Computational Methods for Quantitative Finance, Hilber Norbert
Автор: Blyth Stephen Название: An Introduction to Quantitative Finance ISBN: 0199666598 ISBN-13(EAN): 9780199666591 Издательство: Oxford Academ Рейтинг: Цена: 6810.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types. This book gives an insight into financial engineering while building on introductory probability courses by detailing one of the most fascinating applications of the subject.
Автор: Svetlozar T. Rachev; George A. Anastassiou Название: Handbook of Computational and Numerical Methods in Finance ISBN: 1461264766 ISBN-13(EAN): 9781461264767 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The subject of numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance, and numerical analysis. Although numerical methods in finance have been studied intensively in recent years, many theoretical and practical financial aspects have yet to be explored.
Автор: Matt Davison Название: Quantitative Finance ISBN: 143987168X ISBN-13(EAN): 9781439871683 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Teach Your Students How to Become Successful Working Quants
Quantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techniques of financial mathematics, but it also helps them gain significant intuition about what the techniques mean, how they work, and what happens when they stop working.
After introducing risk, return, decision making under uncertainty, and traditional discounted cash flow project analysis, the book covers mortgages, bonds, and annuities using a blend of Excel simulation and difference equation or algebraic formalism. It then looks at how interest rate markets work and how to model bond prices before addressing mean variance portfolio optimization, the capital asset pricing model, options, and value at risk (VaR). The author next focuses on binomial model tools for pricing options and the analysis of discrete random walks. He also introduces stochastic calculus in a nonrigorous way and explains how to simulate geometric Brownian motion. The text proceeds to thoroughly discuss options pricing, mostly in continuous time. It concludes with chapters on stochastic models of the yield curve and incomplete markets using simple discrete models.
Accessible to students with a relatively modest level of mathematical background, this book will guide your students in becoming successful quants. It uses both hand calculations and Excel spreadsheets to analyze plenty of examples from simple bond portfolios. The spreadsheets are available on the book's CRC Press web page.
Автор: Guyon Название: Nonlinear Pricing Methods in Quantitative Finance ISBN: 1466570334 ISBN-13(EAN): 9781466570337 Издательство: Taylor&Francis Рейтинг: Цена: 27562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
New Tools to Solve Your Option Pricing Problems
For nonlinear PDEs encountered in quantitative finance, advanced probabilistic methods are needed to address dimensionality issues. Written by two leaders in quantitative research--including Risk magazine's 2013 Quant of the Year--Nonlinear Option Pricing compares various numerical methods for solving high-dimensional nonlinear problems arising in option pricing. Designed for practitioners, it is the first authored book to discuss nonlinear Black-Scholes PDEs and compare the efficiency of many different methods.
Real-World Solutions for Quantitative Analysts
The book helps quants develop both their analytical and numerical expertise. It focuses on general mathematical tools rather than specific financial questions so that readers can easily use the tools to solve their own nonlinear problems. The authors build intuition through numerous real-world examples of numerical implementation. Although the focus is on ideas and numerical examples, the authors introduce relevant mathematical notions and important results and proofs. The book also covers several original approaches, including regression methods and dual methods for pricing chooser options, Monte Carlo approaches for pricing in the uncertain volatility model and the uncertain lapse and mortality model, the Markovian projection method and the particle method for calibrating local stochastic volatility models to market prices of vanilla options with/without stochastic interest rates, the a + bλ technique for building local correlation models that calibrate to market prices of vanilla options on a basket, and a new stochastic representation of nonlinear PDE solutions based on marked branching diffusions.
Автор: Vogel Curtis R Название: Computational Methods for Inverse Problems ISBN: 0898715504 ISBN-13(EAN): 9780898715507 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10534.00 р. Наличие на складе: Нет в наличии.
Описание: Inverse problems arise in a number of important practical applications, ranging from biomedical imaging to seismic prospecting. This book provides the reader with a basic understanding of both the underlying mathematics and the computational methods used to solve inverse problems. It also addresses specialized topics like image reconstruction, parameter identification, total variation methods, nonnegativity constraints, and regularization parameter selection methods. Because inverse problems typically involve the estimation of certain quantities based on indirect measurements, the estimation process is often ill-posed. Regularization methods, which have been developed to deal with this ill-posedness, are carefully explained in the early chapters of Computational Methods for Inverse Problems. The book also integrates mathematical and statistical theory with applications and practical computational methods, including topics like maximum likelihood estimation and Bayesian estimation.
Автор: Norbert Hilber; Oleg Reichmann; Christoph Schwab; Название: Computational Methods for Quantitative Finance ISBN: 3642435327 ISBN-13(EAN): 9783642435324 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces algorithms for fast, accurate pricing of derivative contracts. These are developed in classical Black-Scholes markets, and extended to models based on multiscale stochastic volatility, to Levy, additive and classes of Feller processes.
Автор: Watsham, Terry J. Parramore, Keith Название: Quantitative methods in finance ISBN: 186152367X ISBN-13(EAN): 9781861523679 Издательство: Cengage Learning Рейтинг: Цена: 13304.00 р. Наличие на складе: Нет в наличии.
Описание: This text explains the mathematical and statistical applications relevant to modern financial instruments and risk management techniques. It progresses at a comfortable pace for those with less mathematical expertise yet reaches a high level of analysis for the more experienced.
Автор: Matthias Ehrhardt; Michael G?nther; E. Jan W. ter Название: Novel Methods in Computational Finance ISBN: 3319612816 ISBN-13(EAN): 9783319612812 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book discusses the state-of-the-art and open problems in computational finance. It presents a collection of research outcomes and reviews of the work from the STRIKE project, an FP7 Marie Curie Initial Training Network (ITN) project in which academic partners trained early-stage researchers in close cooperation with a broader range of associated partners, including from the private sector.
The aim of the project was to arrive at a deeper understanding of complex (mostly nonlinear) financial models and to develop effective and robust numerical schemes for solving linear and nonlinear problems arising from the mathematical theory of pricing financial derivatives and related financial products. This was accomplished by means of financial modelling, mathematical analysis and numerical simulations, optimal control techniques and validation of models.
In recent years the computational complexity of mathematical models employed in financial mathematics has witnessed tremendous growth. Advanced numerical techniques are now essential to the majority of present-day applications in the financial industry.
Special attention is devoted to a uniform methodology for both testing the latest achievements and simultaneously educating young PhD students. Most of the mathematical codes are linked into a novel computational finance toolbox, which is provided in MATLAB and PYTHON with an open access license. The book offers a valuable guide for researchers in computational finance and related areas, e.g. energy markets, with an interest in industrial mathematics.
Автор: Erricos John Kontoghiorghes; B. Rustem; S. Siokos Название: Computational Methods in Decision-Making, Economics and Finance ISBN: 1441952306 ISBN-13(EAN): 9781441952301 Издательство: Springer Рейтинг: Цена: 41787.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
Описание: This book puts numerical methods in action for the purpose of solving practical problems arising in quantitative finance. Part one develops a comprehensive toolkit including Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, Laplace transforms and quadrature methods. Part two proposes eighteen self-contained cases covering model simulation, derivative valuation, dynamic hedging, portfolio selection, risk management, statistical estimation and calibration. It encompasses a wide variety of problems arising in markets for equity, interest rates, credit risk, energy and exotic derivatives. Each case introduces a problem, develops a detailed solution and illustrates empirical results. Proposed algorithms are implemented using either Matlab or Visual Basic. The book originates from class notes and case-studies developed within courses on Numerical Methods for Finance and Exotic Derivatives held by the authors at Bocconi University since the year 2000.
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