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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
Attention for Chapter 8: Using Public Information to Predict Corporate Default Risk
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Chapter title
Using Public Information to Predict Corporate Default Risk
Chapter number 8
Book title
Applied Quantitative Finance
Published by
Springer, Berlin, Heidelberg, January 2017
DOI 10.1007/978-3-662-54486-0_8
Book ISBNs
978-3-66-254485-3, 978-3-66-254486-0
Authors

C. N. Peng, J. L. Lin, Peng, C. N., Lin, J. L.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 17%
Student > Bachelor 1 17%
Student > Master 1 17%
Unknown 3 50%
Readers by discipline Count As %
Unspecified 1 17%
Agricultural and Biological Sciences 1 17%
Engineering 1 17%
Unknown 3 50%