Download or read book Nonlinear Models in Mathematical Finance written by Matthias Ehrhardt and published by Nova Science Pub Incorporated. This book was released on 2008 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview on the current state-of-the-art research on non-linear option pricing. Non-linear models are becoming more and more important since they take into account many effects that are not included in the linear model. However, in practice (i.e. in banks) linear models are still used, giving rise to large errors in computing the fair price of options. Hence, there exists a noticeable need for non-linear modelling of financial products. This book will help to foster the usage of non-linear Black-Scholes models in practice.
Download or read book Non Linear Time Series Models in Empirical Finance written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2000-07-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2000 volume reviews non-linear time series models, and their applications to financial markets.
Download or read book Nonlinear Financial Econometrics Forecasting Models Computational and Bayesian Models written by G. Gregoriou and published by Springer. This book was released on 2010-12-21 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
Download or read book Nonlinear Option Pricing written by Julien Guyon and published by CRC Press. This book was released on 2013-12-19 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: New Tools to Solve Your Option Pricing ProblemsFor 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 hi
Download or read book Non Linear Models in Mathematical Finance written by Marlo Avellaneda and published by . This book was released on 1996-08 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear Optimization with Engineering Applications written by Michael Bartholomew-Biggs and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook examines a broad range of problems in science and engineering, describing key numerical methods applied to real life. The case studies presented are in such areas as data fitting, vehicle route planning and optimal control, scheduling and resource allocation, sensitivity calculations and worst-case analysis. Chapters are self-contained with exercises provided at the end of most sections. Nonlinear Optimization with Engineering Applications is ideal for self-study and classroom use in engineering courses at the senior undergraduate or graduate level. The book will also appeal to postdocs and advanced researchers interested in the development and use of optimization algorithms.
Download or read book State Space Models written by Yong Zeng and published by Springer Science & Business Media. This book was released on 2013-08-15 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.
Download or read book Recent Advances in Estimating Nonlinear Models written by Jun Ma and published by Springer. This book was released on 2013-09-24 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.
Download or read book Nonlinear Valuation and Non Gaussian Risks in Finance written by Dilip B. Madan and published by Cambridge University Press. This book was released on 2022-02-03 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore how market valuation must abandon linearity to deliver efficient resource allocation.
Download or read book Nonlinear Option Pricing written by Julien Guyon and published by CRC Press. This book was released on 2013-12-19 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Nonlinear Time Series Modeling with Application to Finance and Other Fields written by Shusong Jin and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Nonlinear Time Series Modeling With Application to Finance and Other Fields" by Shusong, Jin, 金曙松, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled "NONLINEAR TIME SERIES MODELING WITH APPLICATION TO FINANCE AND OTHER FIELDS" Submitted by JIN Shusong for the degree of Doctor of Philosophy at The University of Hong Kong in May 2005 This thesis investigates the extension and application of nonlinear time series methodologies in both finance and ecology. The nonlinear time series structure consideredhastheflavourofamixturemodel. Themixingmechanismcanfollow the threshold approach or the classical mixture approach. A simple Wald test was developed to check the number of components in a mixture structure. The penalized likelihood was used for parameter estimation. The consistency of the estimates and the asymptotic distribution of the test statistic which was based on the estimates was derived. New models for the di- rectmodelingofvalue-of-risk(VaR)infinancewereconsideredbasedontheabove framework. It was shown that modeling VaR directly using a nonlinear frame- work resulted in more reliable estimates than traditional methods. A nonlinear bivariate time series was constructed whose relationship between the marginal processes was defined by a copula. This nonlinear model was then applied to the modeling of the exchange rates of Deutsch-Mark/U.S.-Dollar (DEM/USD)and Japanese-Yen/U.S. Dollar (JPY/USD). The above nonlinear framework was extended to the analysis of panel time series. Mixture autoregressive models with a common component among all member series was proposed. Estimation of the model was done via the Expectation-Maximization (EM) algorithm. The model was illustrated using the grey-sided voles data collected from Hokkaido, Japan. A partial linear model was proposed for panel data with contemporane- ous correlations. A semiparametric estimation procedure was proposed and some asymptotic results of the estimates were obtained. This extended the classical seemingly uncorrelated regression model to the panel time series context. The modelwasappliedtothemodernCanadianlynxdatasetandthegrey-sidedvoles data. It was found that the new model provided a better understanding of the underlying structure of these two time series. DOI: 10.5353/th_b3199605 Subjects: Linear models (Statistics) Time-series analysis Finance - Mathematical models Ecology - Mathematical models
Download or read book Nonlinear Optimization with Financial Applications written by Michael Bartholomew-Biggs and published by Springer Science & Business Media. This book was released on 2005-01-04 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This instructive book introduces the key ideas behind practical nonlinear optimization, accompanied by computational examples and supporting software. It combines computational finance with an important class of numerical techniques.
Download or read book Mathematical Finance written by Christian Fries and published by John Wiley & Sons. This book was released on 2007-10-19 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A balanced introduction to the theoretical foundations and real-world applications of mathematical finance The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today's most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models. Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book's principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises. While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
Download or read book Nonlinear Financial Econometrics Markov Switching Models Persistence and Nonlinear Cointegration written by Greg N. Gregoriou and published by Springer. This book was released on 2010-12-08 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes new methods to value equity and model the Markowitz efficient frontier using Markov switching models and provide new evidence and solutions to capture the persistence observed in stock returns across developed and emerging markets.
Download or read book Optimization in Economics and Finance written by Bruce D. Craven and published by Springer Science & Business Media. This book was released on 2005-10-24 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
Download or read book Mathematical Models in Finance written by S.D. Howison and published by CRC Press. This book was released on 1995-05-15 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Models in Finance compiles papers presented at the Royal Society of London discussion meeting. Topics range from the foundations of classical theory to sophisticated, up-to-date mathematical modeling and analysis. In the wake of the increased level of mathematical awareness in the financial research community, attention has focused on fundamental issues of market modelling that are not adequately allowed for in the standard analyses. Examples include market anomalies and nonlinear coupling effects, and demand new synthesis of mathematical and numerical techniques. This line of inquiry is further stimulated by ever tightening profits due to increased competition. Several papers in this volume offer pointers to future developments in this area.
Download or read book Uncertain Volatility Models written by Robert Buff and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the only books to describe uncertain volatility models in mathematical finance and their computer implementation for portfolios of vanilla, barrier and American options in equity and FX markets. Uncertain volatility models place subjective constraints on the volatility of the stochastic process of the underlying asset and evaluate option portfolios under worst- and best-case scenarios. This book, which is bundled with software, is aimed at graduate students, researchers and practitioners who wish to study advanced aspects of volatility risk in portfolios of vanilla and exotic options. The reader is assumed to be familiar with arbitrage pricing theory.
