Exploiting Intraday Decompositions in Realized Volatility Forecasting: A Forecast Reconciliation Approach

Massimiliano Caporin, Tommaso Di Fonzo and Daniele Girolimetto

Journal of Financial Econometrics, 2024, vol. 22, issue 5, 1759-1784

Abstract: We address the construction of Realized Variance (RV) forecasts by exploiting the hierarchical structure implicit in available decompositions of RV. We propose a post-forecasting approach that utilizes bottom-up and regression-based reconciliation methods. By using data referred to the Dow Jones Industrial Average Index and to its constituents we show that exploiting the informative content of hierarchies improves the forecast accuracy. Forecasting performance is evaluated out-of-sample based on the empirical MSE and QLIKE criteria as well as using the Model Confidence Set approach.

Keywords: forecast reconciliation; good and bad volatility; hierarchical forecasting; realized volatility (search for similar items in EconPapers)
JEL-codes: C10 C13 C32 C33 C55 C58 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbae014 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:22:y:2024:i:5:p:1759-1784.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani

More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().