Dimensional’s Savina Rizova Shares Her Expertise on Excess Returns Podcast
Dimensional Global Head of Research Savina Rizova recently appeared on an episode of Excess Returns. The podcast focuses on strategies and tactics designed to help individuals become better long-term investors.
In this episode, Rizova talks with show hosts Jack Forehand and Justin Carbonneau of Validea Capital Management about the size and value premiums, incorporating momentum into the investment process, and more. Below, find a summary of the podcast, edited for clarity and length.
To watch the interview, click here.
Share a little about yourself.
I was born in Bulgaria. I was 8 years old when communism ended in Bulgaria, and a very painful transition from communism to capitalism began. There were economic problems, and the quality of public education went down. When it came time to go to college, I decided I should try to get my education in the US. Dartmouth College not only accepted me but gave me full financial aid.
When I got to Dartmouth, I already had an idea that I wanted to study economics and finance. Both of my parents have their master’s degrees in economics, so I have loved that area of study since I was little. At Dartmouth, I started working as a research assistant for Professor Ken French, who recommended I get some real-world experience before continuing on to get my PhD. I followed his advice and joined Dimensional Fund Advisors. After three years, I left the firm to get my PhD at the University of Chicago, and then I came back to Dimensional.
How do you narrow the scope of your research?
Dimensional Fund Advisors aims to provide clients with systematic, robust investment solutions that go beyond indexing. We seek to add value in a long-term, sustainable manner without trying to outguess market prices, but instead embracing them. Therefore, the role of research at Dimensional is not to identify mispricings or give thoughts on how to time markets.
The research at Dimensional is focused on two areas: the need to help clients build a robust framework to think about important investing topics and improving upon the firm’s investment process on an ongoing basis. You focus on how you design portfolios, how you manage them, and how you trade them. A lot of the research we do is related to every step of that investment process.
What are some of the most exciting areas of research you are focused on right now?
Currently, on the equity side, we are collaborating with Robert Novy-Marx on short-term reversal—the tendency of stocks that have performed well in the last month to underperform peers in the next month or so—and how we can capture it more effectively in our portfolios. The other big focus is profitability growth. There has been research saying that price momentum we see in the data is actually driven by earnings momentum. And profitability growth is connected to earnings momentum. It is an additional signal about near-term profitability and future profitability. So we are trying to see if we can effectively use information in the latest quarter’s profitability growth (relative to four quarters ago) in our daily investment processes.
What do you think is the best way to measure value?
Our research on value sorts with individual metrics vs. blended metrics has shown that a blended metric is no better than even a price-to-book sort over the last 30 years. Returns would have been reliably similar whether you use a composite of price-to-earnings, price-to-cash, or price-to-book vs. any of those individual metrics.
The reason we prefer to use price-to-book as a primary metric in how we identify value vs. growth stocks is that it tends to generate lower turnover. We think deeply about implementation—how the pursuit of higher expected returns interacts with diversification, risk, and trading costs. As a result, we prefer to focus on a metric that is a little more stable, with lower turnover and similar performance, over the long term.
Do intangibles impact today’s use of the price-to-book metric?
Intangibles have been with us for a very long time as part of the economic landscape. There are two kinds of intangibles from the accounting perspective: externally developed intangibles and internally developed intangibles.
Externally developed intangibles are acquired by buying another company, and they are reported on the balance sheet. They show up in assets and book equity. Internally developed intangibles include things like research and advertising. These are not reported on the balance sheet. They are the intangibles we do not easily observe.
To see whether you are missing out by not having internally developed intangibles in book equity, you must estimate them. But there is a lot of noise in that data, a lot of caveats with the data. That doesn’t mean we shouldn’t take intangibles into account. It doesn’t mean that price-to-book is perfect or any other metric is perfect. But our research taught us that incorporating noisy estimates into our metrics for daily implementation might not be the best way to go forward. A better way forward might be to think about tightening our sector controls in how we run our value and profitability strategies.
Do you find any evidence of a decay in the size premium?
For the size premium, in the last 10–15 years, the number of small cap companies that are publicly traded in the US has been shrinking. As a result, we looked at whether that affected the capture of the size premium and found that it does not. Even if you confine yourself to the top 3,000 names going back in time, you will have seen a positive, very similar size premium compared to using the full universe at any point in time.
We don’t see the size premium disappearing, but it is very important how you go about capturing the size premium. There are segments of the small caps that have meaningfully lower expected returns. It is consistent with valuation theory. Within small caps, companies with low profitability and companies that are very expensive tend to have very low average returns. Companies that have high asset growth tend to get very low average returns. Those are the companies that typically drag down the performance of small caps. It might suggest there is no size premium, but once you exclude them from the small cap universe, the way we systematically do at Dimensional, you historically get a more reliable and larger size premium.
How do you think about incorporating momentum into your investment process?
Momentum has been a bit of a puzzle in finance because it is hard to link it directly to valuation theory. It is a pervasive and persistent return pattern out there, which means you should acknowledge it and ideally incorporate it in your investment process, and that is what we do.
But trying to actively pursue it can be risky from two perspectives. One, do we really have a good story for why we should expect momentum to persist in the future? And two, momentum is a very high-turnover type of signal, very fast-decaying. Six to 12 months out, the winners are no longer outperforming the market and the recent losers are no longer underperforming. So, you’d be required to trade a lot to capture it and incur those costs.
Instead of pursuing momentum actively, a good approach is to consider momentum when you decide what to buy and sell on a daily basis. We go through these decisions every day.
If you could impart one piece of wisdom to the average investor, what would it be?
Have a framework, ideally a robust framework. This is where it all starts when it comes to investing. Having a framework will give you the best foundation for a good investment experience.
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