Семинары

16.02.2010. Очередное заседание семинара "Вероятностные проблемы управления и стохастические модели в экономике, финансах и страховании"

(руководители - к.ф.-м.н. Аркин Вадим Иосифович, д.ф.-м.н. Пресман Эрнст Львович)

Очередное заседание семинара "Вероятностные проблемы управления и стохастические модели в экономике, финансах и страховании" состоится:

во вторник, 16 февраля 2010 г., в 17 часов.

Программа заседания:

R.Douady (RiskData, Ecole Normale Superieure of Cachan, CNRS)

1. CHAOS AND BIFURCATIONS IN 2007-08 FINANCIAL CRISIS: BUILDING A MARKET INSTABILITY INDICATOR

The impact of increasing leverage in the economy produces hyperreaction of market participants to variations of their revenues. If the income of banks decreases, they mass-reduce their lendings; if corporations sales drop, and due to existing debt they cannot adjust their liquidities by further borrowings, then they must immediately reduce their expenses, lay off staff, and cancel investments. This hyperreaction produces a bifurcation mechanism, and eventually a strong dynamical instability in capital markets, commonly called systemic risk. We show that this instability can be monitored by measuring the highest eigenvalue of a matrix of elasticities. These elasticities measure the reaction of each sector of the economy to a drop in its revenues from another sector. This highest eigenvalue - also called the spectral radius - of the elasticity matrix, can be used as an early indicator of market instability and potential crisis. Grandmont and subsequent research showed the possibility that the "invisible hand" of markets become chaotic, opening the door to uncontrolled swings. Our contribution is to provide an actual way of measuring how close to chaos the market is. Estimating elasticities and actually generating the indicators of instability will be the topic of forthcoming research.

2. ON MEASURING RISK WITH SCARCE OBSERVATIONS

We consider the problem of measuring the risk of a portfolio with scarce observations by linking it to several risk factors. A typical example is measuring the risk of a hedge fund. It is assumed that from the available data one can estimate the joint law of all the factors as well as all the 2-dimensional joint laws of the portfolio's return and increments of each factor. The problem is to recover the conditional mean of the portfolio's return given the values for all factors. We present an analytic computationally feasible solution of this problem for the case when the joint law of factors is a Gaussian copula.


Семинары проходят в здании ЦЭМИ РАН по адресу: Нахимовский проспект 47, 19 этаж, аудитория 1921-2.

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