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Large Deviations and Asymptotic Methods in Finance

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Cover of 'Large Deviations and Asymptotic Methods in Finance'

Table of Contents

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    Book Overview
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    Chapter 1 Probability Distribution in the SABR Model of Stochastic Volatility
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    Chapter 2 Large Deviations and Asymptotic Methods in Finance
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    Chapter 3 Unifying the BGM and SABR Models: A Short Ride in Hyperbolic Geometry
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    Chapter 4 Second Order Expansion for Implied Volatility in Two Factor Local Stochastic Volatility Models and Applications to the Dynamic $$\lambda $$ -Sabr Model
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    Chapter 5 General Asymptotics of Wiener Functionals and Application to Implied Volatilities
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    Chapter 6 Implied Volatility of Basket Options at Extreme Strikes
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    Chapter 7 Small-Time Asymptotics for the At-the-Money Implied Volatility in a Multi-dimensional Local Volatility Model
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    Chapter 8 A Remark on Gatheral’s ‘Most-Likely Path Approximation’ of Implied Volatility
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    Chapter 9 Implied Volatility from Local Volatility: A Path Integral Approach
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    Chapter 10 Extrapolation Analytics for Dupire’s Local Volatility
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    Chapter 11 The Gärtner-Ellis Theorem, Homogenization, and Affine Processes
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    Chapter 12 Asymptotics for $$d$$ -Dimensional Lévy-Type Processes
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    Chapter 13 Asymptotic Expansion Approach in Finance
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    Chapter 14 On Small Time Asymptotics for Rough Differential Equations Driven by Fractional Brownian Motions
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    Chapter 15 On Singularities in the Heston Model
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    Chapter 16 On the probability density function of baskets
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    Chapter 17 On Small-Noise Equations with Degenerate Limiting System Arising from Volatility Models
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    Chapter 18 Long Time Asymptotics for Optimal Investment
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    Chapter 19 Systemic Risk and Default Clustering for Large Financial Systems
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    Chapter 20 Estimation of Volatility Functionals: The Case of a $$\sqrt{n}$$ Window
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Title
Large Deviations and Asymptotic Methods in Finance
Published by
Springer International Publishing, June 2015
DOI 10.1007/978-3-319-11605-1
ISBNs
978-3-31-911604-4, 978-3-31-911605-1
Editors

Friz, Peter K., Gatheral, Jim, Gulisashvili, Archil, Jacquier, Antoine, Teichmann, Josef

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 33%
Student > Doctoral Student 2 11%
Professor > Associate Professor 2 11%
Researcher 2 11%
Other 1 6%
Other 2 11%
Unknown 3 17%
Readers by discipline Count As %
Mathematics 10 56%
Economics, Econometrics and Finance 2 11%
Physics and Astronomy 2 11%
Engineering 1 6%
Unknown 3 17%

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