Advances in data gathering are breathing new life into active fund management.
ACSI Funds CEO Phil Bak says his firm's recently launched American Customer Satisfaction Core Alpha ETF, which tracks customer sentiment and stock performance of the highest rated companies in the American Customer Satisfaction Index, signifies one example of how managers may offer clients low-cost active products in the year ahead.
The fund's managers choose holdings based on the index's quantifiable ranking of customer reviews; a tool he expects will provide a sneak peek at those companies' annual performance reports.
Competition, he adds, is forcing fund companies to deliver "outperformance to their clients in new and innovative ways."
In an interview with Money Management Executive, Bak shared insight on the future regulatory environment, technology and trends he expects will shape the ETF marketplace.
The following is an edited transcript of the conversation.
How is the ETF industry is preparing for the year ahead?
There are two separate trends at hand. People, in general, are moving towards ETFs broadly, but more often they are not moving towards low-cost, broad cap-weighted index funds.
We are seeing tremendous flows into Vanguard, BlackRock's core product suite, and Schwab, and some of the competitors that are offering low-cost cap-weighted products. The ETF is just a more efficient vehicle to deliver those products, but as more people are adopting index-based strategies, the need for differentiation and for outperformance is pretty evident. It's not difficult to go online and get an asset allocation model, cap-weighted index funds, at no or very little charge. Then you have robo advisers mostly offering exactly that strategy.
For advisers and for institutional investors, the challenge becomes: How do they offer something differentiated and of value to their clients, and how can they find outperformance, but find outperformance in a way that can also take advantage of the benefit of the ETF and the product vehicle but can also be rules-based and process-driven?
I think the anticipation that advisers have that an asset manager can randomly take stock based on his gut and outperform the market; those days are over. That's been proven, but there are systematic ways that people can beat the market.
We have 25 years of research showing that our proprietary data leads to stock outperformance, and I think that there is now a whole set of smart-beta products that employ different strategies where they are index-based products. They follow process, they follow a rules-based approach — there's no discretion involved -but their design is to embed a feature they hope will outperform the market.
What types of trends do you foresee within the alternatives space?
One of the things that we're seeing now is that correlations between stocks within asset classes are falling, and they're falling pretty drastically. Correlations between asset classes are also coming down a bit, and that's a good thing for portfolio managers.
It means that there's more opportunity now to differentiate a stock portfolio, whether you're actively managed or whether you're buying off of a rules-based approach. But, if you're trying to differentiate from the broad market and you're trying to justify a higher fee point, that differentiation is essential. Correlation between the stocks within each asset class has been increasing for some time and seeing that trend reverse bodes well for people who are trying to beat the market.
Despite recent reports touting the power of passive investing over active, is still a place for active management?
There's no question there is.There's a reason why, on average, hedge fund equity managers have beaten passive indices over time, where mutual fund managers have not. Growth of these might be a different story, but it tells you that there is an edge. The question is: How do you distill that edge into a process that's repeatable and sustainable over time?
We believe we have the methodology that is a leading indicator to how stocks perform down the road.
How does ACSI approach this data?
We have a proprietary process in the Khan Metric model that is a patented process to be able to look at customer satisfaction of public companies, within each sector, and apply one uniform standard across all companies. So, we source all of the data ourselves and we use that as a signal to see where we think there are going to be changes in stock prices down the road.
If customers — who are essentially the earnings that are forthcoming to company - are dissatisfied with a product or a service they will presumably take their business elsewhere. If they are satisfied then they will continue and that company will be able to grow their earnings.
We are not pulling these metrics out of the financial statements that happened historically. We are measuring the customers' responses in real time and anticipate where those changes are going to happen in the future.
When go out for lunch, the restaurant doesn't know you are coming until you go there. The analysts looking at that company won't know it until you have already gone, paid, and the company released their financial statements.
So, we are looking at data that is really ahead of the curve. We have shown over time that a 1% change in a company's customer satisfaction leads to a 4% change in the stock price and market cap of the company. By capturing these trends with the world's best data to capture these trends, we are able to in a systematic, transparent way, invest in companies we think are poised for earnings growth.
Can you discuss how his process was developed?
With the ability of big data, there are a lot of different signals that people can now measure.
ACSI is the only company in the U.S. that is really measuring public company customer satisfaction data with one uniform methodology. Any company could send out a survey to their own customers and ask if they're happy or not with their services, but they don't access their competitors' data. We have one methodology we can apply to every automaker, but also every consumer goods and technology company, or financial sector company as well. That way we can then normalize the data based on region, gender, age, and a half-dozen other factors. That allows us to apply the one uniform methodology across all large cap U.S. equities and create a portfolio that really solves a problem for people.
We are not a niche satellite fund where you are not really sure what to do. We are a core holding. We are investing in large cap names and we are giving people exposures to the same general risk tolerance levels, the same general average market cap and sector constraints that they are expecting in say an S&P fund or a large cap core fund.
Has the anticipation of a looser regulatory environment under President-elect Trump resulted in any innovation here?
I wouldn't equate that with the regulatory environment, per say. I would say, however that the marketplace itself, and the competitiveness of the marketplace, is forcing fund companies to be more creative and find ways of delivering outperformance to their clients in new and innovative ways.
You can only have so many index funds in the market. You can only have so many funds that use traditional growth and value metrics in the market. For issuers to really find something that's differentiated, that solves a problem and can carve out a market for themselves, they are forced to come up with different ideas and ways of looking at the market that haven't really been exploited yet.
What types of products do you foresee becoming more prevalent this year?
I think there is a whole set of products that a would be called smart beta, but use a proprietary model that have traditionally been offered in hedge funds, or have been relied upon within mutual funds, and we are going to start seeing them come out either in an ETF vehicle or otherwise as rules based, index funds, where index funds not in the traditional cap-weighted, broad index-type of way, but as a rules-based transparent approach.
In what ways do you see technological advances in the finance industry impacting new product development?
Robo advisers are clearly carving out a substantial asset base, and that's probably going to continue. But it does two things.
One is that the robo adviser and technology that's embedded in it is something we expect to grow and we think has tremendous value to the investment landscape. Further than that is that it puts the impetus on asset gatherers to think more about being asset managers so that they can compete with the robo advisers, not only on relationships but on the asset management. They should think about how they can differentiate the asset management side by coming up with portfolios that are either more customized or that can perform better than what the robos are currently.
Would you say qualitative data gathering is one way to separate the human portfolio manager from a robo?
Yes. I think there's something to be said for sentiment and gathering sentiment data, but it must be quantified. It has to be tied back to risk-adjusted alpha. You have to be able to prove it. Your clients have to be able to understand how it's being put together and how it works, but this is just one example of many different ways that people can be looking at the market.
At the end of the day, we are talking about investing in stocks, and I think the industry has gotten a little bit away from the idea that a stock is a collection of people that are selling a good or a service to other people.
The industry as a whole has gotten into the habit of looking at stocks as a collection of growth and value signals and historical price return streams, and getting away from the idea that there is a real company here and that people have a real view of the company.
Customers that transact with that company also have a view. For any company to success, they will need to have satisfied customers, create new and better products and be able to continue to grow their balance sheets, not just by playing around with the numbers but by actually providing good experiences to their customers.
The more the industry gets back to that, and gets back to that type of analysis that Peter Lynch was doing 20 years ago, I think that's where there is opportunity.