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Identifying Systemically-Important Commodity Futures: Pattern Causality from the Perspective of the Dynamics of Complex Systems

Year: 2025

Type: article

Abstract: : This study uses a pattern causality theory to identify the complex interdependence (positive, negative, and dark) and systemically-important individuals among the returns of 37 commodity futures in China. Positive and dark causality are found to play dominant and stable roles; both are closely related to situations of continuous decline of returns, or of volatility. By measuring the influence exerted and received of each of the 37 futures, some relatively important individuals are detected, both in positive and dark patterns. Results provide a new perspective and a useful basis for policy-making and investment decisions in futures markets. Keywords: Commodity Futures, Pattern Causality, Dynamic System, Network JEL Classification Number: C6; G13

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15125510

Authors: Xue Gao, Xin Li

Institutions: Qingdao Vocational and Technical College of Hotel Management, Wuchang University of Technology

Language: English

Topic: Complex Systems and Time Series Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6968143753

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