Periphery portfolios from core-periphery network structures consistently outperform traditional strategies, offering valuable insights for inter-day and intraday trading.
Authors
Imran Ansari, Department of Mathematics, Shiv Nadar Institution of Eminence Deemed to be University, Delhi-NCR, India
Charu Sharma, Department of Mathematics, Shiv Nadar Institution of Eminence Deemed to be University, Delhi-NCR, India
Akshay Agrawal, Associate Professor, Jindal Centre for Digital Sciences, O.P. Jindal Global University, Sonipat, Haryana, India
Niteesh Sahni, Department of Mathematics, Shiv Nadar Institution of Eminence Deemed to be University, Delhi-NCR, India
Summary
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 Minimum Spanning Trees and 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, Sortino ratio, information ration and average return. 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.
Published in: Scientific Reports
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