Do we need high frequency data to forecast variances?
Year of publication: |
December 2016
|
---|---|
Authors: | Banulescu-Radu, Denisa ; Hurlin, Christophe ; Candelon, Bertrand ; Laurent, Sébastien |
Published in: |
Annals of economics and statistics. - Amiens : GENES, ISSN 2115-4430, ZDB-ID 2588293-4. - Vol. 123/124.2016, p. 135-174
|
Subject: | Variance Forecasting | MIDAS | High-Frequency Data | Prognoseverfahren | Forecasting model | Volatilität | Volatility | Zeitreihenanalyse | Time series analysis | Varianzanalyse | Analysis of variance | Theorie | Theory | Prognose | Forecast | Börsenkurs | Share price |
-
Improving variance forecasts : the role of Realized Variance features
Papantonis, Ioannis, (2023)
-
From zero to hero: realized partial (co)variances
Bollerslev, Tim, (2021)
-
From zero to hero : realized partial (co)variances
Bollerslev, Tim, (2022)
- More ...
-
Candelon, Bertrand, (2010)
-
Currency crises Early Warning Systems : why they should be dynamic
Candelon, Bertrand, (2010)
-
Backtesting value-at-risk : a GMM duration-based test
Candelon, Bertrand, (2011)
- More ...