Introducción al Cálculo Estocástico Aplicado a la Modelización Económico-financiero-actuarial PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Introducción al Cálculo Estocástico Aplicado a la Modelización Económico-financiero-actuarial PDF full book. Access full book title Introducción al Cálculo Estocástico Aplicado a la Modelización Económico-financiero-actuarial by Josefina Martínez Barbeito. Download full books in PDF and EPUB format.
Author: Josefina Martínez Barbeito
Publisher: Netbiblo
ISBN: 9788497450249
Category : Derivative securities
Languages : es
Pages : 320
Get Book Here
Book Description
Este libro trata de suministrar una introducion al Calculo Estocastico con algunas de sus aplicaciones al campo economico-financiero-actuarial. Recientemente ha habido una gran demanda a nivel internacional de libros relacionados con el Calculo Estocastico y sus aplicaciones en economia financiera matematica donde el Calculo Estocastico se utiliza para valorar y arbitrar toda clase de derivados financieros. La presente obra proporciona una introduccion matematicamente rigurosa, pero comprensible, para el calculo economicofinanciero moderno, por lo que es apropiada para cursos selectivos de economia y empresa tanto en Facultades de Ciencias Economicas como en Facultades de Matematicas y Escuelas de Ingenieria. Asimismo, es adecuada para practicos que quieran obtener los conocimientos precisos para estudiar la problematica de los diferentes titulos derivados de la maxima actualidad.
Author: Josefina Martínez Barbeito
Publisher: Netbiblo
ISBN: 9788497450249
Category : Derivative securities
Languages : es
Pages : 320
Get Book Here
Book Description
Este libro trata de suministrar una introducion al Calculo Estocastico con algunas de sus aplicaciones al campo economico-financiero-actuarial. Recientemente ha habido una gran demanda a nivel internacional de libros relacionados con el Calculo Estocastico y sus aplicaciones en economia financiera matematica donde el Calculo Estocastico se utiliza para valorar y arbitrar toda clase de derivados financieros. La presente obra proporciona una introduccion matematicamente rigurosa, pero comprensible, para el calculo economicofinanciero moderno, por lo que es apropiada para cursos selectivos de economia y empresa tanto en Facultades de Ciencias Economicas como en Facultades de Matematicas y Escuelas de Ingenieria. Asimismo, es adecuada para practicos que quieran obtener los conocimientos precisos para estudiar la problematica de los diferentes titulos derivados de la maxima actualidad.
Author: Zura Kakushadze
Publisher: Springer
ISBN: 3030027929
Category : Business & Economics
Languages : en
Pages : 480
Get Book Here
Book Description
The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.
Author: Wayne B. Nelson
Publisher: SIAM
ISBN: 0898715229
Category : Technology & Engineering
Languages : en
Pages : 157
Get Book Here
Book Description
Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.
Author: John Moubray
Publisher: Industrial Press Inc.
ISBN: 9780831131463
Category : Business & Economics
Languages : en
Pages : 452
Get Book Here
Book Description
Completely reorganised and comprehensively rewritten for its second edition, this guide to reliability-centred maintenance develops techniques which are practised by over 250 affiliated organisations worldwide.
Author: Aravind Dasari
Publisher: Springer
ISBN: 1447168097
Category : Technology & Engineering
Languages : en
Pages : 311
Get Book Here
Book Description
This highlights ongoing research efforts on different aspects of polymer nanocomposites and explores their potentials to exhibit multi-functional properties. In this context, it addresses both fundamental and advanced concepts, while delineating the parameters and mechanisms responsible for these potentials. Aspects considered include embrittlement/toughness; wear/scratch behaviour; thermal stability and flame retardancy; barrier, electrical and thermal conductivity; and optical and magnetic properties. Further, the book was written as a coherent unit rather than a collection of chapters on different topics. As such, the results, analyses and discussions presented herein provide a guide for the development of a new class of multi-functional nanocomposites. Offering an invaluable resource for materials researchers and postgraduate students in the polymer composites field, they will also greatly benefit materials
Author: Wayne B. Nelson
Publisher: John Wiley & Sons
ISBN: 0470317477
Category : Mathematics
Languages : en
Pages : 626
Get Book Here
Book Description
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . . a goldmine of knowledge on accelerated life testing principles and practices . . . one of the very few capable of advancing the science of reliability. It definitely belongs in every bookshelf on engineering." –Dev G. Raheja, Quality and Reliability Engineering International ". . . an impressive book. The width and number of topics covered, the practical data sets included, the obvious knowledge and understanding of the author and the extent of published materials reviewed combine to ensure that this will be a book used frequently." –Journal of the Royal Statistical Society A benchmark text in the field, Accelerated Testing: Statistical Models, Test Plans, and Data Analysis offers engineers, scientists, and statisticians a reliable resource on the effective use of accelerated life testing to measure and improve product reliability. From simple data plots to advanced computer programs, the text features a wealth of practical applications and a clear, readable style that makes even complicated physical and statistical concepts uniquely accessible. A detailed index adds to its value as a reference source.
Author: Andrey Itkin
Publisher: World Scientific
ISBN: 9811212783
Category : Business & Economics
Languages : en
Pages : 205
Get Book Here
Book Description
The concept of local volatility as well as the local volatility model are one of the classical topics of mathematical finance. Although the existing literature is wide, there still exist various problems that have not drawn sufficient attention so far, for example: a) construction of analytical solutions of the Dupire equation for an arbitrary shape of the local volatility function; b) construction of parametric or non-parametric regression of the local volatility surface suitable for fast calibration; c) no-arbitrage interpolation and extrapolation of the local and implied volatility surfaces; d) extension of the local volatility concept beyond the Black-Scholes model, etc. Also, recent progresses in deep learning and artificial neural networks as applied to financial engineering have made it reasonable to look again at various classical problems of mathematical finance including that of building a no-arbitrage local/implied volatility surface and calibrating it to the option market data.This book was written with the purpose of presenting new results previously developed in a series of papers and explaining them consistently, starting from the general concept of Dupire, Derman and Kani and then concentrating on various extensions proposed by the author and his co-authors. This volume collects all the results in one place, and provides some typical examples of the problems that can be efficiently solved using the proposed methods. This also results in a faster calibration of the local and implied volatility surfaces as compared to standard approaches.The methods and solutions presented in this volume are new and recently published, and are accompanied by various additional comments and considerations. Since from the mathematical point of view, the level of details is closer to the applied rather than to the abstract or pure theoretical mathematics, the book could also be recommended to graduate students with majors in computational or quantitative finance, financial engineering or even applied mathematics. In particular, the author used to teach some topics of this book as a part of his special course on computational finance at the Tandon School of Engineering, New York University.
Author: Frédéric Ferraty
Publisher: OUP Oxford
ISBN: 0199568448
Category : Mathematics
Languages : en
Pages : 512
Get Book Here
Book Description
This Handbook aims to present a state of the art exploration of the high-tech field of functional data analysis, by gathering together most of major advances in this area.
Author: Lynne Billard
Publisher: John Wiley & Sons
ISBN: 0470090170
Category : Mathematics
Languages : en
Pages : 330
Get Book Here
Book Description
With the advent of computers, very large datasets have become routine. Standard statistical methods don’t have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal structure, which must be taken into account in any analysis. This text presents a unified account of symbolic data, how they arise, and how they are structured. The reader is introduced to symbolic analytic methods described in the consistent statistical framework required to carry out such a summary and subsequent analysis. Presents a detailed overview of the methods and applications of symbolic data analysis. Includes numerous real examples, taken from a variety of application areas, ranging from health and social sciences, to economics and computing. Features exercises at the end of each chapter, enabling the reader to develop their understanding of the theory. Provides a supplementary website featuring links to download the SODAS software developed exclusively for symbolic data analysis, data sets, and further material. Primarily aimed at statisticians and data analysts, Symbolic Data Analysis is also ideal for scientists working on problems involving large volumes of data from a range of disciplines, including computer science, health and the social sciences. There is also much of use to graduate students of statistical data analysis courses.
Author: Hao Ni
Publisher: World Scientific
ISBN: 1786349388
Category : Business & Economics
Languages : en
Pages : 263
Get Book Here
Book Description
In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!
