Minicourses
Rama Cont: Calibration of option pricing models: theory and algorithms
 The calibration problem and its role in option pricing and hedging
 Model calibration as an illposed inverse problem
 Ill posed problems and regularization methods
 Implied distributions and risk neutral densities
 Implied trees and implied diffusions
 Calibration of diffusion models: variational approach
 Calibration of diffusion models: stochastic control approach
 Calibration of jumpdiffusion models
 Calibration of LIBOR models
 Calibrationfree models: using implied volatility as state variable
References
[1] Calibration of jumpdiffusion optionpricing
models:
a robust nonparametric approach
[2] Nonparametric calibration of jumpdiffusion
models (slides)
Marek Rutkowski: Credit Risk: Modelling, Valuation and Hedging
 Introduction to Credit Risk and Credit Derivatives
 Classification of Financial Risks
 Overview of Credit Derivatives
 Defaultable Claims
 Structural (ValueoftheFirm) Approach
 Corporate Bonds
 Merton's Model
 Black and Cox Model
 Structural Models with Random Interest Rates
 ReducedForm (IntensityBased) Approach
 Stochastic Intensity of a Random Time
 General Valuation Formula for Defaultable Claims
 Recovery Schemes for Corporate Bonds
 Hybrid Models
 Modelling of Dependent Defaults
 Basket Credit Derivatives
 Conditionally Independent Default Times
 Duffie and Singleton Approach
 Jarrow and Yu Model and its Extension
 Credit Ratings and Credit Migrations
 Jarrow, Lando and Turnbull Approach
 Conditionally Markov Chains
 Bielecki and Rutkowski Approach
References
 [1] Ammann, M. (2001) Credit Risk Valuation: Methods, Models, and Applications.
SpringerVerlag, Berlin Heidelberg New York.
 [2] Arvanitis, A. and Gregory, J. (2001) Credit: The Complete Guide to Pricing, Hedging and Risk Management. RISK Books, London.
 [3] Bielecki, T.R. and Rutkowski, M. (2002) Credit Risk: Modeling, Valuation and Hedging. SpringerVerlag, Berlin Heidelberg New York.
 [4] Cossin, D. and Pirotte, H. (2000) Advanced Credit Risk Analysis.
John Wiley & Sons, New York.
 [5] Schmid, B. (2002) Pricing Credit Linked Financial Instruments.
SpringerVerlag, Berlin Heidelberg New York.

[6] Credit Risk Modelling,
Course notes

[7] Valueofthefirm approach (slides)

[8] Intensitybased approach (slides)

[9] Modelling of dependent defaults (slides)

[10] Credit ratings and migrations (slides)
Special invited lectures
Damiano Brigo: VolatilitySmile Modeling with DensityMixture Stochastic
Differential Equations
We introduce the volatilitysmile problem. Among the several approaches
that are treated in the literature, we focus on the local volatility
models setup, consisting in selecting particular functional forms for the
diffusion coefficients in the stochastic differential equation describing
the relevant dynamics of the underlying asset.
We introduce a new general class of analytically tractable models for such
dynamics based on the assumption that the assetprice density is given by a
mixture of known basic densities. We consider the lognormalmixture model
as a fundamental example, and we derive the related explicit diffusion
dynamics and show that it leads to a stochastic differential equation
admitting a unique strong solution. We also provide closed form formulas
for option prices and analytical approximations for the implied volatility
function. We then introduce the assetprice model that is obtained by
shifting the previous lognormalmixture dynamics and investigate its
analytical tractability.
A seemingly paradoxical result on the correlation between the average
volatility and the underlying asset is introduced, also in relation with
stochastic volatility models.
Further extensions of the basic model are considered. Finally, we consider
specific examples of calibration to real market option data from the
equity, FX and interestrate markets.
References
[1] Lognormalmixture dynamics and calibration to
market volatility smiles
[2] The general mixturediffusion dynamics for SDEswith a result on the volatilityasset covariance.
[3] VolatilitySmile Modeling
with DensityMixture
Stochastic Differential Equations (slides)
Dilip Madan: Purely Discontinuous Processes in Asset Pricing
The talk will outline the case for the use of purely discontinuous
price processes in modeling the statistical and risk neutral dynamics
of asset prices. The theoretical and empirical case will be presented
along with results emphasizing the lessons to be learned from such a
perspective and the advantages attained in understanding the nature of
investment. The primary example presented will be that of a Levy process
but this will generalized to address issues of stochastic volatility as
well.
References
[1] Option Pricing, Lévy
Processes, Stochastic
Volatility, Stochastic Levy
Volatility, VG Markov Chains
and Derivative Investment (slides)
[2] Optimal Derivative
Investment for Lévy
Systems (slides)
[3] Purely Discontinuous Asset Price Processes
Jan Kallsen: Risk Management Based on Stochastic Volatility
Risk management approaches that do not incorporate randomly changing
volatility tend to under or overestimate the risk depending on current
market conditions. We show how some popular stochastic volatility models in
combination with the hyperbolic distribution can be applied quite easily for
risk management purposes. Moreover, we compare their relative performance on
the basis of German stock index data.
Reference
[1] Risk Management Based on Stochastic Volatility
Short lectures
Steffan Berridge:
An irregular grid method for pricing highdimensional American options
We propose and test a new method for pricing American options in a high
dimensional setting. The method is centred around the approximation of the
associated variational inequality on an irregular grid. We approximate the
partial differential operator on this grid by appealing to the SDE
representation of the stock process and computing the logarithm of the
transition probability matrix of an approximating Markov chain. The results
of numerical tests in five dimensions are promising.
Reference
[1] An irregular grid method for pricing highdimensional American options
Dominique Dupont: Hedging barrier options: current methods and alternatives
Objectives of the paper:
To introduce a flexible method for hedging barrier options or other exotic derivatives
with regular options and to incorporate linear constraints on the hedging residual into
the hedging process. Attention is limited to static hedging strategies, that is,
strategies that allow trading in the hedging portfolio before maturity only at the first
crossing of the barrier (The paper uses the example of an upandout call).
Problems with the current methods:
 The current methods make strong assumptions on the availability of regular
options with particular strikes and maturities, or on the probability distribution of
the underlying asset.
 There is no clear way on how to adapt these methods to situations where their
assumptions are violated.
 The current methods neglect model risk, that is, the risk that the prices at which
one can trade the regular options when the barrier is attained are different from
those implied by the pricing model.
Properties of the new method:
 The new method is more general. It is based on a technique, meansquare hedging,
designed to approximate the payoff of an asset, a barrier option for example, when
exact replication may not be possible.
 The new method is user friendly. The user chooses the strikes and the maturities of
the regular options he wishes to trade, and the pricing model used to evaluate the
regular and exotic options (for example, the pricing tree). The optimal hedging
portfolio is then computed to minimize the mean of the square of the hedging
residual.
 Constraints on the hedging residual can be imposed, for example, to control the
size of the hedging error in the tails.
 Model risk can be taken into account within the meansquare hedging framework
by introducing shocks on the local volatility of each regular option at the barrier.
This creates more statesoftheworld but meansquare hedging can then be
applied as before.
Reference
[1] Hedging Barrier Options: Current Methods and
Alternatives
André Lucas: Extreme tails for linear portfolio credit risk models
We consider the extreme tail behavior of the CreditMetrics model
for portfolio credit losses. We generalize the model to allow for alternative
distributions of the risk factors. We consider two special cases
and provide alternative tail approximations. The results reveal that
one has to be careful in applying extreme value theory for computing
extreme quantiles efficiently. The applicability of extreme value theory
in characterizing the tail shape very much depends on the exact
distributional assumptions for the systematic and idiosyncratic credit
risk factors.
References
[1] Extreme tails for linear portfolio credit risk
models
[2] Tail Behavior of Credit Loss Distributions
for General Latent Factor Models
Berend Roorda: Dynamic aspects of coherent acceptability measures
Many problems in finance come down to deciding the acceptability
of a position that generates an uncertain stream of future revenues
or losses. In line with the coherent risk framework, introduced in Artzner et al. (1999),
we take our starting point in a definition of acceptability in terms of
worst expected value: a coherent acceptability measure is represented by a
collection of probability measures, called the test set, and a position is deemed
acceptable if it has nonnegative expected net value under all measures in that test set.
In this talk we discuss the extension of the onestep framework in Artzner et al.(1999)
to a multiperiod setting, in which acceptablity not only depends on an initial position,
but evolves over time on the basis of incoming information.
We first discuss some consistency problems that arise in this dynamic setting.
It may occur, even in seemingly natural examples, that e.g. initially acceptable positions
for sure turn into unacceptable. A notion of timeconsistency for acceptability measures is
proposed, in order to rule out such anomalies and to reduce mathematical and computational
complexity.
Secondly, we describe how the effect of hegding on acceptability is reflected at the
level of test sets. In particular we show how test sets turn into martingale measures
under the assumption of an ideal market for hedging instruments. This result will be
exploited to indicate the close connection between the coherent risk framework and
mainstream finance concepts as arbitrage, completeness, and valuation bounds.
References
[1] Coherent Acceptability Measures
in Multiperiod Models
[2] Martingale characterizations of
coherent acceptability measures
