Invited Session Mon.3.H 3027

Monday, 15:15 - 16:45 h, Room: H 3027

Cluster 7: Finance & economics [...]

Risk management in finance and insurance


Chair: Walter Farkas



Monday, 15:15 - 15:40 h, Room: H 3027, Talk 1

Walter Farkas
Acceptability and risk measures: effectiveness, robustness and optimality

Coauthors: Pablo Koch-Medina, Cosimo-Andrea Munari


We discuss risk measures generated by general acceptance sets allowing for capital injections to be invested in a pre-specified eligible asset. Risk measures play a key role when defining required capital for a financial institution. We address the three critical questions: when is required capital a well-defined number for any financial position? When is required capital a continuous function of the financial position? Can the eligible asset be chosen in such a way that for every financial position the corresponding required capital is lower than if any other asset had been chosen? Our discussion is not limited to convex or coherent acceptance sets and this generality opens up the field for applications to acceptance sets based both on Value-at-Risk and on Tail Value-at-Risk.



Monday, 15:45 - 16:10 h, Room: H 3027, Talk 2

Cosimo-Andrea Munari
Risk measures and capital requirements with multiple eligible assets

Coauthors: Walter Farkas, Pablo Koch-Medina


We discuss risk measures associated with general acceptance sets for financial positions. Such risk measures represent the cost expressed as the minimum additional capital amount that, when invested in a pre-specified set of eligible assets, makes an unacceptable position acceptable. In contrast to earlier papers where the attention was focused on a single eligible asset, here we allow for multiple eligible assets. We show that the multiple eligible asset case can be reduced to the single asset case, provided that the set of acceptable positions can be properly enlarged. This is the case when it is not possible to make every financial position acceptable by adding a zero-cost portfolio of eligible assets. The results here simplify and generalize results of Fritelli and Scandolo from 2006 and of Artzner, Delbaen and Koch-Medina from 2009. However, in contrast to the literature, we do not impose any coherence or convexity requirements on the acceptance sets.



Monday, 16:15 - 16:40 h, Room: H 3027, Talk 3

William Pouliot


The implementation of appropriate statistical techniques
(backtesting) for monitoring conditional VaR models is the mechanism
used by financial institutions to determine the severity of the
departures of the VaR model from market results and, subsequently
the tool used by regulators to determine the penalties imposed for
inadequate risk models. So far, however, there has been no attempt
to determine the timing of this rejection and with it to obtain some
guidance regarding the cause of failure in reporting an appropriate
VaR. This paper corrects this by proposing U-statistic type
processes that extend standard CUSUM statistics widely employed for
change-point detection. In contrast to CUSUM statistics these new
tests are indexed by certain weight functions that enhance their
statistical power to detect the timing of the market risk model
failure. These tests are robust to estimation risk and can be
devised to be very sensitive to detection of market failure produced early
in the out-of-sample evaluation period, in which standard methods
usually fail due to the absence of data.


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