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Stochastic Financial Models

Stochastic Financial Models
  • Author : Douglas Kennedy
  • Publsiher : CRC Press
  • Release : 19 April 2016
  • ISBN : 1439882711
  • Pages : 264 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKStochastic Financial Models

Summary:
Filling the void between surveys of the field with relatively light mathematical content and books with a rigorous, formal approach to stochastic integration and probabilistic ideas, Stochastic Financial Models provides a sound introduction to mathematical finance. The author takes a classical applied mathematical approach, focusing on calculations rather than seeking the greatest generality. Developed from the esteemed author’s advanced undergraduate and graduate courses at the University of Cambridge, the text begins with the classical topics of utility and the mean-variance approach to portfolio choice. The remainder of the book deals with derivative pricing. The author fully explains the binomial model since it is central to understanding the pricing of derivatives by self-financing hedging portfolios. He then discusses the general discrete-time model, Brownian motion and the Black–Scholes model. The book concludes with a look at various interest-rate models. Concepts from measure-theoretic probability and solutions to the end-of-chapter exercises are provided in the appendices. By exploring the important and exciting application area of mathematical finance, this text encourages students to learn more about probability, martingales and stochastic integration. It shows how mathematical concepts, such as the Black–Scholes and Gaussian random-field models, are used in financial situations.


Stochastic Models of Financial Mathematics

Stochastic Models of Financial Mathematics
  • Author : Vigirdas Mackevicius
  • Publisher : Elsevier
  • Release : 08 November 2016
GET THIS BOOKStochastic Models of Financial Mathematics

This book presents a short introduction to continuous-time financial models. An overview of the basics of stochastic analysis precedes a focus on the Black-Scholes and interest rate models. Other topics covered include self-financing strategies, option pricing, exotic options and risk-neutral probabilities. Vasicek, Cox-Ingersoll-Ross, and Heath-Jarrow-Morton interest rate models are also explored. The author presents practitioners with a basic introduction, with more rigorous information provided for mathematicians. The reader is assumed to be familiar with the basics of probability theory. Some

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Stochastic Financial Models

Stochastic Financial Models
  • Author : Douglas Kennedy
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKStochastic Financial Models

Filling the void between surveys of the field with relatively light mathematical content and books with a rigorous, formal approach to stochastic integration and probabilistic ideas, Stochastic Financial Models provides a sound introduction to mathematical finance. The author takes a classical applied mathematical approach, focusing on calculations rather than seeking the greatest generality. Developed from the esteemed author’s advanced undergraduate and graduate courses at the University of Cambridge, the text begins with the classical topics of utility and the

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Mathematical Finance

Mathematical Finance
  • Author : Jacques Janssen,Raimondo Manca,Ernesto Volpe
  • Publisher : John Wiley & Sons
  • Release : 07 March 2013
GET THIS BOOKMathematical Finance

This book provides a detailed study of Financial Mathematics. In addition to the extraordinary depth the book provides, it offers a study of the axiomatic approach that is ideally suited for analyzing financial problems. This book is addressed to MBA's, Financial Engineers, Applied Mathematicians, Banks, Insurance Companies, and Students of Business School, of Economics, of Applied Mathematics, of Financial Engineering, Banks, and more.

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Stochastic Modeling in Economics and Finance

Stochastic Modeling in Economics and Finance
  • Author : Jitka Dupacova,J. Hurt,J. Stepan
  • Publisher : Springer Science & Business Media
  • Release : 18 April 2006
GET THIS BOOKStochastic Modeling in Economics and Finance

In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented. The method of presentation is simple enough to bridge the elements of financial arithmetic and complex models of financial math developed in the later parts. It covers characteristics of cash flows, yield curves, and valuation of securities. Part II is devoted to the allocation of funds and risk management: classics (Markowitz theory of portfolio), capital asset pricing model, arbitrage pricing theory, asset & liability management,

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Methods of Mathematical Finance

Methods of Mathematical Finance
  • Author : Ioannis Karatzas,Steven Shreve
  • Publisher : Springer
  • Release : 10 January 2017
GET THIS BOOKMethods of Mathematical Finance

This sequel to Brownian Motion and Stochastic Calculus by the same authors develops contingent claim pricing and optimal consumption/investment in both complete and incomplete markets, within the context of Brownian-motion-driven asset prices. The latter topic is extended to a study of equilibrium, providing conditions for existence and uniqueness of market prices which support trading by several heterogeneous agents. Although much of the incomplete-market material is available in research papers, these topics are treated for the first time in a

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Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations

Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations
  • Author : Steven R. Dunbar
  • Publisher : American Mathematical Soc.
  • Release : 03 April 2019
GET THIS BOOKMathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations

Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis.

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Martingale Methods in Financial Modelling

Martingale Methods in Financial Modelling
  • Author : Marek Musiela
  • Publisher : Springer
  • Release : 12 March 2014
GET THIS BOOKMartingale Methods in Financial Modelling

A comprehensive and self-contained treatment of the theory and practice of option pricing. The role of martingale methods in financial modeling is exposed. The emphasis is on using arbitrage-free models already accepted by the market as well as on building the new ones. Standard calls and puts together with numerous examples of exotic options such as barriers and quantos, for example on stocks, indices, currencies and interest rates are analysed. The importance of choosing a convenient numeraire in price calculations

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Random Evolutions and their Applications

Random Evolutions and their Applications
  • Author : Anatoly Swishchuk
  • Publisher : Springer Science & Business Media
  • Release : 31 May 2000
GET THIS BOOKRandom Evolutions and their Applications

This book is devoted to new trends in random evolution and their applications to the stochastic evolutionary system. It contains new developments such as an analogue of Dynkin's formula, boundary value problems, stability and control of random evolutions, stochastic evolutionary equations, and driven martingale measures. In addition, it treats statistics of random evolutions processes, statistics of financial stochastic models, and stochastic stability and control of financial markets. Audience: This volume will be of interest to research and applied mathematicians working

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Stochastic Models of Structural Plasma Turbulence

Stochastic Models of Structural Plasma Turbulence
  • Author : Victor Yu Korolev,Nina N. Skvortsova
  • Publisher : Walter de Gruyter
  • Release : 09 August 2022
GET THIS BOOKStochastic Models of Structural Plasma Turbulence

The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.

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Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes

Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
  • Author : Cornelis W Oosterlee,Lech A Grzelak
  • Publisher : World Scientific
  • Release : 29 October 2019
GET THIS BOOKMathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes

This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several

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Financial Mathematics

Financial Mathematics
  • Author : Andrea Pascucci,Wolfgang J. Runggaldier
  • Publisher : Springer Science & Business Media
  • Release : 05 April 2012
GET THIS BOOKFinancial Mathematics

With the Bologna Accords a bachelor-master-doctor curriculum has been introduced in various countries with the intention that students may enter the job market already at the bachelor level. Since financial Institutions provide non negligible job opportunities also for mathematicians, and scientists in general, it appeared to be appropriate to have a financial mathematics course already at the bachelor level in mathematics. Most mathematical techniques in use in financial mathematics are related to continuous time models and require thus notions from

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