. The first few principal components usually explain the most of historical variability. In our research we used the prices of electric energy from the Day Ahead Market (DAM) of the Polish Power Exchange from 30.03.03 to 27.03.04. We conclude by discussing practical applications of the results of our research in risk management on the Polish Power Exchange.
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Trzpiot, G., Ganczarek, A. (2006). Value at Risk Using the Principal Components Analysis on the Polish Power Exchange. In: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (eds) From Data and Information Analysis to Knowledge Engineering. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31314-1_67
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DOI: https://doi.org/10.1007/3-540-31314-1_67
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