Speaker:
Marco Bee
- University of Trento
Thursday, March 1, 2018
at
12:30 PM
Polo Santa Marta, Via Cantarane 24, Sala Vaona (Room 1.59)
Recent contributions to the financial econometrics literature exploit high-frequency
(HF) data to improve models for daily asset returns. We propose a new
class of dynamic extreme value models that profit from HF data when estimating
the tails of daily asset returns. Our Realized Peaks-Over-Threshold approach provides
estimates for the tails of the time-varying conditional return distribution. An in-sample
fit to the S&P 500 index returns suggests that HF data convey information on daily
extreme returns beyond that included in low frequency (LF) data. Finally, out-of-
sample forecasts of conditional risk measures obtained with HF measures outperform
those obtained with LF measures.
- Programme Director
-
Roberto
Renò
-
External reference
-
- Publication date
-
January 4, 2018