Showing papers on "Financial risk published in 2000"

Value At Risk: The New Benchmark for Managing Financial Risk

Abstract: Since its original publication, Value at Risk has become the industry standard in risk management. Now in its Third Edition, this international bestseller addresses the fundamental changes in the field that have occurred across the globe in recent years. Philippe Jorion provides the most current information needed to understand and implement VAR-as well as manage newer dimensions of financial risk. Featured updates include: An increased emphasis on operational risk Using VAR for integrated risk management and to measure economic capital Applications of VAR to risk budgeting in investment management Discussion of new risk-management techniques, including extreme value theory, principal components, and copulas Extensive coverage of the recently finalized Basel II capital adequacy rules for commercial banks, integrated throughout the book A major new feature of the Third Edition is the addition of short questions and exercises at the end of each chapter, making it even easier to check progress. Detailed answers are posted on the companion web site www.pjorion.com/var/. The web site contains other materials, including additional questions that course instructors can assign to their students. Jorion leaves no stone unturned, addressing the building blocks of VAR from computing and backtesting models to forecasting risk and correlations. He outlines the use of VAR to measure and control risk for trading, for investment management, and for enterprise-wide risk management. He also points out key pitfalls to watch out for in risk-management systems. The value-at-risk approach continues to improve worldwide standards for managing numerous types of risk. Now more than ever, professionals can depend on Value at Risk for comprehensive, authoritative counsel on VAR, its application, and its results-and to keep ahead of the curve.

Risk Analysis: A Quantitative Guide

Abstract: Preface. Part 1: Introduction. 1. Why do a risk analysis? 1.1. Moving on from "What If" Scenarios. 1.2. The Risk Analysis Process. 1.3. Risk Management Options. 1.4. Evaluating Risk Management Options. 1.5. Inefficiencies in Transferring Risks to Others. 1.6. Risk Registers. 2. Planning a risk analysis. 2.1. Questions and Motives. 2.2. Determine the Assumptions that are Acceptable or Required. 2.3. Time and Timing. 2.4. You'll Need a Good Risk Analyst or Team. 3. The quality of a risk analysis. 3.1. The Reasons Why a Risk Analysis can be Terrible. 3.2. Communicating the Quality of Data Used in a Risk Analysis. 3.3. Level of Criticality. 3.4. The Biggest Uncertainty in a Risk Analysis. 3.5. Iterate. 4. Choice of model structure. 4.1. Software Tools and the Models they Build. 4.2. Calculation Methods. 4.3. Uncertainty and Variability. 4.4. How Monte Carlo Simulation Works. 4.5. Simulation Modelling. 5. Understanding and using the results of a risk analysis. 5.1. Writing a Risk Analysis Report. 5.2. Explaining a Model's Assumptions. 5.3. Graphical Presentation of a Model's Results. 5.4. Statistical Methods of Analysing Results. Part 2: Introduction. 6. Probability mathematics and simulation. 6.1. Probability Distribution Equations. 6.2. The Definition of "Probability". 6.3. Probability Rules. 6.4. Statistical Measures. 7. Building and running a model. 7.1. Model Design and Scope. 7.2. Building Models that are Easy to Check and Modify. 7.3. Building Models that are Efficient. 7.4. Most Common Modelling Errors. 8. Some basic random processes. 8.1. Introduction. 8.2. The Binomial Process. 8.3. The Poisson Process. 8.4. The Hypergeometric Process. 8.5. Central Limit Theorem. 8.6. Renewal Processes. 8.7. Mixture Distributions. 8.8. Martingales. 8.9. Miscellaneous Example. 9. Data and statistics. 9.1. Classical Statistics. 9.2. Bayesian Inference. 9.3. The Bootstrap. 9.4. Maximum Entropy Principle. 9.5. Which Technique Should You Use? 9.6. Adding uncertainty in Simple Linear Least-Squares Regression Analysis. 10. Fitting distributions to data. 10.1. Analysing the Properties of the Observed Data. 10.2. Fitting a Non-Parametric Distribution to the Observed Data. 10.3. Fitting a First-Order Parametric Distribution to Observed Data. 10.4. Fitting a Second-Order Parametric Distribution to Observed Data. 11. Sums of random variables. 11.1. The Basic Problem. 11.2. Aggregate Distributions. 12. Forecasting with uncertainty. 12.1. The Properties of a Time Series Forecast. 12.2. Common Financial Time Series Models. 12.3. Autoregressive Models. 12.4. Markov Chain Models. 12.5. Birth and Death Models. 12.6. Time Series Projection of Events Occurring Randomly in Time. 12.7. Time Series Models with Leading Indicators. 12.8. Comparing Forecasting Fits for Different Models. 12.9. Long-Term Forecasting. 13. Modelling correlation and dependencies. 13.1. Introduction. 13.2. Rank Order Correlation. 13.3. Copulas. 13.4. The Envelope Method. 13.5. Multiple Correlation Using a Look-Up Table. 14. Eliciting from expert opinion. 14.1. Introduction. 14.2. Sources of Error in Subjective Estimation. 14.3. Modelling Techniques. 14.4. Calibrating Subject Matter Experts. 14.5. Conducting a Brainstorming Session. 14.6. Conducting the Interview. 15. Testing and modelling causal relationships. 15.1. Campylobacter Example. 15.2. Types of Model to Analyse Data. 15.3. From Risk Factors to Causes. 15.4. Evaluating Evidence. 15.5. The Limits of Causal Arguments. 15.6. An Example of a Qualitative Causal Analysis. 15.7. Is Causal Analysis Essential? 16. Optimisation in risk analysis. 16.1. Introduction. 16.2. Optimisation Methods. 16.3. Risk Analysis Modelling and Optimisation. 16.4. Working Example: Optimal Allocation of Mineral Pots. 17. Checking and validating a model. 17.1. Spreadsheet Model Errors. 17.2. Checking Model Behaviour. 17.3. Comparing Predictions Against Reality. 18. Discounted cashflow modelling. 18.1. Useful Time Series Models of Sales and Market Size. 18.2. Summing Random Variables. 18.3. Summing Variable Margins on Variable Revenues. 18.4. Financial Measures in Risk Analysis. 19. Project risk analysis. 19.1. Cost Risk Analysis. 19.2. Schedule Risk Analysis. 19.3. Portfolios of risks. 19.4. Cascading Risks. 20. Insurance and finance risk analysis modelling. 20.1. Operational Risk Modelling. 20.2. Credit Risk. 20.3. Credit Ratings and Markov Chain Models. 20.4. Other Areas of Financial Risk. 20.5. Measures of Risk. 20.6. Term Life Insurance. 20.7. Accident Insurance. 20.8. Modelling a Correlated Insurance Portfolio. 20.9. Modelling Extremes. 20.10. Premium Calculations. 21. Microbial food safety risk assessment. 21.1. Growth and Attenuation Models. 21.2. Dose-Response Models. 21.3. Is Monte Carlo Simulation the Right Approach? 21.4. Some Model Simplifications. 22. Animal import risk assessment. 22.1. Testing for an Infected Animal. 22.2. Estimating True Prevalence in a Population. 22.3. Importing Problems. 22.4. Confidence of Detecting an Infected Group. 22.5. Miscellaneous Animal Health and Food Safety Problems. I. Guide for lecturers. II. About ModelRisk. III. A compendium of distributions. III.1. Discrete and Continuous Distributions. III.2. Bounded and Unbounded Distributions. III.3. Parametric and Non-Parametric Distributions. III.4. Univariate and Multivariate Distributions. III.5. Lists of Applications and the Most Useful Distributions. III.6. How to Read Probability Distribution Equations. III.7. The Distributions. III.8. Introduction to Creating Your Own Distributions. III.9. Approximation of One Distribution with Another. III.10. Recursive Formulae for Discrete Distributions. III.11. A Visual Observation On The Behaviour Of Distributions. IV. Further reading. V. Vose Consulting. References. Index.

Financial Risk Tolerance and Additional Factors That Affect Risk Taking in Everyday Money Matters

Abstract: The purpose of this research was to extend the investigative line of inquiry, as initiated by Carducci and Wong (1998), regarding risk taking in everyday money matters by examining demographic, socioeconomic, and attitudinal characteristics that may be used either individually or in combination as determinants of financial risk tolerance. Discriminant analysis results indicated that risk tolerance was associated with being male, older, married, professionally employed with higher incomes, more education, more financial knowledge, and increased economic expectations. Findings suggest that the achievement of financial success can be explained, at least in part, by a combination of someone's personality characteristics and socioeconomic background.

Theory of financial risks : from statistical physics to risk management

Abstract: 1. Probability theory: basic notions 2. Statistics of real prices 3. Extreme risks and optimal portfolios 4. Futures and options: fundamental concepts 5. Options: some more specific problems Glossary.

Theory of financial risk and derivative pricing

Abstract: Risk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets Summarising theoretical developments in the field, this 2003 second edition has been substantially expanded Additional chapters now cover stochastic processes, Monte-Carlo methods, Black-Scholes theory, the theory of the yield curve, and Minority Game There are discussions on aspects of data analysis, financial products, non-linear correlations, and herding, feedback and agent based models This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies

Liquidity and Risk Management

Abstract: Firms and financial institutions are best viewed as ongoing entities, whose project completion may require renewed injections of liquidity. This paper proposes a contract-theoretic framework integrating three dimensions of corporate financing and prudential regulation: (a) liquidity management, (b) risk management, and (c) capital structure. It concludes with a preliminary assessment of recent regulatory approaches to the treatment of market risk.

Predicting the Financial Vulnerability of Charitable Organizations

Abstract: This article describes a model that can be used to predict which nonprofit organizations are vulnerable to financial problems. The model is based on financial indicators developed by Tuckman and Chang (1991), adapts methodologies that have been developed in the for-profit sector to predict financial vulnerability, and was empirically tested using a multiyear Internal Revenue Service database provided by the National Center for Charitable Statistics. Both internal and external stakeholders can use the model when making allocation decisions during the strategic planning process and in evaluating financial risk.

Asset Allocation in a Downside Risk Framework

Abstract: Executive Summary. The traditional Markowitz portfolio optimization has two serious drawbacks. First, mean-variance portfolio optimization is inadequate when asset returns are skewed. Second, inves...

The Cost of Equity in Emerging Markets: A Downside Risk Approach

Abstract: Every company evaluating an investment project or an acquisition in an emerging market must not only estimate future cash flows but also an appropriate discount rate. Although not free from controversy, the cost of equity in developed markets is typically estimated with the CAPM. In emerging markets, however, betas and stock returns seem to be unrelated. This article argues that total risk, idiosyncratic risk, and some measures of downside risk are significantly related to emerging-mark et stock returns, and proposes to estimate costs of equity in these markets based on the semideviation with respect to the mean, a well-known measure of downside risk.

Credit Risk Assessment Using Statistical and MachineLearning: Basic Methodology and Risk Modeling Applications

Abstract: Risk assessment of financial intermediaries is an area of renewed interest due to the financial crises of the 1980's and 90's. An accurate estimation of risk, and its use in corporate or global financial risk models, could be translated into a more efficient use of resources. One important ingredient to accomplish this goal is to find accurate predictors of individual risk in the credit portfolios of institutions. In this context we make a comparative analysis of different statistical and machine learning modeling methods of classification on a mortgage loan data set with the motivation to understand their limitations and potential. We introduced a specific modeling methodology based on the study of error curves. Using state-of-the-art modeling techniques we built more than 9,000 models as part of the study. The results show that CART decision-tree models provide the best estimation for default with an average 8.31% error rate for a training sample of 2,000 records. As a result of the error curve analysis for this model we conclude that if more data were available, approximately 22,000 records, a potential 7.32% error rate could be achieved. Neural Networks provided the second best results with an average error of 11.00%. The K-Nearest Neighbor algorithm had an average error rate of 14.95%. These results outperformed the standard Probit algorithm which attained an average error rate of 15.13%. Finally we discuss the possibilities to use this type of accurate predictive model as ingredients of institutional and global risk models.

Foreign Direct Investment: Good Cholesterol?

Abstract: This paper studies the proposition that capital inflows tend to take the form of FDI -i.e., the share of FDI in total liabilities tends to be higher- in countries that are safer, more promising and with better institutions and policies. It finds that this view is patently wrong since it stands the historical record on its head. It then uses alternative theories to make sense of the facts. It begins by studying the determinants of the size and composition of the flows of private capital across countries. It finds that while capital flows tend to go to countries that are safer and have better institutions and financial markets, the share of FDI in total flows is not an indication of good health. On the contrary, countries that are riskier, less financially developed and have weaker institutions tend to attract less capital but more of it in the form of FDI. Hence, interpreting the rising share of FDI as a sign of good health is unwarranted. This is even more so, given that FDI's recent rise has taken place while total private capital inflows have fallen.

Microfinance, risk management, and poverty

Abstract: The study presented in this report addresses the question of whether microfinance can reduce poverty. It seeks to improve understanding of the impact of microfinance services on selected non-income dimensions of poverty and emphasizes the role of assets in reducing vulnerability. The study focuses on clients from selected microfinance institutions (MFIs) in Bangladesh, Bolivia, the Philippines and Uganda. The purpose of the study is to improve understanding of the impact of microfinance services on selected non-income dimensions of poverty, specifically those related to risk, vulnerability, and assets. The study emphasizes the role of financial, physical, human, and social assets in reducing vulnerability by helping individuals and households protect against risks ahead of time and manage economic losses afterwards.

Sending the Herd Off the Cliff Edge: The Disturbing Interaction Between Herding and Market‐Sensitive Risk Management Practices

Abstract: In the international financial arena, G7 policymakers chant three things: more market‐sensitive risk management, stronger prudential standards, and improved transparency. The message is that we do not need a new world order, but we can improve the workings of the existing one. While many believe this is an inadequate response to the financial crises of the last two decades, few argue against risk management, prudence, and transparency. Perhaps we should, especially with regards to market‐sensitive risk management and transparency. The underlying idea behind this holy trinity is that it better equips markets to reward good behavior and penalize the bad, across governments and market players. However, while the market is discerning in the long run, there is now compelling evidence that in the short run, market participants find it hard to distinguish between the good and the unsustainable; they herd; and contagion is common.

Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management

Abstract: Extreme value theory (EVT) holds promise for advancing the assessment and management of extreme financial risks. Recent literature suggests that the application of EVT generally results in more precise estimates of extreme quantiles and tail probabilities of financial asset returns. This article assesses EVT from the perspective of financial risk management. The authors believe that the recent optimism regarding EVT may be appropriate but exaggerated, and that much of its potential remains latent. They support their claim by describing various pitfalls associated with the current use of EVT techniques, and illustrate how these can be avoided. In conclusion, the article defines several specific research directions that may further the practical and effective application of EVT to risk management.

Evaluating credit risk models

Abstract: Over the past decade, commercial banks have devoted many resources to developing internal models to better quantify their financial risks and assign economic capital. These eAorts have been recognized and encouraged by bank regulators. Recently, banks have extended these eAorts into the field of credit risk modeling. However, an important question for both banks and their regulators is evaluating the accuracy of a model’s forecasts of credit losses, especially given the small number of available forecasts due to their typically long planning horizons. Using a panel data approach, we propose evaluation methods for credit risk models based on cross-sectional simulation. Specifically, models are evaluated not only on their forecasts over time, but also on their forecasts at a given point in time for simulated credit portfolios. Once the forecasts corresponding to these portfolios are generated, they can be evaluated using various statistical methods. ” 2000 Elsevier Science B.V. All rights reserved.

A critique on the theory of financial intermediation

Abstract: This comment discusses the review by Franklin Allen and Anthony Santomero of the theory of financial intermediation in the 20th anniversary special issue of the Journal of Banking and Finance. We do not fully agree with their view that risk management is only of recent importance to the financial industry and with putting central the concept of participation costs. We suggest how the theory of financial intermediation might be developed further in order to understand present-day phenomena in the financial services sector.

Managing the risk of performance based rates

Abstract: A profound consequence of deregulation is the emergence of performance based rates (PBRs). PBRs are contracts that penalize and/or reward a utility based on system performance. These contracts can be based on average system reliability, or can be based on individual customer reliability. In either case, utilities are exposed to financial risk due to the uncertainty of system reliability. This paper presents a method of assessing the uncertainty of system reliability and discusses how to use this information to manage PBR risk. This method can be used to negotiate a fair PBR, to compute the expected financial impact of a PBR, and to make design decisions that maximize profits while minimizing risk.

Risk management practices of German firms

Abstract: Identifies some gaps in corporate risk management research and presents a study of risk management practices in large, non‐financial German firms. Compares the perceived relevance of different types of risk with the intensity of their management and reports that no respondents admitted major difficulty in developing a risk management system. Finds that firm survival is rated as the top goal of risk management, that respondents are closer to risk‐neutral than risk‐averse for financial risks, that around half centralize treasury management and 88 per cent use derivatives. Ranks the types of derivatives used and the importance of associated problems; shows how foreign exchange risk, US $ exposure and interest rate risk are managed; and assesses attitudes towards foreign exchange and interest rate risk management. Considers consistency with other research and calls for more.

A survey into the use of derivatives by large non‐financial firms operating in Belgium

Abstract: Empirical evidence on the use of derivatives for risk management on the European continent is virtually non-existent. To fill this gap, our survey documents the usage of derivatives by non-financial large firms operating in Belgium. This paper provides descriptive evidence with respect to several questions that are raised in the literature. Why do firms hedge? Which financial risks are being managed? How widespread is the use of derivatives? Which derivatives are used for which purposes? How is a risk management policy implemented? How are performance measurement and reporting structured?

Corporate Risk around the World

Abstract: Corporate financing patterns around the world reflect countries' institutional environments. Weaknesses in the corporate sector have increasingly been cited as important factors in financial crises in both emerging markets and industrial countries. Analysts have pointed to weak corporate performance and risky financing patterns as major causes of the East Asian financial crisis. And some have argued that company balance sheet problems may also have played a role, independent of macroeconomic or other weaknesses, including poor corporate sector performance. But little is known about the empirical importance of firm financing choices in predicting and explaining financial instability. Firm financing patterns have long been studied by the corporate finance literature. Financing patterns have traditionally been analyzed in the Modigliani-Miller framework, expanded to incorporate taxes and bankruptcy costs. More recently, asymmetric information issues have drawn attention to agency costs and their impact on firm financing choices. There is also an important literature relating financing patterns to firm performance and governance. Several recent studies have focused on identifying systematic cross-country differences in firm financing patterns - and the effects of these differences on financial sector development and economic growth. They have also examined the causes of different financing patterns, particularly countries' legal and institutional environments. The literature has devoted little attention to corporate sector risk characteristics, however, aside from leverage and debt maturity considerations. Even these measures have been the subject of few empirical investigations, mainly because of a paucity of data on corporate sectors around the world. Building on data that have recently become available, Claessens, Djankov, and Nenova try to fill this gap in the literature and shed light on the risk characteristics of corporate sectors around the world. They investigate how corporate sectors' financial and operating structures relate to the institutional environment in which they operate, using data for more than 11,000 firms in 46 countries. They show that: - The origins of a country's laws, the strength of its equity and creditor rights, and the nature of its financial system can account for the degree of corporate risk-taking. - In particular, corporations in common law countries and market-based financial systems have less risky financing patterns. - Stronger protection of equity and creditor rights is also associated with less financial risk. This paper - a product of the Financial Sector Strategy and Policy Group, Financial Sector Vice Presidency - is part of a larger effort in the Bank to study the determinants of the riskiness of countries' corporate and financial systems.

Risk, trust and welfare

Abstract: List of Tables Preface Notes on the Contributors Risk and Welfare P.Taylor-Gooby PART I: MOTIVES, POLICY AND BEHAVIOUR From Knight to Knave: Public Policy and Endogenous Motivation J.LeGrand Motivation and Human Behaviour B.S.Frey Managing Risk by Controlling Behaviour: Social Security Administration and the Erosion of Welfare Citizenship H.Dean PART II: RESPONSES TO RISK The Rationality Mistake: New Labour's Communitarianism and 'Supporting Families' A.Barlow & S.Duncan with R.Edwards Coping with Risk in a Flexible Labour Market J.Ford Public Understanding of Financial Risk: The Challenge to Regulation P.Lunt & J.Blundell Insights into the Uncertain World of the Consumer: Reflections on the Risks of Non-Prescription Medicines P.R.Ward, P.Bissell & P.R.Noyce Choices in Owner-Occupation M.Munro Risk and the Need for Long-Term Care G.Parker References Index

Corporate risk around the world

Abstract: Weaknesses in the corporate sector have increasingly been cited as important factors in financial crises in both emerging markets and industrial countries. Analysts have pointed to weak corporate performance and risky financing patterns as major causes of the East Asian financial crisis. And some have argued that company balance sheet problems may also have played a role, independent of macroeconomic or other weaknesses, including poor corporate sector performance. But little is known about the empirical importance of firm financing choices in predicting and explaining financial instability. Firm financing patterns have long been studied by the corporate finance literature. Financing patterns have traditionally been analyzed in the Modigliani-Miller framework, expanded to incorporate taxes and bankruptcy costs. More recently, asymmetric information issues have drawn attention to agency costs and their impact on firm financing choices. There is also an important literature relating financing patterns to firm performance and governance. Several recent studies have focused on identifying systematic cross-country differences in firm financing patterns - and the effects of these differences on financial sector development and economic growth. They have also examined the causes of different financing patterns, particularly countries'legal and institutional environments. The literature has devoted little attention to corporate sector risk characteristics, however, aside from leverage and debt maturity considerations. Even these measures have been the subject of few empirical investigations, mainly because of a paucity of data on corporate sectors around the world. Building on data that have recently become available, the authors try to fill this gap in the literature and shed light on the risk characteristics of corporate sectors around the world. They investigate how corporate sectors'financial and operating structures relate to the institutional environment in which they operate, using data for more than 11,000 firms in 46 countries. They show that: 1) the origins of a country's laws, the strength of its equity and creditor rights, and the nature of its financial system can account for the degree of corporate risk-taking. 2) In particular, corporations in common law countries and market-based financial systems have less risky financing patterns. 3) Stronger protection of equity and creditor rights is also associated with less financial risk.

Techniques of Financial Analysis; A Guide to Value Creation

Abstract: A systems context for financial management managing operating funds assessment of business performance projection of financial requirements dynamics and growth of the business system cash flows an dthe time value of money nanalysis of investment decisions cost of capital and business decisions analysis of financial choices valuaiton and business performance managing for shareholder value. Appendices: financial analysis using financial genome glossary of key terms and concepts financial informaiton and on-line sources basic inflation concepts some issues in multinational financial analysis solutions to self-study exercises and problems, with questions for discussion.

Business Risk Management in Government: Pitfalls and Possibilities

Abstract: Business risk management, taking a variety of forms, has been a growth point in corporate management in recent years. That change in emphasis is said to stem from responses to high-profile disasters like Bhopal and Exxon Valdez, increasing legal and regulatory pressure on risk management and a search for new approaches to formulating corporate strategy. Risk management of many types is well-established in the public sector, in domains as various as the management of offenders, health-care systems, tax audits and the operations of weapons systems. Risk management has always been central to strategic planning in defence, internal security and foreign affairs. But risk management systems in government tend to be policy-domain-specific. Most are directed towards policy rather than 'business' risks and some are focused on risks to third parties rather than risks to producer organisations. Accordingly, if the various private-sector business risk approaches raise issues for the design of institutional routines in government, the issue concerns how far a generic approach to factoring risk into decision-making at senior managerial level is appropriate across government. In principle a case could be made for a more generic approach that involved the integration of business risk management techniques into management control and organisational strategy in the public sector. Many of the environmental and technological changes causing risk management to assume greater importance in business strategy (like increased litigation risks, risks of IT failure, financial risks arising from global markets) affect governments as well as business. There is evidence that the 1999 Turnbull ICAEW report on internal control has influenced public as well as private sector developments. Inquiries into government decision making often produce examples of risks being taken with public money or the quality of public services without adequate strategic consideration at senior management level or careful contingency planning. Yet public servants are almost equally often berated for being too risk-averse and not sufficiently entrepreneurial. A business risk management approach offers the possibility for striking a judicious and systematically argued balance between risk and opportunity in the form of the contradictory pressures for greater entrepreneurialism on the one hand and limitation of downside risks on the other that are experienced by contemporary public sector managers.

Recognition versus disclosure : an investigation of the impact on equity risk using UK operating lease disclosures

Abstract: This study examines the equivalency of accounting recognition versus disclosure. OLS regression analysis is used to determine whether there is an association between equity risk and an adjustment to financial risk for off-balance sheet operating leases. Two methods of adjustment are considered: constructive capitalisation and a simple factor method. The observation of a reliably positive association suggests that UK investors/analysts view operating leases from a property rights perspective rather than an ownership perspective. This supports the argument for recognition of all lease rights and obligations ‘on-balance sheet’, as proposed in the recent G4+1 discussion paper ASB (1999).

Mutual fund tournament: risk taking incentives induced by ranking objectives

Abstract: There is now extensive empirical evidence showing that fund managers have relative performance objectives and adapt their investment strategy in the last part of the calendar year to their performance in the early part of the year. However, emphasis was put on returns in excess of some exogenous benchmark return.In this paper, we investigate whether fund managers have ranking objectives (as in a tournament).First, in a two-period model, we analyze the game played by two risk-neutral fund managers with ranking objectives.We derive conditions on the set of possible strategies under which the aggregate amount of risk undertaken in the late period is larger than in the first period.In the second part of the paper, we provide evidence that (i) funds have risk incentives generated by ranking objectives, (ii) risk induced by ranking objectives is mainly idiosyncratic, and (iii) risk incentives generated by ranking objectives are stronger for funds ranked in the top decile after the first part of the year.

The Effects of Liberalization on Market and Currency Risk in the European Union

Abstract: This paper investigates the effects of liberalization on the pricing of market and currency risk for a number of financial markets in the European Union (EU). An International Asset Pricing Model with a multivariate GARCH-in-Mean specification and time-varying prices of risk is used for the four markets with the largest market capitalization in the EU. Only one price of market risk exists and international investors are rewarded for their exposure to currency risk. The evidence shows that all prices of risk are time-varying and have been decreasing during the process of liberalization. There is also evidence that financial markets react to periods of uncertainty in the process toward the completion of liberalization. In addition, the operation of the European Monetary System has generated lower covariances. As a consequence, total risk premia have declined in the last decade.

New Approaches to Multi-pillar Pension Systems: What in the World is Going On?

Abstract: The last five years have been a period of blossoming innovation in pension reform. Macroeconomic forces have been driving changes, as the largely unfunded debt of payas-you-go systems are challenging countries with very diverse historical backgrounds to find solutions to the financing the aging population of coming decades. Demographic changes and behavioral responses are also key factors, however, as countries are trying to shift some of the financial risk of the aging population away from future generations to the generation affected, in order to improve incentives to workers and employers. The traditional one pillar, defined benefit schemes are being retooled to meet these challenges. Two major trends in pension reform are emerging. First, countries are modifying PAYGO systems to strengthen the links between contributions and benefits, increase fullbenefit pension ages and phase out seniority arrangements and special privileges. The NDC is the newest tool to achieve this goal, and it has been introduced in both Western Europe and transition economies. Second, privately managed financial account systems are growing. Third, countries with large pension debts are finding it difficult to finance a transition to more funding. These countries are not aspiring for full funding, but instead are retaining PAYGO systems indefinitely. This has the advantage over recognition bonds of not locking in current entitlements. Emerging issues in the reforms include: how to hold down the administrative costs of privately managed financial account systems, how ex ante to assign risks and what low-income countries should do.