Gathering selected, revised and extended contributions from the conference 'Forecasting and Risk Management for Renewable Energy FOREWER', which took place in Paris in June 2017, this book focuses on the applications of statistics to the risk management and forecasting problems arising in the renewable energy industry. The different contributions explore all aspects of the energy production chain: forecasting and probabilistic modelling of renewable resources, including probabilistic forecasting approaches; modelling and forecasting of wind and solar power production; prediction of electricity demand; optimal operation of microgrids involving renewable production; and finally the effect of renewable production on electricity market prices. Written by experts in statistics, probability, risk management, economics and electrical engineering, this multidisciplinary volume will serve as a reference on renewable energy risk management and at the same time as a source of inspiration for statisticians and probabilists aiming to work on energy-related problems.

During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing applications. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematical tools required for applications can be intimidating. Potential end users often get the impression that jump and Lévy processes are beyond their reach.

Financial Modelling with Jump Processes demonstrates that this is not so. It provides a self-contained overview of the theoretical, numerical, and empirical aspects of using jump processes in financial modeling, and does so in terms well within the grasp of nonspecialists. With clear-sighted explanations, the authors motivate the use of the various mathematical tools used in the modelling process, and while giving an intuitive understanding of proofs, provide precise mathematical statements of the results. They illustrate the mathematical concepts with many numerical and empirical examples and provide the details of numerical implementation of pricing and calibration algorithms.

This book clearly shows that the concepts and tools necessary for understanding and implementing these models can be much more accessible and intuitive that those involved in the Black Scholes and diffusion models. If you have even a basic familiarity with quantitative methods in finance, Financial Modelling with Jump Processes will give you a valuable new set of tools for modelling market fluctuations.