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researResearch
IBAF
Engineering for banking insurance and finance
Aims and objectives throughout the project
Project Leader :
Jean-Marc Le Caillec
Department:
• Image and Information
Processing
Project team:
Gilles Coppin,
Philippe Lenca,
Sorin Moga,
Jean-Marc Le Caillec,
Didier Guériot,
Grégoire Mercier,
Roger Waldeck.
Publications
Articles in a peer-review journals
[1] Jean-Marc Le Caillec. Time series modeling by a second
Order Hammerstein system. IEEE transactions on signal
processing, january 2008, vol. 56, n° 1, pp. 96-110
[2Jean-Marc Le Caillec. Hypothesis testing for nonlinearity
detection based on an MA model. IEEE transactions on signal
processing, february 2008, vol. 56, n° 2, pp. 816-821
The IBAF project exploits a specific knowhow - that is modelling, signal
processing methods and algorithms - for extracting information from banking,
insurance and finance data. The project went on to aggregate complementary
fields, thereby reinforcing its coherence, eg considering, in the models, the
behaviour of managers in time of crisis, and designing and developing market
simulation platforms or information systems for the three sectors mentioned
to better come to grip with complexity.
Main achievements of the project
Results obtained can be classified
as preliminary research in
stochastic models (particularly nonlinear)
and research more
immediately usable in the
management of portfolios and
market simulation.
From the stochastic model point of
view, work on second order
Hammerstein blind model
identification has been published. In
synthesis, blind identification
consists in identifying a model
having white noise (supposed
Gaussian) on entry and for which
only the exit is available. This means
modelling chronological sequences
or modelling non-linear
micro/macro economic
data interactions on
liquidity values or funds,
for example.
This method of
identification can be
applied for nodes (linear
and quadratic) of infinite
impulsional response
(such as auto-predictive
systems). A hypothetical
evaluation test of
Hammerstein modelling
was proposed.
In a second article, a
paper on an hypothesis test on
modelling chronological series by a
linear system has been published.
This modelling choice (linear vs
non-linear) is crucial in
understanding the evolution of
chronological series whether
financial or other. This particular
hypothesis test relies on a calibrated
parametric model ( so deriving a
finished correlation and the
possibility that its spectral density is
cancelled) contrary to other tests
which rely on autoregressive
models, the latter not being able to
verify these properties.
From an application point of view,
2008 marked the end of the ASUR
project. This project allowed the
application of an algorithm for
rebalancing portfolios based on
hidden Markov models. Results
showed that the algorithm
succeeded in surpassing the
performance of heuristic
management of portfolios generally
used by fund-managers.
2008 also saw an advance in the
CPER (Contrat Projet Etat Région)
project in market simulation, as a
first prototyping of this simulator
was formulated.
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