Coherent risk measures under filtered historical simulation [An article from: Journal of Banking and Finance]

Coherent risk measures under filtered historical simulation [An article from: Journal of Banking and Finance]
This digital document is a journal article from Journal of Banking and Finance, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Recent studies have strongly criticised conventional VaR models for not providing a coherent risk measure. Acerbi provides the intuition for an entire family of coherent measures of risk known as ”spectral risk measures” [Spectral measures of risk: A coherent representation of subjective risk aversion. Journal of Banking and Finance 26 (7) (2002) 1505-1518]. In this study we illustrate how the Filtered Historical Simulation [Barone-Adesi, G., Bourgoin, F., Giannopoulos, K., 1998. Don't look back. Risk 11, 100-104; Barone-Adesi, Giannopoulos, K., Vosper, L., 1999. VaR without correlations for non-linear portfolios. Journal of Futures Markets 19, 583-602], can provide an improved methodology for calculating the Expected Shortfall. Thereafter, we prove that these new risk measures are spectral and are coherent as well, following Acerbi. Furthermore, we provide the statistical error formula that allows to calculate the error for our model.

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On the simulation of portfolios of interest rate and credit risk sensitive securities [An article from: European Journal of Operational Research]

On the simulation of portfolios of interest rate and credit risk sensitive securities [An article from: European Journal of Operational Research]
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
We discuss extensions of reduced-form and structural models for pricing credit risky securities to portfolio simulation and valuation. Stochasticity in interest rates and credit spreads is captured via reduced-form models and is incorporated with a default and migration model based on the structural credit risk modelling approach. Calculated prices are consistent with observed prices and the term structure of default-free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds and the sensitivity of future portfolio valuation with respect to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) study of the structure of credit risk by investigating the impact of disparate risk factors on portfolio risk, and (iii) tracking of corporate bond indices via simulation and optimisation models. In particular, we study the effect of uncertainty in credit spreads and interest rates on the overall risk of a credit portfolio, a topic that has been recently discussed by Kiesel et al. [The structure of credit risk: spread volatility and ratings transitions. Technical report, Bank of England, ISSN 1268-5562, 2001], but has been otherwise mostly neglected. We find that spread risk and interest rate risk are important factors that do not diversify away in a large portfolio context, especially when high-quality instruments are considered.

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Simulation Techniques in Financial Risk Management.(Book review): An article from: Journal of Risk and Insurance

This digital document is an article from Journal of Risk and Insurance, published by American Risk and Insurance Association, Inc. on June 1, 2009. The length of the article is 1553 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available immediately after purchase. You can view it with any web browser.

Citation Details
Title: Simulation Techniques in Financial Risk Management.(Book review)
Author: Puneet Prakash
Publication: Journal of Risk and Insurance (Magazine/Journal)
Date: June 1, 2009
Publisher: American Risk and Insurance Association, Inc.
Volume: 76 Issue: 2 Page: 455(4)

Article Type: Book review

Distributed by Gale, a part of Cengage Learning

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Electronics Process Technology: Production Modelling, Simulation and Optimisation

Electronics Process Technology: Production Modelling, Simulation and Optimisation

This book provides a systemized presentation of new techniques and methods in electronics manufacture. It helps the reader reduce the cost and increase the reliability of electronic products by employing up-to-date technology. It also details the latest ideas for reducing the scale of electronic components and products to the nano-scale by organizing all the elements of the complicated modern electronics manufacturing process showing how they affect each other.

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Simulation Methods for Reliability and Availability of Complex Systems (Springer Series in Reliability Engineering)

Simulation Methods for Reliability and Availability of Complex Systems (Springer Series in Reliability Engineering)

Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems.

Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.

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Pension Fund Risk Management: Financial and Actuarial Modeling (Chapman & Hall/Crc Finance Series)

Pension Fund Risk Management: Financial and Actuarial Modeling (Chapman & Hall/Crc Finance Series)

As pension fund systems decrease and dependency ratios increase, risk management is becoming more complex in public and private pension plans. Pension Fund Risk Management: Financial and Actuarial Modeling sheds new light on the current state of pension fund risk management and provides new technical tools for addressing pension risk from an integrated point of view.

Divided into four parts, the book first presents the correct measurement of risk in pension funds, fund dynamics under a performance-oriented arrangement, an attribution model for monitoring the performance and risk of a defined benefit (DB) pension fund, and an optimal investment problem of a defined contribution (DC) pension fund under inflationary risk. It also describes a pension plan from a dynamic optimization viewpoint, the optimal asset allocation of U.S. pension funds, the identification of stakeholders’ risks, value-at-risk (VaR) methodology, and various effects on the asset allocation of DB pension schemes.

The second section focuses on the effects of uncertainty on employer-provided DB private pension plan liabilities; wage-based lump sum payments by death, retirement, or dismissal by the employer; fundamental retirement changes; occupational pension insurance in Germany; and longevity risk securitization in pension schemes.

In the third part, the book examines employers’ risks, accountability rules and regulations, useful actuarial analysis instruments, risk-based solvency regime in the Netherlands, and the impact of the 2008 global financial crisis on pension participants.

The final part covers DB pension freezes and terminations of plans, the two-pillar social security system of Italy, the Greek social security system, the effect of a company’s unfunded pension liabilities on its stock market valuation, and the returns of Spanish balanced pension plans and portfolio performance.

With contributions from well-known, international academics and professionals, this book will assist pension fund executives, risk managers, consultants, and academic researchers in attaining a clear picture of the integration of risks in the pension world. It offers a comprehensive, contemporary account of how to handle the risks involved with pension funds.

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Ecological Models for Regulatory Risk Assessments of Pesticides: Developing a Strategy for the Future (Society of Environmental Toxicology and Chemistry)

Ecological Models for Regulatory Risk Assessments of Pesticides: Developing a Strategy for the Future (Society of Environmental Toxicology and Chemistry)

Bringing together more than thirty influential regulators, academics, and industry scientists, Ecological Models for Regulatory Risk Assessments of Pesticides: Developing a Strategy for the Future provides a coherent, science-based view on ecological modeling for regulatory risk assessments. It discusses the benefits of modeling in the context of registrations, identifies the obstacles that prevent ecological modeling being used routinely in regulatory submissions, and explores the actions needed to overcome these obstacles.

The book focuses on the following issues:

  • Uncertainties in the process of model development, such as design, analysis, documentation, and communication
  • The availability of data and background information needed for optimal modeling
  • The limited knowledge of modeling
  • The lack of confidence in the outcome of ecological models and their reliability in pesticide risk assessment

It also suggests future solutions to these challenges, including:

  • A guidance document on the modeling process
  • Case studies that show how ecological models can provide reliable ecologically relevant risk assessments
  • Training the people who generate or evaluate results obtained by ecological models

Focusing on ecological models, such as unstructured population models, stage-structured matrix models, and individual- or agent-based models, this volume helps regulatory authorities, manufacturers, and scientists assess the risk of plant protection products in nontarget organisms. Armed with this knowledge, readers will better understand the challenges of using ecological modeling in the regulatory process.

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Modeling Risk: Applying Monte Carlo Simulation, Real Options Analysis, Forecasting, and Optimization Techniques (Wiley Finance)

Modeling Risk: Applying Monte Carlo Simulation, Real Options Analysis, Forecasting, and Optimization Techniques (Wiley Finance)

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Computer Simulation in Financial Risk Management: A Guide for Business Planners and Strategists

Computer Simulation in Financial Risk Management: A Guide for Business Planners and Strategists
Computer programs that simulate complex processes in the real world can provide a quantitative tool for determining how much debt can be added safely to a company’s capital structure. The increasing number of bankruptcies and defaults in today’s international business arena result from debt overload and point to major shortcomings in the conventional financial evaluation process. In this book, Roy L. Nersesian describes why current methods of risk management fail and how computer simulation can be employed to determine the safe level of debt more accurately. Because the decision to add debt to an organization requires favorable, and essentially independent, decisions from both the borrower and lender, it is necessary to quantify both perspectives. Through actual examples readers will learn how to do this and to translate an actual business situation into a simulation model or program. Current evaluation systems, according to Nersesian, fail to incorporate the cyclical nature of business activity. They result all too often in an overly optimistic projection of cash flow. Simulation techniques are better able to incorporate the transience of good times and put quantitative analysis of risk on par with quantitative analysis of reward. Simulation techniques also reduce the role of speculative, and highly subjective, judgment. For example, decisionmakers who are not familiar personally with a particular business area, assign more risk to that area than those who are. A quantified risk management system enables executives to rank projects by the degree of risk much as they currently rank them by degree of profitability. The book presents the concept of simulation in terms that can be understood by generalists in corporations and financial institutions. At the same time, it provides computer programmers with an understanding of risk management principles. It will provide a valuable resource for: financial executives, planners and strategists in corporate and governmental organizations; bank lending officers; and computer programmers working with these organizations.

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Flood Risk Simulation (Progress in Water Resources)

Flood Risk Simulation (Progress in Water Resources)
An up-to-date text on the simulation of flood risk in both rural and urban areas, this book begins by presenting the main concepts related to one- dimensional flood propagation. Detailed mathematical models that place particular emphasis on numerical modelling are featured. There are also sections on practical aspects in river flood routing problems, parameter identification in I-D flood routing including optimizing techniques with applications, and the routing of dam-break waves with a brief description of historical dam failures and their main causes.

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