Quantitative Financial Risk Management - Henry Stewart Talks

Quantitative Financial
Risk Management
Fundamentals, Models and Techniques
There can be no more topical issue in financial markets than managing RISK.
That is what this series of eighteen specially prepared, animated audiovisual briefings
streamed to you when you want, where you want and as often as you want is all about.
Briefings on Quantitative Financial Risk Management by many of the world’s leading experts.
If you want to know how to measure and manage financial risk – and if you want those
working with and for you to know how to measure and manage financial risk you want
these briefings.
■ CONCISE ■ COMPREHENSIVE ■ PRACTICAL ■ ESSENTIAL
Series Editor:
Dr. Stephen E. Satchell – Fellow, University of Cambridge, UK
Stephen Satchell is a Fellow of Trinity College and the Reader in Financial Econometrics at the University of
Cambridge. He is interested in finance and econometrics and has written at least 150 papers in this area. He is an
Academic Advisor to many leading asset management companies and a frequent speaker at City conferences.
Visit our website at www.hstalks.com/risk/ or contact us on Email: annag@henrystewart.co.uk Tel: +44 (0)20 7092 3479

Quantitative Financial Risk Management
Specially prepared, animated, audiovisual briefings by leading experts from industry and academia;
available when you want, where you want and as often as you want.
Available on individual user license for $2500 (£1515, €1775) and on site license for $4999 (£2999,
€3550) giving unlimited access for all members of an organization within a single country.
To purchase the series complete and return order form on page 6.
I: INTRODUCTORY REVIEWS
1. Practical use of portfolio risk management
today
Definitions of risk management (RM) in different contexts –
Practical application rather than theory – Does RM make a
major contribution to portfolio safety – Can RM exacerbate
adverse markets – The impacts of regulatory risk on fund
managers – Appropriate or mistargeted – How is risk forecast
and how does that feed into the investment process – Do
quantitative techniques add value or lower risk – Risk
strategies: how to measure, implement and control
Mr. Daryl Roxburgh – Head, BITA Risk Solutions, UK and
USA
Daryl Roxburgh is Head of BITA Risk Solutions, the London and
New York based portfolio construction and risk solutions
provider. Daryl is a graduate of the City University (now John
Cass) Business School and his career commenced as a private
client fund manager with Buckmaster & Moore. He progressed
to a senior management role in 1987 and was subsequently
appointed Director of IT in 1994 for Credit Suisse Asset
Management. Following two years at M&G, he was recruited by
Prudential Portfolio Managers as Global Head of IT in 1998. He
now specializes in portfolio construction and risk analysis
solutions for the quantitative, institutional and private banking
markets.
2. Statistical models for risk management
Definition of returns: simple returns and log returns –
Distribution of returns, univariate: normal and log-normal
distribution – Stylized facts of historical returns – Skewness,
kurtosis, autocorrelation and stationarity – ARCH, GARCH and
stochastic volatility (SV) models – Distribution of returns,
multivariate: multivariate normal distribution – Multivariate
GARCH and SV models – Copulas and non-linear dependence
Prof. John Knight – Professor of Economics, University of
Western Ontario, Canada
John Knight received his PhD from the University of New South
Wales, Australia in 1980. He has held teaching and research
positions in the US, Australia, UK and Canada and has been in
his current position since 1987. His extensive list of research
publications are in theoretical econometrics and more recently
in financial econometrics. In 2002 he was awarded a Plura
Scripsit Award by the journal Econometric Theory. He has also
won awards for his graduate teaching and PhD supervision.
Current research interests include stochastic volatility modeling
and the estimation of continuous time processes in finance.
3. Utility theory and mean variance
Expected utility representation of preferences – Rationality
criteria – State independent utility – Risk averse behavior – Risk
and insurance premium – Arrow-Pratt’s absolute risk aversion
coefficient – Risk aversion and small risk – Relative risk
aversion coefficient – Risk tolerance – CARA utility – CRRA
utility – Risk aversion and large risk – Utility and variance
measures of risk – Variance aversion and two fund separation –
Local risk neutrality – Marginal utility and two fund separation –
Factor structure and two fund separation
Dr. Norvald Instefjord – Reader in Finance, University of
Essex, UK
Norvald is a Reader in Finance and an Associate Director of
Finance Studies at the Department of Accounting, Finance and
Management at the University of Essex. He received a PhD in
finance from the London Business School in 1995 and was a
Lecturer in Finance at Birkbeck College, University of London,
from 1994 to 2004. Norvald’s primary research interests are
corporate finance (including disclosure and corporate
governance issues), banking (including risk management and
issues linked to fraud and operational risk), and security and
market design. He also has extensive teaching experience in
general and corporate finance, mathematical and theoretical
finance and market microstructure.
4. Definitions of risk
Distributional properties of risk – Variance – Risk aversion and
variance aversion – First order stochastic dominance – Second
order stochastic dominance – Axiomatic approach to risk
measures – Risk as a choice variable – Acceptable and nonacceptable
risk – Single-dimensional risk measures – Risk
measure and risk capital – Coherent risk measures – Value-atrisk
(VaR) is not coherent – TailVaR and worst conditional
expectations – Rotschild/Stiglitz increasing risk – Conclusions:
risk definition depends on context and purpose
Dr. Norvald Instefjord – Reader in Finance, University of
Essex, UK
Norvald is a Reader in Finance and an Associate Director of
Finance Studies at the Department of Accounting, Finance and
Management at the University of Essex. He received a PhD in
finance from the London Business School in 1995 and was a
Lecturer in Finance at Birkbeck College, University of London,
from 1994 to 2004. Norvald’s primary research interests are
corporate finance (including disclosure and corporate
governance issues), banking (including risk management and
issues linked to fraud and operational risk), and security and
market design. He also has extensive teaching experience in
general and corporate finance, mathematical and theoretical
finance and market microstructure.

Quantitative Financial Risk Management
5. Volatility
Volatility is the most heavily used measure of risk in financial
decision making – Discussion of validity of various measures of
risk – Statement of conditions under which volatility is a good
measure – Explanation of the empirical properties of data and
their dynamics – Why models need to capture these
characteristics – Analysis of various approaches of volatility
estimation with particular emphasis on dynamic models in both
univariate and multivariate contexts – Techniques for volatility
model validation – Explanation of possible pitfalls – Out-ofsample
volatility forecasting using dynamic models and various
methods for volatility forecast evaluation
Dr. George A. Christodoulakis – Assistant Professor of
Finance, University of Manchester, UK and Advisor, Bank of
Greece, Greece
George A. Christodoulakis is Assistant Professor of Finance at
Manchester Business School, University of Manchester and
Advisor at the Bank of Greece. In the past he has held
positions at Cass Business School of City University, London
and the University of Exeter and has provided advice for a
number of companies. He holds a PhD and MSc in finance
from the University of London as well as an MSc and BSc in
economics and econometrics from the AUEB in Athens. His
expertise concerns the area of credit and market risk theory
and applications, approached from both a mathematical
finance and a financial econometrics perspective. George is a
regular contributor to international refereed research journals
and a frequent speaker in specialist conferences.
6. Hedge fund risk assessment
Environmental scan/allocation strategies – Discerning how
alpha is generated – Criteria for hedge fund success –
Evaluating returns – Warning signs to monitor – Portfolio
considerations
Mr. David Martin – Senior Vice President and Chief Risk
Officer, AllianceBernstein L.P., USA
David Martin is Senior Vice President and Chief Risk Officer of
AllianceBernstein LP. Mr. Martin joined the firm in December
2001 and is responsible for the risk management function. Mr.
Martin began his career at Price Waterhouse & Co in 1972 in
the audit and consulting practices. In 1979 he joined Citibank
and held numerous positions during his 20-year tenure. Mr.
Martin was a Senior Risk Officer responsible for the global
windows on risk processes that were used to proactively
manage the entire risk profile of Citigroup. From 1999-2001, Mr.
Martin was an active Director of DFD Select Group, a manager
and distributor of funds of hedge funds.
II: PORTFOLIO RISK
7. The structure of equity risk models
Stock risk models for portfolio risk analysis – Generic risk
model data – Betas and covariances – Two significant choices
about structure and their consequences for estimation error –
The impact on portfolio risk forecasts – A short digression on
stock selection – Choosing factors
Mr. Jason MacQueen – Chairman, Alpha Strategies, LLC, UK
Jason MacQueen founded QUANTEC in 1980, which was the first
firm to develop risk models for equity markets outside the USA. In
1984 QUANTEC launched the first global asset allocation model,
which was enhanced in 1985 by the addition of currency hedging
overlays and in 1986 by reverse optimization for efficient portfolio
rebalancing. Jason also pioneered the development and use of
multi-factor stock selection models in both the USA and Japan
and the investment track record of his long-term collaborators is
exceptional. In the late 1990s he helped to develop the first truly
global risk model and a global stock selection model, both
incorporating global common factors. He is currently working
with R-Squared to develop customized hybrid risk models for
institutional investors and with Apollo Advisors, which uses a
proprietary risk overlay system to manage a fund of funds and
optimize the portfolio risk-return trade-off.
8. Risk decomposition (and risk budgeting)
The standard method of decomposing portfolio risk into
contributions from individual assets – ‘Risk budgeting’ by
pension funds – Unfortunately, while this analysis gives a
unique answer for absolute risk, it gives three very different
answers for tracking error, or risk relative to some benchmark
(such as the pension fund’s liabilities) – Description of what is
happening – Analysis used by most practitioners does not give
the most useful answer
Mr. Jason MacQueen – Chairman, Alpha Strategies, LLC, UK
Jason MacQueen founded QUANTEC in 1980, which was the
first firm to develop risk models for equity markets outside the
USA. In 1984 QUANTEC launched the first global asset
allocation model, which was enhanced in 1985 by the addition
of currency hedging overlays and in 1986 by reverse
optimization for efficient portfolio rebalancing. Jason also
pioneered the development and use of multi-factor stock
selection models in both the USA and Japan and the
investment track record of his long-term collaborators is
exceptional. In the late 1990s he helped to develop the first
truly global risk model and a global stock selection model, both
incorporating global common factors. He is currently working
with R-Squared to develop customized hybrid risk models for
institutional investors and with Apollo Advisors, which uses a
proprietary risk overlay system to manage a fund of funds and
optimize the portfolio risk-return trade-off.
III: MARKET RISK
9. Estimating risk models
Defining a risk model – Assembling data – Non-parametric
estimation methods – Parametric estimation methods – Monte
Carlo simulation methods
Prof. Kevin Dowd – Professor of Financial Risk
Management, Nottingham University, UK
Kevin Dowd is Professor of Financial Risk Management at
Nottingham University Business School, where he works with
the Center for Risk and Insurance Studies. His research
interests cover macro, monetary and financial economics,
financial risk management, insurance, pensions and political
economy. His latest book, Measuring Market Risk (2nd edition)
was published by John Wiley in 2005.

Quantitative Financial Risk Management
10. Measures of financial risk
Nature of financial risk – Representing financial risk using a
density function – VaR as a risk measure – Expected shortfall –
Coherent risk measures – Worst-case scenario analyses
Prof. Kevin Dowd – Professor of Financial Risk
Management, Nottingham University, UK
Kevin Dowd is Professor of Financial Risk Management at
Nottingham University Business School, where he works with
the Center for Risk and Insurance Studies. His research
interests cover macro, monetary and financial economics,
financial risk management, insurance, pensions and political
economy. His latest book, Measuring Market Risk (2nd edition)
was published by John Wiley in 2005.
11. VaR when volatility is changing
What can we learn from problems with VaR models –
Common patterns in volatility (the clustering effect) –
Forecasting volatility using GARCH – Implications for VaR,
stress testing and capital requirements
Dr. Elizabeth Sheedy – Associate Professor, Macquarie
Applied Finance Center, Macquarie University, Australia
Elizabeth Sheedy joined Macquarie University in 1993. Prior to
this she worked in the finance industry for institutions including
Macquarie Bank and Westpac. She now teaches financial risk
management courses in the popular master of applied finance
program. Her current research focus is on volatility clustering
and its application to modeling market risk. She is also on the
Academic Advisory Committee for the Professional Risk
Managers’ International Association (PRMIA). She co-edited the
Professional Risk Managers’ Guides recently published by
McGraw-Hill.
IV: APPLICATIONS TO CREDIT RISK AND
MARKET RISK
12. Structural and reduced form models
Structural models – The Merton approach: bond pricing, stock
pricing, default probability, credit spreads, bond volatility –
Parameter estimation – Limitations – Extending Merton: the
CreditGrades model reduced form models – Default intensity –
Examples: constant, deterministic and stochastic intensities –
Linking reduced and structural models – Recovery rates
Dr. Theo Darsinos – Associate Director, Fixed Income
Trading, Barclays Capital, UK
Theo Darsinos is an Associate Director of Fixed Income Trading
at Barclays Capital. Prior to this he was a Vice President in the
global markets, fixed income research division of Deutsche
Bank. Theo received his PhD in financial econometrics from the
University of Cambridge and a BSc in mathematics from the
University of London. Prior to joining Deutsche Bank in 2003,
he was a Research Fellow in the Department of Applied
Economics, University of Cambridge.
13. Modeling business dependencies for credit
portfolios
Portfolio credit risk – Integrating macrostructural and
microstructural interdependencies – Gaussian copula – Credit
portfolio as a graph – Impact of business dependencies on
correlation – Feedback effects – Marginal risk contribution
Dr. Markus A. Leippold – Assistant Professor, Swiss
Banking Institute, University of Zurich, Switzerland
Markus Leippold is Assistant Professor of Finance at the Swiss
Banking Institute of the University of Zurich. Prior to moving
back to academia he was working for Sungard, Trading and
Risk Management Systems and the Zurich Cantonal Bank.
Markus’ main research interests are term structure modeling,
asset pricing and risk management. He was a Research Fellow
at the Stern School of Business in New York and obtained his
PhD from the University of St. Gallen, Switzerland, in 1999. He
has published in several Journals such as Journal of Financial
and Quantitative Analysis, Journal of Economic Dynamics and
Control, Journal of Banking and Finance, Review of Derivative
Research, Journal of Risk, Journal of Futures Markets and
Review of Finance. In 2004, the research paper he co-authored
on credit contagion won the STOXX Gold Award at the annual
conference of the European Financial Management
Association. During 2005, he was a Visiting Researcher at the
Federal Reserve Bank in New York.
14. Extreme value theory and copulas
Extremes in quantitative risk management – Limiting behavior
of sums and maxima – Fisher/Tippett theorem – Extreme value
distributions and domains of attraction – Block maxima method
– Threshold exceedances – Picands/Balkema/de Haan theorem
– Threshold selection – Quantile estimation – Point process
approach – Banking and insurance regulation – Critical
appraisal
Prof. Paul Embrechts – Professor of Mathematics, Swiss
Federal Institute of Technology, Switzerland
Paul Embrechts is Professor of Mathematics at ETH Zurich
specializing in actuarial mathematics and quantitative risk
management. Previous academic positions include the
Universities of Leuven, Limburg and London (Imperial College).
Prof. Embrechts has held visiting appointments at the
University of Strasbourg, ESSEC Paris, the Scuola Normale in
Pisa and the London School of Economics (Centennial
Professor of Finance). He is an Elected Fellow of the Institute of
Mathematical Statistics, Honorary Fellow of the Institute of
Actuaries, corresponding member of the Italian Institute of
Actuaries and Associate Editor of numerous journals. His areas
of specialization include insurance risk theory, quantitative risk
management, the interplay between insurance and finance and
the modeling of rare events. He co-authored the influential
books Modelling of Extremal Events for Insurance and Finance,
Springer, 1997 and Quantitative Risk Management: Concepts,
Techniques and Tools, Princeton University Press, 2005.
Dr. Johanna Neslehova – Postdoctoral Research Fellow,
Swiss Federal Institute of Technology, Switzerland
Johanna Neslehova is currently a Postdoctoral Research Fellow
at the risk management research centre RiskLab, ETH Zurich.
She completed her PhD on dependence of non-continuous
random variables with Professor Dietmar Pfeifer at the
University of Oldenburg in 2004. Her research interests include
stochastic methods for quantitative risk management in

Quantitative Financial Risk Management
finance, dependence modeling, discrete copulas, point
processes, extreme value theory and operational risk. She has
spoken at various conferences on risk management. She is
involved in the German e-learning project EStat and wrote a
book on elementary mathematics with Erhard Cramer
published by Springer in 2004.
15. Dependence modeling with copulas
Impact of extremes and dependence in finance and insurance –
Correlation issues – Copulas and Sklar’s theorem – Copula
generation – Frechet-Hoeffding bounds – Limitations of
correlation – Rank correlation measures – An application to
credit risk – Tail dependence – Bounds on risk measures –
Critical appraisal
Prof. Paul Embrechts – Professor of Mathematics, Swiss
Federal Institute of Technology, Switzerland
Paul Embrechts is Professor of Mathematics at ETH Zurich
specializing in actuarial mathematics and quantitative risk
management. Previous academic positions include the
Universities of Leuven, Limburg and London (Imperial College).
Prof. Embrechts has held visiting appointments at the
University of Strasbourg, ESSEC Paris, the Scuola Normale in
Pisa and the London School of Economics (Centennial
Professor of Finance). He is an Elected Fellow of the Institute of
Mathematical Statistics, Honorary Fellow of the Institute of
Actuaries, corresponding member of the Italian Institute of
Actuaries and Associate Editor of numerous journals. His areas
of specialization include insurance risk theory, quantitative risk
management, the interplay between insurance and finance and
the modeling of rare events. He co-authored the influential
books Modelling of Extremal Events for Insurance and Finance,
Springer, 1997 and Quantitative Risk Management: Concepts,
Techniques and Tools, Princeton University Press, 2005.
Dr. Johanna Neslehova – Postdoctoral Research Fellow,
Swiss Federal Institute of Technology, Switzerland
Johanna Neslehova is currently a Postdoctoral Research Fellow
at the risk management research centre RiskLab, ETH Zurich.
She completed her PhD on dependence of non-continuous
random variables with Professor Dietmar Pfeifer at the
University of Oldenburg in 2004. Her research interests include
stochastic methods for quantitative risk management in
finance, dependence modeling, discrete copulas, point
processes, extreme value theory and operational risk. She has
spoken at various conferences on risk management. She is
involved in the German e-learning project EStat and wrote a
book on elementary mathematics with Erhard Cramer
published by Springer in 2004.
V: RISK MODEL VALIDATION
16. Validation techniques I: regulatory and
statistical background
Historical background – New capital standards (Basel II) –
Requirements on quantitative validation – The binary
classification model for rating systems – Bayes’ formula –
Modeling cyclical effects – Conditional probabilities of default
(PD)
Dr. Dirk Tasche – Head of Modeling for Corporate Markets
Rating Systems, Lloyds TSB Bank, UK
Dirk Tasche is currently Head of Modeling for Corporate
Markets Rating Systems at Lloyds TSB Bank. In this role, he
oversees development and maintenance of all wholesale rating
models for the Basel II IRB approach. Dirk has more than
twelve years experience in risk management, from industry,
supervisory and academic positions. Before joining Lloyds
TSB, he was a Senior Director at Fitch Ratings, heading the
Quantitative Financial Research Group in London. He has
published a number of papers on the measurement of financial
risk and capital allocation in refereed journals. He holds a PhD
in probability theory from Berlin University of Technology.
17. Validation techniques II: discriminatory
power and calibration
Validation principles – Predictive ability, discriminatory power and
PD calibration – Cumulative accuracy profile (CAP) – Accuracy
ratio (AR) – Receiver operating characteristic – Kolmogorov-
Smirnov statistic – Conditional and unconditional tests – Binomial
test – Hosmer-Lemeshow test – Spiegelhalter test – Normal test
Dr. Dirk Tasche – Head of Modeling for Corporate Markets
Rating Systems, Lloyds TSB Bank, UK
Dirk Tasche is currently Head of Modeling for Corporate
Markets Rating Systems at Lloyds TSB Bank. In this role, he
oversees development and maintenance of all wholesale rating
models for the Basel II IRB approach. Dirk has more than
twelve years experience in risk management, from industry,
supervisory and academic positions. Before joining Lloyds
TSB, he was a Senior Director at Fitch Ratings, heading the
Quantitative Financial Research Group in London. He has
published a number of papers on the measurement of financial
risk and capital allocation in refereed journals. He holds a PhD
in probability theory from Berlin University of Technology.
VI: ECONOMIC CAPITAL
18. Leading bank credit portfolio strategies
Leading banks manage their credit portfolios actively – Active
credit portfolio management objectives and principles – Active
credit portfolio management trends and success stories –
Leading bank economic capital management strategies – Uses
of required economic capital at leading banks – Leading bank
credit portfolio management organizational models – Leading
bank credit portfolio management strategies – Adopting leading
bank strategies
Mr. Brian Dvorak – Managing Director, Moody’s KMV Credit
Strategies Group, USA
Brian Dvorak is the Managing Director of Moody’s KMV’s Credit
Strategies Group. He supports clients globally in creating value
from their investment in the products and services of Moody’s
KMV, the world’s leading provider of quantitative credit risk
analysis tools to lenders, investors and corporations. Before
joining KMV in 1998, Mr. Dvorak was Vice President of Product
Marketing and Technical Support at CATS Software Inc.
Previously, he was Executive Vice President and Chief
Operating Officer of LOR/Geske Bock Associates, Inc. and
LORGB Investment Advisors, Inc. Mr. Dvorak received both his
AB in economics with highest honors and his MBA in finance
from the University of California, Berkeley.

Quantitative Financial Risk Management
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