George Levy works as a Quantitative Analyst at RWE npower developing systems to estimate both the risk and value associated with energy contracts. He has been invited to speak at numerous conferences and published articles in various international journals including: Energy Risk Magazine, The Journal of Computational Finance, and Software Practice & Experience. He is also the author of two books: Computational Finance: Numerical Methods for Pricing Financial Derivatives, Academic Press (2004), and Computational Finance using C and C#: Derivatives and Valuation (2nd Edition), Academic Press (2016).

Levy, a quantitative analyst who develops systems to estimate the risk and value associated with energy contracts in the UK, provides mathematical and computational tools for the quantification and management of energy/power risk and derivative valuations. He discusses the mathematics of Brownian motion and stochastic processes, the mathematics of spot and forward curve commodity models, Merton's jump diffusion model, non-normal distributions, the modeling of half hourly UK power pricing, and pricing single and multi-asset European and American derivatives, as well as Markowitz portfolio optimization and examples of how to create C++ vector and random number classes that facilitate the development of energy risk and derivative pricing software. He includes his research on UK power contracts, including the topics of power imbalance, renewable generation, intraday storage, and demand optionality. Basic understanding of linear algebra and calculus is assumed.

• Chapter 1. OverviewChapter 2. Brownian Motion and Stochastic Processes  Chapter 3. Fundamental Power Price Model Chapter 4. Single Asset European Options Chapter 5. Single Asset American Style Options Chapter 6. Multi-Asset Options Chapter 7. Power Contracts Chapter 8. Portfolio Optimisation Chapter 9. Example C++ Classes Appendix A. The Greeks for Vanilla European Options Appendix B. Standard Statistical Results Appendix C. Statistical Distribution FunctionsAppendix D. Mathematical Reference Appendix E. Answers to Problems

George Levy works as a Quantitative Analyst at RWE npower developing systems to estimate both the risk and value associated with energy contracts. He has been invited to speak at numerous conferences and published articles in various international journals including: Energy Risk Magazine, The Journal of Computational Finance, and Software Practice & Experience. He is also the author of two books: Computational Finance: Numerical Methods for Pricing Financial Derivatives, Academic Press (2004), and Computational Finance using C and C#: Derivatives and Valuation (2nd Edition), Academic Press (2016).

Levy, a quantitative analyst who develops systems to estimate the risk and value associated with energy contracts in the UK, provides mathematical and computational tools for the quantification and management of energy/power risk and derivative valuations. He discusses the mathematics of Brownian motion and stochastic processes, the mathematics of spot and forward curve commodity models, Merton's jump diffusion model, non-normal distributions, the modeling of half hourly UK power pricing, and pricing single and multi-asset European and American derivatives, as well as Markowitz portfolio optimization and examples of how to create C++ vector and random number classes that facilitate the development of energy risk and derivative pricing software. He includes his research on UK power contracts, including the topics of power imbalance, renewable generation, intraday storage, and demand optionality. Basic understanding of linear algebra and calculus is assumed.

• Chapter 1. OverviewChapter 2. Brownian Motion and Stochastic Processes  Chapter 3. Fundamental Power Price Model Chapter 4. Single Asset European Options Chapter 5. Single Asset American Style Options Chapter 6. Multi-Asset Options Chapter 7. Power Contracts Chapter 8. Portfolio Optimisation Chapter 9. Example C++ Classes Appendix A. The Greeks for Vanilla European Options Appendix B. Standard Statistical Results Appendix C. Statistical Distribution FunctionsAppendix D. Mathematical Reference Appendix E. Answers to Problems