
THE
FIELDS INSTITUTE FOR RESEARCH IN MATHEMATICAL SCIENCES


Time 
Speaker, Title and Abstract 
Thursday, August 8 2:002:45PM 
Fernando Valvano Cerezetti, BM&FBOVESPA
Managing Risk in MultiAsset Class, Multimarket Central Counterparties:
The CORE Approach
Multiasset class, multimarket central counterparties (CCPs)
are becoming less uncommon as a result of merges between specialized
(singleasset class, single market) CCPs and market demands for more
capital efficiency. Yet, traditional CCP risk management models often
lack the necessary sophistication to estimate potential losses relative
to the closeout process of a defaulter's portfolio in a multiasset
class, multimarket environment. As a result, multiasset class, multimarket
CCPs usually rely upon a simplied silo approach for calculating risk
that, not only fails to deliver efficiency, but can also increase
systemic risk. The CORE (Closeout Risk Evaluation) approach, on the
other hand, provides the conceptual and mathematical tools necessary
for robust and efficient central counterparty risk evaluation in multiasset
class and multimarket environments, acknowledging the portfolio dynamics
involved in the closeout process, as well as important "real
life" market frictions.

Tuesday, August 20
2:00PM

Franziska Schulz, HumboldtUniversität zu Berlin
Forecasting generalized quantiles of electricity demand: A functional
data approach
Electricity load forecasts are in various ways valuable
for the operation of utilities. However, for a sustainable risk management
of utility operators not only a forecast
of expected demand, but also knowledge about the uncertainty and dispersion
of
future load plays an important role. The aim of our research is to
model and forecast generalized quantiles of electricity demand, which,
in contrast to forecasts of the conditional mean, yield a whole picture
of the distribution of electricity demand. We apply methods from functional
data analysis to model dynamics of daily generalized quantile curves.
Taking temporal dependence between curves into account allows us to
conduct short term forecasts at an intraday resolution using multivariate
timeseries techniques.

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