Quantitative Financial Risk Management

Quantitative Financial Risk Management
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Оглавление

Galariotis Emilios. Quantitative Financial Risk Management

The Frank J. Fabozzi Series

Preface

About the Editors

Section One. Supervisory Risk Management

Chapter 1. Measuring Systemic Risk: Structural Approaches

Systemic Risk: Definitions

From Structural Models to Systemic Risk

Measuring Systemic Risk

Systemic Risk and Copula Models

Conclusions

References

Chapter 2. Supervisory Requirements and Expectations for Portfolio-Level Counterparty Credit Risk Measurement and Management

Introduction

Review of the Literature

Supervisory Requirements for CCR

Conceptual Issues in CCR: Risk versus Uncertainty

Conclusions

References

Chapter 3. Nonperforming Loans in the Bank Production Technology

Introduction

Selective Literature Review

Method

Empirical Application

Summary and Conclusion

Appendix 3.1 Bank Names and Type

References

Section Two. Risk Models and Measures

Chapter 4. A Practical Guide to Regime Switching in Financial Economics

A Brief Look at Markov Regime Switching in Academic Economics and Finance

Regime Switching and Interest Rate Processes

Regime Switching and Exchange Rates

Regime Switching, Stock Returns, and Asset Allocation

Single-Asset Markov Models

Two-State Estimation

Three-State Estimation

Markov Models for Multiple Assets

Practical Application of Regime Switching Models for Investment Purposes

Intuitive Appeal of Such Models

Implementation Challenges

Selecting the “Right” Model Structure

Calibrating the Selected Model Type to Suitable Data

Drawing the Right Conclusions from the Model

References

Chapter 5. Output Analysis and Stress Testing for Risk Constrained Portfolios

Introduction

Worst-Case Analysis

Stress Testing via Contamination

Conclusions and New Problems

References

Chapter 6. Risk Measures and Management in the Energy Sector

Introduction

Uncertainty Characterization via Scenarios

Measures of Risks

Case Studies

Summary

References

Section Three. Portfolio Management

Chapter 7. Portfolio Optimization: Theory and Practice

Static Portfolio Theory

Importance of Means

Stochastic Programming Approach to Asset Liability Management

Siemens InnoALM Pension Fund Model

Dynamic Portfolio Theory and Practice: The Kelly Capital Growth Approach

Transactions Costs

Some Great Investors

Appendix 7.1: Estimating Utility Functions and Risk Aversion

References

Chapter 8. Portfolio Optimization and Transaction Costs

Introduction

Literature Review on Transaction Costs

An LP Computable Risk Measure: The semi-MAD

Modeling Transaction Costs

Non-Unique Minimum Risk Portfolio

Experimental Analysis

Conclusions

Appendix

References

Chapter 9. Statistical Properties and Tests of Efficient Frontier Portfolios

Introduction

Notation and Setup

Distribution of Portfolio Weights

Empirical Study

Discussion and Concluding Remarks

References

Section Four. Credit Risk Modelling

Chapter 10. Stress Testing for Portfolio Credit Risk: Supervisory Expectations and Practices

Introduction and Motivation

Conceptual Issues in Stress Testing: Risk versus Uncertainty

The Function of Stress Testing

Supervisory Requirements and Expectations

Empirical Methodology: A Simple ST Example

Conclusion and Future Directions

References

Chapter 11. A Critique of Credit Risk Models with Evidence from Mid-Cap Firms

Introduction

Summary of Credit Model Methodologies

Our Empirical Methodology

Critique

Conclusions

References

Chapter 12. Predicting Credit Ratings Using a Robust Multicriteria Approach

Introduction

Credit Scoring and Rating

Multicriteria Methodology

Empirical Analysis

Conclusions and Future Perspectives

References

Section Five. Financial Markets

Chapter 13. Parameter Analysis of the VPIN (Volume-Synchronized Probability of Informed Trading) Metric

Introduction

Definition of VPIN

Computational Cost

Optimization of FPR

Uncertainty Quantification (UQ)

Conclusion

References

Chapter 14. Covariance Specification Tests for Multivariate GARCH Models1

Introduction

Covariance Specification Tests

Application of Covariance Specification Tests

Empirical Findings and Discussion

Conclusion

References

Chapter 15. Accounting Information in the Prediction of Securities Class Actions

Introduction

Literature Review

Methodology

Data

Results

Conclusions

References

About the Contributors

Chris Adcock

David E. Allen

Vassiliki Balla

Marida Bertocchi

Iain Clacher

Jitka Dupačová

Mark Freeman

Hirofumi Fukuyama

Rosella Giacometti

David Hillier

Michael Jacobs JR., Ph.D., CFA

Malcolm Kemp

Miloš Kopa

Gregory Koutmos

Raimund M. Kovacevic

Renata Mansini

Wlodzimierz Ogryczak

Georg Ch. Pflug

Robert J. Powell

Horst D. Simon

Abhay K. Singh

Jung Heon Song

M. Grazia Speranza

Maria Teresa Vespucci

William L. Weber

Kesheng Wu

Qi Zhang

William T. Ziemba

Constantin Zopounidis

Glossary

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Quantitative Financial Risk Management

Theory and Practice

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That is, the conditional value at risk at level is compared to the conditional value at risk at the median level. From all the values, it is possible to construct another kind of dependency matrix.

This idea can also be applied to the system as a whole: If is replaced by the distance to default of the whole system, (1.16) to (1.18), leads to a quantity that measures the impact of entity i on the system. In this way one is able to analyze notions like “too big to fail” or “too interconnected to fail.”

.....

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