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Better to stay apart: asset commonality, bipartite network centrality, and investment strategies

  • S.I.: Recent Developments in Financial Modeling and Risk Management
  • Published:
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Abstract

By exploiting a bipartite network representation of the relationships between mutual funds and portfolio holdings, we propose an indicator that we derive from the analysis of the network, labelled the Average Commonality Coefficient (ACC), which measures how frequently the assets in the fund portfolio are present in the portfolios of the other funds of the market. This indicator reflects the investment behavior of funds’ managers as a function of the popularity of the assets they held. We show that ACC provides useful information to discriminate between funds investing in niche markets and those investing in more popular assets. More importantly, we find that ACC is able to provide indication on the performance of the funds. In particular, we find that funds investing in less popular assets generally outperform those investing in more popular financial instruments, even when correcting for standard factors. Moreover, funds with a low ACC have been less affected by the 2007–2008 global financial crisis, likely because less exposed to fire sales spillovers.

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Notes

  1. Portfolio overlaps are receiving increasing attention, especially in the literature of systemic risk due to fire sales spillover. See, for example, Caccioli et al. (2014), Greenwood et al. (2015), Corsi et al. (2016), Di Gangi et al. (2018).

  2. In the paper the terms constituents and assets, or holdings and compositions are considered interchangeable.

  3. Following Cohen et al. (2005) we include the annual expense ratio and 12(b)1 fees given by CRSP; we divide these amounts by 252 to get daily quota, and we add the resulting value to each daily net fund’s return to obtain gross returns.

  4. The interested reader may refer to the Financial Crisis Timeline, provided by the Federal Reserve Bank of St. Louis, for a detailed list of episodes related to the subprime crisis. See: https://www.stlouisfed.org/financial-crisis/full-timeline.

  5. To be precise, the quantity \({\small k}_{F_{i},0}\) represents the number of constituents held by a fund whose holding is greater than or equal to the share held on average by the other funds.

  6. Hence, the term commonality applied here is slightly different from the usage in other financial applications (see e.g., Flannery and James 1984; Allen et al. 2012; Namvar and Phillips 2013, among others).

  7. We have also applied higher order measures of commonality as, for instance, \({\small k}_{F_{i},2}\) to compute investment strategies along the line described in the paper. Since results are in line with the ones presented in the paper, for sake of brevity, we exclude them from the work but they are available from authors upon request.

  8. We use subscripts 3f and 5f to indicate alpha computed from the three- and the five-factors model, respectively. The estimate of portfolio expected return is computed as \(r_{3f} = R_{f}+\beta _{1}(R_{m}-R_{f})+\beta _{2} SMB + \beta _{3} HML + \alpha \), where the market premium (\(R_{m} - R_{f}\)) is enriched by factors that refer to Small minus Big capitalization (SMB) and High minus Low book-to-market ratio (HML); the five factors model adds to the previous three factors model the profitability (Robust minus Weak, RMW) and the investment (Conservative minus Aggressive, CMA) factors.

  9. For the topological properties ACC and diversification the top best performer decile refers to Q1, while it is Q10 for past-\({\hat{\alpha }}\) and the \(\hat{\delta ^{*}}\) indicator of Cohen et al. (2005).

  10. This choice prevents estimates with few data points. Results are qualitatively similar to those obtained using tertiles for the ACC distribution.

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Acknowledgements

Authors acknowledge support from CNR PNR Project “CRISIS Lab”.

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Authors and Affiliations

  1. Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy

    Andrea Flori & Fabio Pammolli

  2. Center for Analysis, Decisions, and Society (CADS) - Human Technopole, Milan, Italy

    Fabrizio Lillo, Fabio Pammolli & Alessandro Spelta

  3. Department of Mathematics, Università di Bologna, Bologna, Italy

    Fabrizio Lillo

  4. Department of Economics and Management, University of Pavia, Pavia, Italy

    Alessandro Spelta

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  1. Andrea Flori
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  2. Fabrizio Lillo
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Correspondence to Alessandro Spelta.

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Flori, A., Lillo, F., Pammolli, F. et al. Better to stay apart: asset commonality, bipartite network centrality, and investment strategies. Ann Oper Res 299, 177–213 (2021). https://doi.org/10.1007/s10479-019-03277-0

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  • DOI: https://doi.org/10.1007/s10479-019-03277-0

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