Introduction to financial models for management and planning, Morris, James R. (university Of Colorado, Denver, Usa) Daley, John P. (university Of Colorado, Denver, Usa)
Автор: James, Gareth Witten, Daniela Hastie, Trevor Tibsh Название: Introduction to statistical learning ISBN: 1071614177 ISBN-13(EAN): 9781071614174 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more.
Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers.
An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.
Описание: This book brings together, in a single volume, the fields of multicriteria decision making and multiobjective optimization that are traditionally covered by different books. It is written in a didactic form using examples to help understanding of the proposed methodologies better.
Автор: Tayali, Halit Alper (istanbul Universitesi) Название: Introduction to mathematical models in operations planning ISBN: 1032191996 ISBN-13(EAN): 9781032191997 Издательство: Taylor&Francis Рейтинг: Цена: 8420.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Valdez Stephen Название: An Introduction to Global Financial Markets ISBN: 1137497556 ISBN-13(EAN): 9781137497550 Издательство: Springer Рейтинг: Цена: 8524.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An accessible but comprehensive guide to the world of finance and financial markets. Taking an international approach, the authors examine the different types of banking and markets around the world, and cover foreign exchange and derivative products. This edition is right up to date and incorporates recent events and developments in finance.
Автор: Hastings Название: Introduction to Financial Mathematics ISBN: 149872390X ISBN-13(EAN): 9781498723909 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Introduction to Financial Mathematics is ideal for an introductory undergraduate course. Unlike most textbooks aimed at more advanced courses, the textmotivates students through a discussion of personal finances and portfolio management. The author then goes on to covervaluation of financial derivatives in discrete time, using all of closed form, recursive, and simulation methods.
The text covers nearly all of the syllabus topics of the Financial Mathematics Actuarial examination, providing students with the foundation they require for future studies and throughout their careers. It begins by covering standard material on the mathematics of interest, including compound interest, present value, annuities, loans, several versions of the rate of return on an investment, and interest in continuous time. The text explains how to value bonds at their issue dates, at coupon times, between coupon times, and in cases where the bonds are terminated early. Next, it supplies a rapid-fire overview of the main ideas and techniques of discrete probability, including sample spaces and probability measures, random variables and distributions, expectation, conditional probability, and independence. The author introduces the basic terminology of stocks and stock trading. He also explains how to derive the rate of return on a portfolio and how to use the idea of risk aversion to model the investor tradeoff between risk and return. The text also discusses the estimation of parameters of asset models from real data. The text closes with a detailed discussion of how to value financial derivatives using anti-arbitrage assumptions. The one-step and multi-step cases are covered, and exotic options such as barrier options are also introduced, to which simulation methods are applied. Many of the examples in the book involve numerical solution of complicated non-linear equations; others ask students to produce algorithms which beg to be implemented as programs. For maximum flexibility, the author has produced the text without adhering to any particular computational platform. A digital version of this text is also available in the form of Mathematica notebooks that contain additional content.
Автор: Feng Название: An Introduction To Computational Ri ISBN: 1498742165 ISBN-13(EAN): 9781498742160 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development. Today's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency. Features Provides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samples Includes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians Summarizes state-of-arts computational techniques for risk management professionals Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insurance Gives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow. Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.
Автор: Hens, Thorsten Rieger, Marc Oliver Название: Financial economics ISBN: 3662496860 ISBN-13(EAN): 9783662496862 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Financial economics is a fascinating topic where ideas from economics, mathematics and, most recently, psychology are combined to understand financial markets. This book gives a concise introduction into this field and includes for the first time recent results from behavioral finance that help to understand many puzzles in traditional finance.
Автор: Olivieri, Annamaria Pitacco, Ermanno Название: Introduction to insurance mathematics ISBN: 3319213768 ISBN-13(EAN): 9783319213767 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to Insurance Mathematics
Автор: Igor V. Evstigneev; Thorsten Hens; Klaus Reiner Sc Название: Mathematical Financial Economics ISBN: 3319165704 ISBN-13(EAN): 9783319165707 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook is an elementary introduction to the key topics in mathematical finance and financial economics - two realms of ideas that substantially overlap but are often treated separately from each other.
Автор: Ali Hirsa Название: An Introduction to the Mathematics of Financial Derivatives, ISBN: 012384682X ISBN-13(EAN): 9780123846822 Издательство: Elsevier Science Рейтинг: Цена: 13304.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A text that eases the transition between basic summaries of financial engineering to more advanced treatments using stochastic calculus. Requiring a basic knowledge of calculus and probability, it takes readers on a tour of advanced financial engineering. It encourages use of discrete chapters as complementary readings on different topics.
Автор: Severini, Thomas A Название: Introduction to Statistical Methods for Financial Models ISBN: 0367657872 ISBN-13(EAN): 9780367657871 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Letter Jam is a 2-6 player cooperative word game where players assist each other in composing meaningful words from letters around the table. The trick is holding the letter card so that it`s only visible to other players and not to you.At the start of the game, each player receives a set of face-down letter cards that can be arranged to form an existing word. The setup can be prepared by using a special card scanning app, or by players selecting words for each other. Each player then puts their first card in their stand facing the other players without looking at it, and the game begins.The game is played in turns. Each turn, players simultaneously search other players` letters to see what words they can spell out (telling the others the length of the word they can make up). The player who offers the longest word can then be chosen as the clue giver.The clue giver spells out their clue by putting numbered tokens in front of the other players. Number one goes to the player whose letter comes first in the clue, number two to the second letter etc. They can always use a wild card which can be any letter, but they cannot tell others which letter it represents.Each player with a numbered token (or tokens) in front of them then tries to figure out what their letter is. If they do, they place the card face down before revealing the next letter. At the end of the game, players can then rearrange the cards to try to form an existing word. All players then reveal their cards to see if they were successful or not. The more players who have an existing word in front of them, the bigger their common success.
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