Risk management in finance and logistics /

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Bibliographic Details
Author / Creator:Xu, Chunhui, author.
Imprint:Singapore : Springer, [2018]
Description:1 online resource
Series:Translational systems sciences ; volume 14
Translational systems sciences ; v. 14.
Subject:Risk management -- Mathematical models.
Finance -- Mathematical models.
Business logistics -- Mathematical models.
BUSINESS & ECONOMICS -- Industrial Management.
BUSINESS & ECONOMICS -- Management Science.
BUSINESS & ECONOMICS -- Organizational Behavior.
Business logistics -- Mathematical models.
Finance -- Mathematical models.
Risk management -- Mathematical models.
Electronic books.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11678896
Hidden Bibliographic Details
Other authors / contributors:Shiina, Takayuki, author.
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (EBSCO, viewed July 30, 2018).
Summary:This is the first book to introduce the major quantitative tools in risk management taking financial investments and logistics planning as the background: optimization and stochastic programming. Contained here are the fundamentals of portfolio selection theory from the point of view of risk control, and methods for risk control with new and popular risk measures such as VaR (Value-at-Risk) and CVaR (Conditional VaR). The book also introduces a new theory for risk management in more general investment situations such as flexible investment decisions, providing an accessible and comprehensive introduction to the interrelations between these fields of research. Basic concepts of stochastic programming are introduced, and their applications to risk management in inventory distribution and network design are covered as well. Illustrated by carefully chosen examples and supported by extensive data analyses, this book is highly recommended to readers who seek an in-depth and up-to-date integrated overview of the ever-expanding theoretical and quantitative fields of risk management in financial investment and logistics planning.--
Other form:Print version: Xu, Chunhui. Risk management in finance and logistics. Singapore : Springer, [2018] 9811303169 9789811303166
Standard no.:10.1007/978-981-13-0317-3
Table of Contents:
  • Intro; Preface; Contents; Part I Risk Management in Finance; 1 Financial Investment, Financial Risk and Risk Management; 1.1 Financial Markets and Financial Investment; 1.2 Main Risks in Financial Markets; 1.3 Risk Countermeasures: Hedging and Diversifying; 1.4 Risk Management by Diversification; 1.5 Outline of Part I; 2 Market Risk Measures in Financial Investments; 2.1 Market Risk and Its Measurement; 2.2 Variance: Fluctuation Is Taken as Risk; 2.2.1 Definition of Variance; 2.2.2 Estimation of Variance; 2.3 Value at Risk: A Likely Loss Is Taken as Risk; 2.3.1 Definition of Value at Risk.
  • 2.3.2 Estimation of VaR: Three Methods2.3.2.1 Variance-Covariance Method; Historical Simulation Method; Monte Carlo Simulation Method; 2.4 Conditional VaR: Expected Loss Behind VaR Is Taken as Risk; 2.4.1 Definition of Conditional VaR; 2.4.2 Estimation of CVaR; 2.5 Other Risk Measures: Failure Is Taken as Risk; 2.6 Summary; 3 Market Risk Control in Investment Decisions; 3.1 Portfolio Selection and Its Models; 3.2 MV Model and Its Variations; 3.2.1 The Base MV Model and Its Two Variations; 3.2.2 Solving Methods for MV Based Models.
  • 3.2.3 Two MV Based Models with Computational Advantages3.3 M-VaR Model and Its Solving Method; 3.3.1 Methods for Solving M-VaR Models; Minimize VaR Approximately; Minimize VaR Indirectly; Minimize VaR Using Heuristics; 3.3.2 Solving M-VaR Model Using the Soft Optimization Approach; The Ideas of the Soft Optimization Approach; The Algorithm for Solving Model (3.20); 3.4 M-CVaR Model and Its Solving Method; 3.5 Other M-Risk Models and Solving Methods; 3.6 Summary; 4 Market Risk Measures for Flexible Investments; 4.1 Flexible Investments.
  • 4.2 Risk Measures for Investments with Uncertain Exit Time4.2.1 Period Value at Risk; 4.2.2 Risk Measures Based on Average Loss in Time Axis; 4.3 Estimation of PVaR with Scenario Simulation; 4.3.1 Monte Carlo Simulation Method for Estimating PVaR; 4.3.2 Historical Simulation Method for Estimating PVaR; 4.4 Estimation of Risk Measures Based on Average Loss; 4.4.1 Estimation of Risk Measures Under Complete Information About the Probabilities of Exit Time; 4.4.2 Estimation of Risk Measures Under Partial Information About the Probabilities of Exit Time; 4.5 Summary.
  • 5 Market Risk Control in Flexible Investment Decisions5.1 Evaluation of Investments with Flexible Investment Term; 5.2 Two Kinds of Model for Flexible Investment Decisions; 5.3 M-PVaR Model and Solving Methods; 5.3.1 Solving PVaR Minimization Model by Solving a Mixed Integer Linear Programming; 5.3.2 Solving PVaR Minimization Model Using the Soft Optimization Approach; 5.4 M-Risk Models and Solving Methods; 5.4.1 M-Risk Models with Complete Probability Information Regarding Exit Time; 5.4.2 M-Risk Models with Partial Probability Information Regarding Exit Time.