Derivatives Algorithms

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Derivatives Algorithms - Volume 1: Bones

Author : Tom Hyer
Publisher : World Scientific
ISBN 13 : 9814289884
Total Pages : 319 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Derivatives Algorithms - Volume 1: Bones by : Tom Hyer

Download or read book Derivatives Algorithms - Volume 1: Bones written by Tom Hyer and published by World Scientific. This book was released on 2010 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derivatives Algorithms provides a unique expert overview of the abstractions and coding methods which support real-world derivatives trading. Written by an industry professional with extensive experience in large-scale trading operations, it describes the fundamentals of library code structure, and innovative advanced solutions to thorny issues in implementation. For the reader already familiar with C++ and arbitrage-free pricing, the book offers an invaluable glimpse of how they combine on an industrial scale. Topics range from interface design through code generation to the protocols that support ever more complex trades and models.

Derivatives Algorithms - Volume 1: Bones (Second Edition)

Author : Thomas Hyer
Publisher : World Scientific
ISBN 13 : 9814699535
Total Pages : 346 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Derivatives Algorithms - Volume 1: Bones (Second Edition) by : Thomas Hyer

Download or read book Derivatives Algorithms - Volume 1: Bones (Second Edition) written by Thomas Hyer and published by World Scientific. This book was released on 2015-09-18 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derivatives Algorithms — Volume 1: Bones (Second Edition) is for practicing quants who already have some expertise in risk-neutral pricing and in programming, and want to build a reusable and extensible library. Rather than specific models, this volume provides foundations common to all pricing, such as C++ code structure, interfaces, and several widely used mathematical methods. It also presents a set of protocols, by which models and trades can collaborate to support pricing and hedging tasks, and illustrates their use with several example trade types and models. Readers will learn to deploy the results of their research work with productivity-enhancing methods that are not taught elsewhere, including object serialization, code generation, and separation of concerns for continuous improvement. Of all the books on derivatives pricing, only Derivatives Algorithms shows the internals of a high-quality working library.The new Second Edition is more accessible to readers who are not already familiar with the book's concepts; there is an increased focus on explaining the motivation for each step, and on providing a high-level perspective on design choices. The chapters on Persistence and Protocols have been substantially rewritten, providing motivating examples and additional detail in the code. The treatment of yield curves and funding has been modernized, with the increased sophistication required by today's markets. And a new final chapter, describing the next phase in the evolution of derivatives valuation and risk, has been added.

Options and Derivatives Programming in C++

Author : CARLOS OLIVEIRA
Publisher : Apress
ISBN 13 : 1484218140
Total Pages : 273 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Options and Derivatives Programming in C++ by : CARLOS OLIVEIRA

Download or read book Options and Derivatives Programming in C++ written by CARLOS OLIVEIRA and published by Apress. This book was released on 2016-09-30 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how C++ is used in the development of solutions for options and derivatives trading in the financial industry. As an important part of the financial industry, options and derivatives trading has become increasingly sophisticated. Advanced trading techniques using financial derivatives have been used at banks, hedge funds, and pension funds. Because of stringent performance characteristics, most of these trading systems are developed using C++ as the main implementation language. Options and Derivatives Programming in C++ covers features that are frequently used to write financial software for options and derivatives, including the STL, templates, functional programming, and support for numerical libraries. New features introduced in the C++11 and C++14 standard are also covered: lambda functions, automatic type detection, custom literals, and improved initialization strategies for C++ objects. Readers will enjoy the how-to examples covering all the major tools and concepts used to build working solutions for quantitative finance. It includes advanced C++ concepts as well as the basic building libraries used by modern C++ developers, such as the STL and Boost, while also leveraging knowledge of object-oriented and template-based programming. Options and Derivatives Programming in C++ provides a great value for readers who are trying to use their current programming knowledge in order to become proficient in the style of programming used in large banks, hedge funds, and other investment institutions. The topics covered in the book are introduced in a logical and structured way and even novice programmers will be able to absorb the most important topics and competencies. What You Will Learn Grasp the fundamental problems in options and derivatives trading Converse intelligently about credit default swaps, Forex derivatives, and more Implement valuation models and trading strategies Build pricing algorithms around the Black-Sholes Model, and also using the Binomial and Differential Equations methods Run quantitative finance algorithms using linear algebra techniques Recognize and apply the most common design patterns used in options trading Save time by using the latest C++ features such as the STL and the Boost libraries Who This Book Is For Professional developers who have some experience with the C++ language and would like to leverage that knowledge into financial software development. This book is written with the goal of reaching readers who need a concise, algorithms-based book, providing basic information through well-targeted examples and ready to use solutions. Readers will be able to directly apply the concepts and sample code to some of the most common problems faced in the analysis of options and derivative contracts.

Algorithms for Minimization Without Derivatives

Author : Richard P. Brent
Publisher : Courier Corporation
ISBN 13 : 0486143686
Total Pages : 210 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Algorithms for Minimization Without Derivatives by : Richard P. Brent

Download or read book Algorithms for Minimization Without Derivatives written by Richard P. Brent and published by Courier Corporation. This book was released on 2013-06-10 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: DIVOutstanding text for graduate students and research workers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating local and global minima. /div

An Introduction to the Mathematics of Financial Derivatives

Author : Salih N. Neftci
Publisher : Academic Press
ISBN 13 : 0125153929
Total Pages : 550 pages
Book Rating : 4.1/5 (251 download)

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Book Synopsis An Introduction to the Mathematics of Financial Derivatives by : Salih N. Neftci

Download or read book An Introduction to the Mathematics of Financial Derivatives written by Salih N. Neftci and published by Academic Press. This book was released on 2000-05-19 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step explanation of the mathematical models used to price derivatives. For this second edition, Salih Neftci has expanded one chapter, added six new ones, and inserted chapter-concluding exercises. He does not assume that the reader has a thorough mathematical background. His explanations of financial calculus seek to be simple and perceptive.

Automatic Differentiation of Algorithms

Author : George Corliss
Publisher : Springer Science & Business Media
ISBN 13 : 1461300754
Total Pages : 431 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Automatic Differentiation of Algorithms by : George Corliss

Download or read book Automatic Differentiation of Algorithms written by George Corliss and published by Springer Science & Business Media. This book was released on 2013-11-21 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey book focusing on the key relationships and synergies between automatic differentiation (AD) tools and other software tools, such as compilers and parallelizers, as well as their applications. The key objective is to survey the field and present the recent developments. In doing so the topics covered shed light on a variety of perspectives. They reflect the mathematical aspects, such as the differentiation of iterative processes, and the analysis of nonsmooth code. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. They also cover "implementation" problems.

Evaluating Derivatives

Author : Andreas Griewank
Publisher : SIAM
ISBN 13 : 0898716594
Total Pages : 448 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Evaluating Derivatives by : Andreas Griewank

Download or read book Evaluating Derivatives written by Andreas Griewank and published by SIAM. This book was released on 2008-11-06 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title is a comprehensive treatment of algorithmic, or automatic, differentiation. The second edition covers recent developments in applications and theory, including an elegant NP completeness argument and an introduction to scarcity.

Numerical Methods for Fractional Differentiation

Author : Kolade M. Owolabi
Publisher : Springer Nature
ISBN 13 : 9811500983
Total Pages : 338 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Numerical Methods for Fractional Differentiation by : Kolade M. Owolabi

Download or read book Numerical Methods for Fractional Differentiation written by Kolade M. Owolabi and published by Springer Nature. This book was released on 2019-10-14 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses numerical methods for solving partial differential and integral equations, as well as ordinary differential and integral equations, involving fractional differential and integral operators. Differential and integral operators presented in the book include those with exponential decay law, known as Caputo–Fabrizio differential and integral operators, those with power law, known as Riemann–Liouville fractional operators, and those for the generalized Mittag–Leffler function, known as the Atangana–Baleanu fractional operators. The book reviews existing numerical schemes associated with fractional operators including those with power law, while also highlighting new trends in numerical schemes for recently introduced differential and integral operators. In addition, the initial chapters address useful properties of each differential and integral fractional operator. Methods discussed in the book are subsequently used to solved problems arising in many fields of science, technology, and engineering, including epidemiology, chaos, solitons, fractals, diffusion, groundwater, and fluid mechanics. Given its scope, the book offers a valuable resource for graduate students of mathematics and engineering, and researchers in virtually all fields of science, technology, and engineering, as well as an excellent addition to libraries.

The Art of Differentiating Computer Programs

Author : Uwe Naumann
Publisher : SIAM
ISBN 13 : 9781611972078
Total Pages : 358 pages
Book Rating : 4.9/5 (72 download)

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Book Synopsis The Art of Differentiating Computer Programs by : Uwe Naumann

Download or read book The Art of Differentiating Computer Programs written by Uwe Naumann and published by SIAM. This book was released on 2012-01-01 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first entry-level book on algorithmic (also known as automatic) differentiation (AD), providing fundamental rules for the generation of first- and higher-order tangent-linear and adjoint code. The author covers the mathematical underpinnings as well as how to apply these observations to real-world numerical simulation programs. Readers will find: examples and exercises, including hints to solutions; the prototype AD tools dco and dcc for use with the examples and exercises; first- and higher-order tangent-linear and adjoint modes for a limited subset of C/C++, provided by the derivative code compiler dcc; a supplementary website containing sources of all software discussed in the book, additional exercises and comments on their solutions (growing over the coming years), links to other sites on AD, and errata.

Recent Advances in Algorithmic Differentiation

Author : Shaun Forth
Publisher : Springer Science & Business Media
ISBN 13 : 3642300235
Total Pages : 356 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Recent Advances in Algorithmic Differentiation by : Shaun Forth

Download or read book Recent Advances in Algorithmic Differentiation written by Shaun Forth and published by Springer Science & Business Media. This book was released on 2012-07-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of AD theory and its implementation in tools. For all papers the referees, selected from the program committee and the greater community, as well as the editors have emphasized accessibility of the presented ideas also to non-AD experts. In the AD tools arena new implementations are introduced covering, for example, Java and graphical modeling environments or join the set of existing tools for Fortran. New developments in AD algorithms target the efficiency of matrix-operation derivatives, detection and exploitation of sparsity, partial separability, the treatment of nonsmooth functions, and other high-level mathematical aspects of the numerical computations to be differentiated. Applications stem from the Earth sciences, nuclear engineering, fluid dynamics, and chemistry, to name just a few. In many cases the applications in a given area of science or engineering share characteristics that require specific approaches to enable AD capabilities or provide an opportunity for efficiency gains in the derivative computation. The description of these characteristics and of the techniques for successfully using AD should make the proceedings a valuable source of information for users of AD tools.

Inclusion Methods for Nonlinear Problems

Author : Jürgen Herzberger
Publisher : Springer Science & Business Media
ISBN 13 : 3709160332
Total Pages : 247 pages
Book Rating : 4.7/5 (91 download)

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Book Synopsis Inclusion Methods for Nonlinear Problems by : Jürgen Herzberger

Download or read book Inclusion Methods for Nonlinear Problems written by Jürgen Herzberger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This workshop was organized with the support of GAMM, the International Association of Applied Mathematics and Mechanics, on the occasion of J. Herzberger's 60th birthday. GAMM is thankful to him for all the time and work he spent in the preparation and holding of the meeting. The talks presented during the workshop and the papers published in this volume are part of the field of Verification Numerics. The important subject is fostered by GAMM already since a number of years, especially also by the GAMM FachausschuB (special interest group) "Rechnerarithmetik und Wissenschaft liches Rechnen". GiHz Alefeld Karlsruhe, Dezember 2001 (President of GAMM) Preface At the end of the year 2000, about 23 scientists from many countries gathered in the beautiful city of Munich on the occasion of the International GAMM Workshop on "Inclusion Methods for Nonlinear Problems with Applications in Engineering, Economics and Physics" from December 15 to 18. The purpose of this meeting was to bring together representatives of research groups from Austria, Bulgaria, China, Croatia, Germany, Japan, Russia, Ukraine and Yugoslavia who in a wider sense work in the field of calculating numerical solutions with error-bounds. Most of those participants have already known each other from earlier occasions or closely cooperated in the past. Representatives from three Academies of Sciences were among the speakers of this conference: from the Bulgarian Academy, the Russian Academy and the Ukrainian Academy of Sciences.

Mathematics of Derivative Securities

Author : Michael A. H. Dempster
Publisher : Cambridge University Press
ISBN 13 : 9780521584241
Total Pages : 614 pages
Book Rating : 4.5/5 (842 download)

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Book Synopsis Mathematics of Derivative Securities by : Michael A. H. Dempster

Download or read book Mathematics of Derivative Securities written by Michael A. H. Dempster and published by Cambridge University Press. This book was released on 1997-10-13 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: During 1995 the Isaac Newton Institute for the Mathematical Sciences at Cambridge University hosted a six month research program on financial mathematics. During this period more than 300 scholars and financial practitioners attended to conduct research and to attend more than 150 research seminars. Many of the presented papers were on the subject of financial derivatives. The very best were selected to appear in this volume. They range from abstract financial theory to practical issues pertaining to the pricing and hedging of interest rate derivatives and exotic options in the market place. Hence this book will be of interest to both academic scholars and financial engineers.

Automated Solution of Differential Equations by the Finite Element Method

Author : Anders Logg
Publisher : Springer Science & Business Media
ISBN 13 : 3642230997
Total Pages : 723 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Automated Solution of Differential Equations by the Finite Element Method by : Anders Logg

Download or read book Automated Solution of Differential Equations by the Finite Element Method written by Anders Logg and published by Springer Science & Business Media. This book was released on 2012-02-24 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a tutorial written by researchers and developers behind the FEniCS Project and explores an advanced, expressive approach to the development of mathematical software. The presentation spans mathematical background, software design and the use of FEniCS in applications. Theoretical aspects are complemented with computer code which is available as free/open source software. The book begins with a special introductory tutorial for beginners. Following are chapters in Part I addressing fundamental aspects of the approach to automating the creation of finite element solvers. Chapters in Part II address the design and implementation of the FEnicS software. Chapters in Part III present the application of FEniCS to a wide range of applications, including fluid flow, solid mechanics, electromagnetics and geophysics.

Algorithms for Optimization

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262039427
Total Pages : 521 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Algorithms for Optimization by : Mykel J. Kochenderfer

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Execution Algorithms

Author : William Johnson
Publisher : HiTeX Press
ISBN 13 :
Total Pages : 609 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Execution Algorithms by : William Johnson

Download or read book Execution Algorithms written by William Johnson and published by HiTeX Press. This book was released on 2024-10-09 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Execution Algorithms: Precision Trading in Complex Markets" offers a comprehensive exploration into the cutting-edge world of algorithmic trading, where technology meets finance to achieve optimal execution. This meticulously crafted book delves into the nuances of execution algorithms, guiding readers through their evolution and the vital role they play in today's dynamic markets. With clarity and precision, it encapsulates a broad spectrum of topics—from fundamental market microstructures and varied algorithm types to the intricacies of order types and performance metrics. Readers will benefit from insights into the technological infrastructure that underpins these sophisticated systems, while also gaining an understanding of the regulatory frameworks that ensure their ethical deployment. Each chapter is thoughtfully designed to build upon the last, providing a structured and accessible learning path for novices and experts alike. The incorporation of machine learning, risk management, and future trends in trading offers a forward-thinking perspective, equipping traders and financial professionals with the knowledge to navigate and excel within the ever-evolving landscape of execution algorithms. This book stands as an indispensable resource for anyone seeking to understand the multifaceted world of financial execution strategies, offering both depth and breadth of insight. It is an essential guide that empowers readers to enhance their trading acumen, optimize their strategies, and remain at the forefront of financial innovation.

A Derivative-free Two Level Random Search Method for Unconstrained Optimization

Author : Neculai Andrei
Publisher : Springer Nature
ISBN 13 : 3030685179
Total Pages : 126 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis A Derivative-free Two Level Random Search Method for Unconstrained Optimization by : Neculai Andrei

Download or read book A Derivative-free Two Level Random Search Method for Unconstrained Optimization written by Neculai Andrei and published by Springer Nature. This book was released on 2021-03-31 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free optimization method/algorithm based on randomly generated trial points in specified domains and where the best ones are selected at each iteration by using a number of rules. This method is different from many other well established methods presented in the literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a relative large number of variables. Intensive numerical experiments with 140 unconstrained optimization problems, with up to 500 variables, have shown that this approach is efficient and robust. Structured into 4 chapters, Chapter 1 is introductory. Chapter 2 is dedicated to presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous, lower bounded and its minimum value is known. Chapter 3 proves the convergence of the algorithm. In Chapter 4, the numerical performances of the algorithm are shown for solving 140 unconstrained optimization problems, out of which 16 are real applications. This shows that the optimization process has two phases: the reduction phase and the stalling one. Finally, the performances of the algorithm for solving a number of 30 large-scale unconstrained optimization problems up to 500 variables are presented. These numerical results show that this approach based on the two level random search method for unconstrained optimization is able to solve a large diversity of problems with different structures and complexities. There are a number of open problems which refer to the following aspects: the selection of the number of trial or the number of the local trial points, the selection of the bounds of the domains where the trial points and the local trial points are randomly generated and a criterion for initiating the line search.

Evaluation Complexity of Algorithms for Nonconvex Optimization

Author : Coralia Cartis
Publisher : SIAM
ISBN 13 : 1611976995
Total Pages : 549 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Evaluation Complexity of Algorithms for Nonconvex Optimization by : Coralia Cartis

Download or read book Evaluation Complexity of Algorithms for Nonconvex Optimization written by Coralia Cartis and published by SIAM. This book was released on 2022-07-06 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: A popular way to assess the “effort” needed to solve a problem is to count how many evaluations of the problem functions (and their derivatives) are required. In many cases, this is often the dominating computational cost. Given an optimization problem satisfying reasonable assumptions—and given access to problem-function values and derivatives of various degrees—how many evaluations might be required to approximately solve the problem? Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation, and Perspectives addresses this question for nonconvex optimization problems, those that may have local minimizers and appear most often in practice. This is the first book on complexity to cover topics such as composite and constrained optimization, derivative-free optimization, subproblem solution, and optimal (lower and sharpness) bounds for nonconvex problems. It is also the first to address the disadvantages of traditional optimality measures and propose useful surrogates leading to algorithms that compute approximate high-order critical points, and to compare traditional and new methods, highlighting the advantages of the latter from a complexity point of view. This is the go-to book for those interested in solving nonconvex optimization problems. It is suitable for advanced undergraduate and graduate students in courses on advanced numerical analysis, data science, numerical optimization, and approximation theory.