Stochastic 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 basic knowledge of stochastic integration and differential equations theory is preferable, although all preliminary information is given in the first part of the book. Some relatively simple theoretical exercises are also provided. About continuous-time stochastic models of financial mathematics Black-Sholes model and interest rate models Requiring a minimum knowledge of stochastic integration and stochastic differential equations

Produk Detail:

  • Author : Vigirdas Mackevicius
  • Publisher : Elsevier
  • Pages : 130 pages
  • ISBN : 0081020864
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKStochastic Models of Financial Mathematics

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

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.

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

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,

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.

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

Stochastic Finance

Stochastic Finance
  • Author : Nicolas Privault
  • Publisher : CRC Press
  • Release : 20 December 2013
GET THIS BOOKStochastic Finance

Stochastic Finance: An Introduction with Market Examples presents an introduction to pricing and hedging in discrete and continuous time financial models without friction, emphasizing the complementarity of analytical and probabilistic methods. It demonstrates both the power and limitations of mathematical models in finance, covering the basics of finance and stochastic calculus, and builds up to special topics, such as options, derivatives, and credit default and jump processes. It details the techniques required to model the time evolution of risky assets.

Stochastic Processes with Applications to Finance

Stochastic Processes with Applications to Finance
  • Author : Masaaki Kijima
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKStochastic Processes with Applications to Finance

Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved. Stochastic Processes with Applications to Finance, Second Edition presents the mathematical theory of financial engineering using only basic mathematical tools

Stochastic Finance

Stochastic Finance
  • Author : Hans Föllmer,Alexander Schied
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 25 July 2016
GET THIS BOOKStochastic Finance

This book is an introduction to financial mathematics. It is intended for graduate students in mathematics and for researchers working in academia and industry. The focus on stochastic models in discrete time has two immediate benefits. First, the probabilistic machinery is simpler, and one can discuss right away some of the key problems in the theory of pricing and hedging of financial derivatives. Second, the paradigm of a complete financial market, where all derivatives admit a perfect hedge, becomes the

Stochastic Modeling

Stochastic Modeling
  • Author : Barry L. Nelson
  • Publisher : Courier Corporation
  • Release : 11 October 2012
GET THIS BOOKStochastic Modeling

Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.

Probability and Stochastic Modeling

Probability and Stochastic Modeling
  • Author : Vladimir I. Rotar
  • Publisher : CRC Press
  • Release : 25 August 2012
GET THIS BOOKProbability and Stochastic Modeling

A First Course in Probability with an Emphasis on Stochastic Modeling Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different

Introduction to Stochastic Finance

Introduction to Stochastic Finance
  • Author : Jia-An Yan
  • Publisher : Springer
  • Release : 10 October 2018
GET THIS BOOKIntroduction to Stochastic Finance

This book gives a systematic introduction to the basic theory of financial mathematics, with an emphasis on applications of martingale methods in pricing and hedging of contingent claims, interest rate term structure models, and expected utility maximization problems. The general theory of static risk measures, basic concepts and results on markets of semimartingale model, and a numeraire-free and original probability based framework for financial markets are also included. The basic theory of probability and Ito's theory of stochastic analysis, as

Stochastic Volatility Modeling

Stochastic Volatility Modeling
  • Author : Lorenzo Bergomi
  • Publisher : CRC Press
  • Release : 16 December 2015
GET THIS BOOKStochastic Volatility Modeling

Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility? How do we design models and assess their relevance? How do we tell which models are usable and when does c

Financial Modeling

Financial Modeling
  • Author : Stephane Crepey
  • Publisher : Springer Science & Business Media
  • Release : 13 June 2013
GET THIS BOOKFinancial Modeling

Backward stochastic differential equations (BSDEs) provide a general mathematical framework for solving pricing and risk management questions of financial derivatives. They are of growing importance for nonlinear pricing problems such as CVA computations that have been developed since the crisis. Although BSDEs are well known to academics, they are less familiar to practitioners in the financial industry. In order to fill this gap, this book revisits financial modeling and computational finance from a BSDE perspective, presenting a unified view of