{"title":"Liquidity spillovers in US stock market based on multilayer networks","authors":"Jinyu Yuan, Chuangxia Huang","doi":"10.1016/j.frl.2025.107231","DOIUrl":null,"url":null,"abstract":"While there is widespread agreement that liquidity plays a crucial role in financial contagion, the analysis of liquidity spillovers between individual stocks remains underexplored. This study examines liquidity spillover effects among individual stocks within a multilayer network framework. Using data from S&P 500 constituent stocks between 2006 and 2021, we construct annual multilayer liquidity spillover networks, incorporating both linear and nonlinear layers. The results show that, compared to single-layer networks, multilayer networks more accurately and comprehensively capture liquidity spillovers and identify crisis periods. Moreover, liquidity spillovers are significantly heightened during crises. Based on multilayer liquidity spillover network, we identify the main connectors, receivers, and senders of liquidity spillovers, offering valuable insights for pinpointing sources of market volatility and mitigating systemic liquidity risks.","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"27 1","pages":""},"PeriodicalIF":7.4000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Finance Research Letters","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.frl.2025.107231","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
While there is widespread agreement that liquidity plays a crucial role in financial contagion, the analysis of liquidity spillovers between individual stocks remains underexplored. This study examines liquidity spillover effects among individual stocks within a multilayer network framework. Using data from S&P 500 constituent stocks between 2006 and 2021, we construct annual multilayer liquidity spillover networks, incorporating both linear and nonlinear layers. The results show that, compared to single-layer networks, multilayer networks more accurately and comprehensively capture liquidity spillovers and identify crisis periods. Moreover, liquidity spillovers are significantly heightened during crises. Based on multilayer liquidity spillover network, we identify the main connectors, receivers, and senders of liquidity spillovers, offering valuable insights for pinpointing sources of market volatility and mitigating systemic liquidity risks.
期刊介绍:
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