发布求助
文献互助 智能选刊 最新文献

International Journal of Forecasting最新文献

筛选
英文 中文
Combining forecasts under structural breaks using Graphical LASSO 使用图形套索组合结构断裂下的预测
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-05-28 DOI: 10.1016/j.ijforecast.2025.04.003
Tae-Hwy Lee , Ekaterina Seregina
{"title":"Combining forecasts under structural breaks using Graphical LASSO","authors":"Tae-Hwy Lee ,&nbsp;Ekaterina Seregina","doi":"10.1016/j.ijforecast.2025.04.003","DOIUrl":"10.1016/j.ijforecast.2025.04.003","url":null,"abstract":"<div><div><span>In this paper we develop a novel method of combining many forecasts based on Graphical LASSO. We represent forecast errors from different forecasters as a network of interacting entities and generalize network inference in the presence of common factor structure and structural breaks. First, we note that forecasters often use common information and hence make common errors, which makes the forecast errors exhibit common factor structures. We separate common forecast errors from the idiosyncratic errors and exploit sparsity of the precision matrix of the latter. Second, since the network of experts changes over time as a response to unstable environments, we propose Regime-Dependent Factor Graphical LASSO (RD-FGL) that allows factor loadings and idiosyncratic precision matrix to be regime-dependent. The empirical applications to forecasting </span>macroeconomic series using the data of the European Central Bank’s Survey of Professional Forecasters and Federal Reserve Economic Data monthly database demonstrate superior performance of a combined forecast using RD-FGL.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 126-137"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Kairosis: A method for dynamical probability forecast aggregation informed by Bayesian change-point detection Kairosis：一种基于贝叶斯变点检测的动态概率预测聚合方法
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-06-23 DOI: 10.1016/j.ijforecast.2025.03.001
Zane Hassoun, Niall MacKay, Ben Powell
{"title":"Kairosis: A method for dynamical probability forecast aggregation informed by Bayesian change-point detection","authors":"Zane Hassoun,&nbsp;Niall MacKay,&nbsp;Ben Powell","doi":"10.1016/j.ijforecast.2025.03.001","DOIUrl":"10.1016/j.ijforecast.2025.03.001","url":null,"abstract":"<div><div><span><span>We present a new method, ‘kairosis’, for aggregating probability forecasts made over a </span>time period of a single outcome determined at the end of that period. Informed by work on </span>Bayesian<span> change-point detection, we begin by constructing for each time during the period a posterior probability<span> that the forecasts before and after this time are distributed differently. The resulting posterior probability mass function<span> is integrated to give a cumulative mass function, which is used to create a weighted median forecast. The effect is to construct an aggregate in which the most heavily weighted forecasts are those which have been made since the probable most recent change in the forecasts’ distribution. Kairosis outperforms standard methods, and is especially suitable for geopolitical forecasting tournaments because it is observed to be robust across disparate questions and forecaster distributions.</span></span></span></div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 112-125"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hierarchical neural additive models for interpretable demand forecasts 可解释需求预测的层次神经加性模型
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-04-30 DOI: 10.1016/j.ijforecast.2025.03.003
Leif Feddersen, Catherine Cleophas
{"title":"Hierarchical neural additive models for interpretable demand forecasts","authors":"Leif Feddersen,&nbsp;Catherine Cleophas","doi":"10.1016/j.ijforecast.2025.03.003","DOIUrl":"10.1016/j.ijforecast.2025.03.003","url":null,"abstract":"<div><div>Demand forecasts are the basis for numerous business decisions, ranging from inventory management to strategic facility planning. While machine learning approaches offer accuracy gains, they notoriously lack interpretability and acceptance. To address this dilemma, we introduce hierarchical neural additive models (HNAMs) for time series. HNAMs expand upon neural additive models by introducing a time-series-specific additive model consisting of level and covariate effects. Covariates may interact only according to a user-specified hierarchy. For example, given the hierarchy <em>weekday, holiday, promotion</em>, weekday effects are estimated independently, whereas a holiday effect depends on the weekday, and a promotional effect is conditioned on both the weekday and holiday. Thereby, HNAMs clearly attribute additive effects to their respective covariates, enabling intuitive forecasting interfaces with which analysts can interact. We provide benchmarks against established machine learning and statistical models on real-world data to reveal HNAMs’ competitive accuracy.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 216-234"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forecasting and policy when “we simply do not know” “我们根本不知道”时的预测和政策
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-05-30 DOI: 10.1016/j.ijforecast.2025.04.004
Alan Kirman , Angus Armstrong , William Hynes
{"title":"Forecasting and policy when “we simply do not know”","authors":"Alan Kirman ,&nbsp;Angus Armstrong ,&nbsp;William Hynes","doi":"10.1016/j.ijforecast.2025.04.004","DOIUrl":"10.1016/j.ijforecast.2025.04.004","url":null,"abstract":"<div><div>This paper takes the Court of the Bank of England’s Terms of Reference for the Bernanke Review seriously. We explore the underlying issue of radical uncertainty and what this means for forecasting and monetary policy-making. The only logical way to proceed is to embrace Bernanke’s suggestion that we engage ‘alternative modelling frameworks’. What might these be? We need a combination of different types of models, some with closed equilibrium solutions and others that rely on simulations that can provide different insights into what is happening in the economy. The old saying that ‘it takes a model to beat a model’ is just that. We now know that Agent Based Models can perform at least as well as equilibrium models, even on the latter’s own narrow criteria, despite the fraction of resources used in their development. If the Bank is to serve its mission of ‘promoting the good of the people of the UK’ it must start by accepting reality and not limiting itself to a single model framework as if it will somehow deliver ‘the truth’ if only it had more resources.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 34-39"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Is it possible to predict electoral abstention on the individual level? A preregistered test on forecasting the effects of abolishing compulsory voting in Belgium 是否有可能在个人层面上预测选举弃权？一项预先登记的测试，旨在预测比利时废除强制投票的影响
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-06-26 DOI: 10.1016/j.ijforecast.2025.05.002
Dieter Stiers, Marc Hooghe
{"title":"Is it possible to predict electoral abstention on the individual level? A preregistered test on forecasting the effects of abolishing compulsory voting in Belgium","authors":"Dieter Stiers,&nbsp;Marc Hooghe","doi":"10.1016/j.ijforecast.2025.05.002","DOIUrl":"10.1016/j.ijforecast.2025.05.002","url":null,"abstract":"<div><div>There is a vast literature on determinants of electoral turnout that allows us to forecast which groups of the population will turn out to vote and which will not. Here we report on a rather unique forecasting experiment at the individual level. In June 2024, elections were held in Belgium with compulsory voting. In October 2024, another election was held, but this time <em>without</em> compulsory voting. Simultaneously, a panel survey was conducted, spanning from April to November 2024. The information in the first two waves of the panel were used to forecast the likelihood of individual respondents turning out again in October, which we preregistered. The forecasting models were indeed successful in predicting who would turn out to vote, but they tended to give relatively elevated turnout likelihood scores to non-voters. The prediction models tended to underestimate the effect of political interest in explaining actual electoral turnout.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 99-111"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forecasting UK consumer price inflation with RaGNAR: Random generalised network autoregressive processes 用RaGNAR预测英国消费者价格通胀：随机广义网络自回归过程
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-05-17 DOI: 10.1016/j.ijforecast.2025.04.005
Guy P. Nason, Henry Antonio Palasciano
{"title":"Forecasting UK consumer price inflation with RaGNAR: Random generalised network autoregressive processes","authors":"Guy P. Nason,&nbsp;Henry Antonio Palasciano","doi":"10.1016/j.ijforecast.2025.04.005","DOIUrl":"10.1016/j.ijforecast.2025.04.005","url":null,"abstract":"<div><div>This article forecasts consumer price index (CPI) inflation in the United Kingdom using random generalised network autoregressive (RaGNAR) processes. More specifically, we fit generalised network autoregressive (GNAR) processes to a large set of random networks generated according to the Erdős–Rényi–Gilbert model and select the best-performing networks each month to compute out-of-sample forecasts. RaGNAR significantly outperforms traditional benchmark models across all horizons. Remarkably, RaGNAR also delivers materially more accurate predictions than the Bank of England’s four to six month inflation rate forecasts published in their quarterly Monetary Policy Reports. Our results are remarkable not only for their accuracy, but also because of their speed, efficiency, and simplicity compared to the Bank’s current forecasting processes. RaGNAR’s performance improvements manifest in terms of both their root mean squared error and mean absolute percentage error, which measure different, but crucial, aspects of the methods’ performance. GNAR processes demonstrably predict future changes to CPI inflation more accurately and quickly than the benchmark models, especially at medium- to long-term forecast horizons, which is of great importance to policymakers charged with setting interest rates. We find that the most robust forecasts are those which combine the predictions from multiple GNAR processes via the use of various model averaging techniques. By analysing the structure of the best-performing graphs, we are also able to identify the key components that influence inflation rates during different periods.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 181-202"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial and introduction to the special section on the Bernanke’s review of the Bank of England’s forecasting activities 伯南克对英国央行预测活动的评论特别部分的社论和引言
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-11-18 DOI: 10.1016/j.ijforecast.2025.11.002
Pierre Pinson
{"title":"Editorial and introduction to the special section on the Bernanke’s review of the Bank of England’s forecasting activities","authors":"Pierre Pinson","doi":"10.1016/j.ijforecast.2025.11.002","DOIUrl":"10.1016/j.ijforecast.2025.11.002","url":null,"abstract":"","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 1-2"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil? 及时行乞：每日油价能否改善基于模型的原油实际价格预测？
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-03-14 DOI: 10.1016/j.ijforecast.2025.02.009
Amor Aniss Benmoussa , Reinhard Ellwanger , Stephen Snudden
{"title":"Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?","authors":"Amor Aniss Benmoussa ,&nbsp;Reinhard Ellwanger ,&nbsp;Stephen Snudden","doi":"10.1016/j.ijforecast.2025.02.009","DOIUrl":"10.1016/j.ijforecast.2025.02.009","url":null,"abstract":"<div><div>This paper proposes methods to include information from the underlying nominal daily series in model-based forecasts of average real series. We apply these methods to forecasts of the real price of crude oil. Models utilizing information from daily prices yield large forecast improvements and, in some cases, almost halve the forecast error compared to current specifications. We demonstrate for the first time that model-based forecasts of the real price of crude oil can outperform the traditional random walk forecast, that is, the end-of-month no-change forecast, at short forecast horizons.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 281-295"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures 动态预测原油期货日内累计收益的函数混合预测模型
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-05-20 DOI: 10.1016/j.ijforecast.2025.04.001
Deqing Wang , Zhihao Lu , Zhenhua Liu , Shoucong Xue , Mengxia Guo , Yiwen Hou
{"title":"A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures","authors":"Deqing Wang ,&nbsp;Zhihao Lu ,&nbsp;Zhenhua Liu ,&nbsp;Shoucong Xue ,&nbsp;Mengxia Guo ,&nbsp;Yiwen Hou","doi":"10.1016/j.ijforecast.2025.04.001","DOIUrl":"10.1016/j.ijforecast.2025.04.001","url":null,"abstract":"<div><div>Since the high-frequency crude oil futures price data from intraday trading sessions exhibit continuous functional characteristics, we propose a functional mixture prediction (FMP) model for real-time forecasting of crude oil cumulative intraday returns (CIDR). The core idea of FMP is dynamic forecasting after adaptive classification. Specifically, we develop an adaptive functional clustering algorithm to identify the distinct patterns of CIDR curves and establish a probabilistic discriminant model to estimate their cluster membership probabilities. The mixture prediction of a new partially observed CIDR is obtained by weighting its predicted trajectory in each cluster with its estimated membership probabilities. Moreover, we design an adaptive information updating mechanism to further improve the accuracy of intraday forecasts. Empirical results from applying FMP to forecast the CIDR of China’s crude oil futures show that the proposed FMP not only outperforms several competing forecasters but also provides additional insights into CIDR analysis by revealing distinct patterns in daily CIDR curves of similar variability and typical temporal trends. Furthermore, we provide evidence that FMP can achieve greater gains for traders with different risk preferences based on our designed intraday trading strategies.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 158-180"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
When to be discrete: The importance of time formulation in the modeling of extreme events in finance 何时离散：时间公式在金融极端事件建模中的重要性
IF 7.1 2区 经济学
International Journal of Forecasting Pub Date : 2026-01-01 Epub Date: 2025-07-22 DOI: 10.1016/j.ijforecast.2025.06.001
Katarzyna Bień-Barkowska , Rodrigo Herrera
{"title":"When to be discrete: The importance of time formulation in the modeling of extreme events in finance","authors":"Katarzyna Bień-Barkowska ,&nbsp;Rodrigo Herrera","doi":"10.1016/j.ijforecast.2025.06.001","DOIUrl":"10.1016/j.ijforecast.2025.06.001","url":null,"abstract":"<div><div>We propose a novel extension of the score-driven peaks-over-threshold (SPOT) model within a discrete-time framework. This adaptation is motivated by the fact that financial returns and, consequently, extreme events are typically observed at discrete time intervals. Our primary objective is to assess whether this discrete-time SPOT model provides a more precise representation and superior fit for tail risk forecasting. The study reveals several important findings. First, we demonstrate that continuous-time approaches can result in inaccurate value-at-risk and expected-shortfall forecasts. By contrast, discrete-time models provide a more accurate description of the dynamics of extreme losses. Empirical evidence supports the superiority of discrete-duration models, outperforming various continuous-time SPOT specifications and GARCH models. Overall, our study has substantial implications for the modeling and forecasting of extreme financial events, offering a more accurate and efficient approach than traditional approaches.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"42 1","pages":"Pages 61-84"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信
小红书