International Journal of Forecasting最新文献_第5页

Factors affecting preferences between judgmental and algorithmic forecasts: Feedback, guidance and labeling effects 影响判断预测和算法预测之间偏好的因素：反馈、指导和标签效应

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-09-16 DOI: 10.1016/j.ijforecast.2024.08.002

Nigel Harvey , Shari De Baets

引用次数: 0

Guiding supervisors in artificial intelligence-enabled forecasting: Understanding the impacts of salience and detail on decision-making 指导主管进行人工智能预测：理解显著性和细节对决策的影响

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-09-02 DOI: 10.1016/j.ijforecast.2024.08.001

Naghmeh Khosrowabadi , Kai Hoberg , Yun Shin Lee

{"title":"Guiding supervisors in artificial intelligence-enabled forecasting: Understanding the impacts of salience and detail on decision-making","authors":"Naghmeh Khosrowabadi , Kai Hoberg , Yun Shin Lee","doi":"10.1016/j.ijforecast.2024.08.001","DOIUrl":"10.1016/j.ijforecast.2024.08.001","url":null,"abstract":"<div><div>In many real-world situations, multiple humans are involved in decision-making when interacting with machine recommendations. We investigated a setting where an artificial intelligence system creates demand forecasts that a human planner can either accept or revise, and a supervisor then makes the final decision about which forecast to select. We designed and conducted two experimental studies to understand decision-making by a supervisor. First, we provided the improvement probabilities of adjustments at an aggregated level and found evidence for overoptimism bias and mean anchoring. Second, we provided decomposed guidance based on two adjustment attributes, direction and magnitude, to investigate the role of salience based on the distance between the improvement probabilities and level of detail in guidance effectiveness. We found no significant difference in using less and more salient guidance provided that the detail level was fixed. However, revealing more details when the guidance was more salient increased the use of guidance.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 716-732"},"PeriodicalIF":6.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A semi-supervised reject inference framework with hierarchical heterogeneous networks for credit scoring 基于层次异构网络的半监督拒绝推理框架

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-08-31 DOI: 10.1016/j.ijforecast.2024.07.011

Liao Chen , Ning Jia , Zhixian Jiao , Hongke Zhao , Runbang Cui , Huimin Wang

{"title":"A semi-supervised reject inference framework with hierarchical heterogeneous networks for credit scoring","authors":"Liao Chen , Ning Jia , Zhixian Jiao , Hongke Zhao , Runbang Cui , Huimin Wang","doi":"10.1016/j.ijforecast.2024.07.011","DOIUrl":"10.1016/j.ijforecast.2024.07.011","url":null,"abstract":"<div><div>Credit scoring is a popular tool for loan assessment, i.e., deciding whether to accept or reject a loan application. Traditional research into learning for credit scoring has only applied historically accepted samples without rejected applicants whose true repayment performance is absent, thereby causing both sample selection bias and wasting data. Some methods have been proposed for inferring rejected samples but they are still affected by several open problems, especially for medium- and long-term loan applications with a higher rejection rate. In particular, the heterogeneous relationships between accepted and rejected applications have not been well studied. Moreover, the complex repayment behaviors resulting from long repayment terms may lead to poor learning performance. Thus, we propose a reject inference framework with <strong>S</strong>emi-supervised <strong>H</strong>ierarchical <strong>H</strong>eterogeneous <strong>N</strong>etwork (S2HN) for credit scoring. We introduce a hierarchical heterogeneous network for revealing the complex connections between accepted and rejected applications, and use prospective heterogeneous repayment patterns as auxiliary information through clustering and a two-layer prediction architecture. Extensive experiments conducted based on real-world data sets demonstrated the effectiveness of our proposed method.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 3","pages":"Pages 920-939"},"PeriodicalIF":6.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144211930","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

On memory-augmented gated recurrent unit network 关于记忆增强型门控递归单元网络

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-08-31 DOI: 10.1016/j.ijforecast.2024.07.008

Maolin Yang , Muyi Li , Guodong Li

引用次数: 0

A framework for timely and accessible long-term forecasting of shale gas production based on time series pattern matching 基于时间序列模式匹配的页岩气产量长期及时预测框架

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-08-24 DOI: 10.1016/j.ijforecast.2024.07.009

Yilun Dong, Youzhi Hao, Detang Lu

{"title":"A framework for timely and accessible long-term forecasting of shale gas production based on time series pattern matching","authors":"Yilun Dong, Youzhi Hao, Detang Lu","doi":"10.1016/j.ijforecast.2024.07.009","DOIUrl":"10.1016/j.ijforecast.2024.07.009","url":null,"abstract":"<div><div>Shale gas production forecasting is an important research topic in the gas industry. A common shale gas block includes dozens or even thousands of wells and therefore has a great number of historical production series. However, most existing methods apply single-well modelling. This cannot exploit data from other wells and requires a long production history from the target well, so the forecasting timeliness is compromised. Moreover, the parameters required by many of the existing methods are difficult to collect in practice, so the forecasting accessibility is compromised. Therefore, this study presents a shale gas production forecasting framework with improved timeliness and accessibility. To ensure timeliness, the proposed approach utilises historical data from existing wells and only requires a short production history from the target well. To ensure accessibility, the proposed approach only requires past daily production time and gas yield. The performance of the proposed method is demonstrated through a comparison with baseline methods. The results regarding cumulative gas production forecasting indicate that the proposed method has an average overall mean absolute percentage error (OMAPE) of 0.210, outperforming an artificial neural network with an average OMAPE of 0.241 and ARIMA with an average OMAPE of more than 2.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 821-843"},"PeriodicalIF":6.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190564","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 soccer matches with betting odds: A tale of two markets 用赔率预测足球比赛：两个市场的故事

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-08-22 DOI: 10.1016/j.ijforecast.2024.06.013

Tadgh Hegarty, Karl Whelan

引用次数: 0

Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing 预测邮件流量：提高社会福祉的分层方法

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-29 DOI: 10.1016/j.ijforecast.2024.07.001

Nadine Kafa, M. Zied Babai, Walid Klibi

{"title":"Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing","authors":"Nadine Kafa, M. Zied Babai, Walid Klibi","doi":"10.1016/j.ijforecast.2024.07.001","DOIUrl":"10.1016/j.ijforecast.2024.07.001","url":null,"abstract":"<div><div>Forecasting for Social Good has gained considerable attention for its impact on individuals, businesses, and society. This research introduces an integrated hierarchical forecasting-based decision-making approach for mail flow in a major postal organisation, presenting new social performance indicators. These indicators, including the discharge level, discharge rate, and overload rate, guide decision makers toward consistent workload planning, bridging a literature gap concerning forecast utility measures. The study evaluates three forecasting methods—exponential smoothing with error, trend, and seasonality (ETS), the autoregressive integrated moving average (ARIMA), and the light gradient boosting machine (LightGBM)—in terms of forecast accuracy and social measures, comparing them to the organisation’s current method. The empirical results confirm that the proposed approach is more accurate than the current method. Moreover, while ETS shows the highest forecast accuracy, LightGBM outperforms all methods in social measures. This indicates that a highly accurate forecasting method does not always enhance social performance, challenging traditional views on forecasting evaluation.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 1","pages":"Pages 51-65"},"PeriodicalIF":6.9,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704583","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

Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks 不感兴趣：对在线体育博彩错误定价和低效率的纠正研究

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-27 DOI: 10.1016/j.ijforecast.2024.06.012

Lawrence Clegg, John Cartlidge

{"title":"Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks","authors":"Lawrence Clegg, John Cartlidge","doi":"10.1016/j.ijforecast.2024.06.012","DOIUrl":"10.1016/j.ijforecast.2024.06.012","url":null,"abstract":"<div><div>We present a replication and correction of a recent article (Ramirez et al., 2023). RRS measure profile page views on Wikipedia to generate a “buzz factor” metric for tennis players and show that it can be used to form a profitable gambling strategy by predicting bookmaker mispricing. Here, we use the same dataset as RRS to reproduce their results exactly, which confirms the robustness of RRS’ mispricing claim. However, we discover that RRS’ published out-of-sample betting results are significantly affected by a single bet (the “Hercog” bet), which returns substantial outlier profits based on erroneously long odds. When this data quality issue is resolved, the majority of reported profits disappear and only one strategy, which bets on “competitive” matches, remains significantly profitable in the original out-of-sample period. While one profitable strategy offers weaker support than the original study, it still provides an indication that market inefficiencies may exist, as originally claimed by RRS. As an extension, we continue testing after 2020. The strategy generates no further profits and model coefficients estimated over this period are no longer reliable predictors of bookmaker mispricing.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 798-802"},"PeriodicalIF":6.9,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensitivity and uncertainty in the Lee–Carter mortality model Lee-Carter死亡率模型的敏感性和不确定性

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-26 DOI: 10.1016/j.ijforecast.2024.06.010

Wenyun Zuo , Anil Damle , Shripad Tuljapurkar

引用次数: 0

Skew–Brownian processes for estimating the volatility of crude oil Brent 用于估算布伦特原油波动率的偏斜-布朗过程

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-20 DOI: 10.1016/j.ijforecast.2024.06.009

Michele Bufalo , Brunero Liseo , Giuseppe Orlando

引用次数: 0