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  • 1
    UID:
    almafu_BV012120553
    Format: IX, 240 S. : , graph. Darst.
    ISBN: 3-486-24997-5 , 978-3-486-24997-2
    Series Statement: Lehr- und Handbücher zur entscheidungsorientierten Betriebswirtschaft
    Note: Begleitung zu: Fischer, Edwin O.: Finanzwirtschaft für Anfänger
    Additional Edition: Erscheint auch als Online-Ausgabe, PDF ISBN 978-3-486-79958-3
    Language: German
    Subjects: Economics
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    Keywords: Finanzwirtschaft ; Finanzierung ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung
    Author information: Fischer, Edwin O. 1957-
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  • 2
    UID:
    almahu_BV012120555
    Format: XIII, 189 S.
    ISBN: 3-486-24998-3
    Series Statement: Lehr- und Handbücher zur entscheidungsorientierten Betriebswirtschaft
    Note: Ergänzung zu: Fischer, Edwin O.: Finanzwirtschaft für Fortgeschrittene
    Language: German
    Subjects: Economics
    RVK:
    Keywords: Finanzwirtschaft ; Finanzierung ; Investitionsplanung ; Finanzierungstheorie ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung ; Aufgabensammlung
    Author information: Fischer, Edwin O., 1957-
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  • 3
    Online Resource
    Online Resource
    Waltham, Mass. :Academic Press, an imprint of Elsevier,
    UID:
    almahu_9948026072002882
    Format: 1 online resource (601 p.)
    Edition: 1st edition
    ISBN: 1-283-16395-0 , 9786613163950 , 0-12-375663-4
    Content: This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At
    Note: Description based upon print version of record. , pt. 1. Fundamentals -- pt. 2. Simulation -- pt. 3. Optimization. , English
    Additional Edition: ISBN 1-4933-0118-7
    Additional Edition: ISBN 0-12-375662-6
    Language: English
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  • 4
    Online Resource
    Online Resource
    London, England :Elsevier :
    UID:
    almahu_9948212112802882
    Format: 1 online resource (984 pages)
    Edition: Second edition.
    ISBN: 0-12-815066-1
    Note: Front Cover -- Numerical Methods and Optimization in Finance -- Copyright -- Contents -- List of gures -- List of tables -- List of algorithms -- Acknowledgments -- Foreword to the second edition -- About R code -- Part I Fundamentals -- 1 Introduction -- 1.1 About this book -- The growth of computing power -- Computational nance -- 1.2 Principles -- 1.3 On software -- 1.4 On approximations and accuracy -- 1.5 Summary: the theme of the book -- 2 Numerical analysis in a nutshell -- 2.1 Computer arithmetic -- Representation of real numbers -- Machine precision -- Example of limitations of oating point arithmetic -- 2.2 Measuring errors -- 2.3 Approximating derivatives with nite differences -- Approximating rst-order derivatives -- Approximating second-order derivatives -- Partial derivatives -- How to choose h -- Truncation error for forward difference -- 2.4 Numerical instability and ill-conditioning -- Example of a numerically unstable algorithm -- Example of an ill-conditioned problem -- 2.5 Condition number of a matrix -- Comments and examples -- 2.6 A primer on algorithmic and computational complexity -- Criteria for comparison -- Order of complexity and classi cation -- 2.A Operation count for basic linear algebra operations -- 3 Linear equations and Least Squares problems -- Choice of method -- 3.1 Direct methods -- 3.1.1 Triangular systems -- Forward substitution -- Back-substitution -- 3.1.2 LU factorization -- LU factorization with MATLAB -- 3.1.3 Cholesky factorization -- The Cholesky algorithm -- 3.1.4 QR decomposition -- 3.1.5 Singular value decomposition -- 3.2 Iterative methods -- 3.2.1 Jacobi, Gauss-Seidel, and SOR -- Successive overrelaxation -- 3.2.2 Convergence of iterative methods -- 3.2.3 General structure of algorithms for iterative methods -- 3.2.4 Block iterative methods -- 3.3 Sparse linear systems. , 3.3.1 Tridiagonal systems -- 3.3.2 Irregular sparse matrices -- Sparse matrices in MATLAB -- 3.3.3 Structural properties of sparse matrices -- Structural rank -- Block triangular decomposition -- Structurally singular matrices -- 3.4 The Least Squares problem -- 3.4.1 Method of normal equations -- Computation of || r ||22 -- Computation of (A'A)-1 -- 3.4.2 Least Squares via QR factorization -- 3.4.3 Least Squares via SVD decomposition -- 3.4.4 Final remarks -- The backslash operator in MATLAB -- 3.A Solving linear systems in R -- solve -- Least Squares -- 4 Finite difference methods -- 4.1 An example of a numerical solution -- A rst numerical approximation -- A second numerical approximation -- 4.2 Classi cation of differential equations -- 4.3 The Black-Scholes equation -- 4.3.1 Explicit, implicit, and θ-methods -- 4.3.2 Initial and boundary conditions and de nition of the grid -- 4.3.3 Implementation of the θ-method with MATLAB -- 4.3.4 Stability -- 4.3.5 Coordinate transformation of space variables -- 4.4 American options -- 4.A A note on MATLAB's function spdiags -- 5 Binomial trees -- 5.1 Motivation -- Matching moments -- 5.2 Growing the tree -- 5.2.1 Implementing a tree -- 5.2.2 Vectorization -- 5.2.3 Binomial expansion -- 5.3 Early exercise -- 5.4 Dividends -- Continuous dividends -- Discrete dividends -- 5.5 The Greeks -- Greeks from the tree -- Delta Δ -- Gamma Γ -- Theta Θ -- Part II Simulation -- 6 Generating random numbers -- 6.1 Monte Carlo methods and sampling -- 6.1.1 How it all began -- 6.1.2 Financial applications -- 6.2 Uniform random number generators -- 6.2.1 Congruential generators -- 6.2.2 Mersenne Twister -- 6.3 Nonuniform distributions -- 6.3.1 The inversion method -- 6.3.2 Acceptance-rejection method -- 6.4 Specialized methods for selected distributions -- 6.4.1 Normal distribution -- The Box-Muller method. , Marsaglia's polar method -- 6.4.2 Higher order moments and the Cornish-Fisher expansion -- 6.4.3 Further distributions -- 6.5 Sampling from a discrete set -- 6.5.1 Discrete uniform selection -- 6.5.2 Roulette wheel selection -- 6.5.3 Random permutations and shuf ing -- 6.6 Sampling errors-and how to reduce them -- 6.6.1 The basic problem -- 6.6.2 Quasi-Monte Carlo -- General considerations … -- …and caveats -- 6.6.3 Strati ed sampling -- 6.6.4 Variance reduction -- Antithetic variables -- Importance sampling -- 6.7 Drawing from empirical distributions -- 6.7.1 Data randomization -- 6.7.2 Bootstrap -- Basic concepts -- Parametric and nonparametric bootstraps -- 6.8 Controlled experiments and experimental design -- 6.8.1 Replicability and ceteris paribus analysis -- 6.8.2 Available random number generators in MATLAB -- 6.8.3 Uniform random numbers from MATLAB's rand function -- 6.8.4 Gaussian random numbers from MATLAB's randn function -- 6.8.5 Remedies -- 7 Modeling dependencies -- 7.1 Transformation methods -- 7.1.1 Linear correlation -- 7.1.2 Rank correlation -- 7.2 Markov chains -- 7.2.1 Concepts -- 7.2.2 The Metropolis algorithm -- 7.3 Copula models -- 7.3.1 Concepts -- 7.3.2 Simulation using copulas -- Metropolis sampling -- Direct sampling -- 8 A gentle introduction to nancial simulation -- 8.1 Setting the stage -- 8.2 Single-period simulations -- 8.2.1 Terminal asset prices -- 8.2.2 1-over-N portfolios -- 8.2.3 European options -- 8.2.4 VaR of a covered put portfolio -- 8.3 Simple price processes -- 8.4 Processes with memory in the levels of returns -- 8.4.1 Ef cient versus adaptive markets -- 8.4.2 Moving averages -- 8.4.3 Autoregressive models -- 8.4.4 Autoregressive moving average (ARMA) models -- 8.4.5 Simulating ARMA models -- 8.4.6 Models with long-term memory -- 8.5 Time-varying volatility -- 8.5.1 The concepts. , 8.5.2 Autocorrelated time-varying volatility -- 8.5.3 Simulating GARCH processes -- 8.5.4 Selected further autoregressive volatility models -- Additional explanatory variables for returns -- I-GARCH -- GARCH-M -- GJR-GARCH -- T-GARCH -- E-GARCH -- N-GARCH -- Further extensions -- 8.6 Adaptive expectations and patterns in price processes -- 8.6.1 Price-earnings models -- 8.6.2 Models with learning -- 8.7 Historical simulation -- 8.7.1 Backtesting -- 8.7.2 Bootstrap -- 8.8 Agent-based models and complexity -- 9 Financial simulation at work: some case studies -- 9.1 Constant proportion portfolio insurance (CPPI) -- 9.1.1 Basic concepts -- 9.1.2 Bootstrap -- 9.2 VaR estimation with Extreme Value Theory -- 9.2.1 Basic concepts -- 9.2.2 Scaling the data -- 9.2.3 Using Extreme Value Theory -- The Hill estimator -- Further Extreme Value Theory approaches -- Threshold choice -- 9.3 Option pricing -- 9.3.1 Modeling prices -- Arithmetic Brownian motion -- Geometric Brownian motion -- 9.3.2 Pricing models -- Black-Scholes -- One-pass algorithms for variance -- Variance reduction 1: antithetic variates -- Variance reduction 2: control variates -- The Heston model -- 9.3.3 Greeks -- 9.3.4 Quasi-Monte Carlo -- Discrepancy -- Van der Corput sequences -- Dimensionality -- Part III Optimization -- 10 Optimization problems in nance -- 10.1 What to optimize? -- 10.2 Solving the model -- 10.2.1 Problems -- 10.2.2 Classical methods and heuristics -- 10.3 Evaluating solutions -- 10.4 Examples -- Portfolio optimization with alternative risk measures -- Model selection -- Robust/resistant regression -- Agent-based models -- Calibration of option-pricing models -- Calibration of yield structure models -- 10.5 Summary -- 11 Basic methods -- 11.1 Finding the roots of f(x) = 0 -- 11.1.1 A naïve approach -- Graphical solution -- Random search -- 11.1.2 Bracketing. , 11.1.3 Bisection -- 11.1.4 Fixed point method -- Convergence -- 11.1.5 Newton's method -- Comments -- 11.2 Classical unconstrained optimization -- Convergence -- Conditions for local minimizer -- Classi cation of methods -- 11.3 Unconstrained optimization in one dimension -- 11.3.1 Newton's method -- 11.3.2 Golden section search -- 11.4 Unconstrained optimization in multiple dimensions -- 11.4.1 Steepest descent method -- 11.4.2 Newton's method -- 11.4.3 Quasi-Newton method -- 11.4.4 Direct search methods -- 11.4.5 Practical issues with MATLAB -- Unconstrained optimization in MATLAB -- Solution for nonlinear systems of equations in MATLAB -- 11.5 Nonlinear Least Squares -- 11.5.1 Problem statement and notation -- 11.5.2 Gauss-Newton method -- 11.5.3 Levenberg-Marquardt method -- 11.6 Solving systems of nonlinear equations F(x)=0 -- 11.6.1 General considerations -- 11.6.2 Fixed point methods -- Jacobi, Gauss-Seidel, and SOR methods -- 11.6.3 Newton's method -- Convergence -- Computational complexity -- 11.6.4 Quasi-Newton methods -- Broyden's method -- 11.6.5 Further approaches -- Damped Newton -- Solution by minimization -- 11.7 Synoptic view of solution methods -- 12 Heuristic methods in a nutshell -- 12.1 Heuristics -- What is a heuristic? -- Iterative search -- 12.2 Single-solution methods -- 12.2.1 Stochastic Local Search -- 12.2.2 Simulated Annealing -- 12.2.3 Threshold Accepting -- 12.2.4 Tabu Search -- 12.3 Population-based methods -- 12.3.1 Genetic Algorithms -- 12.3.2 Differential Evolution -- 12.3.3 Particle Swarm Optimization -- 12.3.4 Ant Colony Optimization -- 12.4 Hybrids -- Trajectory (single-solution) methods -- Discontinuous methods -- Single-agent methods -- Multi-agent or population-based methods -- Guided search or search with memory usage -- Unguided search or memoryless methods -- Low-level relay hybrid. , Low-level co-evolutionary hybrid.
    Additional Edition: ISBN 0-12-815065-3
    Language: English
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  • 5
    UID:
    b3kat_BV039550685
    Format: XV, 584 S. , Ill., graph. Darst., Kt.
    ISBN: 9780123756626
    Note: Hier auch später erschienene, unveränderte Nachdrucke
    Language: English
    Subjects: Economics , Mathematics
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    Keywords: Finanzierung ; Finanzmathematik ; Optimierung ; Finanzplanungsmodell
    Author information: Gilli, Manfred 1942-
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  • 6
    Book
    Book
    London ; San Diego ; Cambridge ; Oxford :Academic Press, an imprint of Elsevier,
    UID:
    almahu_BV046041436
    Format: xxiv, 614 Seiten : , Diagramme.
    Edition: Second edition
    ISBN: 978-0-12-815065-8 , 0-12-815065-3
    Note: Enthält Literaturverzeichnis (Seite 599-608) und Index
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-0-12-815065-8
    Language: English
    Subjects: Economics , Mathematics
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    RVK:
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    Keywords: Finanzierung ; Finanzmathematik ; Optimierung ; Finanzplanungsmodell
    Author information: Gilli, Manfred, 1942-,
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  • 7
    Online Resource
    Online Resource
    Berlin, Heidelberg : Springer Berlin Heidelberg
    UID:
    b3kat_BV036606450
    Format: 1 Online-Ressource (XXVI, 212, 2 S.) , zahlr. graph. Darst.
    ISBN: 9783642139499 , 9783642139505
    Series Statement: Studies in Computational Intelligence 293
    Language: German
    Keywords: Kreditmarkt ; Entscheidungsfindung ; Evolutionärer Algorithmus ; Computerunterstütztes Verfahren ; Kreditmarkt ; Entscheidungsfindung ; Mehragentensystem ; Aufsatzsammlung
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  • 8
    UID:
    b3kat_BV039829890
    Format: 1 Online-Ressource (1 online resource (xv, 584 p.))
    ISBN: 9780123756626 , 0123756626
    Note: This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website. Shows ways to build and implement tools that help test ideas. Focuses on the application of heuristics; standard methods receive limited attention. Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models , Fundamentals -- Simulation -- Optimization , Includes bibliographical references and index
    Language: English
    Subjects: Economics , Mathematics
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    Keywords: Finanzierung ; Finanzmathematik ; Optimierung ; Finanzplanungsmodell ; Electronic books ; Electronic books ; Electronic resource
    Author information: Gilli, Manfred 1942-
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  • 9
    UID:
    b3kat_BV040125177
    Format: 1 Online-Ressource
    ISBN: 9783642233364
    Series Statement: Studies in Computational Intelligence 380
    Language: English
    Keywords: Kreditmarkt ; Entscheidungsfindung ; Evolutionärer Algorithmus ; Computerunterstütztes Verfahren ; Kreditmarkt ; Entscheidungsfindung ; Mehragentensystem ; Aufsatzsammlung
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  • 10
    Online Resource
    Online Resource
    Dordrecht : Springer
    UID:
    b3kat_BV022309066
    Format: 1 Online-Ressource
    ISBN: 0387258523 , 9780387258522 , 9780387258539
    Series Statement: Advances in computational management science 8
    Note: Zugl.: Erfurt, Univ., Habil.-Schr.
    Language: English
    Subjects: Economics
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    Keywords: Portofoliomanagement ; Heuristik ; Portfolio Selection ; Heuristische Programmierung ; Hochschulschrift ; Portofoliomanagement
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