10610.Pension Fund Risk Management Financial and Actuarial Modeling (Chapman & HallCrc Finance Series)

Edited by

Marco MicocciGreg N. Gregoriou

Giovanni Batista Masala

CHAPMAN & HALL/CRC FINANCE SERIES

Pension Fund Risk

ManagementFinancial and Actuarial Modeling

2010 by Taylor and Francis Group, LLC

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Library of Congress Cataloging-in-Publication Data

Pension fund risk management : financial and actuarial modeling / editors, Marco Micocci, Greg N. Gregoriou, and Giovanni Batista Masala.

p. cm. -- (Chapman & hall/crc finance series ; 5)Includes bibliographical references and index.ISBN-13: 978-1-4398-1752-0 (alk. paper)ISBN-10: 1-4398-1752-9 (alk. paper)1. Pension trusts. 2. Risk management. I. Micocci, Marco. II. Gregoriou, Greg N.,

1956- III. Masala, Giovanni Batista. IV. Title. V. Series.

HD7105.4.P464 2010658.3253--dc22 2009030223

Visit the Taylor & Francis Web site athttp://www.taylorandfrancis.comand the CRC Press Web site athttp://www.crcpress.com


vContents

Preface, ix

Editors, xvii

Contributor Bios, xix

Contributors, xxxiii

I PART Financial Risk Management

1 CHAPTER Quantifying Investment Risk in Pension Funds 003SHANE FRANCIS WHELAN

2 CHAPTER Investment Decision in Defi ned Contribution Pension Schemes Incorporating Incentive Mechanism 039BILL SHIH-CHIEH CHANG AND EVAN YA-WEN HWANG

3 CHAPTER Performance and Risk Measurement for Pension Funds 071AUKE PLANTINGA

4 CHAPTER Pension Funds under Inflation Risk 085AIHUA ZHANG


vi Contents

5 CHAPTER MeanVariance Management in Stochastic Aggregated Pension Funds with Nonconstant Interest Rate 103RICARDO JOSA FOMBELLIDA

6 CHAPTER Dynamic Asset and Liability Management 129RICARDO MATOS CHAIM

7 CHAPTER Pension Fund Asset Allocation under Uncertainty 157WILMA DE GROOT AND LAURENS SWINKELS

8 CHAPTER Different Stakeholders Risks in DB Pension Funds 167THEO KOCKEN AND ANNE DE KREUK

9 CHAPTER Financial Risk in Pension Funds: Application of Value at Risk Methodology 185MARCIN FEDOR

10 CHAPTER Pension Scheme Asset Allocation with Taxation Arbitrage, Risk Sharing, and Default Insurance 211CHARLES SUTCLIFFE

II PART Technical Risk Management

11 CHAPTER Longevity Risk and Private Pensions 237PABLO ANTOLIN

12 CHAPTER Actuarial Funding of Dismissal and Resignation Risks 267WERNER HRLIMANN


Contents vii

13 CHAPTER Retirement Decision: Current Infl uences on the Timing of Retirement among Older Workers 287GAOBO PANG, MARK J. WARSHAWSKY, AND BEN WEITZER

14 CHAPTER Insuring Defi ned Benefi t Plans in Germany 315FERDINAND MAGER AND CHRISTIAN SCHMIEDER

15 CHAPTER The Securitization of Longevity Risk in Pension Schemes: The Case of Italy 331SUSANNA LEVANTESI, MASSIMILIANO MENZIETTI, AND TIZIANA TORRI

III PART Regulation and Solvency Topics

16 CHAPTER Corporate Risk Management and Pension Asset Allocation 365YONG LI

17 CHAPTER Competition among Pressure Groups over the Determination of U.K. Pension Fund Accounting Rules 389PAUL JOHN MARCEL KLUMPES AND STUART MANSON

18 CHAPTER Improving the Equity, Transparency, and Solvency of Pay-as-You-Go Pension Systems: NDCs, the AB, and ABMs 419CARLOS VIDAL-MELI, MARA DEL CARMEN BOADO-PENAS, AND OLE SETTERGREN

19 CHAPTER Risk-Based Supervision of Pension Funds in the Netherlands 473DIRK BROEDERS AND MARC PRPPER


viii Contents

20 CHAPTER Policy Considerations for Hedging Risks in Mandatory Defi ned Contribution Pensions through Better Default Options 509GREGORIO IMPAVIDO

21 CHAPTER Pension Risk and Household Saving over the Life Cycle 549DAVID A. LOVE AND PAUL A. SMITH

IV PART International Experience in Pension Fund Risk Management

22 CHAPTER Public and Private DC Pension Schemes, Termination Indemnities, and Optimal Funding of Pension System in Italy 581MARCO MICOCCI, GIOVANNI B. MASALA, AND GIUSEPPINA CANNAS

23 CHAPTER Effi ciency Analysis in the Spanish Pension Funds Industry: A Frontier Approach 597CARMEN-PILAR MART-BALLESTER AND DIEGO PRIOR-JIMNEZ

24 CHAPTER Pension Funds under Investment Constraints: An Assessment of the Opportunity Cost to the Greek Social Security System 637NIKOLAOS T. MILONAS, GEORGE A. PAPACHRISTOU, AND THEODORE A. ROUPAS

25 CHAPTER Pension Fund Defi cits and Stock Market Effi ciency: Evidence from the United Kingdom 659WEIXI LIU AND IAN TONKS

26 CHAPTER Return-Based Style Analysis Applied to Spanish Balanced Pension Plans 689LAURA ANDREU, CRISTINA ORTIZ, JOS LUIS SARTO, AND LUIS VICENTE

INDEX, 707


ix

Preface

INTEGRATED RISK MANAGEMENT IN PENSION FUNDS

Marco Micocci, Greg N. Gregoriou, and Giovanni B. Masala

Th e world of pension funds is facing a period of extreme changes. Countries around t he world have ex perienced u nexpected i ncreases i n l ife ex pec-tancy and fertility rates, changing accounting rules, contribution reduc-tions, low fi nancial returns, and abnormal volatility of markets. All these elements have led to a fall in funded systems and to an increase in the dependency ratios in many countries. U.K. and U.S. pension funds, which have traditionally had relatively high equity allocations, have been hit hard. Many public pay-as-you-go (PAYGO) systems in Europe are reduc-ing t heir generosity w ith n ew c alculation r ules po inting t oward t he reduction of the substitution ratios of workers. Europe is moving toward a risk-based approach also for the regulation and the control of the techni-cal risk of funded pension schemes.

Risk management is becoming highly complex both in public pension funds and in private pension plans, requiring the expertise of diff erent spe-cialists who are not frequently disposable in the professional market. Th e world is quite rich with skilled investment managers but their comprehen-sion of the demographic and of the actuarial face of pension risk is oft en inadequate. On the other hand, you have many specialized actuaries who are able to perform very sophisticated calculations and forecasts of pension liabilities but who are not able to fully understand the coexistence (or inte-gration) of fi nancial and actuarial risks. Also, the international accounting standards introduce new actuarial and fi nancial elements in t he ba lance sheet of the fi rms that may aff ect the corporate dividend and its investment


x Preface

policy. In other words, little is being said about the integration of actuarial and fi nancial risks in the risk management of pension funds.

We believe the chapters in this book highlight and shed new l ight on the current state of pension fund risk management and provide the reader new technical tools to face pension risk from an integrated point of view. Th e exclusive new research for this book can assist pension fund execu-tives, r isk m anagement d epartments, c onsultancy fi rms, a nd ac ademic researchers to hopefully get a clearer picture of the integration of risks in the pension world. Th e chapters in this book are written by well-known academics a nd p rofessionals w orldwide wh o ha ve p ublished n umerous journal articles and book chapters. Th e book is divided into four partsPart I: Financial Risk Management; Part II: Technical Risk Management; Part I II: Reg ulation a nd S olvency T opics; a nd P art I V: I nternational Experience in Pension Fund Risk Management.

In P art I , C hapter 1 f ocuses o n t he co rrect m easurement o f r isk i n pension funds. Th e author formalizes an intuitive concept of investment risk i n p roviding f or pens ions, t aking i t a s a m easure o f t he fi nancial impact when the actual investment experience diff ers from the expected. Investment risk can be explicitly measured and, through a series of case studies, the author estimates the investment risk associated with diff er-ent investment strategies in diff erent markets over the twentieth century. He shows t hat w ithin a b road r ange, t he relative i nvestment r isk a sso-ciated w ith d iff erent st rategies i s n ot pa rticularly sens itive t o h ow t he pension objective is framed. Th e investment risk associated with equity investment can be o f the same order of magnitude as bond investment if the bond duration mismatches those of the targeted pension. He sug-gests that failure to explicitly measure investment risk entails that pen-sion portfolios might not be optimally structured, holding the possibility that i nvestment r isks could be r educed w ithout reducing t he ex pected pension proceeds.

In Chapter 2 , t he authors scrutinize t he f und dy namics under a per -formance-oriented arrangement (i.e., bonus fees a nd downside pena lty), whereby a st ochastic co ntrol i s f ormulated t o f urther cha racterize t he defi ned contribution (DC) pension schemes. A fi ve-fund separation theo-rem i s der ived to cha racterize i ts optimal st rategy. W hen per formance-oriented arrangement is taken into account, the fund managers tend to increase the holdings in risky assets. Hence, an incentive program has to be carefully implemented in order to balance the risk and the reward in DC pension fund management.


Preface xi

Chapter 3 p roposes a n a ttribution m odel f or m onitoring t he per for-mance a nd t he r isk o f a defi ned benefi t (DB) pens ion f und. Th e model is based on a l iability benchmark t hat refl ects t he r isk a nd return cha r-acteristics of the liabilities. As a result, the attribution model focuses the attention of the portfolio managers on creating a portfolio that replicates liabilities. Th e attribution model a llocates d iff erences in return between the actual portfolio and the benchmark portfolio to decisions relative to the benchmark portfolio. In addition, the model decomposes risks accord-ing to the same structure by using a measure of downside risk.

Chapter 4 i nvestigates an optimal investment problem faced by a DC pension fund manager under infl ationary r isk. It is assumed that a r ep-resentative member of a DC pension plan contributes a fi xed share of his salary to the pension fund during the time horizon. Th e pension contribu-tions are invested continuously in a r isk-free bond, an index bond, and a stock. Th e objective is to maximize the expected utility of terminal value of the pension fund. By solving this investment problem, the author pres-ents a way to deal with the optimization problem, in case of an (positive) endowment (or contribution), using the martingale method.

Chapter 5 deals with the study of a pension plan from the point of view of dy namic o ptimization. Th is sub ject i s c urrently w idely d iscussed i n the literature. Th e optimal management of an aggregated type of DB pen-sion fund, which is common in the employment system, is analyzed by a meanvariance portfolio selection problem. Th e main novelty is that the risk-free market interest rate is a t ime-dependent function and the ben-efi ts are stochastic.

In C hapter 6 , t he author h ighlights t he fac t t hat a pens ion f und i s a complex system. Asset and l iability management (ALM) models of pen-sion f und p roblems i ncorporate, a mong o thers, st ochasticity, l iquidity control, population dynamics, and decision delays to better forecast and foresee solvency in t he long term. In order to model uncertainties or to enable multicriteria analyses, many methods are considered and analyzed to obtain a dynamic asset and liability management approach.

In Chapter 7, the authors investigate the optimal asset allocation of U.S. pension f unds b y t aking i nto acco unt t he f unds l iabilities. B esides t he traditional i nputs, such a s ex pected returns a nd t he covariance matrix, the uncertainty of expected returns plays a crucial role in creating robust portfolios t hat a re less sensitive to small changes in inputs. Th e authors illustrate this with an example of a pension fund that decides on investing in emerging market equities.


xii Preface

Chapter 8 explains that most pension funds already manage the diff er-ent risks they face, but usually from a single stakeholder pension fund perspective, typically expressed in, e.g., the risk of funding shortfall. Th e many d iff erent st akeholders i n pens ion f unds, such a s t he em ployees, retirees, and sponsors, all bear diff erent risks, but there is oft en hardly any insight in the objective market va lue of these r isks. In addition, there is usually no explicit compensation agreement for those who bear the risks. Th erefore, a technique that identifi es and values these stakeholders risks has many useful applications in pension fund management.

Chapter 9 focuses on value-at-risk (VaR). VaR has become a popular risk measure of fi nancial r isk and is a lso used for regulatory capital require-ment purposes in banking and insurance sectors. Th e VaR methodology has be en de veloped ma inly f or ba nks t o co ntrol t heir sh ort-term ma r-ket r isk. Although, VaR is a lready widespread in fi nancial industry, this method has yet to become a standard tool for pension funds. However, just as any other fi nancial institution, pension funds recognize the importance of measuring t heir fi nancial r isks. Th e a im of t his chapter i s to spec ify conditions u nder wh ich VaR co uld be a g ood m easure o f l ong-term market risk.

Chapter 10 examines the eff ects of taxation, risk sharing between the employer and employees, and default insurance on the asset allocation of DB pension schemes. Th ese three factors can have a powerful eff ect on the optimal asset allocation of a fund. Th e authors show that the three factors have the potential to create confl ict between the employer and the employ-ees, particularly when the employer is not subject to taxation.

In Part II, Chapter 11 is devoted to examining how uncertainty regard-ing f uture m ortality a nd l ife ex pectancy o utcomes, i .e., l ongevity r isk, aff ects employer-provided DB private pension plan liabilities. Th e author argues t hat to assess uncertainty a nd associated r isks adequately, a st o-chastic a pproach t o m odel m ortality a nd l ife ex pectancy i s p referable because it allows one to attach probabilities to diff erent forecasts. In this regard, t he cha pter p rovides t he r esults o f e stimating t he L eeCarter model for se veral OECD countries. Furthermore, i t conveys t he u ncer-tainty su rrounding f uture m ortality a nd l ife ex pectancy o utcomes b y means o f M onte-Carlo s imulations o f t he L eeCarter m odel. I n o rder to assess the impact of longevity risk on employer-provided DB pension plans, the author examines the diff erent approaches that private pension plans f ollow i n p ractice wh en i ncorporating l ongevity r isks i n t heir actuarial calculations.


Preface xiii

Chapter 12 analyzes the pension plan of a fi rm that off ers wage-based lump sum payments by death, retirement, or dismissal by the employer, but no payment is made by the employer when the employee resigns. An actu-arial risk model for funding severance payment liabilities is formulated and studied. Th e yearly aggregate lump sum payments are supposed to follow a classical collective model of risk theory with compound distributions. Th e fi nal wealth at an arbitrary time is described explicitly including formulas for the mean and the variance. Annual initial level premiums required for dismissal f unding a re de termined a nd u seful gamma approximations for confi dence intervals of the wealth are proposed. A specifi c numerical example illustrates the non-negligible probability of a bankruptcy in case the employee structure of a dismissal plan is not well balanced.

Chapter 13 starts from the fact that retirement is being remade owing to the confl uence of demographic, economic, and policy factors. Th e authors empirically i nvestigate ma jor i nfl uences on t he re tirement b ehavior of older U.S. workers f rom 1992 t hrough 2004 using survey data f rom t he Health and Retirement Study. Th eir analysis builds on the large empirical literature on retirement, in particular, by examining how market booms and busts aff ect the likelihood and timing of retirement, an issue that will be o f g rowing i mportance g iven t he o ngoing sh ift f rom t raditional DB pensions t o 4 01(k)s. Th ey co mprehensively m odel a ll ma jor so urces o f health i nsurance co verage a nd i dentify t heir va rying i mpacts, a nd a lso reveal the signifi cant policy-driven retirement diff erences across cohorts that are attributable to the changes in social security full-retirement age. Th ese f undamental r etirement cha nges n eed t o be t aken i nto acco unt when we design corporate and public retirement programs.

Chapter 14 deals w ith a st udy on occupational pension insurance for Germanya country where Pillar II pension schemes are (still) widely based on a book reserve system. Th e insurance of occupational pension schemes is prov ided for by t he P ensions-Sicherungs-Verein Versicherungsverein auf Gegenseitigkeit (PSVaG), which is the German counterpart to the U.S. PBGC. Th is study investigates potential adverse selection and moral haz-ard problems originating from the introduction of reduced premiums for funded pensions a nd a ssesses whether t he r isk-adjusted r isk premiums, as i ntroduced by t he U.K. Pension Protection Fund, c an be a m eans to mitigate these problems.

Chapter 1 5 de scribes t he l ongevity r isk sec uritization i n pens ion schemes, f ocusing ma inly o n l ongevity bo nds a nd su rvivor s waps. Th e authors analyze the evaluation of these mortality-linked securities in an


xiv Preface

incomplete market using a risk-neutral pricing approach. A Poisson LeeCarter model is adopted to represent the mortality trend. Th e chapter con-cludes with an empirical application on Italian annuity market data.

In Part III, Chapter 16 highlights t hat t he international t rend toward adopting a fair va lue a pproach t o pens ion acco unting ha s t ranspired the r isks i nvolved i n promises of DB pensions. Th e hunt i s on for ways to remove or l imit the employers r isk exposures to fi nancial statements volatility. Th is chapter examines the U.K. fi rms risk management of their pension f und asset a llocation over a per iod when t he new U.K. pension GAAP (FRS 17) became eff ective. Th e fi ndings suggest that fi rms manage their pension risk exposure in order to minimize cash contribution risks associated w ith t he ad option o f fair va luebased pens ion acco unting rules, consistent with a risk off setting explanation.

Chapter 17 develops and tests a theory of competition among pressure groups over political infl uence in the context of confl icting U.K. standards concerning the factors aff ecting the recent development of pension fund accountability rules. Th e chapter models both sources of pressure aff ect-ing the accountability relationship as well as how those factors combined to i nfl uence U.K. pens ion f und ma nagers d iscretion o ver t he ad option and retention of disclosure regulations. Th e author fi nds that auditors and pension management groups exerted most political pressure, which trans-lated to political infl uence during the extended adoption period. Th e fi nd-ings are mostly consistent with a capture or private interest perspective on pension accounting regulation.

Chapter 18 r eviews t hree u seful i nstrumentsnotional defi ned-con-tribution acco unts (N DCs), t he ac tuarial ba lance ( AB), a nd a utomatic balance mechanisms (ABMs)derived from actuarial analysis methodol-ogy that can be applied to the public management of PAYGO systems to improve t heir fa irness, t ransparency, a nd so lvency. Th e authors su ggest that these tools are not simply theoretical concepts but, in some countries, an already legislated response to the growing social demand for transpar-ency in the area of public fi nance management as well as the desire to set the pension system fi rmly on the road to long-term fi nancial solvency.

In Chapter 19, t he authors review t he r isk-based solvency regime for pension funds in the Netherlands. Th e supervision of pension funds aims to ensure that institutions are always able to meet their commitments to t he benefi ciaries. In addition, t he pension f und must be l egally sepa-rated from the employer off ering the pension arrangement. Furthermore, the ma rked-to-market va lue o f t he a ssets m ust be a t l east eq ual t o t he


Preface xv

marked-to-market value of the liabilities at all times (full funding prereq-uisite). Risk-based solvency requirements are intended as a buff er to absorb the r isks f rom u nexpected cha nges i n t he va lue of a ssets a nd l iabilities. Finally, a key element of the Dutch regulatory approach is the continuity analysis for assessing the pension funds solvency in the long run.

In Chapter 20, the author addresses the fact that the global fi nancial cri-sis of 2008 highlighted the importance of shielding pension participants from market volatility. Th is policy concern is of general relevance due to the global shift from DB to DC as main mechanisms for fi nancing retire-ment income. Policy options being debated in the aft ermath of the crisis include, but are not necessarily limited to, the following: (1) the introduc-tion o f l ifetime m inimum r eturn g uarantees, ( 2) t he r eview o f defa ult investment options, and (3) the outright reversal to PAYGO earningre-lated pensions. Th is chapter reviews the performance during the crisis of countries that a lready rely on mandatory DC plans. Th e author suggests that important welfare gains can be ach ieved by requiring the introduc-tion of l iability-driven default investment products based on a m odifi ed version of the target date funds commonly available in the retail industry for retirement wealth. Such products would reconnect the accumulation with the decumulation phase, improve the hedging of annuitization risk, but avoid the introduction of liabilities for plan managers.

In P art I V, C hapter 2 1 h ighlights t he D B pens ion f reezes i n la rge healthy fi rms such as Verizon and IBM, as well as terminations of plans in the struggling steel and airline industries that cannot be v iewed as risk-free from t he employees perspective. Th e authors de velop a n empirical dynamic programming framework to investigate household saving deci-sions in a s imple life cycle model with DB pensions subject to the risk of being f rozen. Th e model i ncorporates i mportant sources of u ncertainty facing households, including asset returns, employment, wages, and mor-tality, as well as pension freezes.

Chapter 22 is referred to as the Italian experience. In Italy, social secu-rity contributions of Italian employees fi nance a two-pillar system: public and p rivate pens ions t hat a re bo th c alculated i n a DC sch eme (funded for the private pension and unfunded for the public one). In addition to this, a la rge number of workers have also termination indemnities at the end of their active service. Th e authors aim to answer the following ques-tions. A re t he d iff erent fl ows of contributions coherent w ith t he a im of minimizing the pension risk of the workers? Given the actual percentages of contributions, is the asset allocation of private pension funds optimal?


xvi Preface

What percentages would optimize t he pens ion r isk ma nagement o f t he workers ( considering pu blic p ension, pr ivate p ension, a nd t ermination indemnities)?

Chapter 24 examines the Greek experience in limiting the opportunity of investments of pension funds in foreign assets. In fact, suff ering from ineffi cient funding, the current imbalance of the Greek social security sys-tem, to some extent, was the result of the restrictive investment constraints in the period 19582000 that directed reserves to low-yielding deposits with the Bank of Greece with little or no exposure to market yields or the stock market. As shown in the 43 year analysis, these investment restric-tions incurred a s ignifi cant economic opportunity loss both in terms of inferior returns as well as lower risks.

Chapter 25 examines the eff ect of a companys unfunded pension liabil-ities on its stock market valuation. Using a sample of UK FTSE350 fi rms with DB pension schemes, the authors fi nd that although unfunded pen-sion liabilities reduce the market value of the fi rm, the coeffi cient estimates indicate a less than one-for-one eff ect. Moreover, there is no evidence of signifi cantly negative subsequent abnormal returns for highly under-funded schemes. Th ese results suggest that shareholders do take into con-sideration the unfunded pension liabilities when valuing the fi rm, but do not fully incorporate all available information.

Chapter 26 f ocuses on t he selection of a n appropriate st yle model to explain the returns of Spanish ba lanced pension plans as well as on the analysis of the relevance of these strategic allocations on portfolio perfor-mance. Results suggest similar fi ndings than those obtained in previous studies, providing evidence t hat asset a llocations explains about 90% of portfolio r eturns o ver t ime, m ore t han 4 0% o f t he va riation o f r eturns among plans, and about 100% of total returns.

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xvii

Editors

Marco Micocci is a f ull professor of fi nancial mathematics and actuarial science in the Faculty of Economics, University of Cagliari, Italy. He has received deg rees i n eco nomics, ac tuarial st atistics, a nd t he fi nance of fi nancial i nstitutions. H is r esearch i nterests i nclude fi nancial a nd ac tu-arial risk management of pension funds and insurance companies, enter-prise risk management, and operational and reputational r isk va luation. He has published nearly 90 books, chapters of books, journal articles, and papers. He also works as a consultant actuary.

Greg N. Gregoriou has published 34 books, over 50 refereed publications in peer-reviewed journals, and 22 book chapters since his arrival at SUNY (Plattsburgh, New York) in August 2003. Professor Gregorious books have been published by John Wiley & Sons, McGraw-Hill, Elsevier Butterworth/Heinemann, T aylor & F rancis/Chapman-Hall/CRC P ress, P algrave-MacMillan, a nd R isk/Euromoney boo ks. H is a rticles ha ve a ppeared i n the Journal o f P ortfolio M anagement, t he Journal o f F utures M arkets, the European Journal of Operational Research, t he Annals of Operations Research, and Computers and O perations Re search. Professor Gregoriou is a coed itor a nd ed itorial boa rd member for t he Journal o f D erivatives and Hedge Funds, a s well a s a n ed itorial boa rd member for t he Journal of W ealth Man agement, t he Journal o f Ri sk M anagement i n F inancial Institutions, and the Brazilian Business Review. A na tive of Montreal, he received his joint PhD at the University of Quebec at Montreal, Quebec, Canada, in fi nance, which merges the resources of Montreals major uni-versities (McGill University, Concordia University, and cole des Hautes tudes C ommerciales, M ontreal). H is i nterests f ocus o n h edge f unds, funds of hedge funds, and managed futures. He is a lso a m ember of the Curriculum Committee of the Chartered Alternative Investment Analyst Association.


xviii Editors

Giovanni B. Ma sala i s a r esearcher in mathematical methods for econ-omy and fi nance at the Faculty of Economics, University of Cagliari, Italy. He received h is PhD i n pu re mathematics (diff erential geometry) at t he University o f M ulhouse, F rance. H is c urrent r esearch i nterest i ncludes mathematical risk modeling for fi nancial and ac tuarial applications. He attended n umerous i nternational c ongresses to le arn more a bout t hese topics. His results have been published in refereed national and interna-tional journals.


xix

Contributor Bios

Laura Andreu is a junior lecturer in fi nance at the Faculty of Economics and Business Studies, University of Zaragoza, Spain, where she received her degree in business administration and was awarded the Social Science Award for Graduate Students. She is currently working on her PhD on the subject of Spanish pension funds. She has published some papers both in national and international journals and her research interests are focused on portfolio management.

Pablo Antolin is a principal economist at the Private Pension Unit of the OECD Financial Aff airs Division. He is currently managing three projects: (1) a project on annuities and the payout phase, (2) a project on the impact of longevity r isk and other r isks (e.g., investment, infl ation, and interest rate) on retirement income and annuity products, and (3) a j oint project with t he World Ba nk, Washington, Di strict o f C olumbia, o n co mparing the fi nancial per formance of private pens ion f unds ac ross countries. I n the past, he has worked on the impact of aging populations on the econ-omy and on public fi nances. He has produced several studies examining options available to reform pension systems in several OECD countries. Previously, he worked at the IMF and at the OECD Economic Department. He has published journal articles on aging issues as well as on labor mar-ket issues. Antoln has a PhD in economics from the University of Oxford, United K ingdom, a nd a n u ndergraduate deg ree i n economics f rom t he University of Alicante, Spain.

Mara del C armen Boad o-Penas h olds a P hD i n eco nomics ( Doctor Europeus) from the University of Valencia, Spain, and a degree in actuar-ial sciences from the University of the Basque Country, Spain. She has also published three articles on public pension systems in prestigious interna-tional reviews. She has cooperated on various projects related to pension


xx Contributor Bios

systems at the Swedish Social Insurance Agency in Stockholm and at the Spanish Ministry of Labour and Immigration.

Dirk B roeders i s a sen ior eco nomist a t t he su pervisory po licy d ivision within De N ederlandsche Ba nk. H e i s i nvolved i n t he de velopment o f the fi nancial assessment framework, a r isk-based supervisory toolkit for testing solvency requirements for pension funds. Previous to joining the superisory policy division, he was the head of research and strategy at a Dutch asset manager and was responsible for strategic and tactical asset allocation dec isions. Di rk i s one o f t he ed itors o f t he boo k Frontiers in Pension Finance, Edward Elgar Publishing, Gloucestershire, U.K., 2008.

Giuseppina Cannas is a PhD student at the University of Cagliari, Italy. She graduated with honors from the University of Cagliari with a t hesis about t he a nalysis o f per formance a ttribution. C urrently, Gi useppinas prime research interests include risk management in pension funds.

Ricardo Ma tos C haim r eceived h is P hD i n i nformation sc ience a t t he University o f B rasilia, B rasil. C urrently, h e i s w orking as a n as sociate professor a t t he so ft ware eng ineering de partment o f t he U niversity o f Brasilia. Professor Chaim worked for 19 years at a Brasilian governmental social i nsurance company. H is c urrent sc ientifi c i nterests i nclude i nfor-mation management, risk management, information technologies applied to insurance, and methods to model uncertainty and imprecision in pen-sion funds.

Bill Shih-Chieh C hang i s a co mmissioner of t he Financial Supervisory Commission (FSC) of Taiwan, Republic of China. He is the chairman in t he Insurance A nti-fraud Institute of t he Republic of China a nd a lso serves on the board of directors in the Taiwan Insurance Institute. Prior to joining FSC in July 2006 as a commissioner, he served as an EMBA pro-gram director at the College of Commerce, National Chengchi University, Taipei, Republic of China, from 2005 to 2006. From 1999 to 2005, Dr. Chang served as a chairperson of the Department of Risk Management and I nsurance, C ollege o f C ommerce, N ational C hengchi U niversity, Taiwan, Rep ublic o f C hina. Dr. C hang r eceived h is B S i n ma thematics from National Taiwan University, Taiwan, Republic of China, and a doc-torate in statistics from the University of WisconsinMadison, Wisconsin. He was a lso a r esearch sc ientist of t he Bureau of Research, Depa rtment


Contributor Bios xxi

of N atural Re sources, St ate o f Wi sconsin, Mad ison, Wi sconsin, f rom 1993 to 1994, and a v isiting lecturer of t he Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand, in 1994. His research interests are in insurance theory and actuarial science, pension management, fi nance mathematics, and risk management.

Marcin Fedor is an assistant professor at Warsaw School of Economics. He i s a lso a ch ief r isk o ffi cer a t A XA P oland. H e g raduated f rom t he National School of Insurance in Paris, Cracov University of Economics, and Dauphine University in Paris. He also holds a PhD in economics from Paris-Dauphine University. In his dissertation, he investigated the nature and the objectives of investment prudential regulations, and their role in long-term asset allocation. He also worked in the fi nancial division of the second-largest life insurance company in France and actively contributed to activities of the European Th ink Tank Confrontations Europe, which, in cooperation with the European Commission, was involved in preparing the Solvency II Directive. Finally, Marcin was invited to Harvard University (as a visiting researcher) where he worked on fi nancial regulations.

Wilma de Groo t, CFA, is a senior researcher at Robecos Quantitative Strategies Depa rtment i n R otterdam a nd a g uest l ecturer a t Er asmus University Rotterdam, the Netherlands. She received her MSc in econo-metrics from Tilburg University, the Netherlands.

Werner Hrlimann has st udied mathematics and physics at Eidgens-sische Technische H ochschule Z rich (ETHZ), w here he r eceived his PhD in 1980 wi th a t hesis in alg ebra. Aft er postdoctoral fellowships at Yale University and at the Max Planck Institute in B onn, he b ecame an actuary at Winterthur Life and Pensions in 1984. He worked as a senior actuary for Aon Re and International Risk Management Group (IRMG) Switzerland 20032006 a nd is c urrently employed as a b usiness exp ert at FRSGlobal in Z urich. He was visi ting associate professor in ac tuarial science at t he University of Toronto, Ontario, C anada, during t he aca-demic year 19881989. He has written more than 100 papers, published in refereed journals, or presented at international colloquia. His current interests in actuarial science and fi nance encompass theory and applica-tions in r isk management, p ortfolio management, immunization, pric-ing principles, ordering o f r isks, and computational st atistics and data analysis.


xxii Contributor Bios

Evan Ya-Wen Hwang is an assistant professor in the Department of Risk Management and Insurance, Feng Chia University. She obtained a doctorate in risk management and insurance from the National Chengchi University in Taiwan. Her thesis focuses on the topics in continuous time fi nance and actuarial s cience. C urrently she is w orking o n d ynamic ass et allo cation problems for long-term investors. Her research papers have been presented in several international conferences, which include the annual conference of Asia Pacifi c Risk and Insurance Association in Korea, Japan, and Taiwan, as well as the 11th International Congress on Insurance: Mathematics and Economics in Athens.

Gregorio Impavido is a senior fi nancial sector expert in the monetary and capital markets department of the IMF in Washington, District of Columbia. He delivers policy advice on pension reform and the regula-tion and the supervision of private pensions including market stability and developmental issues. Prior to joining the IMF in 2007, he worked for nine years at the World Bank, Washington, District of Columbia. He has written for the World Bank, European Investment Bank (EIB), and European Bank for Reconstruction and Development (EBRD). His writ-ings have been published in refereed journals and books on policy issues related to the development of private pension and insurance markets in developing countries. He received his PhD and MSc in economics from Warwick University, C oventry, United K ingdom, a nd h is B Sc i n eco -nomics from Bocconi University, Milan, Italy.

Ricardo Josa Fombellida was born in Palencia, Spain. He received his MS in mathematics a nd his PhD in statistics a nd operations research, both from the University of Valladolid, Spain. He is a profesor con-tratado d octor (tenured pos ition) i n t he Depa rtment o f S tatistics a nd Operations Research at the University of Valladolid. His main research areas i nclude st ochastic dy namic o ptimization a nd a pplications i n pension f unds a nd eco nomics. H e ha s p ublished pa pers i n sc ientifi c journals suc h a s Insurance: M athematics and E conomics, t he Journal of O ptimization Th eory a nd A pplications, Computers and O perations Research, a nd t he E uropean J ournal o f O perational Re search. H e ha s participated i n n umerous c ongresses on m athematical fi nance, statis-tics, a nd o perations r esearch. H is r esearch i s f unded b y t he M inistry of E ducation a nd S cience o f S pain, a nd t he Reg ional G overnment o f Castilla y Len.


Contributor Bios xxiii

Paul John Marcel Klumpes, BC om (hons), MCom (hons), LLB (hons), PhD, H on ( FIA), CP A, i s a p rofessor o f acco unting a t t he I mperial College Business School, Imperial College London, United Kingdom. His research interests cover the interrelationship of public policy and volun-tary reporting, regulation, fi nancial management, and control of fi nan-cial services, particularly related to pensions and life insurance. Th is growing personal interest has been associated with a g rowing political, economic, and social awareness of the importance of pensions and fi nan-cial services by government and public policy making institutions. He has produced 65 publications, ha lf of which are in published academic journals. Contributions have been to both practice the discipline and to learning and pedagogy.

Th eo Kocken i s t he f ounder a nd t he CEO o f C ardano. H e g radu-ated i n bu siness a dministration (E indhoven), e conometrics ( Tilburg), and r eceived h is P hD a t V U U niversity, A msterdam, t he N etherlands. From 1990 onward, he headed the market r isk departments at ING and Rabobank International. In 2000, he started Cardano. As a market leader, Cardano supports end users such a s pension funds and insurance com-panies a round E urope w ith st rategic der ivative so lutions a nd po rtfolio optimization. Cardano, now having well over 70 employees, has offi ces in Rotterdam and London.

Th eo is the (co)author of various books and articles in the area of risk management. In 2006, he wrote Curious Contracts: Pension Fund Redesign for the Future, in which he applied embedded option theories as a basis for pension fund risk management and redesign.

Anne de Kreuk holds a deg ree in applied mathematics from Eindhoven University of Technology, the Netherlands. In 2005, she started as a port-folio ma nager i n L DI a nd fi duciary ma nagement a t A BN A MRO A sset Management, wh ere sh e ha s be en i nvolved i n de veloping a nd ma nag-ing i nstitutional cl ient so lutions t hat i nvolved st rategic a sset a llocation, derivatives overlay, and manager selection input. In mid-2008, she joined Cardano as a risk management consultant.

Susanna Levantesi is a researcher in mathematical methods for economy and fi nance at La Sapienza-University of Rome. She has been an adjunct professor of actuarial models for health insurance and life insurance tech-niques at the University of Sannio, Beveneto, Italy, since 2004. She received


xxiv Contributor Bios

her PhD in actuarial science at La Sapienza-University of Rome in 2004. She currently works as an actuary. Her main research interests are health and life insurance.

Yong L i has a P hD in accounting (Warwick Business School, Coventry, United K ingdom) a nd a n MSc w ith d istinction i n ba nking a nd fi nance (University of Stirling, Scotland, United Kingdom). She was a research fel-low at Warwick Business School (20012004) and an academic visitor in the accounting department at the London School of Economics from May to July in 2008. Yong is currently a lecturer in accounting at the University of Stirling, United Kingdom (2004 to date).

Weixi Liu is a PhD student in the Xfi Centre for Finance and Investment at the University of Exeter, England. His research interest is in pension economics, especially the funding and the asset allocation of occupational pensions. H is t hesis ex amines t he va luation eff ects o f d efi ned benefi t pension schemes in the United Kingdom under the most recent pension accounting standards and regulations. Weixi also has teaching experience in fi xed income and derivative pricing.

David A. Love is an assistant professor of economics at Williams College, London, United Kingdom. He previously worked as an economist at the F ederal Re serve B oard (20052006) a nd v isited C olumbia B usiness School, N ew York (20072008). H e r eceived h is BA i n eco nomics f rom the University of Michigan, Ann Arbor, Michigan, in 1996 and his PhD in eco nomics f rom Yale U niversity, N ew Ha ven, C onnecticut, i n 2 003. His research interests include macroeconomics, public fi nance, household portfolio choice, and private pensions.

Ferdinand Ma ger i s a p rofessor a t t he E uropean B usiness S chool i n Oestrich-Winkel, Germany. He previously worked at the Queensland University of Technology, School of Economics and Finance, in Brisbane, Australia, a nd a t E rlangen-Nuremberg U niversity, E rlangen, G ermany, where he also received his doctoral degree. His research focuses on empir-ical fi nance.

Stuart Manson is a professor of accounting at Essex Business School at the University of Essex, Colchester, United Kingdom, where he is also a de an o f t he F aculty o f L aw a nd Ma nagement. H is p resent r esearch


Contributor Bios xxv

interests a re i n t he a reas o f pens ions r eporting a nd t he r egulation o f auditing. H e i s a q ualifi ed cha rtered acco untant a nd i s a m ember o f the Institute of Chartered Accountants of Scotland, Edinburgh, United Kingdom.

Carmen-Pilar Mart-Ballester, PhD, is a graduate in business admin-istration a nd a P hD in fi nancial economics at t he Universitat Jaume I, Castellon de la P lana, S pain. Sh e i s c urrently a v isiting p rofessor o f accounting in the Department of Business Economics at the Universitat Autnoma de Barcelona, Spain. Prior to this, she worked as a research assistant o f fi nance a t t he U niversitat J aume I. Sh e wa s a v isiting researcher a t t he U niversidad P blica de N avarra, P amplona, S pain, and Universitat Autnoma de Ba rcelona. She has published in various journals, including Applied Economics, the Spanish Journal of Finance and A ccounting, a nd Pensions, a mong o thers. H er r esearch i nterests include effi ciency, i nvestor behavior, pension f unds per formance, a nd education. S he ha s p articipated i n p rojects o n fi nancial eco nomics and i nvestment a nalysis t hat h ave re ceived gove rnment c ompetitive research grants.

Massimiliano M enzietti i s a p rofessor o f pens ion ma thematics i n t he Faculty of Economics at the University of Calabria, Cosenza, Italy. From 2002 to 2006 he was a researcher in mathematical methods for economy and fi nance in the Department of Actuarial and Financial Science at the Sapienza University of Rome, f rom where he received h is PhD i n ac tu-arial science. His research has focused on actuarial mathematics of pen-sion schemes, fi nancial mathematics (specifi cally on actuarial model for credit risk), and automobile car insurance. He is now working on actuarial mathematics a nd r isk ma nagement of long-term c are i nsurance a nd on longevity risk securitization.

Nikolaos T . M ilonas i s a p rofessor o f fi nance i n t he Depa rtment of E conomics, U niversity of At hens, G reece. He re ceived h is M BA from Ba ruch C ollege, N ew Y ork Ci ty, h is P hD i n fi nance from the Ci ty U niversity o f N ew Y ork. H e ha s t aught a t t he U niversity of Massachusetts at Amherst, at Baruch College, and at ALBA. His research work focuses on i ssues i n c apital, der ivatives, a nd energy markets w ith a spec ial em phasis i n t he a rea o f i nstitutional i nvest-ing. Many of his articles have been published in prestigious academic


xxvi Contributor Bios

journals including the Journal of Finance. In his professional career, he has worked as an investment director and as a consultant to several insti-tutional investors and security fi rms. He currently serves as a board mem-ber i n t he Hellenic E xchanges S .A., Athens, Gr eece, a nd p resides o ver the I nvestment C ommittee o f t he M utual F und C ompany f or Pension Organisations.

Cristina Ortiz is a junior lecturer in fi nance at the Faculty of Economics and Business Studies, University of Zaragoza, Spain. In 2007, she received her PhD in fi nance in the context of the European doctorate. She was awarded the Social Science Award for Graduate Students and has some national and international publications to her credit. She has also pa rticipated i n national a nd i nternational conferences on behav-ioral fi nance.

Gaobo P ang, P hD, i s a sen ior eco nomist a t Watson Wyatt Worldwide, Arlington, Virginia. His research interests include social security, pension fi nance a nd i nvestment, l ife c ycle a nnuityequitybond o ptimizations, and tax-favored savings. Prior to joining Watson Wyatt, Dr. Pang worked at World Bank, Washington, District of Columbia, conducting macroeco-nomic research on sovereign debt sustainability, growth, and effi ciency of public spending.

George A . Papachristou i s a n a ssociate professor o f fi nancial econom-ics in the Department of Economics, Aristotle University of Th essa loniki, Greece. H e r eceived h is MS c a nd P hD f rom t he U niversity o f P aris I , France. Besides pension investment issues he has a lso published in top-ics such a s I POs, st ock ma rket effi ciency, lot tery m arket e ffi ciency, and venture capital fi nance. His research has appeared in reviews such as the Journal of Banking and Finance, Pension Economics and Finance, Applied Economics, Applied Economics Letters, and others.

Auke Plantinga i s a n associate professor of fi nance at t he University of Groningen, the Netherlands. He is involved in research and teaching in the fi eld of fi nance and, in particular, portfolio management. His research is focused on the performance measurement issue of investment portfo-lios, and the impact of liabilities on these methods. His research interest includes studying the behavior of participants in fi nancial markets, both private individuals as well as institutions.


Contributor Bios xxvii

Diego Prior-Jimnez, PhD, is a f ull professor in t he business economics department a t t he Universidad Autnoma de B arcelona, S pain. H e is a member of the editorial committees of several academic jo urnals related with acco unting co ntrol a nd fi nancial a nalysis. H is r esearch in terests, published in in ternational journals, are the effi ciency analysis of organi-zations and fi rms fi nancial analysis. In the fi eld of effi ciency analysis, his research is o riented toward the design o f models to assess the effi ciency of organizations and t o design p rograms t o improve t heir p erformance. Recent a pplications a re f ocused o n p ublic s ector o rganizations (he alth care, municipalities, education, and st ate-owned fi rms) and als o on pri-vate fi rms f rom t he energy, manufacturing, and fi nancial s ectors. In t he fi eld of fi nancial analysis, his research is oriented toward the comparative benchmark of European fi rms in a n environment of g lobal competition. Th e analysis includes fi rms fi nancial position, cost effi ciency, and the pro-cess of value and free cash fl ow generation.

Marc Prpper works as a sen ior policy advisor in the quantitative risk department of De N ederlandsche Ba nk, A msterdam, t he Netherlands, the integrated prudential supervisor and central bank of the Netherlands. Areas of his work include the fi nancial assessment framework for pension funds and t he f uture solvency and supervisory standard for insurance companies, S olvency I I. Th ese n ew so lvency st andards r efl ect a b road development toward risk-based supervision and quantitative approaches by the adoption of market valuation, risk-sensitive solvency require-ments, and internal modeling. He is also active in the fi eld o f st ress testing for ba nks a nd a m ember of t he Basel I I R isk Ma nagement a nd Modelling Group. Marc has graduated as a physicist from the University of U trecht, t he N etherlands, a nd added t wo y ears o f eco nomy a t t he Erasmus University of Rotterdam, t he Netherlands. Following t his, he worked for several years at the combined bank and insurance company, Fortis, i n t he t reasury, t he i nsurance a sset a nd l iability ma nagement (ALM) department, and in central risk management. He regularly pub-lishes articles on insurance and pensions.

Th eodore A . R oupas is a director at the Ministry of Employment and a lecturer (nontenured) i n t he Depa rtment of Business Administration, University o f P atras, Gr eece. He h olds a ma sters deg ree f rom D urham University, United Kingdom, and a P hD from the University of Athens, Greece. H is c urrent r esearch f ocuses o n i ssues o f h ealth a nd pens ion


xxviii Contributor Bios

economics. H is a rticles ha ve be en p ublished i n t he Journal o f P ension Finance and Economics and the European Research Journal.

Jos Luis Sarto is a senior lecturer in fi nance at the Faculty of Economics and Business Studies, University of Zaragoza, Spain, where he obtained his PhD in 1995. He has published a la rge number of papers in national and international journals such as Omega, Applied Economic Letters, and Applied F inancial E conomics. H is r esearch i nterests i nclude beha vioral fi nance a nd per formance pers istence i n t he context of collective i nvest-ment funds.

Christian Schmieder i s a sen ior credit specialist and heads t he Basel I I implementation at the European Investment Bank (EIB), Luxembourg, Belgium. Pr ior to joining t he EIB, he worked for Deutsche Bundesbank and DaimlerChrysler AG. He has also represented Deutsche Bundesbank in working groups of the Basel Committee on Banking Supervision and has published various articles on banking and fi nance.

Ole S ettergren i s t he h ead sec retary o f t he g overnment co mmission charged w ith se tting up a u nifi ed Swedish Pension Agency. He wa s t he director o f t he pens ions depa rtment a t t he S wedish S ocial I nsurance Agency 20042008. As an insurance expert at the Ministry of Health and Social A ff airs (19952000), h e p roposed t he a utomatic ba lance m ethod of securing the fi nancial stability of the new Swedish pension system. He developed the accounting principles that have been used since 2001 in the Annual Report o f t he Swedish Pension System a nd wa s i ts ed itor f rom 2001 to 2007.

Paul A . Sm ith i s a sen ior eco nomist i n t he Re search a nd S tatistics Division o f t he F ederal Re serve B oard o f G overnors. H e p reviously worked as a fi nancial economist in the Offi ce of Tax Policy at the Treasury Department. H e r eceived h is B A i n eco nomics f rom t he U niversity o f Vermont, Burlington, Vermont, in 1991 and his PhD in economics from the University of Wisconsin, Madison, Wisconsin, in 1997. His research interests include household saving and wealth, pensions, and retirement economics.

Charles Sutcliff e is a p rofessor of fi nance at the ICMA Centre, Reading, United Kingdom. From 2001 to 2007, he was a director of USS Ltd.,


Contributor Bios xxix

Northamptonshire, E ngland, wh ich i s t he seco nd-largest U .K. pens ion fund. Pr eviously, h e wa s a p rofessor o f fi nance a nd acco unting a t t he University of Southampton, England, and the Northern Society professor of accounting and fi nance at the University of Newcastle, United Kingdom. In 19951996 a nd 2 0032004 he wa s a v isiting professor at t he L ondon School of Economics, United Kingdom. He has published in a wide range of refereed journals and is also the author of nine books. He has acted as a co nsultant t o t he F inancial S ervices A uthority, t he S ecurities a nd Investments B oard, H. M. Treasury, t he C abinet O ffi ce, the Corporation of London, the United Nations, the Investment Management Association, the L ondon S tock E xchange, a nd t he L ondon I nternational F inancial Futures a nd O ptions E xchange. H e ha s r eceived r esearch g rants f rom the Social Science Research Council, the British Council, the Institute of Chartered Accountants in England and Wales, and the Chartered Institute of Management Accountants. He is a member of the editorial boards of the Journal of Futures Markets, the Journal of Business Finance and Accounting, the European Journal of Finance, and the Journal of Financial Management and Analysis, and is a vice chairman of the Research Board of the Chartered Institute of Management Accountants, London, United Kingdom.

Laurens Swinkels, PhD, is an assistant professor of fi nance at the Erasmus School o f E conomics i n R otterdam, t he N etherlands, a nd a n a ssociate member of t he Erasmus Research Institute of Ma nagement, Rotterdam, the Netherlands. He is also a senior researcher at Robecos Quantitative Strategies Department and a board member of the Robeco Pension Fund. He received his PhD in fi nance at the CentER Graduate School of Tilburg University, the Netherlands.

Ian Tonks is a professor of fi nance in the Business School at the University of E xeter, E ngland. H e te aches ac ross a ll a reas o f fi nancial economics: asset pricing, corporate fi nance, market effi ciency, and performance mea-surement. His research focuses on market microstructure and the orga-nization of stock exchanges, directors trading, pension economics, fund manager performance, and the new issue market. Ian is an associate mem-ber of t he C entre for Ma rket a nd Public Organisation (CMPO), Bristol, United Kingdom, and is also a consultant to the Financial Markets Group at the London School of Economics, United Kingdom. He has previously taught at the London School of Economics and the University of Bristol, United Kingdom, and held a visiting position in the Faculty of Commerce


xxx Contributor Bios

at t he University of British C olumbia, Vancouver, C anada, i n 1991. H is publications include theoretical and empirical articles in leading fi nance and economics journals.

Tiziana T orri i s a P hD st udent i n ac tuarial sc ience a t t he S apienza-University o f R ome a nd t he Ma x P lanck I nstitute f or Dem ographic Research in Rostock. She graduated in actuarial science and statistics at the Sapienza-University of Rome. Currently, she is working as an actuary. Her main research areas are mortality projection models and securitiza-tion of longevity risk.

Luis Vicente is a s enior lec turer in fi nance at t he Faculty of Economics and Business Studies, University of Zaragoza, Spain. He obtained his PhD in fi nancial eco nomics in 2003, w here his do ctoral w ork r eceived the extraordinary prize of social sciences. He has p ublished papers in s ome important journals such as the Journal of Pension Economics and Finance, Geneva Papers, and Applied Economic Letters, among others. His research interests include portfolio management, performance persistence, and style analysis.

Carlos Vidal-Meli is an associate professor of social security and actuar-ial science at Valencia University, Spain, and an independent consultant-actuary. He has published a rticles i n i nternational re fereed publications on public pension reforms, administration charges for the affi l iate in capi-talization systems, the demand for annuities, NDCs, and the actuarial bal-ance for pay-as-you-go fi nance. Dr. Vidal-Meli holds a PhD in economics from the University of Valencia and a degree in actuarial sciences from the Complutense University of Madrid, Spain.

Mark J. Warshawsky, PhD, is a director of retirement research at Watson Wyatt Worldwide, Arlington, Virginia. He is a recognized thought leader on pensions, social security, insurance, and health-care fi nancing. Prior to joining Watson Wyatt, he was an assistant secretary for economic policy at the treasury department; the director of research at Teachers Insurance and A nnuity A ssociation, C ollege Re tirement E quities F und (T IAA-CREF); and a senior economist at the IRS and Federal Reserve Board. He is a m ember o f t he S ocial S ecurity Advisory B oard for a ter m t hrough 2012. He is also on the Advisory Board of the Pension Research Council of the Wharton School. Dr. Warshawsky has written numerous articles,


Contributor Bios xxxi

books, and working papers, and has testifi ed before Congress on pensions, annuities, and other economic issues.

Ben W eitzer i s a b usiness a nalyst a t A merica On line, I nc. ( AOL), Washington, District of Columbia. Prior to joining AOL, Weitzer worked at Watson Wyatt Worldwide, a leading human resources consulting group with a global reach.

Shane Francis Whelan, PhD, FFA, FSA, FSAI, is an actuary with extensive experience of the investment and pensions industries where he has worked as an investment analyst, fund manager, and strategist for over a decade. He has acted as a co nsultant to the Irish Association of Pension Funds and large Irish pension schemes. He was a l ecturer in actuarial science and statistics at University College Dublin, Ireland, in September 2001, and later became the head of department. Dr. Whelan has presented and published many papers on the topics of investment and pension to pro-fessional and academic audiences, and his research has been rewarded by prizes from the Institute of Actuaries, London, United Kingdom, and the Worshipful Company of Actuaries (a g uild in t he City of London). He received his degree in mathematical science from UCD and a doctorate from Heriot-Watt University, E dinburgh, S cotland. He ha s a lso played an active role in the actuarial profession both in the United Kingdom and Ireland.

Aihua Zh ang wa s a postd octoral r esearch f ellow i n t he S chool o f Economics a nd F inance a t t he U niversity o f S t A ndrews, F ife, U nited Kingdom, bef ore j oining t he Div ision o f I nternational B usiness a t t he University of Nottingham, Ningbo Campus. She studied at the University of Kaiserslautern i n Germany, where she received her PhD a nd MSc i n fi nancial mathematics. She received her fi rst MSc in mathematics education and her BSc in mathematics from the Central China Normal University, and then worked as a lecturer in the China Petroleum University, Beijing, China, before going to Germany. She worked as a mentor for MSc students in fi nancial mathematics at the University of Leeds, United Kingdom. She studied economics at the University of Edinburgh, United Kingdom, as an MSc student. She also studied at the University of Bath, United Kingdom, with a PhD scholarship.


xxxiii

Contributors

Laura AndreuAccounting and Finance

DepartmentFaculty of Economics and Business

StudiesUniversity of ZaragozaZaragoza, Spain

Pablo AntolinFinancial Aff airs DivisionDirectorate for Financial and

Enterprise Aff airsOrganisation for Economic

Co-operation and DevelopmentParis, France

Mara del Carmen Boado-PenasDepartment of Foundations of

Economic Analysis IIUniversity of the Basque CountryBilbao, Spain

and

Department of EconomicsKeele Management SchoolKeele UniversityKeele, United Kingdom

Dirk BroedersSupervisory Policy DivisionDe Nederlandsche BankAmsterdam, the Netherlands

Giuseppina CannasFaculty of EconomicsUniversity of CagliariCagliari, Italy

Ricardo Matos ChaimUniversity of BrasiliaBrasilia, Brazil

Bill Shih-Chieh ChangFinancial Supervisory

Commission

and

Department of Risk Management and Insurance

National Chengchi UniversityTaipei, Taiwan

Marcin FedorAXA GroupWarsaw, Poland


xxxiv Contributors

Ricardo Josa FombellidaDepartamento de Estadstica e

Investigacin OperativaUniversidad de ValladolidValladolid, Spain

Wilma de GrootRobeco Quantitative StrategiesRotterdam, the Netherlands

Werner HrlimannFRSGlobalZrich, Switzerland

Evan Ya-Wen HwangDepartment of Risk Management

and InsuranceFeng Chia UniversityTaichung, Taiwan

Gregorio ImpavidoMonetary and Capital Markets

DepartmentInternational Monetary FundWashington, District of Columbia

Paul John Marcel KlumpesImperial College London Business

SchoolLondon, United Kingdom

Th eo KockenCardano Risk ManagementRotterdam, the Netherlands

Anne de KreukCardano Risk ManagementRotterdam, the Netherlands

Susanna LevantesiUniversity of Rome La SapienzaRome, Italy

Yong LiDepartment of ManagementKings College LondonUniversity of LondonLondon, United Kingdom

Weixi LiuDepartment of ManagementKings College LondonUniversity of LondonLondon, United Kingdom

David A. LoveDepartment of EconomicsWilliams CollegeWilliamstown, Massachusetts

Ferdinand MagerEuropean Business SchoolOestrich-Winkel, Germany

Stuart MansonEssex Business SchoolUniversity of EssexColchester, United Kingdom

Carmen-Pilar Mart-BallesterBusiness Economics DepartmentUniversitat Autnoma de BarcelonaBarcelona, Spain

Giovanni B. MasalaFaculty of EconomicsUniversity of CagliariCagliari, Italy


Contributors xxxv

Massimiliano MenziettiFaculty of EconomicsUniversity of CalabriaCosenza, Italy

Marco MicocciFaculty of EconomicsUniversity of CagliariCagliari, Italy

Nikolaos T. MilonasDepartment of EconomicsUniversity of AthensAthens, Greece

Cristina OrtizAccounting and Finance



Gaobo PangResearch and Innovation CenterWatson Wyatt WorldwideArlington, Virginia

George A. PapachristouDepartment of EconomicsAristotle University of Th essa lonikiTh essa loniki, Greece

Auke PlantingaFaculty of EconomicsUniversity of GroningenGroningen, the Netherlands

Diego Prior-JimnezBusiness Economics DepartmentUniversitat Autnoma de BarcelonaBarcelona, Spain

Marc PrpperQuantitative Risk DepartmentDe Nederlandsche BankAmsterdam, the Netherlands

Th eodore A. RoupasDepartment of Business

AdministrationUniversity of PatrasRio, Greece

Jos Luis SartoAccounting and Finance



Christian SchmiederEuropean Investment BankLuxembourg, Luxembourg

Ole SettergrenSwedish Ministry of Health and

Social Aff airsStockholm, Sweden

Paul A. SmithFederal Reserve BoardWashington, District of Columbia

Charles Sutcliff eTh e International Capital Market

Association CentreHenley Business SchoolUniversity of ReadingReading, United Kingdom


xxxvi Contributors

Laurens SwinkelsRobeco Quantitative StrategiesErasmus University RotterdamRotterdam, the Netherlands

Ian TonksXfi Centre for Finance and

InvestmentUniversity of ExeterExeter, United Kingdom

Tiziana TorriUniversity of Rome La SapienzaRome, Italy

and

Max Planck Institute for Demographic Research

Rostock, Germany

Luis VicenteAccounting and Finance



Carlos Vidal-MeliDepartment of Financial Economics

and Actuarial ScienceUniversity of ValenciaValencia, Spain

Mark J. WarshawskyResearch and Innovation CenterWatson Wyatt WorldwideArlington, Virginia

Ben WeitzerAmerica Online, Inc.Washington, District of Columbia

Shane Francis WhelanSchool of Mathematical SciencesUniversity College DublinBelfi eld, Dublin, Ireland

Aihua ZhangSchool of Economics and

FinanceUniversity of St. AndrewsScotland, United Kingdom


1PART IFinancial Risk Management


31C H A P T E R

Quantifying Investment Risk in Pension Funds

Shane Francis Whelan*

CONTENTS1.1 I ntroduction 41.2 Defi ning Investment Risk 61.3 Case Studies Estimating Investment Risk 10

1.3.1 Pension Saving, Person Aged 55 Years and Over 121.3.2 Case Study 1: Measurement of Investment Risk

in Pension FundsTermination Liability 161.3.3 Case Study 2: Measurement of Investment Risk

in Pension FundsOngoing Liabilities 231.3.4 Summary of Findings 26

1.4 T ime Diversifi cation of Risk Argument 261.5 C onclusion 31Appendix 32References 36

The co ncept o f i nv estm ent r isk i s g eneralized, wh ich a llows t he quantifi cation of the investment risk associated with any given invest-ment strategy to provide for a pension. Case studies, using historic mar-ket data over the long term, estimate the investment risk associated with diff erent investment strategies. It is shown that a f ew decades ago, when

* Th is chapter is based on my paper, Defi ning and measuring risk in defi ned benefi t pension funds, Annals of Actuarial Science II(1): 5466. I t hank the copyright holders, the Faculty and Institute of Actuaries, for permission to reproduce and extend that paper here.


4 Pension Fund Risk Management: Financial and Actuarial Modeling

bond ma rkets only ex tended i n depth to 20 year maturities, t he i nvest-ment risk of investing in equities was of the same order of magnitude as the investment risk introduced by the duration mismatch from investing in bonds for immature schemes. It is shown that now, with the extension of the term of bond markets and the introduction of strippable bonds, the least-risk portfolio for the same pension liability is a bond portfolio of suit-able duration. It is argued that the investment risk voluntary undertaken in defi ned benefi t pension plans ha s g rown ma rkedly i n recent dec ades at a t ime wh en t he ab ility t o be ar t he i nvestment r isk ha s d iminished. Investment r isk in pension funds is quite diff erent to i nvestment r isk of other investors, which leads to the possibility that current portfolios are not optimizedthat i s, t here ex ist portfolios t hat i ncrease t he ex pected surplus without increasing risk. Th e formalizing of our intuitive concept of investment risk in pension saving is a fi rst step in the identifi cation of more effi cient portfolios.

Keywords: Investment risk, defi ned benefi t pension funds, invest-ment strategies, actuarial investigations.

1.1 INTRODUCTIONIf a q uantity i s not measured, it i s u nlikely to be o ptimized. Despite its importance, the investment risk in pension funds is not routinely quanti-fi ed. Indeed, no consensus on how to measure the investment risk in pen-sion funds has emerged yet, so pension savers to date have relied on more qualitative assessments of investment risks, oft en assessed against several competing objectives simultaneously.

Th is cha pter, ex tending W helan ( 2007), p roposes a defi nition o f investment risk that formalizes our intuitive concept. We develop, in a more tech nical se tting, ideas fi rst presented i n A rthur a nd R andall (1989) and provide, using historic data on the United Kingdom, United States, and Irish capital markets, an empirical assessment of the mag-nitude of risk entailed by diff erent investment strategies and relative to diff erent objectives. Th e analysis, through a series of case studies, leads to a rather simple conclusion: sovereign bond portfolios (of appropriate duration a nd i ndex-linked/nominal m ix) a re t he l east-risk po rtfolios for pens ion s avers, i rrespective o f t he a ge o f t he pens ion s aver, i rre-spective of the currency of the pension and, within a reasonable range, irrespective of t he precise investment objectives of t he pension saver.


Quantifying Investment Risk in Pension Funds 5

Th e a nalysis a llows u s t o q uantify t he r isks i n a ll i nvestment st rate-gies, and we provide fi gures for the risks inherent in investing in equi-ties, conventional long bonds, cash, and the closest matching bonds by duration.

Investment risk is defi ned i n Section 1.2 a nd some of its properties are considered. From t he defi nition, o ne c an q uantify t he i nvestment risk inherent in any given investment strategy and thereby identify the strategy with the lowest investment risk. Section 1.3 reports the results of case studies that quantify the investment risk for pension savers from various diff erent investment strategies. Th is analysis shows that the rela-tive risk inherent in diff erent strategies appears to be very similar over diff erent t ime per iods a nd d iff erent na tional ma rkets a nd r easonably robust when the objective is to provide pensions in deferment increasing in line with wages or increasing in line with infl ation subject to a nomi-nal cap. We get an important insight f rom t his analysis: even conven-tional long bonds are not long enough to match the liabilities of young scheme members, and investing in such bonds can be as risky as invest-ing in equities but without the expected rewards. We conclude that just as much care must be exercised in matching liabilities by duration as in matching l iabilities by a sset t ype. Section 1.4 demonstrates t he fa l-laciousness of the argument that the risk of equity investment dissipates with time so that, at some long investment horizon, equities are prefer-able o ver o ther a sset cla sses b y a ny r ational i nvestor. Th is argument, generally k nown as t he t ime d iversifi cation of risk, does not hold in that strong a form. True, the expected return from equities might well be higher than other asset classes but, on some measures, so too is the risk and this remains true over all time horizons. We conclude that the most cl osely ma tching a sset f or pens ion f und l iabilities i s co mposed mainly of conventional and index-linked bonds, which, if history is any guide, has a lower expected long-term return than a predominantly equity portfolio.

Our analysis does not allow us to suggest that one investment strategy is preferable to another. Investors, including pension providers, routinely take risks if the reward is judged suffi ciently tem pting. H owever, pen -sion providers should appreciate the risks involved in alternative strate-gies and, at a minimum, seek to ensure that the investment portfolio is effi cient in the sense that risk cannot be diminished without diminishing reward.



1.2 DEFINING INVESTMENT RISKTh ere would be n o concept of r isk i f a ll t he ex pectations were f ulfi lled: risk arises from a clash between reality and expectations. Accordingly, one fi rst needs to formulate and make explicit future expectations before risk can be quantifi ed. Note that future expectations at any point in time are dependent to an extent on the experience up to that time, as past experi-ences infl uence future expectations.

Our intuitive notion of investment risk is that it measures the fi nancial impact when the actual investment experience diff ers from that expected, holding a ll other things equal. In this section, we formalize this notion. Once the investment risk is properly defi ned, it is straightforward (in the-ory at least) to measure and attempt to minimize it.

Th e task of formally setting down future expectations when it comes to investing to generate a ser ies of f uture cash fl ows i s oft en k nown as a valuation (e.g., t he ac tuarial va luation o f defi ned benefi t schemes). We adopt t his ter minology a nd c all t he de sired ser ies of c ash fl ows the liabilities.

Let t = 0 represent the present time and t > 0 be a future time. Let At denote the forecast cash fl ow from the assets at time t and Lt be the forecast liability cash fl ow at t ime t. We shall assume, for convenience, that the investment return expected over each unit time period in the future is constant; it is denoted as i and termed as the valuation rate of interest. It will be clear that allowing i to vary with the time period poses no theoretical issues. Th e reported va luation result at t ime 0, ex pressing t he su rplus (if positive) or defi cit (if negative) of assets relative to liabilities, is denoted as X0. Th us

00

( )(1 ) tt tt

X A L i

=

= + (1.1)

Consider X0. We shall assume that this is a number.* So, under this simpli-fying assumption, X0 is a constant, representing the surplus at the present time identifi ed by the specifi ed (deterministic) valuation methodology.

* If this is allowed to be a nonconstant random variable, then we call the valuation methodol-ogy used stochastic otherwise the valuation approach is said to be deterministic. Note that a stochastic valuation is representing some part of t he assets and/or liabilities as a nontrivial random v ariable at t ime 0 . We s hall d iscuss on ly d eterministic v aluation me thods i n t he sequel to si mplify the analysis but, as should be clear, the results carry through (with rela-tively straightforward extensions) when applied to stochastic valuation approaches.



Let p be t he t ime that the next valuation fa lls due. Let 0pX represent the results of the next valuation at time p, using the same underlying assumptions as used in the valuation at time 0. Th en the relationship between X0 and 0pX is

=

= =

+

= =

= =

=

= +

= + + +

= + + + +

= + + + +

= + + +

00

0

0

0 0

0

0

( )(1 )

( )(1 ) ( )(1 )

( )(1 ) (1 ) ( )(1 )

( )(1 ) (1 ) ( )(1 )

( )(1 ) (1 )

tt t

tp

t tt t t t

t t p

pt p t p

t t t tt t p

pt p s

t t t tt s

pt p

t t pt

X A L i

A L i A L i

A L i i A L i

A L i i A L i

A L i X i (1.2)

If we m ake th e fu rther a ssumption th at th e e xperience i n th e i nter-valuation period is exactly in line with that assumed at time 0, as well as the assumptions underlying the valuation at time p are also the same,

then the valuation result at time p will be X0(1 + i)p, that is, = +0 0 (1 )

ppX X i .

Th is can be readily seen, as the cash fl ow in the inter-valuation period will be invested (or disinvested) at the valuation rate of interest, accumulating at time p to

= =

+ + = + 0 0(1 ) ( )(1 ) ( )(1 )p pp t p t

t t t tt ti A L i A L i an d th is

amount i s to be added t o t he d iscounted va lue of a ll t he yet u nrealized

asset and liability cash fl ows at time p, namely, 0pX . Th e total value at time p is t hen

= + + 00( )(1 )

p p tt t pt

A L i X , which i s just t he r ight-hand side of

Equation 1.2 multiplied by (1 + i)p, whence the result.It is generally possible to form a reasonable apportionment of the diff er-

ence of the valuation result at the next valuation date from that expected from the valuation at time 0 (i.e., X0(1 + i)p) into that due to either

1. Th e actual experience over the inter-valuation period diff ering from that assumed, or

2. A changed valuation method or basis applied at time p

In particular, it is possible to form a reasonable assessment of the fi nancial impact of the actual investment experience relative to that expected, other things being held the same.



Let 0i

pX denote the result of the valuation at time 0, under the same methodology and assumptions as underlying t he va luation result, X0, at t ime 0 b ut n ow r efl ecting the actual investment experience in the inter-valuation period. Th en 0 0i pX X measures the fi nancial impact at time 0 of how the actual investment experience up to time p diff ered from that assumed in the original valuation at time 0. Obviously, if it turns out that the actual investment experience bears out the assumed experience i n t he i nter-valuation pe riod t hen =0 0

ipX X , so 0 0

ipX X

takes the value zero. We shall call 0 0i

pX X the investment variation up to time p.

Th e investment variation, so defi ned, is a nontrivial concept. It mea-sures the fi nancial impact at t ime 0 c reated when the actual investment experience up to time p diff ers from the investment assumptions underly-ing the valuation at time 0. Th is key concept deserves a defi nition.

Defi nition of investment variation (up to time p): Th e fi nancial impact at time 0 created when the actual investment experience up to time p diff ers from the investment assumptions underlying the valuation at time 0, a ll other t hings bei ng equal. I n t he notation i ntroduced e arlier, t he i nvest-ment variation is denoted 0 0

ipX X .

Th e investment variation up to time p can generally only be measured at time p, before that it may be modeled as a random variable with an asso-ciated distribution. Viewed in this way, the investment variation at time 0, up to time p, is a random variable. Th e investment variation at time 0 can be viewed as a stochastic process, 0 0

ipX X , indexed by p.

0 0i

pX X , when viewed at time 0, is a random variable, so it has an associated distribution. Th e mean of this distribution captures the bias in the original investment assumptionsa positive mean implies that the original investment assumptions were conservative (as, on aver-age, t he ex perienced co nditions t urn o ut be tter t han t hat o riginally forecast).

Note that if t he valuation is t esting the adequacy of the existing port-folio, and f uture prescribed contributions, to generate f uture cash fl ows to meet t he targeted pension payments then other expectations (e.g., on future mo rtality) m ust als o b e em bedded in t he lia bility cash fl ows. In the defi nition of the investment variation, these noninvestment expecta-tions are held constant, so only the impact of the variation in t he invest-ment experience is me asured. Th e actual scale of the resultant fi gure for the obs erved investment va riation is, t hough, a f unction o f t hese o ther expectations.



Some prefer to give a single number to capture the notion of riskiness in a distribution, oft en using some parameter that measures the spread of t he d istribution, such a s i ts st andard de viation, i ts sem i-variance, or its inter-quartile spread. Oft en this summary measure is called the investment r isk. A lternatively, o ne c an a pply so me o ther m easures such as the value below in which there is a specifi ed low probability of the outcome fa lling (the so -called va lue-at-risk).* Th e ke y point to be made is that the distribution of 0 0

ipX X is a more foundational con-

cept and maintains more information than any summary spread statis-tic. We do not enter into the wider discussion of the most appropriate measure t o a pply t o t he i nvestment va riation d istribution t o c apture our intuitive notion of risk but adopt the generally accepted measure of standard deviation. So we identify, to a fi rst-order approximation, the investment r isk a s t he st andard de viation of t he i nvestment va riation distribution.

Defi nition of investment risk (up t o time p): A m easure o f t he spread of t he (ex a nte) i nvestment va riation d istribution. F or co ncreteness, w e shall use the standard deviation as our measure of investment risk in the sequel.

If the valuer has p erfect foresight, then the investment assumptions would b e p erfectly in line wi th t he f uture investment exp erience, and so t he in vestment va riation distr ibution w ould b e a deg enerate co n-stant, wi th a st andard de viation o f zer o. M ore uncer tainty a bout t he investment variation implies a greater spread of the (ex ante) distribu-tion, w hich corresponds to a gr eater investment r isk under t he above defi nition.

If we have a perfect matching of assets to liabilities, t hen a ny va lu-ation m ethod w ill a lways r eport t he i nvestment va riation t o be a degenerate d istribution ( i.e., a co nstant) a nd, acco rdingly, t he i nvest-ment risk to be zero. Th is c an be se en a s, b y per fect ma tching,

+ = + = 0 0( )(1 ) 0(1 ) 0t t

t tt tA L i i . Th us, wh ile t he p resent va lue

of the assets at time 0 0

i.e., (1 )( )ttt A i

+ m ight v ary wi th th e

* Of p articular i mportance i n t he pro bability d istribution i s it s e xtreme le ft tail behavior, which g ives t he probability of a re duction i n t he surplus of a ny g iven large a mount. Such an event might cause a sudden and severe fi nancial strain that undermines the whole saving objective. Measures for such extreme risks include, for symmetric distributions, the kurtosis or higher even moments if they exist.

In the technical sense that At = Lt, for all t, independent of any investment assumptions.



investment assumptions, it must vary in a direction proportion to

+ 0 (1 )

ttt

L i . Hence, in aggregate, a gain (loss) on the assets relative

to that expected is exac tly off set by an increase (decrease, respectively) in the value of the liabilities relative to that expected. In short, the per-fect ma tching o f t he ass et a nd lia bility cash fl ows has zer o in vestment variation, ir respective o f t he exp erienced o r t he assumed in vestment conditions.

Let us assume t hat (1) ass ets a re t o b e val ued a t ma rket val ue a nd (2) there exists a p ortfolio of assets that perfectly matches the liabilities. Note, from earlier considerations, we know that if the matching asset port-folio was held at time 0 then the investment variation would be 0 (irrespec-tive of what happened in t he inter-valuation period). Also, at time p, the present value of the future liabilities must be equal to the market value of the matching asset at that time (by the defi nition of matching asset). Hence the exp erienced valuation rate in t he inter-valuation p eriod can now b e seen as t he market return on the matching asset over the inter-valuation period. We see immediately from this that the investment variation is posi-tive only if the increase in the market value of the actual assets held exceeds the increase in the market value of the matching asset.* Th e upshot is that the investment va riation is t he present value o f t he ext ent t o w hich t he increase in the value of the assets exceeds the increase in the liabilities over the inter-valuation period, discounted at the rate of return on the matching asset over the period.

Appendix 1.A.1 draws attention to a major limitation of our defi nition of investment variation (and the associated investment risk) for pension investors.

1.3 CASE STUDIES ESTIMATING INVESTMENT RISKEstimating the investment risk has been identifi ed in the last section with estimating t he st andard de viation o f t he (ex ante) i nvestment va riation distribution. L et u s a ssume t hat t he ex p ost investment variation is a reasonable pro

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10610.Pension Fund Risk Management Financial and Actuarial Modeling (Chapman & HallCrc Finance Series)