If a fund manager can’t pinpoint the sources of their portfolio performance, then how can they possibly value the research they are buying? What is it worth?
Of course, if they’re trading with a brokerage firm to gain access to IPOs or to managements through conferences or non-deal road shows, does it really matter? As long as the end-client (individual investors in mutual and pension funds) bore the load of research costs, this wasn’t much of a concern.
Regulation, Demographics and Technology Change Everything
But it matters now. MiFID II rules going into effect in Europe next year will force the buy-side to justify their research spending to clients because those costs can no longer be baked into trading commissions.
Meanwhile, indexing has grown to a torrent, causing a steady decline in assets under management. This shift is a no-brainer when one considers that the cost of owning a mutual fund is 9x that of an index fund, and that the vast majority of fund managers consistently underperform their benchmarks.
The rising preference for robo advisors by younger investors is also driving this shift. Who needs broker recommendations or pushing in-house funds on you when an app can quickly help determine your risk profile and put you into an appropriate mix of low-cost index funds?
Technology has driven the cost of execution down to fractions of a penny. Advances in networking speeds and processing power, data storage capacity and performance analytics has made this possible. Of course, bad data at the speed of light is still bad data.
Does Research Have Value? At What Price?
And bad broker research at any speed is still bad for investors. Granted, most sell-side analysts these days don’t have the time, training or means to do true fundamental research. It’s hard work that gets devalued when they go into a meeting with a big hedge fund client whose first question is, “What are you best two long and short ideas for the next quarter?”
But what about those few remaining providers that still do fundamental research? Those who have a background in the industry they cover, or can leverage the many industry contacts they have established over the years and are current on all the trade e-zines, or pore over SEC filings, or have detailed models built on years of experience? That depth of knowledge is certainly proprietary and worth something. But what?
Many industry consultants set their prices for research. Whether it’s interpreting OPEC meeting outcomes on future oil prices, analyzing crop yields and planting trends for farm equipment companies, the impact of Amazon’s private label initiative at Whole Foods on packaged goods companies and grocers, or the uptake of Hadoop by enterprise IT shops, these industry experts seem to understand their value to clients – and price their service accordingly. Many offer subscriptions, but also allow customers buy individual reports.
Why can’t Wall Street do the same? Portfolio managers (PMs) are swamped. They must keep up with macroeconomic and political developments. They track hundreds of companies in their funds. They meet with these company managements. And they regularly attend staff and client meetings.
PMs understand that no analyst can predict or explain most short-term stock movements – particularly since over half of trading volume is accounted for by algorithms. But they also appreciate that a well-informed research service can provide insights into industry trends that can help their asset allocation. Whether they want exposure to a sector or not and the impact on adjacent sectors is the big-picture intelligence they gain.
Price Research for Darwinism
This expertise should be priced accordingly – just like other industry experts’ research. If the buy-side demurs, that’s a risk. Research is a Darwinian process. But if PMs realize their decisions are not as well informed or effective without this research input, they will pay the asking price. It is justifiable.
The current rush to incorporate big data analytics into portfolio management cannot compete with this knowledge. However, it can be used to sift through massive data sets of different varieties to complement industry-specific fundamentals. It can help analyze stock movements in the short term. But it’s not going to help find the next 10-bagger.
It’s a mistake for the sell-side to follow the buy-side into it. That’s because unless or until they can prove the ideal blend of fundamental and trading explanations for portfolios that the buy-side may not want to expose to them, spending on this research is a waste.
Which stocks to buy or sell? That’s the PM’s decision. Ultimately, they generate alpha – or they don’t. Which research to pay for? Ultimately, that which they find they can’t make their decisions without.
