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UPCOMING SEMINARS
You are kindly invited to the next
Geneva Research
Collaboration
seminar. The seminar will take place on Monday, 21 March at
17-00 at CERN, conference room 40-S2-B01.
Presentation by Dr. Antti Korhonen:
STRATEGIC FINANCIAL MANAGEMENT IN BANKING AND
INSURANCE: A MULTIPLE GOAL STOCHASTIC PROGRAMMING
APPROACH
Abstact: The
paper discusses a multi-stage stochastic programming approach to the strategic
financial management of banks, life insurance companies, pension funds and
multinational financial conglomerates. The model is an extension of an earlier
model designed to deal with the strategic asset and liability management problem
of a multi-company group with main emphasis on non-insurance activities. Many of
the model components are common to all the institutions and the paper therefore
first gives an outline of these common components and the general model
structure. The special features of life insurance are then discussed in more
detail. The paper ends with some general notes on the use of scenario-based
dynamic optimization in strategic planning.
PAST
EVENTS
You are kindly invited to the next
Geneva Research Collaboration
seminar. The seminar will take place on
Wednesday, 16 February at 17-00 at
CERN, AB Auditorium I inBuilding
6-2-024.
Presentation by Laurent Barras:
Asset allocation and
data-snooping.
Abstact: This paper examines
the impact of real-time uncertainty on the performance of mean-variance
conditional asset allocation. Real-time uncertainty is modeled by implementing a
large number of conditional strategies that an investor could reasonably choose
from. Using data from twelve 12 domestic equity markets between January 1990 and
September 2004, we find that real-time uncertainty greatly reduces the
performance of conditional asset allocation and makes it highly sensitive to the
specification choices. Moreover, it turns out that the different solutions used
to mitigate the impact of real-time uncertainty are not effective and call for
more efficient implementation of these strategies. All these findings are
consistent across different levels of investor's risk aversion and transaction
costs.
You are kindly invited to the next
Geneva Research Collaboration
seminar.
The seminar will
take place on Wednesday, 26 May at 17-15
at CERN, Room 40-S2-B01.
Presentation by Olivier Scaillet:
"A Kolmogorov - Smirnov type test
for positive quadrant dependence"
Abstract:
We consider a consistent test that
is similar to a Kolmogorov-Smirnov test, of the complete set of restrictions
that relate to the copula representation of positive quadrant dependence. For
such a test we propose and justify inference relying on a simulation based
multiplier method and a bootstrap method. A Monte Carlo experiment is used to explore the finite
sample behavior of both methods. A first empirical illustration is given for US
insurance claim data. A second one examines the presence of positive quadrant
dependence in life expectancies at birth of males and females among
countries.
You are kindly invited to the next
Geneva Research Collaboration
seminar.
The seminar will
take place on Wednesday, 19 May at 16-00
at CERN, Room 40-S2-B01.
Presentation by Nikita Stepanov (ITEP/CERN/GRC):
"Predicting randomness" experiment: new perspectives and results from the
test run.
Abstract:
“Predicting
randomness” experiment was proposed about one year ago with the purpose of
investigating the randomness of bit sequences generated from different “random”
sources so as to elucidate if such sequences may be locally predictable in
statistically significant sense by the human being or “intelligent” computer
program. The experiment was
designed to be a large scale internet initiative which could allow thousands of
participants around the world to be involved. During the past year we developed
the hardware and software, a set of statistical tests, which allows one to
estimate the randomness of the experiment data sources and the quality of
predictions of the experiment participants. All this allowed us to launch the
first “technical” run of “Predicting randomness” experiment a few months ago.
Although this event was not announced officially, several human beings and
artificial predictors took part in the test run. The preliminary analysis of the
data accumulated has been finished recently. In this talk we would like to
outline the present status of the experiment hardware and software and present
some interesting observations derived from the test run data analysis; in
particular, the intriguing similarity of prediction results of the human and
artificial predictors. The performance tests fulfilled during this run clearly
indicate that now we are ready to conduct the experiment in full scale, at the
same time, we have realized that the primordial goals of the experiment and
perhaps, even the whole experiment scheme have to be adjusted. We think it can
be made more attractive to participants and more practically feasible, and here
we would like to discuss new proposals for our initiative.
You are kindly invited to the next
Geneva
Research Collaboration seminar.
The
seminar will take place on Wednesday, 5 May at 15.30
in GRC
office at the
following address: Rue de Veyrot 12, CH-1217 Meyrin-Geneva (click here for GRC
location map).
Presentation
by Couderc Fabien on
"Time-to-Default : Life Cycles, Global and Industry Cycle
Impacts"
Abstract:
Investigating once again time-to-default
of individual firms, from our semi-parametric framework
this study proposes a comprehensive analysis of the determinants of
default. We assess whereas rating agencies succeed to achieve their goal or not,
and further shed light on the need for conditioning with respect to economic
conditions even for through-the-cycle ratings. We exhibit various effects
bearing strong implications in credit risk management depending on investment
horizon as well as rebalancing frequency.
In addition extensive studies of
log-linear parametric models of instantaneous probabilities reveal that both
firms life cycles within a given risk class and the global business cycle
matter. Concerning the debate between structural and reduced form models, we
overall point out how lag information can substantially improve performance of
simple models. Indeed, we show that some factors convey anticipations of future
bad default state, even if differences can be observed among studied grades
and industries, as well as the magnitude of their impacts. These underline
importance of ratings in financial decisions.
However this
semi-parametric setting indicates that the business cycle along with the
credit cycle are far from being sufficient to extract all joint movements in
default probabilities. Investigating industry default processes, we
illustrate strong discrepancies between industries which may partially fill this
gap. In particular our results suggest that the default and business cycles are
not always procyclical which can not be caught through economic factors.
Further the default cycle both leads and persists after global cycles which may
only be captured by endogenous modelling of aggregate components of the default
cycle. Therefore, this "snow ball" effect appears to be an important
ingredient to include in a good predictive model.
You are kindly invited to the next Geneva Research Collaboration
seminar.
The seminar will take place on
Thursday 19 February at 15.30
in GRC office at the following address: Rue de Veyrot 12, CH-1217 Meyrin-Geneva (click here for
GRC location map).
Presentation by
Couderc Fabien on : A Default Duration Model in a Multivariate
Setting Consistent with Stylized Facts
Abstract:
This paper
studies time-to-default of individual firms in a multivariate setting. We
concentrate our efforts on analysis and modelling of default intensities. Hence,
this research can be classified into the so-called reduced form class but our
framework exploits information contained in structural factors (macro-economic,
business and firm specific).
Using a Standard & Poor's database,
non-parametric and semi-parametric studies of intensities show that both firms'
life cycles and economic conditions matter. In particular, the largest movements
in intensities are due to economic cycles whereas short and mid term trends are
driven by aging effects. Moreover significant factors varies with the horizon,
the studied grades and the industry, as well as the magnitude of their impacts.
Analysing aggregated default processes, we observe that they can be used as an
indicator of local business conditions, which exhibits markovian
properties.
As most of previous works consider proportional hazard
specifications with constant baseline, we propose to extend these models and further use
random scale changes (i.e. speed varying hazard models) showing especially the
lack of power of non trivial proportional models at short horizons. Further, our
specification allows to achieve realistic correlations of default through
auto-correction from the aggregated default process. Finally, duration
predictions can be run out through simulations thanks to the multivariate hazard
construction method.
 You are kindly invited to the next
Geneva Research Collaboration
seminar.
The seminar will
take place on Wednesday, 12 November at 16-30
at CERN, Room 40-S2-B01.
Presentation by Prof. Olivier
Scalliet on:
Risk Management Using Econometrics
Abstract:
The objective
is to continue the development of econometric tools for an improved assessment
and monitoring of financial and insurance risk. The proposed econometric tools
are both of parametric and non-parametric nature and share the aim of improving
the modeling of the distribution of risk and of the dependencies that can
occur between different sources of risk. The non-parametric approach and
the techniques to be investigated are based on nonparametric estimators based on
asymmetric kernels which avoid the bias that occurs when a random variable is
bounded. The asymmetric nature of these estimators allows the modeling of
distributions that have fat-tails or of distributions that are bounded at some
point. It is envisaged to extend significantly the empirical investigations and
to improve certain technical aspects of these estimators. The econometric tools
under current development may be used in many areas of finance. For example,
they can be applied to various types of data such as interest rates, exchange
rates, stock returns. As such they should allow a better understanding how to
control financial losses for banks and insurance companies. The efforts will
therefore be oriented towards financial econometrics modeling with relevant data
coming from economics, finance and insurance fields. The research is oriented
theoretically as well as empirically. Methods tailored to risk management issues
are to be developed theoretically, to be compared numerically with alternative
methods using Monte Carlo experiments, and to be applied to empirical data to
get a better understanding of risk behavior. We plan to extend the current
results to direct modeling of Value at Risk and expected shortfalls as well as
to the multivariate case.
You can have a look at
the full
text of the research paper as well as at presentation
materials.
You are kindly invited
to the next Geneva Research Collaboration
seminar.
The seminar will take place on Tuesday, 30 September at 17.00 in GRC
office at the following address: Rue de Veyrot 12, CH-1217
Meyrin-Geneva (click here for GRC location map).
Presentation
by Couderc Fabien on Credit
Risk Dynamics:
Forecasting Rating Transitions Matrices
Abstract:
Nowadays,
as one of the most productive area of modern finance, credit risk research has
still an explanatory prospect. Nevertheless, new regulatory requirements and the
growing investments in credit derivatives induce needs for predictive
measurements.
Therefore,
this project consists in the development of a coherent methodology to provide
forecasts of the well-known rating transition matrices at various horizons. In
addition, our forecasts aim to be used as inputs of dynamic credit risk models
so as to bring consistency in the current way to proceed. Indeed, numerous
recent dynamic models of credit use static and time-homogenous transition
matrices as inputs so as to draw dynamic outputs. Our methodology will supply
for time-heterogeneous matrices directly and exclusively from rating event data,
avoiding problems of event scarcities and allowing smart aggregations.
Instead
of looking only straight transitions to default our dynamic model of migrations
take care of both probabilities’ evaluation and evolution. This study will be
empirically supported by rating data from Standard & Poor’s CreditPro
database The model will also allow us to investigate several issues such as the
importance of timing versus aging effects, namely to determine if macro-economic
conditions are more informative than firms’ life cycles. Moreover, for
prediction purposes, conditional and unconditional moments of the whole
transition matrices will be available so as to predict usual inputs of
traditional portfolio models by simulations.
Click
here to access full text of research
paper
You are kindly invited to the next
Geneva Research
Collaboration seminar
Tuesday, 17 June, 16.30-17.30
hours
PS conference room 2-024 building 6, CERN, Meyrin
Note: Participants
from outside CERN, please confirm participation with name and affiliation by
e-mail, at the latest one day in advance.
Dr. A. Din, Geneva Research
Collaboration
"Trend analysis of financial time
series"
Abstract:
A large part of the many claims for
succesfully predicting the directional movement of financial markets is based on
some kind of scheme for "riding the right trend". A problem with such claims is
the lack of general agreement about the definition of what constitutes a "trend"
and how good it is. The talk discusses financial time series in terms of a
discrete change representation which allows for a rather straightforward
definition of a trend process and a range process associated with the time
series.
.
Trend analysis is first carried out for random walks so as to
determine a certain reference probability distribution for the range process. It
is shown how it may be possible to identify a statistically significant signal
for trendy behaviour of a financial time series through the appearance of
enhancements of the lower tail of the cumulative range probability distribution
function. This distribution function leads in a natural way to the definition of
a Trend Index a Range Index.
As an example, the range properties of daily
prices for a few currency crosses, world indices and blue chip stocks are
investigated. Results are presented for these time series which show distinct
trend characteristics of importance for better understanding the dynamics of
financial forecasting.
Full text of research paper
Background
information:
The Geneva Research Collaboration (GRC) is a
non-profit Swiss foundation dedicated to the support of interdisciplinary
research in natural and social sciences, to the development of novel economic
applications of this research, and to contributing to make Geneva a node of
excellence in an international scientific and economic research network.
The
current research of GRC is concentrated on mathematical and econophysics models
applied to financial forecasting, data processing, and risk management. The
applications endeavour to use new conceptual model structures which are
developed into operational tools through the integration of advanced computing
techniques
For further information please consult the GRC web
site: www.genevaresearch.org
Dear Colleague,
 You are kindly invited to the next meeting of the GRC time
series forecasting research group.
The meeting will take place on Wednesday, 21
May at 16.30 hours
at CERN, Building 40
Room R-C 10
Presentation by Allan Din on:
Forecasting of
interest rates using neural network
models
Abstract:
During the past couple of years,
interest rates around the world have declined to very low levels and there is a
quest in the financial community for better understanding the dynamics of this
situation. In the paper, the development of the monthly Libor and Swap rates are
investigated over a 10 year period (1993-2002) in relation to a number of
potentially important factors. For the case of Swiss interest rates, these
factors include a range of rates for different maturities, gross domestic
product, inflation rate and exchange rates.
Interest rate forecasting models
are developed, which endeavour to include the statistically most significant
factors defined in terms of time lag changes of individual time series as well
as of relative movements of different maturity rates. The models are constructed
on the basis of backpropagation neural networks involving one hidden layer of
5-10 nodes. Model validation is done for a period covering the past 5 years with
the model retraining carried out every 3 months.
The results for forecasting
the Libor 3 month rate and the Swap 5 year rate on a forecasting horizon of 12
months show quite a good reliability. The directional movement is forecasted
correctly in 83% of the months of the validation period. The quality of the
models for the Libor 3 month rate and the Swap 5 year rate on a forecasting
horizon of 3 months is somewhat lower, with only 61-63% of accuracy in the
directional forecasting.
Click here to access the corresponding research paper.
Dear
Colleague,
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You are kindly invited to the next meeting of the GRC time
series forecasting research group.
The meeting will take place on
Thursday, 20 February at 16.00 hours
at the CERN, Room
304-1-0001A
Presentation by Nikita Stepanov, Andre Douka, Nikolaj Krasnikov
on:
Predicting randomness - Outline of an experimental
design
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Paper
abstract:
We propose
conducting an experiment to investigate the randomness properties of bit
sequences generated from different “random” sources, including computerized,
physical and economic ones, so as to elucidate if such sequences may be locally
predictable in statistically significant sense. A sign of local predictability
may be said to be demonstrated, for example, by virtue of a capacity by a human
being and/or a computer to recognize and exploit certain patterns or other
repeatable behavior of specific digital data sources.
According to conventional wisdom and modern science, one would
expect a negative result of such an experiment, that is, the absence of any
statistically significant predictive capacity in relation to any truly “random”
process. Nevertheless, we believe that it is of interest to conduct such an
experiment for two good reasons: first, it is a fact that it has proven to be
difficult to give a positive definition of a truly “random” process, and many
commonplace bit sequences are in reality only pseudo-random. Then, there is a
multitude of real life claims of predictable behavior of economic time series
representing so-called efficient markets which supposedly should be random.
To read the entire paper click here.
Dear
Colleague,
You are kindly invited to the next meeting of
the GRC Time Series Forecasting research group.
The
meeting will take place on Thursday, 23 January at 16.00
hours
at the GRC office, Rue de Veyrot 12, 1217
Meyrin
Agenda:
Presentation by Prof. Michel Maignan,
Banque Cantonale de Genève on:
"Lowest level of interest rates
since decades
Bearish behaviour of -33% per year
Highest exchange rate
since 4 years:
New quantitative methods for financial analysis and
forecasting?"
practice and challenges of Technical Analysis of financial data"
at CERN
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Prof. Michel
Maignan Geostatistics/ Statistics Universite de
Lausanne
Membre de la Direction
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GRC Risk management research group meeting.
Wednesday,
11 December at 17.30 hours
at the GRC office, Rue de Veyrot 12, 1217
Meyrin
Presentation by Mikael Angberg on
"Implementing
financial simulation models using Monte Carlo techniques and
Java."
Abstract:
"In this talk I will briefly introduce
the use of Monte Carlo methods in financial simulation models, as well as
discuss some issues related to non-uniform pseudo-number generation, variance
reduction techniques and correlation/co-movement. Some practical examples of
simulation models for option pricing, mortgage-backed securities and Value at
Risk implemented using Java and the Java Analysis Studio and COLT frameworks
will be presented."
GRC Time Series
Forecasting research group meeting
Wednesday, 27
November at 17.30 hours
at the GRC office, Rue de Veyrot 12,
1217 Meyrin
Presentation by Ramo Gencay (University of
Geneva/Windsor):
"Volatility on different time
scales"
GRC
High Performance Computing research group
meeting
Wednesday, 4 December at 17.30
hours
GRC office, Rue de Veyrot 12, 1217 Meyrin
Presentation
by Oxana Smirnova
and Jukka Klem
"The NorduGrid"
The Grid is a technology to
share and access seamlessly computing
resources that are not subject to a
centralized control. The computing
resources are connected together through
a layer of software called
the middleware, which uses standard, open,
general purpose protocols
and interfaces. This middleware forms the glue
binding the resources
into a virtual system.
NorduGrid project (www.nordugrid.org) develops openly available
middleware
and operates a production quality grid testbed. The NorduGrid
system and
its usage will be presented.
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Wednesday, 23 October, 18.00-19.00
hours
Room SS-D01 building 40, CERN, Meyrin
Prof. Urs Luterbacher, Graduate Institute of International
Studies, Geneva:
"Modeling Policy Choices in
Climate Change"
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Abstract:
The
talk will explain how climate policy divergences between major countries can be
examined with the help of a dynamic continuous time simulation model, but with
parameters that can be potentially estimated empirically.
The model uses the
SPARE simulation system which is based in part on software constructed at the
Graduate Institute, in part on the CERN based PAW software package.
It allows the user:
1) to fit model output to historical data series
with procedures based upon the CERN developed MINUIT minimization package,
and
2) to apply a sequential decision making analysis,
similar to game theory, in order to determine why an international solution to
the climate change problem is preferred by a particular country.
The system also helps in determining possible
cooperative solutions to divergent national policies.
A simulation model
prototype is constructed with entities that have the characteristics of the US,
the EU and a Rest of the World category. Some preliminary analysis will be
presented as well as suggestions for further studies along the same lines.
Reference |
Research group discussion meeting of the GRC time series
forecasting group will take place on Tuesday, 15 Oct at 17.30 hours at
CERN
Building 160 (near main entrance) Room 1-009
Meyrin
Prof.
N. V. Krasnikov, Institute of Nuclear Research, Moscow
will lead the
discussion about
"Uncertainty in the choice between economic
models"
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GRC
seminar
Dr. Foort Hamelink, Lombard Odier Darier Hentsch,
Geneva,
Thursday, 26 September 16.30-17.30 hours
CERN
room 60-6-002 building 60
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Empirical factor analysis of
the performance of global equity portfolios
Abstract:
Equity
returns are believed to be strongly influenced by country, sector and style
effects. A key issue is to be able to disentangle those various effects from one
another. In particular, differences between country returns may simply reflect
differences in the sector composition of country markets, which makes it clearly
difficult to disassociate both effects. Similarly, from 1999-2001 the relative
performance of Growth versus Value might be solely due to the striking
performance of the Technology and Telecommunication sectors. For global equity
portfolio managers, it is crucial to identify which factors offer the highest
diversification benefits and return potential. We apply a multi-factor approach
to estimate "pure" country, sector and style factor returns. Using data going
back to 1990, we identify the major changes that have occurred in developed
markets until 2001. Our various indicators clearly point out the growing
influence of sector factors. However, country effects remain important and there
is no clear-cut evidence that sector factors dominate country factors. Style
factors such as Growth, Value and Size also remain significant, even once sector
and country effects are deduced. Finally, we show that momentum strategies based
on sector returns offer substantial gains, while momentum strategies based on
country returns do not. These findings suggest that, while diversification and
return benefits from sector strategies have become substantial, managers should
continue to monitor carefully country as well as style rewards and risks.
Rerefence:
Country, Sector or
Style: What matters most when constructing Global Equity
Portfolios? An
empirical investigation from 1990-2001
by F. Hamelink , H. Harasty and P.
Hillion
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GRC Research Group
Meeting
"Modelling of univariate time series"
Tuesday, 23 July, 14:00 - 15:00
CERN, room
160/1-009
Speakers:
Dr.Allan Din (left),
Geneva Research
Collaboration & CERN,
Introduction, and
Dr.Nikita Stepanov (right),
CERN, Main speaker
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Modelling of the
univariate time series.
Abstract:
After the
introduction to the field of the time series forecasting and modeling which will
include the formal definitions of the two essentially different kinds of
problems and brief attempt to classify the modern methods applied, the speaker
will try to advocate the "computer scientist`s" or "algorithmic" view of the
problems defined which appears to be somewhat unusual and perhaps even unnatural
for the bulk of the scientific community involved in these kinds of researches.
In particular, the speaker will sketch the general theoretical tools and
universal solutions of the probabilistic induction problems obtained already
quite a long time ago. There is however the common drawback of the general
elegant proofs, namely, often they are a bit far away from practical
applications. Thus, after a rather general discussion the speaker will give an
introduction to the phenomenological model (called Dukascopy by its author)
which seems to be surprisingly good for the description of the short term
behavior of the time series induced by the dynamics of the complex
systems.
We are planning
also the online Dukascopy based software demonstration. Everybody interested in
this will be able to check his skill trying to forecast the behaviour of the
natural stochastic process induced by the cosmic rays.
Some useful
links:
http://www.cwi.nl/~paulv/papers/solomonoff.ps
http://www.idsia.ch/~juergen/toesv2/
http://www.dukascopy.com
http://www.cs.auckland.ac.nz/CDMTCS/chaitin/
http://www.cwi.nl/~paulv/
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Dr. Allan Din,
"Optimization and forecasting with financial time series"
Tuesday, 25
June, 14-15 hours
CERN, room 160/1-009
Abstract:
The talk reviews
analytical techniques which may be applied to different types of financial time
series.Optimization techniques are discussed from the perspective of risk
analysis and optimal asset allocation. Forecasting is discussed within the
framework of parametric and non-parametric statistical techniques, involving
neural networks and genetic
algorithms. |
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Prof. Rosario Mantegna,
University of Palermo,
Professor Mantegna is a leading expert in
the field of theoretical and empirical modelling of complex systems. Since 1989
a major focus of his research has been studying financial systems using methods
of statistical physics.
He is a co-author of the essential book on the
subject "An Intruduction to Econophysics".
Prof. Mantegna spoke on the topic
of:
"Econophysics and quantitative finance." |
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Abstract:
During the last years the number of
physicists interested in the analysis and modeling of financial markets for
academic and/or professional reasons is rapidly increased. Finance is today more
and more a quantitative discipline and risk management is a multidisciplinary
task needing several professionals to be performed at a top level. Physicists
concur to these activities and to the modeling of a fascinating "complex system"
with their professional and conceptual background.
6 May, 16.30 hours
CERN Building 40, room
S2-B01
Click here for CERN access
map. |
Background information:
Giovanni
Bonanno, Fabrizio Lillo and Rosario N. Mantegna
Levels of Complexity in Financial Markets, Physica A, 299,
16-27
J. Doyne Farmer, Santa Fe Institute
Physicists Attempt to Scale the Ivory Towers of
Finance
Prof. Alex Gammerman, Royal
Holloway University, London
Professor`s Gammerman`s current research interests lie in the
field of machine learning, inductive/transductive inference and intelligent data
analysis.
The title of his lecture at the University of Geneva
was:
"Predictive algorithms and confidence measures based on
Algorithmic Randomness Theory". |
Abstract:
The talk reviews some theoretical and
experimental developments in building computable approximations of Kolmogorov`s
algorithmic notion of randomness. Based on these approximations a new set of
machine learning algorithms have been developed that can be used to make
predictions and to estimate confidence and credibility. Some recent applications
of these techniques in medical diagnostics, recognition of hand-written digits,
and financial predictions will be presented.
17 April, 16.30 hours
Uni Mail, Room
5020
Blvd du Pont d`Arve 40, Geneve
Thursday, 24 January, 2002, 16.30
Main Auditorium, CERN
Prof.
Ilya Prigogine, Universite Libre, Bruxelles, 1977 Nobel Laureate in
Chemistry
"Dynamics of correlations for integrable and non-integrable
systems -
A two levels formulation of laws of nature"
Tuesday January 15, 2001, 16.30-17.30,
Room 2193, UniMail, Universite de Geneve, Boulevard du Pont-d`Arve
40
by Prof. Olivier Scaillet, Universite de Geneve:
"Nonparametric
estimation of conditional expected shortfall"
Abstract:
We consider a nonparametric method to
estimate conditional expected shortfalls, i.e. conditional expected losses
knowing that losses are larger than a given loss quantile. We derive the
asymptotic properties of kernel estimators of conditional expected shortfalls in
the context of a stationary process satisfactory strong mixing conditions. An
empirical illustration is given for several stock index returns, namely CAC40,
DAX30, SNP500, DJI, and Nikkei225.
Keywords :
Nonparametric, Kernel, Time Series,
Conditional VaR, Conditional Expected Shortfall, Risk Management, Loss Severity
Distribution.
Wednesday, 12 December, 2001, 16.30
hours
CERN
Bruno Estier, Banque Lombard Odier
& Cie
Serge Laedermann, Geneva Finance
"The practice and
challenges of Technical Analysis of financial data"
Monday, 12 November, 2001, 16.30 hours
University
of Geneva, Uni Mail,
Prof. M. Maignan, Banque Cantonale de Geneve
and Universite de Lausanne
Prof. M. Kanevski, IDIAP
"Mortgage Interest
Rate Analysis in Geneva"
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