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Applied Quantitative Finance

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Cover of 'Applied Quantitative Finance'

Table of Contents

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    Book Overview
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    Chapter 1 VaR in High Dimensional Systems-A Conditional Correlation Approach
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    Chapter 2 Multivariate Volatility Models
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    Chapter 3 Portfolio Selection with Spectral Risk Measures
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    Chapter 4 Implementation of Local Stochastic Volatility Model in FX Derivatives
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    Chapter 5 Estimating Distance-to-Default with a Sector-Specific Liability Adjustment via Sequential Monte Carlo
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    Chapter 6 Risk Measurement with Spectral Capital Allocation
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    Chapter 7 Market Based Credit Rating and Its Applications
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    Chapter 8 Using Public Information to Predict Corporate Default Risk
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    Chapter 9 Stress Testing in Credit Portfolio Models
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    Chapter 10 Penalized Independent Factor
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    Chapter 11 Term Structure of Loss Cascades in Portfolio Securitisation
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    Chapter 12 Credit Rating Score Analysis
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    Chapter 13 Copulae in High Dimensions: An Introduction
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    Chapter 14 Measuring and Modeling Risk Using High-Frequency Data
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    Chapter 15 Measuring Financial Risk in Energy Markets
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    Chapter 16 Risk Analysis of Cryptocurrency as an Alternative Asset Class
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    Chapter 17 Time Varying Quantile Lasso
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    Chapter 18 Dynamic Topic Modelling for Cryptocurrency Community Forums
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    Chapter 19 Erratum to: Copulae in High Dimensions: An Introduction
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Title
Applied Quantitative Finance
Published by
Springer Berlin Heidelberg, August 2017
DOI 10.1007/978-3-662-54486-0
ISBNs
978-3-66-254485-3, 978-3-66-254486-0
Editors

Härdle, Wolfgang Karl, Chen, Cathy Yi-Hsuan, Overbeck, Ludger

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 276 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 5 2%
Belgium 4 1%
China 3 1%
Portugal 3 1%
Germany 2 <1%
Brazil 1 <1%
Iran, Islamic Republic of 1 <1%
Slovakia 1 <1%
Other 11 4%
Unknown 240 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 24%
Researcher 47 17%
Student > Master 38 14%
Other 26 9%
Professor > Associate Professor 22 8%
Other 77 28%
Readers by discipline Count As %
Economics, Econometrics and Finance 76 28%
Mathematics 50 18%
Business, Management and Accounting 43 16%
Engineering 26 9%
Computer Science 22 8%
Other 59 21%