LEADER 05298nam 2200625 a 450 001 9910830899103321 005 20170815111207.0 010 $a1-119-20710-X 010 $a1-281-93956-0 010 $a9786611939564 010 $a0-470-72124-3 035 $a(CKB)1000000000553163 035 $a(EBL)366859 035 $a(OCoLC)298842229 035 $a(SSID)ssj0000101577 035 $a(PQKBManifestationID)11122145 035 $a(PQKBTitleCode)TC0000101577 035 $a(PQKBWorkID)10042427 035 $a(PQKB)11775736 035 $a(MiAaPQ)EBC366859 035 $a(CaSebORM)9780470754467 035 $a(EXLCZ)991000000000553163 100 $a20080604d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAlternative beta strategies and hedge fund replication$b[electronic resource] /$fLars Jaeger ; with Jeffrey Pease 205 $a1st edition 210 $aChichester, England ;$aHoboken, NJ $cWiley$dc2008 215 $a1 online resource (275 p.) 300 $aDescription based upon print version of record. 311 $a0-470-75446-X 320 $aIncludes bibliographical references (p. [245]-252) and index. 327 $aAlternative Beta Strategies and Hedge Fund Replication; Contents; Preface; 1 Breaking the Black Box; 1.1 New popularity, old confusion; 1.2 The challenges of understanding hedge funds; 1.3 Leaving Alphaville; 1.4 The beauty of beta; 1.5 Alternative versus traditional beta; 1.6 The replication revolution; 1.7 Full disclosure; 2 What Are Hedge Funds, Where Did They Come From, and Where Are They Going?; 2.1 Characteristics of hedge funds; 2.2 Hedge funds as an asset class; 2.3 Taxonomy of hedge funds; 2.4 Myths, misperceptions, and realities about hedge funds; 2.5 A short history of hedge funds 327 $a2.6 The hedge fund industry today2.7 The future of hedge funds - opportunities and challenges; 3 The Individual Hedge Fund Strategies' Characteristics; 3.1 Equity Hedged - Long/Short Equity; 3.2 Equity Hedged - Equity Market Neutral; 3.3 Equity Hedged - Short Selling; 3.4 Relative Value - general; 3.5 Relative Value - Fixed Income Arbitrage; 3.6 Relative Value - Convertible Arbitrage; 3.7 Relative Value - Volatility Arbitrage; 3.8 Relative Value - Capital Structure Arbitrage; 3.9 Event Driven - general; 3.10 Event Driven - Merger Arbitrage; 3.11 Event Driven - Distressed Securities 327 $a3.12 Event Driven - Regulation D3.13 Opportunistic - Global Macro; 3.14 Managed Futures; 3.15 Managed Futures - Systematic; 3.16 Managed Futures - Discretionary; 3.17 Conclusion of the chapter; 4 Empirical Return and Risk Properties of Hedge Funds; 4.1 When the Sharpe ratio is not sharp enough; 4.2 Challenges of hedge fund performance measurement - the issue with hedge fund indices; 4.3 Sources of empirical data; 4.4 Risk and return properties of hedge fund strategies; 4.5 Comparison with equities and bonds; 4.6 Deviation from normal distribution; 4.7 Unconditional correlation properties 327 $a4.8 Conditional returns and correlations4.9 Hedge fund behavior in extreme market situations; 4.10 Benefits of hedge funds in a traditional portfolio; 4.11 Quantitative portfolio optimization for hedge funds revisited; 4.12 Summary of empirical properties; 4.13 Appendix: Data providers for past hedge fund performance; 5 The Drivers of Hedge Fund Returns; 5.1 Alpha versus beta; 5.2 The enigma of hedge fund returns; 5.3 Hedge fund returns: how much is alpha?; 5.4 The efficient market hypothesis; 5.5 Questioning the efficient market hypothesis: behavioral finance 327 $a5.6 The theoretical framework of modern finance: asset pricing models and the interpretations of alpha5.7 Systematic risk premia: the prevalence of beta in the global capital markets; 5.8 Risk premia and economic functions; 5.9 Market inefficiencies: the 'search for alpha'; 5.10 An illustration of the nature of hedge fund returns; 5.11 The decrease of alpha; 5.12 The beauty of alternative beta; 5.13 The future of hedge fund capacity; 5.14 Momentum and value; 5.15 Active strategies and option-like returns; 5.16 Why manager skill matters 327 $a5.17 Buyer beware: some final words of caution about hedge fund returns 330 $aThere s a buzzword that has quickly captured the imagination of product providers and investors alike: ""hedge fund replication"". In the broadest sense, replicating hedge fund strategies means replicating their return sources and corresponding risk exposures. However, there still lacks a coherent picture on what hedge fund replication means in practice, what its premises are, how to distinguish di erent approaches, and where this can lead us to. Serving as a handbook for replicating the returns of hedge funds at considerably lower cost, Alternative Beta Strategies and Hedge Fund Replicat 606 $aHedge funds 615 0$aHedge funds. 676 $a332.64/524 676 $a332.64524 700 $aJaeger$b Lars$0835567 701 $aPease$b Jeffrey$01636028 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830899103321 996 $aAlternative beta strategies and hedge fund replication$93977113 997 $aUNINA LEADER 04450nam 22006495 450 001 9910864178903321 005 20251225200540.0 010 $a9783031605970 010 $a3031605977 024 7 $a10.1007/978-3-031-60597-0 035 $a(CKB)32200493200041 035 $a(DE-He213)978-3-031-60597-0 035 $a(MiAaPQ)EBC31356916 035 $a(Au-PeEL)EBL31356916 035 $a(EXLCZ)9932200493200041 100 $a20240528d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntegration of Constraint Programming, Artificial Intelligence, and Operations Research $e21st International Conference, CPAIOR 2024, Uppsala, Sweden, May 28?31, 2024, Proceedings, Part I /$fedited by Bistra Dilkina 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (XIV, 349 p. 79 illus., 68 illus. in color.) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14742 311 08$a9783031605963 311 08$a3031605969 320 $aIncludes bibliographical references and index. 327 $aOnline optimization of a dial-a-ride problem with the integral primal simplex -- A Constraint Programming Model for the Electric Bus Assignment Problem with Parking Constraints -- Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem -- Effciently Mining Closed Interval Patterns with Constraint Programming -- Local Alterations of the Lagrange Multipliers for Enhancing the Filtering of the AtMostNValue -- Single Constant Multiplication for SAT -- Towards a Generic Representation of Combinatorial -- Problems for Learning-Based Approaches -- Accelerating Continuous Variable Coherent Ising Machines via Momentum -- Decision-focused predictions via pessimistic bilevel optimization: a computational study -- Bi-Objective Discrete Graphical Model Optimization -- An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis -- UNSAT Solver Synthesis via Monte Carlo Forest Search -- A hybrid approach integrating Generalized Arc Consistency and Differential Evolution for global optimization -- Assessing Group Fairness with Social Welfare Optimization -- Modeling and Exploiting Dominance Rules for Discrete Optimization with Decision Diagrams -- ViolationLS: Constraint-Based Local Search in CP-SAT -- ULD Build-Up Scheduling with Logic-Based Benders Decomposition -- A decomposition approach for a capacitated multi-vehicle covering tour problem with intermediate facilities -- Don?t Explain Noise: Robust Counterfactuals for Randomized Ensembles -- Certifying MIP-based Presolve Reductions for 0-1 Integer Linear Programs -- Learning to Solve Job Shop Scheduling under Uncertainty. 330 $aThis book constitutes the proceedings of the 21st International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024, held in Uppsala, Sweden, during May 28?31, 2024. The 33 full papers and the 9 short papers presented in the proceedings were carefully reviewed and selected from a total of 104 submissions. The content of the papers focus on new techniques or applications in the area and foster the integration of techniques from different fields dealing with large and complex problems. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14742 606 $aComputer science$xMathematics 606 $aArtificial intelligence 606 $aComputer science 606 $aComputer networks 606 $aMathematics of Computing 606 $aArtificial Intelligence 606 $aTheory of Computation 606 $aComputer Communication Networks 615 0$aComputer science$xMathematics. 615 0$aArtificial intelligence. 615 0$aComputer science. 615 0$aComputer networks. 615 14$aMathematics of Computing. 615 24$aArtificial Intelligence. 615 24$aTheory of Computation. 615 24$aComputer Communication Networks. 676 $a006.3 702 $aDilkina$b Bistra 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910864178903321 996 $aIntegration of Constraint Programming, Artificial Intelligence, and Operations Research$92880461 997 $aUNINA