LEADER 04124nam 22007215 450 001 9910298518103321 005 20200919022716.0 010 $a3-662-45037-2 024 7 $a10.1007/978-3-662-45037-6 035 $a(CKB)3710000000311757 035 $a(EBL)1966110 035 $a(OCoLC)897810360 035 $a(SSID)ssj0001407908 035 $a(PQKBManifestationID)11888713 035 $a(PQKBTitleCode)TC0001407908 035 $a(PQKBWorkID)11413033 035 $a(PQKB)11569621 035 $a(DE-He213)978-3-662-45037-6 035 $a(MiAaPQ)EBC1966110 035 $a(PPN)183149181 035 $a(EXLCZ)993710000000311757 100 $a20141204d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA Time Series Approach to Option Pricing $eModels, Methods and Empirical Performances /$fby Christophe Chorro, Dominique Guégan, Florian Ielpo 205 $a1st ed. 2015. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2015. 215 $a1 online resource (202 p.) 300 $aDescription based upon print version of record. 311 $a3-662-45036-4 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- 1 The Time Series Toolbox for Financial Returns -- 2 The Stochastic Discount Factor Approach -- 3 Empirical Performances -- Mathematical Appendix -- Index. 330 $aThe current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book explains how the economic messages delivered by the dynamic evolution of financial asset returns are strongly related to option prices. The Black Scholes framework is introduced and by underlining its shortcomings,an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models. The reader then learns what it takes to understand and implement these option pricing models based on time series analysis in a self-contained way. The discussion covers modeling choices available to the quantitative analyst, as well as the tools to decide upon a particular model based on the historical datasets of financial returns. The reader is then guided into numerical deduction of option prices from these models and illustrations with real examples are used to reflect the accuracy of the approach using datasets of options on equity indices. 606 $aFinance 606 $aMacroeconomics 606 $aEconomics, Mathematical  606 $aStatistics  606 $aFinance, general$3https://scigraph.springernature.com/ontologies/product-market-codes/600000 606 $aMacroeconomics/Monetary Economics//Financial Economics$3https://scigraph.springernature.com/ontologies/product-market-codes/W32000 606 $aQuantitative Finance$3https://scigraph.springernature.com/ontologies/product-market-codes/M13062 606 $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010 615 0$aFinance. 615 0$aMacroeconomics. 615 0$aEconomics, Mathematical . 615 0$aStatistics . 615 14$aFinance, general. 615 24$aMacroeconomics/Monetary Economics//Financial Economics. 615 24$aQuantitative Finance. 615 24$aStatistics for Business, Management, Economics, Finance, Insurance. 676 $a330 676 $a330.015195 676 $a332 676 $a519 700 $aChorro$b Christophe$4aut$4http://id.loc.gov/vocabulary/relators/aut$01065475 702 $aGuégan$b Dominique$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aIelpo$b Florian$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298518103321 996 $aA Time Series Approach to Option Pricing$92545824 997 $aUNINA