Cover Image

Combine and conquer: model averaging for out-of-distribution forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hess, Stephane, van Cranenburgh, Sander
Format:	Preprint
Published:	2025
Subjects:	Econometrics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Flexibility without foresight: the predictive limitations of mixture models
by: Hess, Stephane, et al.
Published: (2025)

Understanding the decision-making process of choice modellers
by: Nova, Gabriel, et al.
Published: (2024)

Can large language models assist choice modelling? Insights into prompting strategies and current models capabilities
by: Sfeir, Georges, et al.
Published: (2025)

An economically-consistent discrete choice model with flexible utility specification based on artificial neural networks
by: Hernandez, Jose Ignacio, et al.
Published: (2024)

Get me out of this hole: a profile likelihood approach to identifying and avoiding inferior local optima in choice models
by: Hess, Stephane, et al.
Published: (2025)

Posterior inference of attitude-behaviour relationships using latent class choice models
by: Vij, Akshay, et al.
Published: (2025)

Beyond utility: incorporating eye-tracking, skin conductance and heart rate data into cognitive and econometric travel behaviour models
by: Hancock, Thomas O., et al.
Published: (2025)

Statistical significance in choice modelling: computation, usage and reporting
by: Hess, Stephane, et al.
Published: (2025)

Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
by: Wang, Shenhao, et al.
Published: (2021)

Ranking probabilistic forecasting models with different loss functions
by: Serafin, Tomasz, et al.
Published: (2024)

Density forecast transformations
by: Mogliani, Matteo, et al.
Published: (2024)

Flexible global forecast combinations
by: Thompson, Ryan, et al.
Published: (2022)

Delphos: A reinforcement learning framework for assisting discrete choice model specification
by: Nova, Gabriel, et al.
Published: (2025)

Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data
by: Christensen, Kim, et al.
Published: (2026)

A machine learning approach to volatility forecasting
by: Christensen, Kim, et al.
Published: (2026)

Prediction intervals for economic fixed-event forecasts
by: Krüger, Fabian, et al.
Published: (2022)

Latent Gaussian dynamic factor modeling and forecasting for multivariate count time series
by: Kim, Younghoon, et al.
Published: (2023)

Linear estimation of global average treatment effects
by: Faridani, Stefan, et al.
Published: (2022)

High-dimensional forecasting with known knowns and known unknowns
by: Pesaran, M. Hashem, et al.
Published: (2024)

Back to Feedback: Dynamics and Heterogeneity in Panel Data
by: Bonhomme, Stephane
Published: (2025)

Is local opposition taking the wind out of the energy transition?
by: Daniele, Federica, et al.
Published: (2024)

Improving volatility forecasts of the Nikkei 225 stock index using a realized EGARCH model with realized and realized range-based volatilities
by: Chang, Yaming
Published: (2025)

From day-ahead to mid and long-term horizons with econometric electricity price forecasting models
by: Ghelasi, Paul, et al.
Published: (2024)

Nowcasting distributions: a functional MIDAS model
by: Marcellino, Massimiliano, et al.
Published: (2024)

Debiasing and $t$-tests for synthetic control inference on average causal effects
by: Chernozhukov, Victor, et al.
Published: (2018)

Dynamic tail risk forecasting: what do realized skewness and kurtosis add?
by: Gallo, Giampiero, et al.
Published: (2024)

Expected Shortfall LASSO
by: Barendse, Sander
Published: (2023)

Estimating Heterogeneous Effects: Applications to Labor Economics
by: Bonhomme, Stephane, et al.
Published: (2024)

Estimating Individual Responses when Tomorrow Matters
by: Bonhomme, Stephane, et al.
Published: (2023)

Diffusion index forecasts under weaker loadings: PCA, ridge regression, and random projections
by: Boot, Tom, et al.
Published: (2025)

A sensitivity analysis for the average derivative effect
by: Zhang, Jeffrey
Published: (2025)

Corrected Forecast Combinations
by: Liu, Chu-An, et al.
Published: (2026)

Combining stated and revealed preferences
by: Meango, Romuald, et al.
Published: (2025)

What drives the European carbon market? Macroeconomic factors and forecasts
by: Bastianin, Andrea, et al.
Published: (2024)

Quantile-based modeling of scale dynamics in financial returns for Value-at-Risk and Expected Shortfall forecasting
by: Liu, Xiaochun, et al.
Published: (2026)

Neural ARFIMA model for forecasting BRIC exchange rates with long memory
by: Chakraborty, Tanujit, et al.
Published: (2025)

Efficient estimation of average treatment effects with unmeasured confounding and proxies
by: Ai, Chunrong, et al.
Published: (2025)

Combining Clusters for the Approximate Randomization Test
by: Lau, Chun Pong
Published: (2025)

Evaluating financial tail risk forecasts: Testing Equal Predictive Ability
by: Bauer, Lukas
Published: (2025)

The Bayesian Context Trees State Space Model for time series modelling and forecasting
by: Papageorgiou, Ioannis, et al.
Published: (2023)