Fundamental networks

Today’s companies exist in increasingly interconnected and complex global eco-systems, with multiple relationships, spread across supply chains, business segments, competitors and partners. Such evolving relationships can pose challenges for investors with finite data-processing capacity. At Man Numeric, we have developed systematic techniques for mapping the ‘fundamental networks’ of companies based on intuitive observations of their various interactions.  Man Numeric Quantitative Researcher Charles Liu outlines how this approach can help to develop a more refined framework for understanding companies.

25 JANUARY 2018

It’s no secret that today’s companies exist in an increasingly complex, interconnected ‘ecosystem’. A single organization has multiple relationships across geographical regions: other companies along the supply chain, competitors, and partners. This evolving web of connections poses challenges for traditional investors who have finite capacity and speed to process information, resulting in potentially exploitable mispricing opportunities. These types of relationships are intuitive, and we believe that ‘fundamental networks’ in markets can help uncover opportunities.

At Man Numeric, our team has developed systematic techniques aiming to extract under-utilized, stock-specific information using fundamental relationship data. Figure 1 gives an example of a fundamental network around a particular company, Apple Inc, where circles (or ‘nodes’) represent the companies connected to each other and their market cap. This is just one way of illustrating such a network – others include more granular analysis of individual business segment revenues or market cap.

Figure 1: Example of fundamental networks – Apple Inc

Source: Man Numeric. For illustrative purposes only. The content of this material is not intended to constitute, and should not be construed as, a recommendation or solicitation to transact in the securities of the companies named. The organisations and/or financial instruments mentioned are for reference purposes only. This information is solely used to demonstrate Man Numeric’s internal research capabilities.

How do we use this type of information to understand a company’s ecosystem? There are three key considerations in using network analysis: record network information, information propagation and node centrality. First, recording network information involves describing precisely how companies interact with each other – for example, the direction of information flow between them, or the properties of each node in a network. Second, information propagation is about the way we observe information from one company impacting another company. For example, two nodes in a network are strongly connected if they are linked by multiple paths. Figure 2 gives an example of both these dynamics, illustrating a simplified undirected global network, comprised of competitors, customers and partners. At top is a representation of a simplified network of companies (1 to 8), connected in various ways. The adjacency matrix in the left shows whether the companies are directly connected (‘1’ indicates they are, ‘0’ indicates they are not), and the matrix on the right plots the number of two-step routes between companies. We have highlighted the links between companies 3 and 7 on each matrix – not connected directly (hence the 0 in the first matrix) but accessible via three different two-walk paths (via nodes 2, 8 or 4, hence the 3 in the second matrix).

Figure 2: Information propagation in a simplified global network

Source: Man Numeric. For illustrative purposes only.

We believe these first two steps are important for quantifying the connectivity of companies in a network. But the third area of focus is the importance of individual nodes – which is not always the same as the number of links it has to others. Indeed, equal weighting of nodes in a network may fail to capture the real dynamics at play between companies, where a node is ‘central’ if it has many connections to others, and where its status can depend on the status of its neighbours. There are multiple ways of quantifying the importance of a company in a network, and the choice between them depends on the specific applications and types of network. For investors, the key question here is about whether they generally look to take positions in more or less ‘central’ companies – which again depends on the investment strategy to which this analysis is being applied.

Ultimately, fundamental networks are built on intuitive observations about the way companies interact. Their basis is nothing new, but we believe that this systematic approach to quantifying relationships across markets can help investors understand the equity market universe using a more consistent framework. As interconnectivity between companies continues to increase, advanced network data analysis can be used to complement existing quantitative equity research, and we believe that if used intelligently, it can potentially provide further opportunities to add value.

Download full article

Latest Research

How we’re turning off-the-shelf ESG data into useful and informative signals.

Robert Furdak, CFA, Ethan Gao, Jeremy Wee, CFA, Eric Wu

Quantitative approaches to credit investing creates potential opportunities and may help portfolios eliminate behavioral biases.

Paul Kamenski, CFA, Robert Lam, Jason Moore, CFA

Important information

Opinions expressed are those of the author and may not be shared by all personnel of Man Group plc (‘Man’). These opinions are subject to change without notice, are for information purposes only and do not constitute an offer or invitation to make an investment in any financial instrument or in any product to which the Company and/or its affiliates provides investment advisory or any other financial services. Any organisations, financial instrument or products described in this material are mentioned for reference purposes only which should not be considered a recommendation for their purchase or sale. Neither the Company nor the authors shall be liable to any person for any action taken on the basis of the information provided. Some statements contained in this material concerning goals, strategies, outlook or other non-historical matters may be forward-looking statements and are based on current indicators and expectations. These forward-looking statements speak only as of the date on which they are made, and the Company undertakes no obligation to update or revise any forward-looking statements. These forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those contained in the statements. The Company and/or its affiliates may or may not have a position in any financial instrument mentioned and may or may not be actively trading in any such securities. This material is proprietary information of the Company and its affiliates and may not be reproduced or otherwise disseminated in whole or in part without prior written consent from the Company. The Company believes the content to be accurate. However accuracy is not warranted or guaranteed. The Company does not assume any liability in the case of incorrectly reported or incomplete information. Unless stated otherwise all information is provided by the Company. Past performance is not indicative of future results.


Please update your browser

Unfortunately we no longer support Internet Explorer 8, 7 and older for security reasons.

Please update your browser to a later version and try to access our site again.

Many thanks.