Which power variation predicts volatility well?
We estimate MIDAS regressions with various (bi)power variations to predict future volatility - measured via increments in quadratic variation. Instead of pre-determining the (bi)power variation we parameterize it and estimate the intra-daily return power transformation that optimally predicts future increments in quadratic variation. We find that the longer the prediction horizon, the smaller the optimal power transformation.
Year of publication: |
2009
|
---|---|
Authors: | Ghysels, Eric ; Sohn, Bumjean |
Published in: |
Journal of Empirical Finance. - Elsevier, ISSN 0927-5398. - Vol. 16.2009, 4, p. 686-700
|
Publisher: |
Elsevier |
Keywords: | Stock Market Volatility Forecasting Power variation MIDAS regressions |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Which power variation predicts volatility well?
Ghysels, Eric, (2009)
-
Stock market volatility and macroeconomic fundamentals
Engle, Robert F., (2013)
-
On the Economic Sources of Stock Market Volatility
Engle, Robert F., (2012)
- More ...