LEADER 02405nam 22007093u 450 001 9910450147503321 005 20210117180240.0 010 $a1-282-86116-6 010 $a9786612861161 010 $a0-7735-7106-X 035 $a(CKB)1000000000244881 035 $a(EBL)3243420 035 $a(SSID)ssj0000278716 035 $a(PQKBManifestationID)11217973 035 $a(PQKBTitleCode)TC0000278716 035 $a(PQKBWorkID)10246990 035 $a(PQKB)11259642 035 $a(MiAaPQ)EBC3330660 035 $a(MiAaPQ)EBC3243420 035 $a(EXLCZ)991000000000244881 100 $a20160606d2014|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDigital Play$b[electronic resource] $eThe Interaction of Technology, Culture, and Marketing 210 $aMontre?al $cMcGill-Queen's University Press$d2014 215 $a1 online resource (378 p.) 300 $aDescription based upon print version of record. 311 $a0-7735-2591-2 311 $a0-7735-2543-2 327 $aPages:1 to 25; Pages:26 to 50; Pages:51 to 75; Pages:76 to 100; Pages:101 to 125; Pages:126 to 150; Pages:151 to 175; Pages:176 to 200; Pages:201 to 225; Pages:226 to 250; Pages:251 to 275; Pages:276 to 300; Pages:301 to 325; Pages:326 to 350; Pages:351 to 375; Pages:376 to 378 606 $aElectronic books 606 $aElectronic games -- Social aspects 606 $aElectronic games industry 606 $aVideo games$xSocial aspects 606 $aVideo games$xEconomic aspects 606 $aIndustries$2HILCC 606 $aRecreation & Sports$2HILCC 606 $aBusiness & Economics$2HILCC 606 $aSocial Sciences$2HILCC 608 $aElectronic books. 615 4$aElectronic books. 615 4$aElectronic games -- Social aspects. 615 4$aElectronic games industry. 615 0$aVideo games$xSocial aspects 615 0$aVideo games$xEconomic aspects 615 7$aIndustries 615 7$aRecreation & Sports 615 7$aBusiness & Economics 615 7$aSocial Sciences 676 $a338.4/77948 700 $aKline$b Stephen$048259 701 $aDyer-Witheford$b Nick$0706529 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910450147503321 996 $aDigital play$91463765 997 $aUNINA LEADER 04573nam 22006615 450 001 9910874679003321 005 20251217135726.0 010 $a9783031605758$b(electronic bk.) 010 $z9783031605741 024 7 $a10.1007/978-3-031-60575-8 035 $a(MiAaPQ)EBC31534705 035 $a(Au-PeEL)EBL31534705 035 $a(CKB)33030951200041 035 $a(DE-He213)978-3-031-60575-8 035 $a(EXLCZ)9933030951200041 100 $a20240719d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputation and Simulation for Finance $eAn Introduction with Python /$fby Cónall Kelly 205 $a1st ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (335 pages) 225 1 $aSpringer Undergraduate Texts in Mathematics and Technology,$x1867-5514 311 08$aPrint version: Kelly, Cónall Computation and Simulation for Finance Cham : Springer International Publishing AG,c2024 9783031605741 320 $aIncludes bibliographical references and index. 327 $a- Part I Modelling Assets and Markets -- Introduction -- The Pricing of Financial Derivatives -- Part II Computational Pricing Methods in the Black-Scholes Framework -- Binomial Tree Methods -- Simulation I: Monte Carlo Methods -- Finite Difference Methods -- Part III Simulation Methods Beyond the Black-Scholes Framework -- Simulation II: Modelling Multivariate Financial Data -- Stochastic Models for Interest Rates -- Simulation III: Numerical Approximation of SDE Models. 330 $aThis book offers an up-to-date introductory treatment of computational techniques applied to problems in finance, placing issues such as numerical stability, convergence and error analysis in both deterministic and stochastic settings at its core. The first part provides a welcoming but nonetheless rigorous introduction to the fundamental theory of option pricing, including European, American, and exotic options along with their hedge parameters, and combines a clear treatment of the mathematical framework with practical worked examples in Python. The second part explores the main computational methods for valuing options within the Black-Scholes framework: lattice, Monte Carlo, and finite difference methods. The third and final part covers advanced topics for the simulation of financial processes beyond the standard Black-Scholes setting. Techniques for the analysis and simulation of multidimensional financial data, including copulas, are covered and will be of interest to those studying machine learning for finance. There is also an in-depth treatment of exact and approximate sampling methods for stochastic differential equation models of interest rates and volatilities. Written for advanced undergraduate and masters-level courses, the book assumes some exposure to core mathematical topics such as linear algebra, ordinary differential equations, multivariate calculus, probability, and statistics at an undergraduate level. 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