LEADER 06854nam 22008655 450 001 9910254863803321 005 20240701122141.0 010 $a9781137560155 010 $a1137560150 024 7 $a10.1057/9781137560155 035 $a(CKB)3710000000526432 035 $a(EBL)4098307 035 $a(SSID)ssj0001616786 035 $a(PQKBManifestationID)16348955 035 $a(PQKBTitleCode)TC0001616786 035 $a(PQKBWorkID)14922465 035 $a(PQKB)10454561 035 $a(DE-He213)978-1-137-56015-5 035 $a(MiAaPQ)EBC4098307 035 $a(PPN)191704733 035 $a(Perlego)3488859 035 $a(EXLCZ)993710000000526432 100 $a20160126d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aModeling and Valuation of Energy Structures $eAnalytics, Econometrics, and Numerics /$fby Daniel Mahoney 205 $a1st ed. 2016. 210 1$aLondon :$cPalgrave Macmillan UK :$cImprint: Palgrave Macmillan,$d2016. 215 $a1 online resource (475 p.) 225 1 $aApplied Quantitative Finance,$x2947-7018 300 $aDescription based upon print version of record. 311 08$a9781349566884 311 08$a1349566888 311 08$a9781137560148 311 08$a1137560142 320 $aIncludes bibliographical references and index. 327 $aCover ; Half-Tile ; Title ; Contents; List of Figures; List of Tables; Preface; Acknowledgments; 1 Synopsis of Selected EnergyMarkets and Structures; 1.1 Challenges of modeling in energy markets; 1.1.1 High volatilities/jumps; 1.1.2 Small samples; 1.1.3 Structural change; 1.1.4 Physical/operational constraints; 1.2 Characteristic structured products; 1.2.1 Tolling arrangements; 1.2.2 Gas transport; 1.2.3 Gas storage; 1.2.4 Load serving; 1.3 Prelude to robust valuation; 2 Data Analysis and StatisticalIssues; 2.1 Stationary vs. non-stationary processes; 2.1.1 Concepts 327 $a2.1.2 Basic discrete time models: AR and VAR2.2 Variance scaling laws and volatilityaccumulation33; 2.2.1 The role of fundamentals and exogenous drivers; 2.2.2 Time scales and robust estimation; 2.2.3 Jumps and estimation issues; 2.2.4 Spot prices; 2.2.5 Forward prices; 2.2.6 Demand side: temperature; 2.2.7 Supply side: heat rates, spreads, and productionstructure; 2.3 A recap; 3 Valuation, Portfolios, andOptimization; 3.1 Optionality, hedging, and valuation; 3.1.1 Valuation as a portfolio construction problem; 3.1.2 Black Scholes as a paradigm; 3.1.3 Static vs. dynamic strategies 327 $a3.1.4 More on dynamic hedging: rolling intrinsic3.1.5 Market resolution and liquidity; 3.1.6 Hedging miscellany: greeks, hedge costs, and discounting; 3.2 Incomplete markets and the minimal martingale measure^61; 3.2.1 Valuation and dynamic strategies; 3.2.2 Residual risk and portfolio analysis; 3.3 Stochastic optimization; 3.3.1 Stochastic dynamic programming and HJB; 3.3.2 Martingale duality; 3.4 Appendix; 3.4.1 Vega hedging and value drivers; 3.4.2 Value drivers and information conditioning; 4 Selected Case Studies; 4.1 Storage; 4.2 Tolling; 4.3 Appendix 327 $a4.3.1 (Monthly) Spread option representation of storage4.3.2 Lower-bound tolling payoffs; 5 Analytical Techniques; 5.1 Change of measure techniques; 5.1.1 Review/main ideas; 5.1.2 Dimension reduction/computation facilitation/estimation robustness; 5.1.3 Max/min options; 5.1.4 Quintessential option pricing formula; 5.1.5 Symmetry results: Asian options; 5.2 Affine jump diffusions/characteristic function methods; 5.2.1 Le?vy processes; 5.2.2 Stochastic volatility; 5.2.3 Pseudo-unification: affine jump diffusions; 5.2.4 General results/contour integration; 5.2.5 Specific examples 327 $a5.2.6 Application to change of measure5.2.7 Spot and implied forward models; 5.2.8 Fundamental drivers and exogeneity; 5.2.9 Minimal martingale applications; 5.3 Appendix; 5.3.1 More Asian option results; 5.3.2 Further change-of-measure applications; 6 Econometric Concepts; 6.1 Cointegration and mean reversion; 6.1.1 Basic ideas; 6.1.2 Granger causality; 6.1.3 Vector Error Correction Model (VECM); 6.1.4 Connection to scaling laws; 6.2 Stochastic filtering; 6.2.1 Basic concepts; 6.2.2 The Kalman filter and its extensions 327 $a6.2.3 Heston vs. generalized autoregressive conditional heteroskedasticity (GARCH) 330 $aCommodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling. 410 0$aApplied Quantitative Finance,$x2947-7018 606 $aEconometrics 606 $aFinance 606 $aBusiness mathematics 606 $aEnergy policy 606 $aEnergy policy 606 $aMathematics 606 $aEconometrics 606 $aFinancial Economics 606 $aBusiness Mathematics 606 $aEnergy Policy, Economics and Management 606 $aMathematics 615 0$aEconometrics. 615 0$aFinance. 615 0$aBusiness mathematics. 615 0$aEnergy policy. 615 0$aEnergy policy. 615 0$aMathematics. 615 14$aEconometrics. 615 24$aFinancial Economics. 615 24$aBusiness Mathematics. 615 24$aEnergy Policy, Economics and Management. 615 24$aMathematics. 676 $a330.015195 700 $aMahoney$b Daniel$4aut$4http://id.loc.gov/vocabulary/relators/aut$0953809 906 $aBOOK 912 $a9910254863803321 996 $aModeling and Valuation of Energy Structures$92156588 997 $aUNINA LEADER 01613nam 22004213 450 001 9911028660803321 005 20250930085251.0 010 $a981-9654-08-4 035 $a(MiAaPQ)EBC32320775 035 $a(Au-PeEL)EBL32320775 035 $a(CKB)41018927200041 035 $a(EXLCZ)9941018927200041 100 $a20250930d2025 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI in Multidimensional Signals Analysis and Processing $eProceedings of The 3DIT-MSP&DL 2024 205 $a1st ed. 210 1$aSingapore :$cSpringer,$d2025. 210 4$dİ2025. 215 $a1 online resource (429 pages) 225 1 $aSmart Innovation, Systems and Technologies Series ;$vv.116 311 08$a981-9654-07-6 330 $aThis book presents high-quality research in the field of 3D imaging technology.The sixth edition of International Conference on 3D Imaging Technology (3DDIT-MSP&DL 2024) continues the good traditions already established by the first five editions of the conference to provide a wide scientific forum for researchers, academia, and practitioners to. 410 0$aSmart Innovation, Systems and Technologies Series 676 $a621.367 700 $aJain$b Lakhmi C$0530242 701 $aKountcheva$b Roumiana$01439064 701 $aLiu$b Yingkai$01770640 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911028660803321 996 $aAI in Multidimensional Signals Analysis and Processing$94438700 997 $aUNINA