This workshop takes place at least once a month on Wednesdays (room N305, time and date as advertised).

Professors from other departments and institutions, as well as PhD students, are more than welcome to attend the workshop so as to get the most recent information on the research areas developed in our department and to foster possible collaborations on common projects.

contact: Marie Kratz (kratz@essec.edu) and Guillaume Chevillon (chevillon@essec.edu) if you want to be included in the mailling list

 

 

Suzanne EMMER (UBS, Zürich)

Thursday, May, 5th, 2011 at 12:30 pm, at La Defense EEE, room 201

Credit Stress Loss

 

After a short overview of currently used credit risk measures and the stress testing landscape we give an introduction to different stress testing methodologies which are applied to the wealth management and business banking portfolio.

 

Shubho DAS (Indian Institute of Management Bangalore)

Wednesday, April, 20th, 2011 at 2 pm, Nautile # N305 -  Cergy Campus

On few Measurement Problems in Sports

 

Application of statistical and OR methods in the domain of sports has been on steady rise, leading to academic conferences and journals dwelling exclusively on this domain.  In this talk, we would discuss approaches to solving couple of such problems. The up-to-date position of competing teams based on points obtained by them in the middle of any round-robin (stage of) tournament may inadequately reflect their actual relative position, because of the strength of the opposition faced till that stage. To help the followers of the game, as well as to possibly help the teams to strategize, a simple probably matrix based approach followed up by computation of the expected points may easily bring clarity to the situation. While an unstructured or unconstrained way of updating these probabilities, reflecting individual perspective, at successive stages of the tournament may be ok, it being ad-hoc, also suffers from arbitrariness and may lack consistency. In that context, we explore how a model based Bayesian adaptation can work effectively. In cricket, batting average has always been used as primary measure of performance of a batsman. But traditional batting average exhibits serious limitation in reflecting true performance of a batsman in light of notout innings. Treating notouts as censored data, adaptation of Kaplan-Meir estimator provides a more reasonable solution, but it still suffers both from conceptual as well as operational problems at certain situations. A generalized class of geometric distribution (GGD) is proposed in this work to model the runs scored by individual batsmen, with the generalization coming in the form of hazard of getting out changing from one score to another.  We consider the change points as the known or specified parameters and derive the general expressions for the restricted maximum likelihood estimators of the hazard rates under the generalized structure considered. Given the domain context, we propose and test ten different variations of the GGD model and carry out the test across the nested models using the asymptotic distribution of the likelihood ratio statistic. We propose two alternative approaches for improved estimation of batting average on the basis of the above modeling.

  

Véronique HEIWY (Université Paris Descartes / LIPADE)

Wednesday, March, 16th, 2011 at 2:15 pm, Nautile # N305 -  Cergy Campus

Will the Next Generation of Campus be Intelligent?

 

Ambient Intelligence is a multi-disciplinary research topic combining ubiquitous computing, distributed architecture and aiming at providing context-aware support to people in various domain such as domotic, health-care or eduction.

After a brief presentation of “Ambient Intelligence” (Aml) and its close relation with Multi-Agent systems (MAS), this presentation will show how Aml services could help the actors of the Paris Descartes Technology Institute (i.e. students, professors and staff) by describing Aml scenarios and giving a possible implementation of these scenarios. Aml provides new solutions but raises also new problems such as security, privacy that should be taken into account.

 

Doug ANDREWS (University of Southampton, UK)

Wednesday, February, 3^rd, 2011 at 1 pm, at La Defense EEE, room 104

Risk Management Considerations for the Canada Pension Plan: A Case Study

 

What are the risks that the Canada Pension Plan faces and how are they managed? This presentation begins with a review of the governance structure, the actuarial valuation method and the automatic balancing mechanism. It then examines particular assumptions, such as fertility, mortality, migration, productivity and investment. It explains the risks, discusses the methods used to derive the assumptions, and outlines some of the sensitivity tests used to quantify the risk.

 

 

 

 

We consider the problem of prediction in a time series when the conditioning event is extreme. The quantities of interest are the limiting conditional distribution of future events given that the past was extreme, and the normalizing functions needed to obtain non degenerate these limit laws. I will consider two classes of processes: GARCH-type and stochastic volatility processes. The main difference is the presence or absence of clustering of extremes.

 

Informed Momentum Trading versus Uninformed “Naïve” Investors Strategies

 

We construct a zero-net-worth uninformed "naive investor" who uses a random portfolio allocation strategy. We then compare the returns of the momentum strategist to the return distribution of naive investors. For this purpose we reward momentum profits relative to the return quintiles of the naive investors with scores that are symmetric around the median. The score function thus constructed is invariant and robust to risk factor models. We find that the average scores of the momentum strategies are close to zero (the score of the median) and statistically insignificant over the sample period between 1926 and 2005, various sub-sample periods including the periods examined in Jegadeesh and Titman (1993 and 2001). The findings are robust with respect to sampling or period-specific effects in our simulations where we randomly select 10 years for 100 times.

 

 

The (Enormous) Cumulative Economic Relevance of Customer Satisfaction - A PLS Based Approach

Claes Fornell presents research and results, from an actual stock portfolio, which seem contradictory to conventional wisdom.  First, it is possible to consistently outperform the stock market.  Second, this can be done without taking on more risk.  While inconsistent with financial theory, the results are consistent with SCIENCE in the more general sense: Knowledge can be used – in just about any context - in order do better (than competition) and it can be used to reduce risk.

In order to gauge the probable future benefit of any corporate economic asset – such as customer satisfaction – it is necessary to examine both contemporaneous and intertemporal effects.  The latter effects have been overlooked in previous studies, but it turns out that they are quite sizable and have about the same size as the contemporaneous ones.  They are obtained from the power of customer satisfaction portfolio returns to predict future excess market returns. If investors would pay more attention to the primary sources of future cash flows – and most of them come from repeat consumer spending - aggregate consumer utility would increase and equity markets would benefit from greater efficiency.