### Abstracts

** Yacine Ait-Sahalia, **Princeton University

*Disentangling Volatility from Jumps*

Realistic models for financial asset prices used in portfolio choice,
option pricing or risk management include both a continuous Brownian
and a jump components. This paper studies our ability to distinguish
one from the other. I find that, surprisingly, it is possible to perfectly
disentangle Brownian noise from jumps. This is true even if, unlike
the usual Poisson jumps, the jump process exhibits an infinite number
of small jumps in any finite time interval, which ought to be harder
to distinguish from Brownian noise, itself made up of many small moves.

**Nour Meddahi**, Université de Montreal

*Correcting the Errors: Volatility Forecast Evaluation based on High-Frequency
Data and Realized Volatilities*

Co-authors: Torben Andersen (Northwestern University) and Tim Bollerslev
(Duke University)

In this talk we will develop general model-free adjustment procedures
for the calculation of unbiased volatility loss functions based on practically
feasible realized volatility benchmarks. The procedures, which exploit
the recent asymptotic distributional results in Barndorff-Nielsen and
Shephard (2002), are both easy-to-implement and highly accurate in empirically
realistic situations. On properly accounting for the measurement errors
in the volatility forecast evaluations reported in Andersen, Bollerslev,
Diebold and Labys (2003), the adjustments result in markedly higher
estimates for the true degree of return-volatility predictability.

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