{"title":"用于估算布伦特原油波动率的偏斜-布朗过程","authors":"Michele Bufalo , Brunero Liseo , Giuseppe Orlando","doi":"10.1016/j.ijforecast.2024.06.009","DOIUrl":null,"url":null,"abstract":"<div><div>To predict the volatility of crude oil Brent price, we propose a novel econometric model <span><span><sup>1</sup></span></span> where the explanatory variables are a combination of macroeconomic variables (<em>i.e.</em> price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 763-780"},"PeriodicalIF":6.9000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Skew–Brownian processes for estimating the volatility of crude oil Brent\",\"authors\":\"Michele Bufalo , Brunero Liseo , Giuseppe Orlando\",\"doi\":\"10.1016/j.ijforecast.2024.06.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>To predict the volatility of crude oil Brent price, we propose a novel econometric model <span><span><sup>1</sup></span></span> where the explanatory variables are a combination of macroeconomic variables (<em>i.e.</em> price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.</div></div>\",\"PeriodicalId\":14061,\"journal\":{\"name\":\"International Journal of Forecasting\",\"volume\":\"41 2\",\"pages\":\"Pages 763-780\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Forecasting\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0169207024000633\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169207024000633","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Skew–Brownian processes for estimating the volatility of crude oil Brent
To predict the volatility of crude oil Brent price, we propose a novel econometric model 1 where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.
期刊介绍:
The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.