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Implementing Models in Quantitative Finance: Methods and Cases

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Cover of 'Implementing Models in Quantitative Finance: Methods and Cases'

Table of Contents

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    Book Overview
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    Chapter 1 Static Monte Carlo
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    Chapter 2 Dynamic Monte Carlo
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    Chapter 3 Dynamic Programming for Stochastic Optimization
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    Chapter 4 Finite Difference Methods
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    Chapter 5 Numerical Solution of Linear Systems
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    Chapter 6 Quadrature Methods
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    Chapter 7 The Laplace Transform
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    Chapter 8 Structuring Dependence using Copula Functions
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    Chapter 9 Portfolio Selection: “Optimizing” an Error
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    Chapter 10 Alpha, Beta and Beyond
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    Chapter 11 Automatic Trading: Winning or Losing in a kBit
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    Chapter 12 Estimating the Risk-Neutral Density
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    Chapter 13 An “American” Monte Carlo
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    Chapter 14 Fixing Volatile Volatility
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    Chapter 15 An Average Problem
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    Chapter 16 Quasi-Monte Carlo: An Asian Bet
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    Chapter 17 Lookback Options: A Discrete Problem
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    Chapter 18 Electrifying the Price of Power
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    Chapter 19 A Sparkling Option
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    Chapter 20 Swinging on a Tree
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    Chapter 21 Floating Mortgages
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    Chapter 22 Basket Default Swaps
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    Chapter 23 Scenario Simulation Using Principal Components
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    Chapter 24 Parametric Estimation of Jump-Diffusions
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    Chapter 25 Nonparametric Estimation of Jump-Diffusions
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    Chapter 26 A Smiling GARCH
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Title
Implementing Models in Quantitative Finance: Methods and Cases
Published by
Springer Berlin Heidelberg, January 2008
DOI 10.1007/978-3-540-49959-6
ISBNs
978-3-54-022348-1, 978-3-54-049959-6
Authors

Fusai, Gianluca, Roncoroni, Andrea

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
United States 1 2%
Argentina 1 2%
Costa Rica 1 2%
Unknown 52 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Researcher 11 19%
Student > Master 10 18%
Professor > Associate Professor 5 9%
Other 4 7%
Other 12 21%
Unknown 4 7%
Readers by discipline Count As %
Economics, Econometrics and Finance 18 32%
Mathematics 14 25%
Business, Management and Accounting 8 14%
Computer Science 5 9%
Engineering 3 5%
Other 4 7%
Unknown 5 9%