Transportation, storage, seasonality and settlement issues hardly figure in financial markets and their modelling. Yet, they are crucial to the working of energy markets and, as a result, traditional financial models must be customised to give useful results. More broadly, traders and portfolio managers, who make crucial decisions based on the output of these models, should be familiar with their power and their limitations. Ronald Huisman has combined both academic and practical approaches in "An Introduction to Models for the Energy Markets" to provide the reader with a clear exposition of the thinking behind the range of models used today in energy finance - from the most basic to the cutting edge. In each chapter, a series of case-study examples offers the reader practical examples of the models' application as well as insights into extension and development. "An Introduction to Models for the Energy Markets" is an essential purchase for all risk and portfolio managers, analysts and researchers for energy companies, banks and energy investment companies. It will also be required reading for students and academic researchers in the energy area.
Ronald Huisman is Associate Professor of Financial Economics and Energy. He is also a director of FinEdge International Group. The FinEdge International Group consists of research-oriented companies working on innovative solutions with respect to financial strategies and trading and investment management in international financial markets. He has published many papers on this subject and has also contributed to various edited books on energy economics.
List of Figures List of Tables About the Author Preface Acknowledgements 1 Data Analysis Summary statistics: average and standard deviation The histogram Summary statistics: skewness and kurtosis Distribution functions Why do we need models if we have distributions? 2 Models What to model: actual prices or log prices? Models Parameter estimation Concluding remarks 3 Standard Models for Prices and Volatility Characteristics of energy prices Mean-reversion models for energy prices Measuring volatility Concluding remarks 4 Beyond Mean Reversion Modelling price spikes Concluding remarks 5 Factor Models for Forward Prices The information embedded in forward prices Factor models The Kalman filter Estimating the parameters in a long-term-short-term model Any other factors? Concluding remarks 6 Extreme Value Theory Estimation procedure for the tail index Risk management Concluding remarks 7 Methods for Valuing Real Options Real options in energy contracts and real assets Black-Scholes related formulas A power plant as an option Option valuation with trees Incorporating operational constraints Least Squares Monte Carlo Concluding remarks References Index