Exploiting intraday decompositions in Realized Volatility forecasting: a forecast reconciliation approach

   Authors

Massimiliano Caporin, Tommaso Di Fonzo, Daniele Girolimetto

   Published

July 31, 2024

   Publication details

Journal of Financial Econometrics, 22(5), 1759-1784

   Links
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.