LEADER 01397nam0 22003493i 450 001 PUV0692977 005 20231121125618.0 010 $a9004047255 100 $a20141114d1976 ||||0itac50 ba 101 | $aeng 102 $anl 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aLatin script and letters A. D. 400-900$eFestschrift presented to Ludwig Bieler on the occasion of his 70th birthday$fedited by John J. O'Meara and Bernd Naumann 210 $aLeidein$cE. J. Brill$d1976 215 $aVI, 276 p., 1 ritr.$d25 cm. 606 $aLetteratura latina$2FIR$3RMLC001853$9N 702 1$aBieler$b, Ludwig$3RAVV076019 702 1$aNaumann$b, Bernd$3SBLV113707 702 1$aO?Meara$b, John J.$3UBOV032333 790 1$aBieler$b, Ludovicus$3UTOV545717$zBieler, Ludwig 790 1$aO?Meara$b, John Joseph$3UFIV127672$zO?Meara, John J. 790 1$aO?Meara$b, John$3UFIV127673$zO?Meara, John J. 790 1$aO'Meara$b, John J.$3UMCV342299$zO?Meara, John J. 801 3$aIT$bIT-01$c20141114 850 $aIT-FR0017 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 $eN 912 $aPUV0692977 950 0$aBiblioteca umanistica Giorgio Aprea$d 52S.SIJ. H1 Bie.$e 52FLS0000198835 VMB RS $fA $h20141114$i20141114 977 $a 52 996 $aLatin script and letters A. D. 400-900$93614231 997 $aUNICAS LEADER 06115nam 2200601Ia 450 001 9910830374503321 005 20230725061354.0 010 $a1-4443-9269-7 010 $a1-4443-9271-9 010 $a1-283-40798-1 010 $a9786613407986 010 $a1-4443-9270-0 035 $a(CKB)3710000000503925 035 $a(EBL)4043985 035 $a(MiAaPQ)EBC4043985 035 $a(MiAaPQ)EBC675177 035 $a(OCoLC)729731400 035 $a(EXLCZ)993710000000503925 100 $a20100929d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 12$aA probability metrics approach to financial risk measures$b[electronic resource] /$fSvetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi 210 $aChichester, West Sussex, U.K. ;$aMalden, MA $cWiley-Blackwell$d2011 215 $a1 online resource (283 p.) 300 $aDescription based upon print version of record. 311 $a1-4051-8369-1 320 $aIncludes bibliographical references and index. 327 $a""Title Page""; ""Copyright""; ""Dedication""; ""Preface""; ""About the Authors""; ""Chapter 1: Introduction""; ""1.1 Probability Metrics""; ""1.2 Applications in Finance""; ""References""; ""Chapter 2: Probability Distances and Metrics""; ""2.1 Introduction""; ""2.2 Some Examples of Probability Metrics""; ""2.3 Distance and Semidistance Spaces""; ""2.4 Definitions of Probability Distances and Metrics""; ""2.5 Summary""; ""2.6 Technical Appendix""; ""References""; ""Chapter 3: Choice under Uncertainty""; ""3.1 Introduction""; ""3.2 Expected Utility Theory""; ""3.3 Stochastic Dominance"" 327 $a""3.4 Probability Metrics and Stochastic Dominance""""3.5 Cumulative Prospect Theory""; ""3.6 Summary""; ""3.7 Technical Appendix""; ""References""; ""Chapter 4: A Classification of Probability Distances""; ""4.1 Introduction""; ""4.2 Primary Distances and Primary Metrics""; ""4.3 Simple Distances and Metrics""; ""4.4 Compound Distances and Moment Functions""; ""4.5 Ideal Probability Metrics""; ""4.6 Summary""; ""4.7 Technical Appendix""; ""References""; ""Chapter 5: Risk and Uncertainty""; ""5.1 Introduction""; ""5.2 Measures of Dispersion"" 327 $a""5.3 Probability Metrics and Dispersion Measures""""5.4 Measures of Risk""; ""5.5 Risk Measures and Dispersion Measures""; ""5.6 Risk Measures and Stochastic Orders""; ""5.7 Summary""; ""5.8 Technical Appendix""; ""References""; ""Chapter 6: Average Value-at-Risk""; ""6.1 Introduction""; ""6.2 Average Value-at-Risk""; ""6.3 AVaR Estimation from a Sample""; ""6.4 Computing Portfolio AVaR in Practice""; ""6.5 Back-Testing of AVaR""; ""6.6 Spectral Risk Measures""; ""6.7 Risk Measures and Probability Metrics""; ""6.8 Risk Measures Based on Distortion Functionals""; ""6.9 Summary"" 327 $a""6.10 Technical Appendix""""References""; ""Chapter 7: Computing AVaR through Monte Carlo""; ""7.1 Introduction""; ""7.2 An Illustration of Monte Carlo Variability""; ""7.3 Asymptotic Distribution, Classical Conditions""; ""7.4 Rate of Convergence to the Normal Distribution""; ""7.5 Asymptotic Distribution, Heavy-tailed Returns""; ""7.6 Rate of Convergence, Heavy-tailed Returns""; ""7.7 On the Choice of a Distributional Model""; ""7.8 Summary""; ""7.9 Technical Appendix""; ""References""; ""Chapter 8: Stochastic Dominance Revisited""; ""8.1 Introduction"" 327 $a""8.2 Metrization of Preference Relations""""8.3 The Hausdorff Metric Structure""; ""8.4 Examples""; ""8.5 Utility-type Representations""; ""8.6 Almost Stochastic Orders and Degree of Violation""; ""8.7 Summary""; ""8.8 Technical Appendix""; ""References""; ""Index"" 330 $a"A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. Helps to answer the question: which risk measure is best for a given problem? Finds new relations between existing classes of risk measures. Describes applications in finance and extends them where possible. Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field. Applications include optimal portfolio choice, risk theory, and numerical methods in finance. Topics requiring more mathematical rigor and detail are included in technical appendices to chapters."--Provided by publisher. 330 $a"Is the behavior of the stocks in our portfolio close to their behavior during the most recent crisis? How close is the strategy of hedge fund A to the strategy of hedge fund B? In which proportions do we invest in a given universe of stocks so that the resulting portfolio matches as much as possible the strategy of fund C? All of these questions are essential to finance and they have one feature in common: measuring distances between random quantities. Problems of this kind have been explored for many years in areas other than finance. In A Probability Metrics Approach to Financial Risk Measures, the field of probability metrics and risk measures are related to one another and applied to finance for the first time, revealing groundbreaking new classes of risk measures, finding new relations between existing classes of risk measures, and providing answers to the question of which risk measure is best for a given problem. Applications include optimal portfolio choice, risk theory, and numerical methods in finance"--Provided by publisher. 606 $aFinancial risk management 606 $aProbabilities 615 0$aFinancial risk management. 615 0$aProbabilities. 676 $a332.015192 686 $aBUS033070$2bisacsh 700 $aRachev$b S. T$g(Svetlozar Todorov)$059738 701 $aStoyanov$b Stoyan V$01654203 701 $aFabozzi$b Frank J$0109596 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830374503321 996 $aA probability metrics approach to financial risk measures$94047799 997 $aUNINA