{"title":"A novel portfolio construction strategy based on the core-periphery profile of stocks","authors":"Imran Ansari, Charu Sharma, Akshay Agrawal, Niteesh Sahni","doi":"arxiv-2405.12993","DOIUrl":null,"url":null,"abstract":"This paper highlights the significance of mesoscale structures, particularly\nthe core-periphery structure, in financial networks for portfolio optimization.\nWe build portfolios of stocks belonging to the periphery part of the Planar\nmaximally filtered subgraphs of the underlying network of stocks created from\nPearson correlations between pairs of stocks and compare its performance with\nsome well-known strategies of Pozzi et. al. hinging around the local indices of\ncentrality in terms of the Sharpe ratio, returns and standard deviation. Our\nfindings reveal that these portfolios consistently outperform traditional\nstrategies and further the core-periphery profile obtained is statistically\nsignificant across time periods. These empirical findings substantiate the\nefficacy of using the core-periphery profile of the stock market network for\nboth inter-day and intraday trading and provide valuable insights for investors\nseeking better returns.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"173 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.12993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper highlights the significance of mesoscale structures, particularly
the core-periphery structure, in financial networks for portfolio optimization.
We build portfolios of stocks belonging to the periphery part of the Planar
maximally filtered subgraphs of the underlying network of stocks created from
Pearson correlations between pairs of stocks and compare its performance with
some well-known strategies of Pozzi et. al. hinging around the local indices of
centrality in terms of the Sharpe ratio, returns and standard deviation. Our
findings reveal that these portfolios consistently outperform traditional
strategies and further the core-periphery profile obtained is statistically
significant across time periods. These empirical findings substantiate the
efficacy of using the core-periphery profile of the stock market network for
both inter-day and intraday trading and provide valuable insights for investors
seeking better returns.