{"title":"动态行业不确定性网络与商业周期","authors":"Jozef Baruník , Mattia Bevilacqua , Robert Faff","doi":"10.1016/j.jedc.2023.104793","DOIUrl":null,"url":null,"abstract":"<div><p><span>This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in terms of forecasting. Such information is stronger when the network is formed on uncertainty hubs, firms identified as the main contributors to uncertainty shocks. The stronger </span>predictive ability of the hubs-based network is robust to a wide range of checks, the inclusion of a large set of controls, and is also confirmed out-of-sample.</p></div>","PeriodicalId":48314,"journal":{"name":"Journal of Economic Dynamics & Control","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic industry uncertainty networks and the business cycle\",\"authors\":\"Jozef Baruník , Mattia Bevilacqua , Robert Faff\",\"doi\":\"10.1016/j.jedc.2023.104793\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in terms of forecasting. Such information is stronger when the network is formed on uncertainty hubs, firms identified as the main contributors to uncertainty shocks. The stronger </span>predictive ability of the hubs-based network is robust to a wide range of checks, the inclusion of a large set of controls, and is also confirmed out-of-sample.</p></div>\",\"PeriodicalId\":48314,\"journal\":{\"name\":\"Journal of Economic Dynamics & Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economic Dynamics & Control\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165188923001999\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Dynamics & Control","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165188923001999","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Dynamic industry uncertainty networks and the business cycle
This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in terms of forecasting. Such information is stronger when the network is formed on uncertainty hubs, firms identified as the main contributors to uncertainty shocks. The stronger predictive ability of the hubs-based network is robust to a wide range of checks, the inclusion of a large set of controls, and is also confirmed out-of-sample.
期刊介绍:
The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.