Risk Management for Energy Markets.

ABSTRACT: This thesis is concerned with risk management. The unifying theme is the risk management of the energy market. The different chapters deal with risk management in a different way and consider different energy markets. The first chapter addressed the issue of risk assessment applied to two major European electricity markets: Powernext (France) and EEX (Germany and Austria). In the second chapter the measurement of risk is done through the application of the optimal portfolio in the electricity markets calculated using the returns on the futures prices. In the third chapter, the theory of optimal allocation of the portfolio is applied to the zonal Italian market (using physical zones). The modeling, measurement and accounting of risk are important from a theoretical point of view and, in particular, from the practical point of view. In practice, it plays a key role in the strategy of portfolio allocation in the energy markets. In the present context, the operators active on energy markets are facing unprecedented levels of risk. The importance of a proper risk management and a proper understanding of the risk are crucial to the making of a good investment and to guide decisions contract. Risk management must lead to the achievement of a balance mix of risk and return through a particular trading strategy. While “trading strategy" means a defined set of rules to follow to make good trading decisions. This thesis consists of three self-contained chapters. In the first chapter, we carry out an econometric analysis of the risk in the electricity market using spot prices. The energy market, and in particular the electricity market is going through a transition phase in the world. Price fluctuations and their correlation with demand are common features of all liberalized electricity markets. The most important test for the new liberalized market is the ability to manage excessive volatility connected to a system with substantial temporal variations of generation capacity. We have proposed the use of AR-GARCH-type-EVT (Extreme Value Theory) with different distributions of the innovations and variations that take into account the asymmetric response of volatility to estimate the value at risk in the electricity markets. Thus, the risk of investment in electricity markets is calculated based on the estimated VaR and conditional VaR using GARCH filters distributions with heavy tails. The focus is fixed from the point of view of the regulators (upper tails) and investors (lower tails). Supervisors and regulators are in fact more concerned with the risk of experiencing high prices because their aim is to ensure the efficiency of the market. The second chapter suggests the application of the theory of the optimal portfolio to energy markets through a modified version of the classical mean-variance approach originally suggested by Markowitz. The main result of the chapter shows that portfolios with different maturities could provide market operators with guidelines for a good strategy of risk management in energy markets. Optimization techniques are used to obtain optimal weights for the allocation of financial investments, in order to analyze the investment risk connected to the electricity market using futures prices. It is an original application of an optimization technique already known in the literature, but which has not yet been explored in the study of the energy market. In particular, the optimization technique based on conditional VaR as a risk measure has not yet been used for the analysis of the risk inherent in the electricity markets. In the third chapter; we carry out a spatial analysis of the risks of investing in local markets. Since the Italian electricity market has been liberalized, there are no documents as the author knows that they have considered the zonal portfolio optimization in the Italian market. In liberalized electricity markets with zonal prices, the market is divided into several zones, each of which is assigned a market price at which participants react at any moment in time. Our contribution consists in the application of the allocation of the portfolio based on VaR as a risk measure to the market to make informed decisions about zonal Italian investment in the different areas that comprise the market. The main purpose is to mitigate the risk associated with investments in the market. The analysis therefore moves from the perspective of a temporal diversification to that of a spatial diversification.