{"title":"在2019冠状病毒病和俄罗斯-乌克兰冲突期间测试油价预测修正的效率","authors":"Ana María Iregui , Héctor M. Núñez , Jesús Otero","doi":"10.1016/j.jcomm.2025.100513","DOIUrl":null,"url":null,"abstract":"<div><div>We investigate weak- and strong-form efficiency in fixed-event forecast revisions for Brent and WTI prices using proprietary microdata from Energy & Metals Consensus Forecasts™ by Consensus Economics®. Our findings indicate forecasters mostly revise independently of past revisions, suggesting weak efficiency. Contributing to the strong-form efficiency literature, we compile data on 75 publicly available variables, which capture COVID-19, the Russia–Ukraine conflict, macroeconomic, financial, and oil market indicators. To ensure the information available to forecasters matched what was realistic at the time of their predictions, we lagged the variables to account for publication delays. Additionally, we added another lag to each variable, doubling the information set from 75 to 150 variables. This constitutes a significant effort in comprehending the information accessible to crude oil forecasters. Employing innovative multiple testing and penalised regression methods to address variable selection in a data-rich environment, we find that, conditional on passing weak efficiency, support for strong-form efficiency is limited. Notably, analysts incorporate past variable values, including COVID-19 and Russia–Ukraine conflict metrics, in their revisions. Our econometric modelling sheds light on how analysts’ decision-making adapt to changing market conditions, sociopolitical developments, and critical information.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100513"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Testing the efficiency of oil price forecast revisions in times of COVID-19 and the Russia–Ukraine conflict\",\"authors\":\"Ana María Iregui , Héctor M. Núñez , Jesús Otero\",\"doi\":\"10.1016/j.jcomm.2025.100513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We investigate weak- and strong-form efficiency in fixed-event forecast revisions for Brent and WTI prices using proprietary microdata from Energy & Metals Consensus Forecasts™ by Consensus Economics®. Our findings indicate forecasters mostly revise independently of past revisions, suggesting weak efficiency. Contributing to the strong-form efficiency literature, we compile data on 75 publicly available variables, which capture COVID-19, the Russia–Ukraine conflict, macroeconomic, financial, and oil market indicators. To ensure the information available to forecasters matched what was realistic at the time of their predictions, we lagged the variables to account for publication delays. Additionally, we added another lag to each variable, doubling the information set from 75 to 150 variables. This constitutes a significant effort in comprehending the information accessible to crude oil forecasters. Employing innovative multiple testing and penalised regression methods to address variable selection in a data-rich environment, we find that, conditional on passing weak efficiency, support for strong-form efficiency is limited. Notably, analysts incorporate past variable values, including COVID-19 and Russia–Ukraine conflict metrics, in their revisions. Our econometric modelling sheds light on how analysts’ decision-making adapt to changing market conditions, sociopolitical developments, and critical information.</div></div>\",\"PeriodicalId\":45111,\"journal\":{\"name\":\"Journal of Commodity Markets\",\"volume\":\"40 \",\"pages\":\"Article 100513\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Commodity Markets\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405851325000571\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Commodity Markets","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405851325000571","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Testing the efficiency of oil price forecast revisions in times of COVID-19 and the Russia–Ukraine conflict
We investigate weak- and strong-form efficiency in fixed-event forecast revisions for Brent and WTI prices using proprietary microdata from Energy & Metals Consensus Forecasts™ by Consensus Economics®. Our findings indicate forecasters mostly revise independently of past revisions, suggesting weak efficiency. Contributing to the strong-form efficiency literature, we compile data on 75 publicly available variables, which capture COVID-19, the Russia–Ukraine conflict, macroeconomic, financial, and oil market indicators. To ensure the information available to forecasters matched what was realistic at the time of their predictions, we lagged the variables to account for publication delays. Additionally, we added another lag to each variable, doubling the information set from 75 to 150 variables. This constitutes a significant effort in comprehending the information accessible to crude oil forecasters. Employing innovative multiple testing and penalised regression methods to address variable selection in a data-rich environment, we find that, conditional on passing weak efficiency, support for strong-form efficiency is limited. Notably, analysts incorporate past variable values, including COVID-19 and Russia–Ukraine conflict metrics, in their revisions. Our econometric modelling sheds light on how analysts’ decision-making adapt to changing market conditions, sociopolitical developments, and critical information.
期刊介绍:
The purpose of the journal is also to stimulate international dialog among academics, industry participants, traders, investors, and policymakers with mutual interests in commodity markets. The mandate for the journal is to present ongoing work within commodity economics and finance. Topics can be related to financialization of commodity markets; pricing, hedging, and risk analysis of commodity derivatives; risk premia in commodity markets; real option analysis for commodity project investment and production; portfolio allocation including commodities; forecasting in commodity markets; corporate finance for commodity-exposed corporations; econometric/statistical analysis of commodity markets; organization of commodity markets; regulation of commodity markets; local and global commodity trading; and commodity supply chains. Commodity markets in this context are energy markets (including renewables), metal markets, mineral markets, agricultural markets, livestock and fish markets, markets for weather derivatives, emission markets, shipping markets, water, and related markets. This interdisciplinary and trans-disciplinary journal will cover all commodity markets and is thus relevant for a broad audience. Commodity markets are not only of academic interest but also highly relevant for many practitioners, including asset managers, industrial managers, investment bankers, risk managers, and also policymakers in governments, central banks, and supranational institutions.