Data analysis and applications.

Data analysis and applications. 4, Financial data analysis and methods /

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Bibliographic Details
Other Authors: Makrides, Andreas, Karagrigoriou, Alex, Skiadas, Christos H.
Format: Electronic eBook
Language:English
Published: London : Hoboken : ISTE, Ltd. ; Wiley, 2020.
Series:Big data, artificial intelligence and data analyst set ; v. 6.
Subjects:
Quantitative research.
Regression analysis.
Forecasting.
Data mining.
Online Access:CONNECT
Table of Contents:
  • Cover
  • Half-Title Page
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • PART 1: Financial Data Analysis and Methods
  • 1. Forecasting Methods in Extreme Scenarios and Advanced Data Analytics for Improved Risk Estimation
  • 1.1. Introduction
  • 1.2. The low price effect and correction
  • 1.2.1. Percentage value at risk and low price correction
  • 1.2.2. Expected Percentage Shortfall (EPS) and Low Price Correction
  • 1.2.3. Adjusted Evaluation Measures
  • 1.2.4. Backtesting and Method's Advantages
  • 1.3. Application
  • 1.3.1. The Alpha warrant
  • 1.3.2. The ARTX stock
  • 1.4. Conclusion
  • 1.5. Acknowledgements
  • 1.6. References
  • 2. Credit Portfolio Risk Evaluation with Non-Gaussian One-factor Merton Models and its Application to CDO Pricing
  • 2.1. Introduction
  • 2.2. Model and assumptions
  • 2.3. Asymptotic evaluation of credit risk measures
  • 2.4. Data analysis
  • 2.5. Conclusion
  • 2.6. Acknowledgements
  • 2.7. References
  • 3. Towards an Improved Credit Scoring System with Alternative Data: the Greek Case
  • 3.1. Introduction
  • 3.2. Literature review: stages of credit scoring
  • 3.3. Performance definition
  • 3.4. Data description
  • 3.4.1. Alternative data in credit scoring
  • 3.4.2. Credit scoring data set
  • 3.4.3. Data pre-processing
  • 3.5. Models' comparison
  • 3.6. Out-of-time and out-of-sample validation
  • 3.7. Conclusion
  • 3.8. References
  • 4. EM Algorithm for Estimating the Parameters of the Multivariate Stable Distribution
  • 4.1. Introduction
  • 4.2. Estimators of maximum likelihood approach
  • 4.3. Quadrature formulas
  • 4.4. Computer modeling
  • 4.5. Conclusion
  • 4.6. References
  • PART 2: Statistics and Stochastic Data Analysis and Methods
  • 5. Methods for Assessing Critical States of Complex Systems
  • 7. Generalizations of Poisson Process in the Modeling of Random Processes Related to Road Accidents
  • 7.1. Introduction
  • 7.2. Non-homogeneous Poisson process
  • 7.3. Model of the road accident number in Poland
  • 7.3.1. Estimation of model parameters
  • 7.3.2. Anticipation of the accident number
  • 7.4. Non-homogeneous compound Poisson process
  • 7.5. Data analysis
  • 7.6. Anticipation of the accident consequences
  • 7.7. Conclusion
  • 7.8. References
  • 8. Dependability and Performance Analysis for a Two Unit Multi-state System with Imperfect Switch
  • 8.1. Introduction

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