Introduction to Risk Analysis
Gianluca Fusai
Cass Business School
MSc Mathematical Trading and Finance
Risk Analysis and Modeling
Academic Year 2012-13
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Introduction to Risk Analysis
We will introduce the course by setting the scene for:
What financial risk analysis deals with,
Where it is used,
The main different types of financial risk,
Risk in context: some historical landmarks, and
What makes risk analysis difficult.
I will describe the structure of the course.
We will also consider:
Some of the relevant history and
A flavor of recent experiences.
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Structure of the course
Two main topics
1 Market Risk:
Value at Risk as measure of risk;
Estimating VaR: parametric and non parametric approaches;
Estimating VaR for portfolios: bottom up and top down;
Monte Carlo Simulation;
Backtesting VAR;
Derivative positions.
2 Credit Risk:
Credit Derivatives and models;
Commercial Models;
Counterparty exposure.
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Reading List
There are many texts that cover risk topics but the most useful resources
are:
Main References
1 Jorion, P. (2007). Value at Risk, McGraw-Hill, 3rd Edition.
2 Christoffersen, P, (2003). Elements of Financial Risk Management,
Academic Press.
3 RiskMetrics Technical Document, available on the Moodle system
4 CreditMetrics Technical Document, available on the Moodle system
Additional Useful References
1 Alexander, C. (2008). Market Risk Analysis, Volume IV, Wiley.
2 Dowd, K, (2005). Measuring Market Risk + CD-ROM , 2nd Edition,
Wiley.
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What is Risk Analysis?
Definition
Risk Analysis seeks to measure financial risks so that they may be
controlled.
It quantifies:
The exposures to various risk factors (such as interest rates and equity
indexes),
and the prospective distribution of gains or losses at a specific horizon.
Once measured, the risk can be controlled:
by constructing hedges against the major exposures, and
by imposing limits on the remaining exposures.
If a risk limit is breached then appropriate action will be taken
immediately.
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Where is Risk Analysis Used? I
Risk analysis also forms the basis of:
Regulation and capital adequacy requirements,
Internal controls, and
Communication with clients.
It is equally relevant in:
Banking,
Insurance, and
Investment
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Where is Risk Analysis Used? II
Example (Risk Analysis in Investment)
In many types of fund management, including pension funds, unit trusts
(mutual funds) a great deal of emphasis is placed on risk budgeting.
A detailed plan is prepared of what risks need to be taken in order to
reach a particular expected return goal.
The fund is committed to stay within the budgeted risk limits, which
are either negotiated with clients or communicated to them (either
directly or indirectly).
Typically (but not always!) the risks are adequately controlled within
the budget – while the expected return premium may or may not be
achieved.
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The Main Types of Risk
It is usual to distinguish among the following kinds of risk:
1 Market risk (due to changes in market values),
2 Credit risk (of credit contingent claims, including sub-prime debt,
CDOs, CDSs etc).
3 Liquidity Risk (risk of markets drying up and large bid/ask spreads
appearing).
4 Operational Risk (of all other kinds of mishaps and disasters), and
We shall be primarily concerned with market and credit risks, without
denying the importance of other risks.
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Some Historical Landmarks
Financial Bubbles and Crashes ..are as old as the hills:
1634-7 Tulip mania
1711 South Sea bubble
1926-9 Bull market leading to crash and the great depression
[City of London deregulation 1986]
1987 Black Friday (/Monday) crash(es)
2000-2 Dot com bubble
2007-? Banking meltdown
2010-? Sovereign crisis
[More about this on Jorion, chapter 2]
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Evolution of Analytical Techniques
1938 Bond duration
1952 Markowitz mean-variance analysis
1966 Multi-factor equity models
1973 Black-Scholes option pricing, and “Greeks”
1993 Value at Risk (VaR)
1994 RiskMetrics (for market risk)
1997 CreditMetrics (for credit risk)
[see Jorion’s more complete list]
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Landmarks in Regulation of Commercial Banks
1988 Basel I Accord (fully implemented 1992)
Minimum capital ratios to cover credit risk, as
Risk Capital ≥ 8% of Risk-Weighted Assets,
but led to increased regulatory arbitrage.
1996 Added charge for market risks attributable to proprietary
trading, Internal models approach introduced VaR to determine the
capital required.
1999 Repeal of the Glass-Steagall Act, which separated banking and
securities functions in the US.
2004 Basel II Accord (implemented 06-09) introduced 3 pillars:
Minimum regulatory requirements,
Supervisory review, and
Market discipline also Quantified Operational Risk..
2010 Basel III framework published December 2010.
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Why is Risk Analysis Difficult?
Never make forecasts, especially about the future
(Samuel Goldwyn)
The stock market will fluctuate
(J. P. Morgan)
Problem
How well can you navigate ahead using only the rear view mirror?
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Limitations of Risk Models
Among the many reasons for this:
Asset prices follow rather unstable processes;
Derivatives contracts often make payoffs extraordinarily complex
functions of the underlying factors;
We are dealing with very large numbers of risk factors and security
holdings;
It is difficult to model many factors at once;
A lot of computation may be required to analyze a large portfolio of
holdings.
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SP500 2000-2004. And afterwards?
2004 2004 2005 2005 2006 2006 2007
1050
1100
1150
1200
1250
1300
1350
1400
1450
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1550
SP500 Index: 2004−July 2007
Time
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What happened next
2006 2006 2007 2007 2008 2009
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
SP500 Index: 2004−2009
Time
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SP500 1950-2011
1954 1960 1965 1971 1976 1982 1987 1993 1998 2004 2009
0
200
400
600
800
1000
1200
1400
1600
SP500 Index: 1950−2011
Time
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Multiplicity of Factors
We need a large number of risk factors to represent the risks of
bonds, equities and currencies in today’s world.
Simply from a statistical point of view, this makes life difficult.
The empirical observations that we have don’t amount to much if we
need to model the joint behavior of a hundred or so risk factors.
Multivariate space is only sparsely inhabited by the data.
Many statistical papers on “multivariate techniques” mean
considering at most 3 or 4 variables!
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Conclusions: Learning outcomes
On completion of this module students will be able to:
demonstrate systematic and comprehensive knowledge of the different
sources and types of financial risk
demonstrate sound appreciation of the different purposes of risk
analysis and modelling and the steps involved in defining, measuring
and managing risk
appreciate the importance of risk management for a wide range of
stakeholders at trader, corporation and institution level
respect and value the role of financial regulation and understand the
issues related to its reform.
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Introduction