Greg Kapoustin Headshot
Greg Kapoustin, Principal at AlphaBetaWorks

The world of smart beta is in its infancy. Traditional indexes are constructed based on market capitalization. Creative and resourceful individuals are turning the idea of index construction upside down on its head by introducing new factors and methodologies for weighting the stocks that are included in the index.

I spent some time talking with Greg Kapoustin, who is a fascinating individual with an interesting life story. Greg has collaborated with the NYSE to create a new index family which launched last year.

The former MSFT software engineer has found his true passion and is hitting his stride by creating new products to help investors generate alpha and manage risk.

Tell me a little about your history in the industry, how a mathematician got into finance.

It may be overly ambitious for me to call myself a mathematician. I am an engineer with some mathematics background. I first got into finance because of personal needs. As I worked at Microsoft and began to accumulate assets, I started doing a lot of research so I could have a better understanding of my investments. I had an interest since college and the more I learned, I found I really enjoyed it. It was then I realized finance was (is) an area where I could have a competitive advantage.

As I started to do financial analysis, it became clear that there were very few people who were equally adept at technology and finance, who were decent at fundamental analysis, who could understand end customer needs, institutional investor needs, wealth client needs and who could, at the same time, understand software engineering and quantitative methods deeply. It seemed I could contribute something perhaps truly unique.

Also, it seemed that finance was becoming more and more systematized so there would be more and more opportunity to do work at the intersection of software engineering, quantitative methods, and client needs within finance.

Sounds like the perfect combination.

Certainly, some of those hopes and interests were definitely vindicated. When I got into finance it was during the very early days of smart beta and very early days of popular use of systematic strategies, which is essentially what smart beta is. I couldn’t have imagined how much opportunity there would be to combine engineering and finance down the road.

Vindicated indeed. So clearly ETF’s are gaining market share – from your perspective, what do you think that’s attributed to?

I read somewhere that if finance industry professionals knew back in the day what they know today about some of the structural issues of mutual funds and the advantages of ETFs, we may not have had mutual funds as a product class. Some of the advantages and traction of ETFs seem to be the result of the ways in which they fix these issues of mutual funds. Probably the most widely discussed issues are the taxable events that occur when capital moves in and out of mutual funds and when mutual funds are rebalanced. These can create liabilities for investors even when a fund’s performance  is down.

ETFs are free of that baggage. That is one part. Another part is that investment strategies based on simple transparent rules can do really well. As academics and practitioners looked at the performance of some of the most celebrated skilled active managers with long track records, a substantial chunk of performance results of those who never set out to do any kind of quantitative work can be explained with very basic rules. For instance, there’s plentiful research that shows that while you can’t precisely replicate what Warren Buffet and Berkshire Hathaway achieved, by following rules that very simply encode and replicate the process, you will get much of that performance.

ETFs, because of their transparency, efficiency, and because of their natural fit for these systematic strategies, were in the perfect place at the perfect time.

We’ve seen robo-advisors spring up – broadly speaking they use ETFs version 1.0 – broad capital weighted indexes. How do you think robo-advisors should interface with smart BETA investing?

I think the one key point about smart beta, ETFs, and robo-advising is that robo-advisors today are at an early stage of development. They’re using fairly basic portfolio construction, glide path construction techniques, little tax optimization and no portfolio completion. In time, it seems that robo-advisors who restrict themselves to only using passive strategies available via passive index ETFs will be at a structural disadvantage.

Given the competition and a general lack of differentiation, they cannot afford to be at such a disadvantage. If sound smart beta strategies do provide superior returns to passive investing over the long term in a competitive environment, how can you afford to compete without having smart beta as part of the platform? I think over the longer term, smart beta will be an important part of the success of the robo-advisors that do survive and thrive.

Another source of potential competitive advantage will be a combination of smart beta with tax optimization and portfolio completion, taking processes that are not scalable and currently done very expensively in high-end wealth management by democratizing them.

Do you think smart beta / ETFs are a fad?

I don’t think ETFs or smart beta are fads. There is (as with any industry that is growing very rapidly and attracts a lot of attention) lots of financial innovation as various players try to figure out where the sweet spot of the market is. There are mini fads within this. When you have a gold rush out West, there’ll be plenty of questionable leases for sale in the mountains. Likewise, there are some products that are launched very quickly to try to stake a claim and hope something works. The deep underlying reasons for the success of ETFs and smart beta strategies are sound. Though there certainly are going to be, and there are, some products, many products, that are less sound.

Right now, we’re in the world of this wild innovation where many products are excellent products, but many others do not provide any advantage over existing plain vanilla passive indexing. In fact, many are just running a very complicated process with a higher risk and more leverage of a traditional index, perhaps with a higher fee and essentially more complexity which means more confusion for clients. Does that make sense how that could happen?

Yes, definitely.

I could come up with a set of rules, and I can run those rules, and perhaps those rules do produce a product that outperforms the market, but the question is why has it outperformed the market? It may be in the end those rules deliver an S&P 500 index that’s basically leveraged 10%. So it’s a portfolio that just takes somewhat more risk than a passive portfolio and generates higher returns when the market does well, which is most of the time. This product doesn’t do anything that you couldn’t do if you bought the S&P 500 on margin.

What’s lacking today is the ordering in of what Research Affiliates aptly describe as the Smart Beta Zoo. What our work with the New York Stock Exchange on Pure Exposure Indices does is add one more tool that can be used to manage the risk of smart beta products, as well as organize and refine systematic strategies.

At a higher level, really most smart beta strategies that work take advantage of momentum or value effects – anomalies that have been long described in finance. There’s some academic disagreement over other anomalies such as size, quality, low volatility and the work we do helps organize and manage those exposures.

That makes sense. Where do you see smart beta investing going in the next five years?

What is best about successful and effective smart beta strategies is that they seem to capture what simple rules good, active investors do well and provide some of that performance cheaply, transparently, and conveniently. Like most technology, as smart beta goes through this cycle of somebody getting a bright idea, it receives skepticism, then the idea is proven to work, and once something is a commercial success, there’s this period of wild innovation.

The smart beta landscape today makes me think of the state of automobile manufacturing in the early 20th century when there were dozens, it not hundreds, of auto manufacturers. There were lots of good ideas. There were some good manufacturers and then there were also lots of firms that were just trying to get in on what was working. After that comes a period of rationalization and consolidation where over time and over some cycles, it becomes clear what is a sound product and what is not a sound product.

I think over the next five to 10 years, there will be increased rationalization and consolidation where some issuers will understand that certain products are not providing investors with a unique, truly smart, beta offering. It will become clear that some of those are plain old dumb beta, just rebuilt with an elaborate set of rules.

So basically, right now it’s popular and there are a lot in the market, but eventually it will taper off and only the strong will survive.

Yeah. That’s a true statement. But it can be confusing because some of the strategies and products that appear strong may not actually be inherently strong. For instance, if I launched a smart beta strategy in April 2009 which was in a high risk version of the S&P 500, it would have had a spectacular record, and it would have attracted massive capital inflows, and it would have been a very successful product. Many smart beta strategies are in fact that. They appear strong, but they’re built on very weak foundations.

The truly strong products will certainly survive and do well. Our opinion of who was a strong handset maker in the early 2000s, BlackBerry, would have been a very poor predictor for who was going to survive.

Some of the changes that will happen will be over the longer term. Over longer cycles, the weaknesses of a few products that were in the right place at the right time being laid bare and the underlying strength of the great products will become more visible as we experience a few different market regimes.

Talk about your ETF partner, how long did it take you to conceive of the idea and bring it to market? Where do you see this going? Anything you’d do differently?

We spent about a year confronting problems where clients could not easily manage their exposures with existing indices and ETFs before we realized there might be a product opportunity here. If we keep encountering investors that have a particular problem, maybe there is need for a product to solve that problem. Then there was about another year of brainstorming and formal discussions with our partners, before we officially launched the Pure Exposure Indices.

At the outset, we were thinking about the products more academically. What would make for a neat, intellectually pretty, consistent and elegant product?

I wish when we started this journey we thought more about end user needs – the ways in which this product will help somebody run a better business and ultimately achieve their business objective – not just create a better portfolio or improved returns, but be more successful in what they do.

The two are not mutually exclusive; customer needs do not necessarily exclude a product from being a clean, elegant, mathematically pretty product. It’s just a different focus. One is more abstract. The other is more concrete.

In the end, we found that the areas where pure exposure indices are getting the most traction are those areas where they’re most aligned with the business needs and business objectives. We could have probably gotten places faster and saved some time. There’s a cautionary tale, this is sort of an aside, but for somebody with a mathematics and engineering background it can be very, very tempting to do something for the sake of its inherent mathematical or design beauty. That’s a good motivator, but it can also draw focus away from the everyday problems people need to solve.

How should advisors think about using this in their client portfolio?

As before, as in the case of institutional investors, most of the interesting uses of Pure Exposure Indices are work-in-progress under NDAs. The scenario that motivated our work on Pure Exposure Indices was trying to find a way to express strong views on a particular sector in periods of market turmoil. Often times when advisors or institutional investors, asset managers, are in a period of extreme uncertainty, extreme concern, their best option is to raise cash.

They increase the allocation of cash and they sit on cash and wait for better opportunities. However, oftentimes those investors, as they’re sitting on cash, have very strong sector views. In this case, they can use pure exposure products to express their sector views without taking market risk. They can continue to play offense, continue to express their views in areas where they have an edge without taking market risk and also without having to resort to sitting on cash.

For the advisor who’s reading this article, what’s the one thing you want them to know?

I alluded to it in the discussion of smart beta trends and evolution, but I would put it more emphatically here. Many, if not most, smart beta products are not passive. They’re not a version of passive investing. They are, in fact, as active as a typical active manager. In fact, given the widespread problem of closet indexing among active managers, smart beta products might actually be more active than your typical active manager.

Advisors generally cannot put smart beta products in the same mental bucket as S&P 500. Advisors need to do as much, if not more, due diligence on smart beta products as they would on an active manager. There is less qualitative oversight, less human oversight with some systematic strategies. Consequently, they can do funny things that a human wouldn’t. The diligence can be especially complicated because some of these strategies are pretty technical.

Would you ever contemplate a robo-advisor offering?

Running a robo-advisor requires a very specific skill set, business capabilities, competencies, etc. We are very unlikely to have a competitive advantage when it comes to running a robo-advisor. However, we do have some technological and data expertise that would provide robo-advisors with a significant competitive edge. In fact, this is not an area where I can comment freely because in some cases we’re under NDAs, but we’re in discussions both with robo-advisors and conventional asset management firms on their offerings in this space.

There will certainly be some areas where companies with relevant technological and engineer expertise can provide robo-advisors who have the right vision with competitive edge and with an opportunity to leapfrog their competition. We are happy to be part of that, but we certainly do not have the muscle to run a competitive robo-advisor ourselves.

How can asset managers better leverage their competencies?

I do think that it’s important for every firm to focus on their core competencies, especially given the very rapid pace of product and technological innovation. That’s actually why I think some robo-advisors may be better served in licensing, relevant technology, or data from somebody who has built it already rather than trying to spend the time to hire and build out internal expertise, if they want to get at the smart beta for instance.

Likewise, communication, fact sheets, web presence and documentation are certainly areas to consider external expertise for an asset manager or financial firm.

It’s an area that’s also ripe for Uberization, for lack of a better word, where you want the platform to provide it. Your readers would benefit from consistency, would benefit from rigor, and would benefit from kind of a recognizable format instead of every firm, every institution having to run their own in-house department to do this work. It would be one thing if we still lived in a world where you have 10 years to ramp up your strategy and ramp up your staff. You can afford to hire people to do that. But, in a world where you might be launching a smart beta product and by the time you hired a team and you sort of slowly organically developed all of this capability in-house, the world has already changed. You can’t afford to do it and it becomes very important to rely on platforms that provide document and communication services and functionality that is core, but not part of your competitive advantage.

The world is moving too fast to do everything by yourself. I think that where standardization would really help is to my earlier point about the Wild West of strategies, improving disclosures, and documentation. Better standardization would ultimately benefit investors who can not easily compare potentially incomparable fact sheets.

For example, if I ask six analysts to calculate Sharpe ratios with the same return series, I’ll likely get six different numbers because of the subtle differences in assumptions going into the Sharpe ratio calculations. One of the industry’s problems is this lack of standardization. This is a big deal for the industry in general, and helping to standardize reporting is critical.

Thank you Greg.

Greg Kapoustin is a principal at AlphaBetaWorks. He is an expert in the diverse areas of software engineering, portfolio management, and financial risk management, with a track record of design and implementation of complex synthesis projects spanning these fields.

Prior to ABW, Greg was a senior analyst at Burlingame Asset Management in San Francisco for nine years. In addition to his responsibilities in portfolio management, Greg leveraged his software engineering expertise to design reporting, risk management, and performance evaluation systems, including the multi-factor risk models that became the basis of AlphaBetaWorks’ offerings.

Previously, Greg spent five years as a software engineer in an industry-leading Windows Platform technical team at Microsoft.

Greg is an Amherst College graduate and speaks fluent Russian. He is a CFA® charterholder, a member of the Global Association of Risk Professionals (GARP), and a member of the Professional Risk Managers’ International Association (PRMIA).

Follow Greg on Twitter or email him at GregK@AlphaBetaworks.com

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