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Energy Power Risk : Derivatives, Computation and Optimization.
The book describes both mathematical and computational tools for energy and power risk management, deriving from first principles stochastic models for simulating commodity risk and how to design robust C++ to implement these models.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Bingley :
Emerald Publishing Limited,
2018.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 020 | |a 9781787435278 | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Levy, George. | |
| 245 | 1 | 0 | |a Energy Power Risk : |b Derivatives, Computation and Optimization. |
| 260 | |a Bingley : |b Emerald Publishing Limited, |c 2018. | ||
| 300 | |a 1 online resource (345 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover; Energy Power Risk: Derivatives, Computation and Optimization; Copyright Page; Contents; List of Figures; List of Tables; Notations; Preface; Chapter 1 Overview; Chapter 2 Brownian Motion and Stochastic Processes; 2.1. Brownian Motion; 2.1.1. The Properties of Brownian Motion; 2.1.2. A Brownian Model of Asset Price Movements; 2.2. Ito's Formula (or Lemma); 2.3. Girsanov's Theorem; 2.4. Ito's Lemma for Multi-Asset Geometric Brownian Motion; 2.5. Ito Product and Quotient Rules in Two Dimensions; 2.6. Ito Product in n Dimensions; 2.7. The Brownian Bridge; 2.9. Poisson Process | |
| 505 | 8 | |a 2.10. Stochastic Integrals2.10.1. Fubini's Theorem; 2.11. Selected Problems; Chapter 3 Fundamental Power Price Model; 3.1. A Power Stack Model; 3.2. ModelingWind and Solar Generation; 3.3. Simulated Half Hourly Power Price; 4 Single Asset European Options; 4.1. Introduction; 4.2. Pricing Derivatives Using a Martingale Measure; 4.3. Put -- Call Parity; 4.3.1. Continuous Dividends; 4.4. Vanilla Options and The Black -- Scholes Model; 4.4.1. The Option Pricing Partial Differential Equation; 4.4.2. The Multi-Asset Option Pricing Partial Differential Equation; 4.4.3. The Black-Scholes Formula | |
| 505 | 8 | |a 4.4.3.1. The Inclusion of Continuous Dividends4.4.3.2. The Greeks; 4.4.4. Historical and Implied Volatility; 4.4.4.1. Historical Volatility; 4.4.4.2. Implied Volatility; 4.4.5. Microsoft Excel; 4.5. One-factor Spot Model; 4.6. One Factor Forward Curve Model; 4.6.1. Introduction; 4.6.2. The Spot Price Process; 4.6.3. The Relationship Between the Forward Price and the Spot Price; 4.6.4. Option Pricing Formula; 4.7. Two- factor Spot Model; 4.8. Multifactor Forward Curve Model; 4.9. Johnson Distribution; 4.9.1. Option Pricing Formula; 4.9.2. Parameter Estimation; 4.10. Weibull Distribution | |
| 505 | 8 | |a 4.10.1. StandardWeibull Distribution4.10.2. Doubly TruncatedWeibull Distribution; 4.11. Merton Jump Diffusion Model; 4.11.1. Monte Carlo Simulation; 4.11.2. Analytic Option Pricing Formulae; Chapter 5 Single Asset American Style Options; 5.1. Introduction; 5.2. Lattice Methods for Vanilla Options; 5.2.1. Standard Binomial Lattice; 5.2.2. Constructing and Using the Standard Binomial Lattice; 5.2.3. Log Transformed Binomial Lattice; 5.2.4. Johnson Binomial Lattice; 5.2.5. Trinomial Lattice; 5.3. Grid Methods for Vanilla Options; 5.3.1. Introduction; 5.3.2. Standard Grids | |
| 505 | 8 | |a 5.3.3. Log-transformed GridsChapter 6 Multi-asset Options; 6.1. Introduction; 6.2. The Multi-asset Black-Scholes Equation; 6.3. Multidimensional Monte Carlo Methods; 6.4. Introduction to Multidimensional Lattice Methods; 6.5. Two Asset Options; 6.5.1. European Exchange Options; 6.5.2. European Options on the Maximum or Minimum; 6.5.3. American Options; 6.6. Three Asset Options; Chapter 7 Power Contracts; 7.1. Imbalance Risk; 7.1.1. The Stand-alone Cost; 7.1.2. The Bene.t of Including the Customer into the Portfolio; 7.1.3. Market Index Price (MIP) | |
| 500 | |a 7.1.4. System Buy Price (SBP) and System Sell Price (SSP) | ||
| 520 | |a The book describes both mathematical and computational tools for energy and power risk management, deriving from first principles stochastic models for simulating commodity risk and how to design robust C++ to implement these models. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Power resources |x Risk management |x Mathematical models. | |
| 650 | 0 | |a Power resources |x Risk management |x Data processing. | |
| 650 | 6 | |a Ressources énergétiques |x Gestion du risque |x Modèles mathématiques. | |
| 650 | 6 | |a Ressources énergétiques |x Gestion du risque |x Informatique. | |
| 650 | 7 | |a Computer science. |2 bicssc | |
| 650 | 7 | |a Computers |x General. |2 bisacsh | |
| 758 | |i has work: |a Energy power risk (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGqRjbh4DCKBtcGXV96CpK |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Levy, George. |t Energy Power Risk : Derivatives, Computation and Optimization. |d Bingley : Emerald Publishing Limited, ©2018 |z 9781787435285 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5608877 |z Texto completo |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH34988389 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5608877 | ||
| 938 | |a YBP Library Services |b YANK |n 15877159 | ||
| 994 | |a 92 |b IZTAP | ||