动态行业不确定性网络与商业周期

IF 1.9 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control Pub Date : 2023-11-24 DOI:10.1016/j.jedc.2023.104793

Jozef Baruník , Mattia Bevilacqua , Robert Faff

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引用次数: 0

摘要

本文从期权价格中识别出平滑变化的行业不确定性网络，其中包含有关商业周期的有价值信息，特别是在预测方面。当网络是在不确定性中心上形成时，这些信息会更强，这些公司被认为是不确定性冲击的主要贡献者。基于枢纽的网络具有更强的预测能力，对广泛的检查具有鲁棒性，包括一组大的控制，并且也被证实是样本外的。

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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.

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来源期刊

Journal of Economic Dynamics & Control ECONOMICS-

CiteScore

3.10

自引率

10.50%

发文量

199

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.