Bøker av Fred Espen Benth

Power markets are undergoing a major transformation from gas and oil-fueled generation toward renewable electricity production from wind and solar sources. Simultaneously, there is an increasing demand for electrification, coupled with long-term climate-induced weather changes. The uncertainties confronting energy market participants require sophisticated modelling techniques to effectively understand risk, many of which are covered in this book.Comprising invited papers by high-profile researchers, this volume examines the empirical aspects of forward and futures prices, uncovering patterns of noise factors in various European electricity markets. Additionally, it delves into the recent, influential classes of Hawkes and trawl processes, emphasizing their significance in energy markets. The impact of renewables on energy market prices is a pivotal concern for both producers and consumers. Mean-field games provide a powerful mathematical framework for this, and a dedicated chapter outlining their dynamics is included in the book. The book also explores structural financial products and their connection to climate risk as a risk management tool, underscoring the essential need for a comprehensive understanding of these products in the realm of "green finance," to which the energy industry is integral. Lastly, the book thoroughly analyzes spatial smoothing and power purchase (PPA) contracts, addressing central issues in energy system planning and financial operations.Tailored for researchers, PhD students, and industry energy analysts, this volume equips readers with insights and tools to navigate the constantly evolving energy market landscape. It serves as a sequel to the earlier Quantitative Energy Finance book, featuring all-new chapters.

This monograph presents a theory for random field models in time and space, viewed as stochastic processes with values in a Hilbert space, to model the stochastic dynamics of forward and futures prices in energy, power, and commodity markets. In this book, the well-known Heath¿Jarrow¿Morton approach from interest rate theory is adopted and extended into an infinite-dimensional framework, allowing for flexible modeling of price stochasticity across time and along the term structure curve. Various models are introduced based on stochastic partial differential equations with infinite-dimensional Lévy processes as noise drivers, emphasizing random fields described by low-dimensional parametric covariance functions instead of classical high-dimensional factor models. The Filipovi¿ space, a separable Hilbert space of Sobolev type, is found to be a convenient state space for the dynamics of forward and futures term structures. The monograph provides a classification of important operators in this space, covering covariance operators and the stochastic modeling of volatility term structures, including the Samuelson effect. Fourier methods are employed to price many derivatives of interest in energy, power, and commodity markets, and sensitivity 'delta' expressions can be derived. Additionally, the monograph covers forward curve smoothing, the connection between forwards with fixed delivery and delivery period, as well as the classical theory of forward and futures pricing. This monograph will appeal to researchers and graduate students interested in mathematical finance and stochastic analysis applied in the challenging markets of energy, power, and commodities. Practitioners seeking sophisticated yet flexible and analytically tractable risk models will also find it valuable.

Drawing on advanced probability theory, Ambit Stochastics is used to model stochastic processes which depend on both time and space. This monograph, the first on the subject, provides a reference for this burgeoning field, complete with the applications that have driven its development.Unique to Ambit Stochastics are ambit sets, which allow the delimitation of space-time to a zone of interest, and ambit fields, which are particularly well-adapted to modelling stochastic volatility or intermittency. These attributes lend themselves notably to applications in the statistical theory of turbulence and financial econometrics. In addition to the theory and applications of Ambit Stochastics, the book also contains new theory on the simulation of ambit fields and a comprehensive stochastic integration theory for Volterra processes in a non-semimartingale context.Written by pioneers in the subject, this book will appeal to researchers and graduate students interested in empirical stochastic modelling.