Quantitative Financial Risk Management - Henry Stewart Talks

Quantitative Financial Risk Management
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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.