European Journal of Operational Research 150 (2003) 463–465

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Editorial

Financial modelling and extreme events

1. Introduction

Although the tragic attacks of September 11th

gave a new and grim meaning to the phrase ‘‘ex-treme events’’, its study is not new in financial

economics. The occurrence of extreme events in

financial risk management has become a major

focus of study in recent years as financial instru-

ments have become increasingly complex and

volatile. What is relevant today is not only finan-

cial shocks but also events from other sources such

as political, social and environmental events. Po-litical leaders warn us of more terrorist attacks

that can affect economic stability. Climatologists

predict more turbulent weather conditions as a

result of global warming that can affect agricul-

tural production. Health experts predict different

forms of diseases that can affect productivity and

industrial output. These events manifest into a

series of shocks that affect the economy continu-ously. No industry has felt that more than the

insurance industry who have not only witnessed an

increase in frequency of losses but also in magni-

tude. The claim amounts for recent catastrophic

events have been huge and are indeed staggering.

Tentative assessments of the damage from the at-

tacks on September 11th range from $30 billion to

$70 billion, 1 approximately half the record dam-age claims from the Kobe earthquake in 1995.

Similarly, the shocks to the financial sector

appear to also increase in frequency and size. The

recent scandals of Enron, WorldComm and Ar-

1 Flynn, P., 2002. Financial bailout of September 11: Rapid

response. Challenge 45 (1), 104–116.

0377-2217/03/$ - see front matter � 2002 Elsevier B.V. All rights res

doi:10.1016/S0377-2217(02)00771-3

thur Anderson appear to over-shadow some of

the earlier eye-opening events of Orange County,

NatWest, Barings Bank, Sumitomo, LTCM and

ENRON. There is sufficient evidence to indicatethat inadequate risk management tools can be

blamed partially on the high incidence of frauds

and the inability to forecast catastrophic mishaps.

The calls for sophisticated risk management tools

to counter the increasingly complex financial in-

struments appear not to be in place, resulting in

such extreme events.

Several obstacles hamper the proper inclusionof extreme events in risk management tools. Risk

management tools often involve a trade-off be-

tween the quality of the �central� versus the �tail�properties. It is not surprising that in the early

phases, more emphasis was placed on the former

rather than on the latter. Inferences about the tail

of a distribution are usually much harder to make,

since only a few observations enter the tail region.Moreover, the inferences are very sensitive to the

largest observed losses and the introduction of new

extreme losses to a dataset may have a substantial

impact. Further, since extreme events are rare by

definition, most managers will not be confronted

with them during their time on a specific job. Few

organisations have incentives to stimulate the

performance of future managers at the expense ofthe current generation. Finally, for many users the

psychological perception of the risk of an extreme

event is more determined by how vividly they re-

member the last instance than by the statistical

probability of re-occurrence.

These obstacles are, however, being removed

at a rapid rate by the recent developments in

techniques to assess and forecast the risk of

erved.

464 Editorial / European Journal of Operational Research 150 (2003) 463–465

extreme events. The Value-at-Risk (VaR) meth-

odology has found its way into textbooks and

practice as a primary tool for financial risk as-

sessment. Specialized methods for VaR prediction,

based on extreme value theory, are now available.

This is a crucial development since VaR is calcu-lated from the lowest tail part and is therefore

highly dependent on good predictions of extreme

events. As a result, we know more about the na-

ture of extreme events, their relation with volatility

and their time dependence. This enables us, among

other things, to put large stock price movements

into perspective 2 and to assess the extreme cor-

relation between stock markets. 3

In response to the changing nature of the risks

faced by the business community, the regulators of

financial institutions have developed more elabo-

rate frameworks to account for the increasingly

complex securities used by corporations. One re-

sult has been the proposed implementation of the

new minimum capital standards under the �threepillars approach� of the Basel II. In anticipation ofthese changes, an enormous, worldwide research

effort is going on to have the necessary risk man-

agement tools in place when the new framework is

implemented. Many of the new insights and re-

search should contribute to enhancing the existing

tools for risk management. Slowly but inexorably

extreme events are becoming an integral part of

risk management systems.This feature issue presents some examples of

the kind of research discussed above, as well as

examples from other areas in the broad field of

financial modelling.

2. Contents of this issue

In the first paper, Berger, highlights the effi-

ciency effects of a single market for financial ser-

2 See Jansen, D.W., de Vries, C.G., 1991. On the frequency

of large stock returns: Putting booms and busts into perspec-

tive. The Review of Economics and Statistics 73 (1), 18–24.3 Longin, F., Solnik, B., 2001. Extreme correlation of

international equity markets. The Journal of Finance LVI (2),

649–676.

vices in Europe. In an exhaustive survey of the

literature, he finds that mergers and acquisitions

produce efficiency gains only when they occur

within a country and not across borders. Although

formal regulatory barriers may have been removed,

cultural and other differences appear to have stillprevented efficiency gains from being fully ex-

ploited. More research is recommended in the area

of cross-border mergers and acquisitions.

In the second paper, Spronk and Vermeulen

propose a multidimensional framework for com-

parative performance evaluation. The framework

corrects for risks beyond the control of the deci-

sion maker and takes account of differences inoperational characteristics between firms. Thus, it

combines the advantages of extended comparison

techniques and the multifactor method.

Steuer and Na provide a categorized bibliogra-

phy on the application of multiple criteria decision

making in the area of finance. This extensive study

shows the world wide origins of contributions to

this important area and underlines the position ofthe European Journal of Operational Research at

the very front of scientific developments.

A new method to estimate VaR is put forward

by Cabedo, Semper and Clemente. Combining

ARCH models with factor analysis techniques,

this method overcomes the drawback of the ex-

cessive number of parameters required in ARCH

models.Castellacci and Siclari examine this issue from

the software implementation of VaR methodo-

logies. They examine five different methodologies

for quadratic portfolios, Delta-Normal, Delta-

Gamma-Normal, Cornish-Fisher, Delta-Gamma

Monte Carlo and Full Monte Carlo models, in-

cluding computational efficiency. One interesting

result among the many they find is that taking intoaccount non-linearity by using higher moments

may be more beneficial than the full Monte Carlo

evaluation.

Crama and Schyns describe the application of a

simulated annealing approach to a complex port-

folio selection model, and report promising results

for this class of problems.

Benati examines the portfolio selection problemby modifying the standard Markowitz mean–

variance model, replacing variance with the worst

Editorial / European Journal of Operational Research 150 (2003) 463–465 465

conditional expectation variable. He shows that

using a linear programming approach with an

exponential number of constraints and appropri-

ate separation sub-routines can solve for optimal

portfolio values.

3. The next feature issues on financial modelling

Over the past fifteen years, the EURO Working

Group on financial modelling has been a successful

platform to establish and maintain contact with

the work and ideas of other financial modellers

from both academia and practice. Many of thepapers in this feature issue have their roots in the

Working Group. The Meetings of this Working

Group, organised twice per year, 4 have become an

important place for presenting papers, exchanging

ideas and starting joint research projects. EJOR�sfeature issues on financial modelling intend to

follow up on these meetings with a feature issue

after every meeting or combination of meetings.

4 The previous two meetings were in Haarlem (Holland) and

Capri, the next will be on Cyprus.

This mutually enforcing cycle of publications and

presentations can be a powerful instrument to

keep abreast with developments in a rapidly chang-

ing area of research like financial modelling. The

purpose is by no means to exclude papers from

outside the EURO Working Group Meetings. Onthe contrary, all papers that fit the editorial pol-

icy 5 will remain welcome as before.

Anoop Rai

Department of Finance

Hofstra University

221 Weller Hall

Hempstead

NY 1155, USA

Fax: +1-516-463-4834

E-mail address: anoop.rai@hofstra.edu

Nico van der Wijst

Department of Industrial

Economics and Technology Management

Norwegian University of Science and Technology

N-7491 Trondheim, Norway

5 Papers on financial modelling are solicited that help to

solve financial-economic decision problems in practice. They

may relate to new insights, both theoretical and empirical, into

the decision maker�s environment, new tools and the integration

of these tools within frameworks for decision making.