RISK MANAGEMENT WITH BENCHMARKING

Portfolio theory must address the fact that, in reality, portfolio managers are evaluated relative to a benchmark, and therefore adopt risk management practices to account for the benchmark performance. We capture this risk management consideration by allowing a pre-specified shortfall from a target benchmark-linked return, consistent with growing interest in such practice. In a dynamic setting, we demonstrate how a risk-averse portfolio manager optimally under- or over-performs a target benchmark under different economic conditions, depending on his attitude towards risk and choice of the benchmark. The analysis therefore illustrates how investors can achieve their desired gain/loss characteristics for funds under management through an appropriate combined choice of the benchmark and money manager. We consider a variety of extensions, and also highlight the ability of our setting to shed some light on documented return patterns across segments of the money management industry

Risk Management with Benchmarking

Portfolio theory must address the fact that, in reality, portfolio managers are evaluated relative to a benchmark, and therefore adopt risk management practices to account for the benchmark performance. We capture this risk management consideration by allowing a pre-specified shortfall from a target benchmark-linked return, consistent with growing interest in such practice. In a dynamic setting, we demonstrate how a risk averse portfolio manager optimally under- or over-performs a target benchmark under different economic conditions, depending on his attitude towards risk and choice of the benchmark. The analysis therefore illustrates how investors can achieve their desired gain/loss characteristics for funds under management through an appropriate combined choice of the benchmark and money manager. We consider a variety of extensions, and also highlight the ability of our setting to shed some light on documented return patterns across segments of the money management industry

Quantitative Validation: An Overview and Framework for PD Backtesting and Benchmarking.

The aim of credit risk models is to identify and quantify future outcomes of a set of risk measurements. In other words, the model's purpose is to provide as good an approximation as possible of what constitutes the true underlying risk relationship between a set of inputs and a target variable. These parameters are used for regulatory capital calculations to determine the capital needed that serves a buffer to protect depositors in adverse economic conditions. In order to manage model risk, financial institutions need to set up validation processes so as to monitor the quality of the models on an ongoing basis. Validation is important to inform all stakeholders (e.g. board of directors, senior management, regulators, investors, borrowers, …) and as such allow them to make better decisions. Validation can be considered from both a quantitative and qualitative point of view. Backtesting and benchmarking are key quantitative validation tools. In backtesting, the predicted risk measurements (PD, LGD, CCF) will be contrasted with observed measurements using a workbench of available test statistics to evaluate the calibration, discrimination and stability of the model. A timely detection of reduced performance is crucial since it directly impacts profitability and risk management strategies. The aim of benchmarking is to compare internal risk measurements with external risk measurements so to allow to better gauge the quality of the internal rating system. This paper will focus on the quantitative PD validation process within a Basel II context. We will set forth a traffic light indicator approach that employs all relevant statistical tests to quantitatively validate the used PD model, and document this complete approach with a reallife case-study.Framework; Benchmarking; Credit; Credit scoring; Control;

Risk Management with Benchmarking

Portfolio theory must address the fact that in reality, portfolio managers are evaluated relative to a benchmark, and therefore adopt risk management practices to account for the benchmark performance. We capture this risk management consideration by allowing a prespecified shortfall from a target benchmark-linked return, consistent with growing interest in such practice. In a dynamic setting, we demonstrate how a risk averse portfolio manager optimally under- or overperforms a target benchmark under different economic conditions, depending on his attitude towards risk and choice of the benchmark. Investors can therefore achieve their desired gain/loss characteristics for funds under management through an appropriate combined choice of the benchmark and money manager

Teplá: Risk Management with Benchmarking

P ortfolio theory must address the fact that, in reality, portfolio managers are evaluated relative to a benchmark, and therefore adopt risk management practices to account for the benchmark performance. We capture this risk management consideration by allowing a prespecified shortfall from a target benchmark-linked return, consistent with growing interest in such practice. In a dynamic setting, we demonstrate how a risk-averse portfolio manager optimally under-or overperforms a target benchmark under different economic conditions, depending on his attitude towards risk and choice of the benchmark. The analysis therefore illustrates how investors can achieve their desired performance profile for funds under management through an appropriate combined choice of the benchmark and money manager. We consider a variety of extensions, and also highlight the ability of our setting to shed some light on documented return patterns across segments of the money management industry

Pre-Disaster Risk Management in Post-Earthquake (1999) Turkey

This paper assesses the status of pre-disaster risk management in the case of Turkey. By focusing on the period following the catastrophic August 17, 1999 earthquake, the study benefits from USAID’s Disaster Risk Management Benchmarking Tool (DRMBT). In line with the benchmarking tool, the paper covers key developments in the four components of pre-disaster risk management, namely: risk identification, risk mitigation, risk transfer and disaster preparedness. In the end, it will present three major conclusions: (i) Although post-1999 Turkey has made some important progress in the pre-disaster phase of DRM, particularly with the enactment of obligatory earthquake insurance and tightened standards for building construction, the country is far away from substantial levels of success in DRM. (ii) In recent years, local governments have had been given more authority in the realm of DRM, however, Turkey’s approach to DRM is still predominantly centralized at the expense of successful DRM practices at the local level. (iii) While the devastating 1999 earthquake has resulted in advances in the pre-disaster components of DRM; progress has been mostly in the realm of earthquakes. Turkey’s other major disasters (landslides, floods, wild fires i.e.) also require similar attention by local and central authorities

Benchmarking Of Risk Management Methods With Regard to Variations As A Source Of Risk

When developing new systems, there is always some kind of reference to existing systems. Various approaches aim at describing qualitatively different characteristics of such connections, often depicted as some form of variation. Among other things, this is done with regard to innovation potential and development risk. In this paper, we investigate the extent to which established methods of risk management refer to modelling approaches for variations by means as mentionend above. After a litertaure search 11 methods and method clusters are analyzed more in detail within a method benchmark

Benchmarking of project planning and success in selected industries

Purpose - To identify the industry in which projects are best planned and executed and use it as a benchmark for improving project planning in other industries. Design/methodology/approach - Based on data collected from 280 project managers, project success and quality of project planning were evaluated and analyzed for four industries - construction and engineering, software and communications, services, and production and maintenance. Findings - Quality of project planning was found to be the highest in construction and engineering organizations and the lowest in manufacturing organizations. This is a result of a few factors, among them the intensive organizational support which is offered to project managers working in construction and engineering organizations. The other three industries limit their support mostly to tactical aspects, such as the purchasing of project management software. The high quality of project planning in the construction and engineering organizations resulted in their ability to complete projects by almost half the cost and schedule overruns, as compared to organizations belonging to the other industries. Finally, results of the industries in Israel and Japan are compared and analyzed. Research limitations/implications - Findings are limited to the four industries included in the study. Practical implications - If organizations, not belonging to the construction industry, wish to improve the probability of success in project planning and execution, they should follow methodologies commonly used in the construction industry. Originality/value - This paper introduces a valid field study, exploring project management practices in four industries and identifies the one which may be used as a benchmark for the others. It also identifies specific strengths and weaknesses in project management within the explored industries

The development of a Quality Risk Management solution designed to facilitate compliance with the risk-based qualification, validation and change control GMP requirement of the EU

This research work was concerned with investigating the risk-based regulatory requirements that are currently in place in the European Union governing the manufacture of medicinal products. The main goal of this research was to develop a practical Quality Risk Management methodology that served as a solution for facilitating compliance with the EU GMP requirements in the area of risk-based Qualification, Validation and Change Control, and which was fully in line with the principles and guidance of ICH Q9, on Quality Risk Management. Following extensive testing and evaluation activities with a range of key stakeholders including the pharmaceutical manufacturing sector in Ireland, the UK and the US, and GMP Inspectors from a wide range of countries, this work resulted in a formal, readily usable, rigorous and complete Quality Risk Management Methodology. It is designed to facilitate compliance with the risk based qualification, validation and change control GMP requirements of the EU, and is fully in line with ICH Quality Risk Management principles and guidelines. A practical and detailed training programme on the use of this methodology is also presented. This provides comprehensive training materials for facilitating training activities, as well as a documented strategy for the provision of such training in a timely and resource-efficient manner. In a comprehensive benchmarking exercise, this approach to Quality Risk Management was compared with the application of Risk Management in two industries that are considered mature and advanced in their application of Risk Management principles and methodologies. These were the US aeronautics industry, as represented by the work of the National Aeronautics Space Administration (NASA) and the US nuclear power generation industry, as represented by the work of the US Nuclear Regulatory Commission (NRC). The methodology performed very favourably in this benchmarking exercise, and many examples of common best practices were identified. The Quality Risk Management methodology developed in this work has attracted wide interest, not only from within the pharmaceutical manufacturing industry, but also from the GMP Inspectorates of several countries, from academic bodies involved in the teaching of pharmacy and pharmaceutical-related sciences in Ireland, from the publishers of research journals involved in pharmaceutical science, among others. The methodology has already found application in several multinational pharmaceutical manufacturing and other companies, and has served as a valuable educational and training resource in the practical application of Quality Risk Management in the GMP environment. The application of formal Quality Risk Management methodologies in the EU pharmaceutical manufacturing environment is still at its early stages, relative to that in other industries, and several opportunities to further develop and build upon this research work has been identified. The intention behind these recommendations for further work is to promote the continued development of Quality Risk Management methodologies and approaches within the GMP environment, so that the risks posed by medicine to patients and animals may continually be reduced and managed