In a complex market, investors need to connect information signals more effectively

A growing body of research suggests equity investors are poor at recognising the connections and interrelationships between companies. A fresh approach is needed, argues Mikhail Zverev, head of global equities at Aviva Investors.

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The ability to spot the relationships between assets, markets and economic data is critical for success in finance. What does the US-China trade war mean for Vietnamese exporters? How will Amazon’s move into prescription medication affect share prices among health insurance companies? Answering these sorts of questions requires teams of experts that can work together to understand how each moving piece interacts with the others.

This might sound like common sense, but evidence suggests many asset managers are bad at it. The efficient markets hypothesis – the idea that market pricing always incorporates all the relevant available information, rendering the hunt for undervalued stocks futile – has long since been debunked by behavioural economists. But the industry has yet to fully appreciate the extent to which relevant data goes overlooked.

Links between companies were being missed due to investor inattention

A growing body of research is addressing this phenomenon. In a landmark 2008 paper, the academics Lauren Cohen and Andrea Frazzini found links between companies were being missed due to “investor inattention”. This was the case even when the connections were obvious, such as the relationship between a customer and a large supplier.

Cohen and Frazzini cited as an example the long-standing association between Coastcast, a manufacturer of golf-club heads, and its major customer, Calloway, a retailer of golf equipment. In June 2001, Calloway was downgraded by analysts and slashed its earnings projections by $50 million; its shares fell by 30 per cent in two days. But these developments took two months to affect Coastcast’s share price, even though Calloway accounted for half its sales.

The authors found this sort of lag – known as “slow information diffusion” in academic parlance – repeated across the US stock market. And the effect was predictable, such that a long-short equity strategy based on responding quickly to salient news about a company yielded monthly alpha of over 150 basis points.

Recent studies indicate slow information diffusion remains a problem

You might have expected equity markets to have become more responsive and efficient in the years since this research was published, thanks to the advent of faster communications technology. But recent studies indicate slow information diffusion remains a problem. The predictable pricing effect has been observed across companies linked by international supply chains, as well as domestic ones.

Further evidence of investor inattention arrived in a 2014 study from Anna Scherbina and Bernd Schlusche, which found news pertaining to certain “leader” stocks influenced the market performance of other companies in predictable ways. Only a select group of asset managers were acting on this information quickly enough to profit from it.

So how can investors do better in this area? It is possible artificial intelligence could eventually be used to spot overlooked relationships between companies and respond to relevant news faster than the wider market. But market connections are not static, and, as AI algorithms tend to learn from past examples, they may fail to recognise the relevance of new trends.

This is where old-fashioned teamwork can play an important role. By collaborating with colleagues working in different asset classes, investment teams can gain an insight into connections that would not otherwise be clear as well as an understanding of how fresh developments will affect other companies and sectors.

By collaborating across asset classes, investment teams can gain new insights into connections

For example, an equity investor who owns shares in electric-vehicle manufacturers may be aware that targeted research and development spending is leading to rapid improvements in battery technology. This information will to be of interest to colleagues who invest in infrastructure assets such as windfarms, as the availability of longer-lasting batteries should boost the prospects of renewable energy companies.

Telecommunications is another good example. In this complex industry, new technological breakthroughs can ripple across companies and industries at speed. The next big development, 5G, is set to reshape the fortunes of firms that manufacture telecoms equipment as well as those that rely on intensive data processing and transfer.

Piecing together the puzzle to gain a picture of how companies connect and influence each other could give investors the edge

In particular, 5G is set to give a much-needed shot in the arm to smartphone makers – which have been struggling with underwhelming sales over the past two years – along with the semiconductor manufacturers that supply them. Yet none of this is evident in market pricing across companies in these sectors, suggesting most investors have yet to grasp how 5G will affect this interconnected web of companies.

Amid the rise of passive equity funds and quant investing, an approach based on collaboration across asset class specialisms – piecing together the puzzle to gain a picture of how companies connect and influence each other – could give human investors the edge. 

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