As one of the new breed of artificial intelligence (AI)-powered investor targeting firms, Intro-act, which launched in 2017, has been using machine learning to help move targeting technology into the future.
Now the firm has selected six metrics it deems key to building an ‘ownership score’, which makes up its new IR scorecard, aimed at offering further insight for Russell 3000 companies:
- Concentration among the top 10 owners
- Directionality – or owners’ trade flow on a buy/sell ratio
- Breadth – the number of owners a company has
- Impact – institutional ownership size vs your peers
- Depth – looking at the support that could come from current investors
- Duration of ownership.
With so many elements involved in assessing the health of a company’s investor base and where it could go with its targeting, how did Peter Wright, company co-founder, and his team whittle it down to these six metrics?
By analyzing the following equation, as he explains: ‘More volume traded suggests more liquidity and more liquidity suggests a richer multiple (all else being equal), and a richer multiple suggests a lower cost of capital. So we started to identify metrics that could be managed to promote more active trading (and ownership) in a specific stock.’
The firm then took these six metrics to ‘a handful of IR professionals’ for validation, with IROs agreeing that these ‘fairly well encompass the metrics that matter most,’ says Wright.
He is quick to point out that while Intro-act is part of a next-gen group of IR service providers making use of big data and AI, at least when it comes to the new scorecard, human analysis – ‘at least for today’ – is still required. This is because the current scorecard treats each factor on an equal-weighted basis, and Wright says his firm recognizes ‘this shouldn’t be the case across the entire Russell 3000.’
For example, he says that for ‘smaller-cap companies that might have only around 10 investors, concentration across these top 10 is only meaningful in terms of setting a benchmark for comparison vs peers and putting it in context vs the trend over time. Similarly, shares of Fang [Facebook, Amazon, Netflix and Google – now Alphabet] companies are widely owned and score more poorly on depth (ownership relative to buying power), because everyone wants at least a little Fang exposure.’
Intro-act originally launched as a company offering AI-powered targeting predictions over a 90-day timeframe, and Wright says it can make these predictions with 60 percent accuracy. While it isn’t the only firm offering such solutions, each has its own way of gathering and assessing data.
Intro-act makes use of 13F filings, for example, which Wright says offer both pros and cons. On the pro side, the quarterly release of data – which is factual and so requires no speculation – allows IROs to cut through the ‘noise’ of trading decisions, rather than the true investment direction. ‘We are not a substitute for surveillance data,’ he adds, ‘but a complement to it.’
On the con side, of course, is the fact that 13Fs are released on a 45-day delay. ‘This is both a challenge and an opportunity,’ suggests Wright. As it’s the biggest weakness in the 13F data, he says it’s what the company wanted to bring greater context and predictive insight to with the new scorecard.
‘Our predictions can now be put in context relative to a peer group and relative to time,’ Wright continues. ‘This enables IR professionals to see whether our predictions might be based on more of a sector rotation vs stock-specific issues that are causing money flows to move toward or away from the stock at different points in time.’
Of course, liquidity is also very much key here, he adds: ‘There are many great institutionally worthy stocks, but they have limited to no ownership among institutions because the stock isn’t liquid enough.’
So what advice would Wright offer IROs looking to expand their targeting efforts?
‘My single biggest piece of advice is to appreciate that any targeting system is valuable only if integrated into the bigger IR strategy,’ he says. ‘It should include elements of learning – from how different types of investors prepare (or don’t prepare) for meetings with your executive team and, most importantly, how to maintain relationships.
‘And remember that targeting isn’t only about hunting for the new investor; it is also about understanding the metrics that might result in current owners reducing their position.’
