Deterministic and Stochastic Topics in Computational Finance Deterministic and Stochastic Topics in Computational Finance

Deterministic and Stochastic Topics in Computational Finance

    • ‏52٫99 US$
    • ‏52٫99 US$

وصف الناشر

What distinguishes this book from other texts on mathematical finance is the use of both probabilistic and PDEs tools to price derivatives for both constant and stochastic volatility models, by which the reader has the advantage of computing explicitly a large number of prices for European, American and Asian derivatives. The book presents continuous time models for financial markets, starting from classical models such as Black–Scholes and evolving towards the most popular models today such as Heston and VAR. A key feature of the textbook is the large number of exercises, mostly solved, which are designed to help the reader to understand the material. The book is based on the author's lectures on topics on computational finance for senior and graduate students, delivered in USA (Princeton University and EMU), Taiwan and Kuwait. The prerequisites are an introductory course in stochastic calculus, as well as the usual calculus sequence. The book is addressed to undergraduate and graduate students in Masters of Finance programs as well as to those who wish to become more efficient in their practical applications. Topics covered: Interest Rates and Bonds Forward Rates and Yield Curves Risk-neutral Valuation Martingale Measures Black–Scholes Analysis American Options Stochastic Volatility Models (Heston, AR, GARCH) Stochastic Return Models (VAR) Request Inspection Copy Contents: Introduction: Determinism or Stochasticity? Calibration to the MarketInterest Rates and Bonds: Modeling Stochastic Rates Bonds, Forward Rates and Yield CurvesRisk-Neutral Valuation Pricing: Modeling Stock-Prices Risk-Neutral Valuation Martingale MeasuresPDE Approach: Black-Scholes Analysis Black-Scholes for Asian Derivatives American OptionsStochastic Volatility and Return Models: Heston Model GARCH Model AR(1) Model Stochastic Return Models Hints and SolutionsAppendices: Useful Transforms Probability Concepts Elements of Stochastic Calculus Series and Equations Bibliography Index Readership: Undergraduates, graduate students and researchers in Mathematical Finance. Black–Scholes Equation;Stochastic Volatility Model;Heston Model;Derivatives PricingKey Features: The book contains a chapter on pricing options when the underlying asset has stochastic volatility. Models such as Heston, Garch and Arch are presented. Heston model is one of the most popular these days and the book provides a clear presentation involving only elementary mathematics The last chapter deals with pricing options in the case when the underlying asset has a stochastic rate of return. This is a topic of ongoing research and it is related with the topic of 2013 Nobel Price in Economics. There are very few sources that provide this type of developments. This chapter was developed by the author A large number of the proposed problems (about 150) are solved completely or partially in the Hints and Solutions chapter The book contains an Appendix section containing the most useful information the reader needs to have in order to fully understand the text, without consulting another text

النوع
تمويل شركات وأفراد
تاريخ النشر
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٢٥ نوفمبر
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
World Scientific Publishing Company
البائع
Ingram DV LLC
الحجم
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‫م.ب.‬
The Black-Scholes Model The Black-Scholes Model
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Pathwise Estimation and Inference for Diffusion Market Models Pathwise Estimation and Inference for Diffusion Market Models
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Term-Structure Models Term-Structure Models
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Paris-Princeton Lectures on Mathematical Finance 2004 Paris-Princeton Lectures on Mathematical Finance 2004
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Mathematical Finance Mathematical Finance
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Mathematics of Financial Markets Mathematics of Financial Markets
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An Informal Introduction to Stochastic Calculus with Applications An Informal Introduction to Stochastic Calculus with Applications
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INFORM INTRO STOCH CAL (2ND ED) INFORM INTRO STOCH CAL (2ND ED)
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Geometric Modeling in Probability and Statistics Geometric Modeling in Probability and Statistics
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STOCHASTIC GEOMETRIC ANALYSIS WITH APPLICATIONS STOCHASTIC GEOMETRIC ANALYSIS WITH APPLICATIONS
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Geometric Mechanics on Riemannian Manifolds Geometric Mechanics on Riemannian Manifolds
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Heat Kernels for Elliptic and Sub-elliptic Operators Heat Kernels for Elliptic and Sub-elliptic Operators
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