activity
20202026
most citedCross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives

37 citations · 78 across the 16 of their papers we have counts for

collaborators

17 papers

stat.CO2026

conformalForecast: An R package for sequential conformal prediction in time series

Xiaoqian Wang, Daniele Girolimetto

Reliable uncertainty quantification is central to modern forecasting. Conformal prediction offers model-agnostic intervals with coverage guarantee under exchangeability, but existi…

stat.AP2026

Thick as THieFs: Temporal coherent forecast combination for day-ahead electricity prices

Daniele Girolimetto

Day-ahead electricity prices are forecast by many competing models and at several temporal granularities, from hourly prices to block and baseload products. The resulting forecasts…

stat.AP2026

Multivariate GARCH and portfolio variance prediction: A forecast reconciliation perspective

Massimiliano Caporin, Daniele Girolimetto, Emanuele Lopetuso

We assess the advantage of combining univariate and multivariate portfolio risk forecasts with the aid of forecast reconciliation techniques. In our analyzes, we assume knowledge o…

stat.CO2026

FoReco and FoRecoML: A Unified Toolbox for Forecast Reconciliation in R

Daniele Girolimetto, Jeroen Rombouts, Ines Wilms +1

Forecast reconciliation has become key to improving the accuracy and coherence of forecasts for linearly constrained multiple time series, such as hierarchical and grouped series.…

stat.ME2025

Forecast reconciliation with non-linear constraints

Daniele Girolimetto, Anastasios Panagiotelis, Tommaso Di Fonzo +1

Methods for forecasting time series adhering to linear constraints have seen notable development in recent years, especially with the advent of forecast reconciliation. This paper…

stat.AP2025

Forecasting Italian daily electricity generation disaggregated by geographical zones and energy sources using coherent forecast combination

Daniele Girolimetto, Tommaso Di Fonzo

A novel approach is applied for improving forecast accuracy and achieving coherence in forecasting the Italian daily energy generation time series. In hierarchical frameworks such…

stat.AP2025

Energy load forecasting using Terna public data: a free lunch multi-task combination approach

Daniele Girolimetto, Tommaso Di Fonzo

We propose a quick-and-simple procedure to augment the accuracy of 15-minutes Italian load forecasts disaggregated by bidding zones published by Terna, the operator of the Italian…

stat.ME2024

Balancing Accuracy and Costs in Cross-Temporal Hierarchies: Investigating Decision-Based and Validation-Based Reconciliation

Mahdi Abolghasemi, Daniele Girolimetto, Tommaso Di Fonzo

Wind power forecasting is essential for managing daily operations at wind farms and enabling market operators to manage power uncertainty effectively in demand planning. This paper…

stat.ME2024

Coherent forecast combination for linearly constrained multiple time series

Daniele Girolimetto, Tommaso Di Fonzo

Linearly constrained multiple time series may be encountered in many practical contexts, such as the National Accounts (e.g., GDP disaggregated by Income, Expenditure and Output),…

stat.ME2024

Insights into regression-based cross-temporal forecast reconciliation

Daniele Girolimetto, Tommaso Di Fonzo

Cross-temporal forecast reconciliation aims to ensure consistency across forecasts made at different temporal and cross-sectional levels. We explore the relationships between seque…

stat.ME2023

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

Massimiliano Caporin, Tommaso Di Fonzo, Daniele Girolimetto

We address the construction of Realized Variance (RV) forecasts by exploiting the hierarchical structure implicit in available decompositions of RV. By using data referred to the D…

stat.ME2023★ 18 cited

Point and probabilistic forecast reconciliation for general linearly constrained multiple time series

Daniele Girolimetto, Tommaso Di Fonzo

Forecast reconciliation is the post-forecasting process aimed to revise a set of incoherent base forecasts into coherent forecasts in line with given data structures. Most of the p…

stat.ME2023★ 18 cited

Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues

Daniele Girolimetto, George Athanasopoulos, Tommaso Di Fonzo +1

Forecast reconciliation is a post-forecasting process that involves transforming a set of incoherent forecasts into coherent forecasts which satisfy a given set of linear constrain…

stat.AP2022★ 3 cited

Enhancements in cross-temporal forecast reconciliation, with an application to solar irradiance forecasts

Tommaso Di Fonzo, Daniele Girolimetto

In recent works by Yang et al. (2017a,b), and Yagli et al. (2019), geographical, temporal, and sequential deterministic reconciliation of hierarchical photovoltaic (PV) power gener…

stat.AP2021

Forecast combination based forecast reconciliation: insights and extensions

Tommaso Di Fonzo, Daniele Girolimetto

In a recent paper, while elucidating the links between forecast combination and cross-sectional forecast reconciliation, Hollyman et al. (2021) have proposed a forecast combination…

stat.ME2020★ 37 cited

Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives

Tommaso Di Fonzo, Daniele Girolimetto

Forecast reconciliation is a post-forecasting process aimed to improve the quality of the base forecasts for a system of hierarchical/grouped time series (Hyndman et al., 2011). Co…

stat.ME2020★ 2 cited

Fully reconciled GDP forecasts from Income and Expenditure sides

Luisa Bisaglia, Tommaso Di Fonzo, Daniele Girolimetto

We propose a complete reconciliation procedure, resulting in a 'one number forecast' of the GDP figure, coherent with both Income and Expenditure sides' forecasted series, and eval…