Using Decision Science in Investing: Masters in Business with Omar Aguilar

Masters in Business

Barry Ritholtz interviews Omar Aguilar, CEO and CIO of Schwab Asset Management, about his academic background in decision sciences and how Bayesian statistics inform modern investment

Key takeaways

• Omar Aguilar holds a Ph.D. in decision sciences from Duke University and applied Bayesian statistics to quantitative modeling early in his career at Bankers Trust and Merrill Lynch.
• Schwab Asset Management has grown to nearly $2 trillion in assets under management, becoming the fifth-largest ETF manufacturer globally with an asset-weighted expense ratio of just eight basis points.

Main topics

• Decision science and Bayesian statistics in investing
• Schwab Asset Management growth and ETF strategy

Notable quotes

The 4% rule became just like a number that somebody picked out of the hat... it is really a dynamic process that depends on the needs of the moment.

Conclusion

Aguilar's data-driven approach underscores how merging quantitative ri

Transcript preview

Speaker 6 (0:00) Gain insight on the innovators, disruptors, and tech-driven trends shaping today's complex economy. I'm Carol Masser. And I'm Tim Stenevek. Speaker 5 (0:07) Wrap up your workday with the Bloomberg Businessweek Daily Podcast. Speaker 6 (0:11) We bring you deeper dives into the stories shaping your world, from the evolution of AI to the shifting priorities of global business. Plus, Silicon Valley power players and the latest tech trends. Catch up on the conversations you miss during the day. Speaker 5 (0:24) Subscribe to the Bloomberg Businessweek Daily Podcast on Apple, Spotify, or anywhere. you listen. Speaker 6 (0:32) Bloomberg Audio Studios. Podcasts. Radio. Speaker 3 (0:36) News. I'm Barry Ritholtz. You're listening to Masters in Business on Bloomberg Radio. My extra special guest this week is Omar Aguilar. He is president, CEO. and chief investment officer of Schwab Asset Management. They run over a trillion dollars across 100 different ETFs, mutual funds, and separately managed account strategies. He also runs the Schwab Center for Financial Research, sits on the firm's executive council. He joined Schwab in 2011, specializing in equities and multi-asset strategy. Schwab's total assets are over $13 trillion. and its asset weighted expense ratio of eight basis points is amongst the lowest in the fund industry. I thought this conversation was fascinating. And I think you will also, with no further ado, Schwab's Omar Agarwal. Speaker 3 (1:42) Omar Aguilar, welcome to Bloomberg. It's a pleasure to be here with you, Barry. It's a pleasure to have you. So I want to get into your career and some of your conversations about what's going on in the market today and what's happening at Schwab. But you have such a fascinating background. I have to start there. Bachelors in actuarial science, then a master's in applied statistics from the Institute of Technology in Mexico City. Then you come to the U.S. and at Duke, you're a Fulbright scholar where you get both a master's in statistics and a Ph.D. in decision sciences. Am I getting that right? It sounds like you were planning for a career in academia. Speaker 1 (2:28) It is true. And actually, I did in my last year and my Ph.D. program, I did apply for a couple of academic jobs before I was lucky enough to basically get back to Wall Street as an analyst. Speaker 3 (2:41) Yes. So you your first gig is your your was it at Merrill Lynch was Bankers Trust, Bankers Trust and then Merrill Lynch. You have this deep quant research. background what did you do when you were first starting at bankers trust and then merrill lynch Speaker 1 (2:56) well you know if you uh recall from what the degree that you mentioned uh you know my dissertation and the work that i did was in how to use statistical models now they're called data science back then it was statistics um in terms of how use those models for making decisions the whole process of decision on their uncertainty was the whole you know research that I did. And we apply that, you know, in particular to areas like currencies, you know, equity, asset allocation. And I was hired at Bankers Trust to develop those models. So, you know, I call that the, you know, before any AI or anything else, they were just quantitative models that were able to help people being faster to understand how people make decisions. Speaker 2 (3:45) And Speaker 3 (3:46) I don't remember if it was the Ph.D. paper or the 2001 paper that it's still one of the most cited papers in quantitative research. How did you jump from Bankers Trust to Merrill Lynch? When did that transition happen? Speaker 1 (4:01) Well, there was, you know, if you follow the path of my background, a lot of that is related to the activities on Wall Street because there were a series of mergers and events that happened that took me to where I am today. You know, Bankerstross was bought by Deutsche Bank. And at that point, the group that I was part of was lifted out to join Merrill Lynch. Merrill Lynch Investment Management was starting to just build their institutional business. And that's where we became really nice fit. Unfortunately, September 11 happened 25 years ago. And then, you know, that basically took us to create the private bank asset management services for Lehman Brothers that wanted to branch out into the asset management business. their wealthy clients. And then from there, you know, it started to just get a little bit, you know, sensitive in terms of the Lehman business. So I had the opportunity to work with a former colleague of Bankers Trust, you know, at ING to basically rebuild their quantitative and systematic, you know, investment processes. So that was all related to activities that happened through the Wall Street, you know, acquisitions, events and so forth. Speaker 3 (5:11) And ING, now better known as Voya. That was $20 billion across 15 strategies, including active index, enhanced index, pensions, variable annuities, and mutual funds. Once you stand that up and get that to a reasonable side, was Lehman before that or after that? Speaker 1 (5:33) That was before. That was before. You know, we were able to build a lot of these things at Lehman Brothers. It goes back a lot of what my philosophy is, is you have to be in a place where you can marry distribution with manufacturing. That's what we believe asset management success relies on. ING had a very good distribution. Our idea was to build these more institutional type scalable businesses using quantitative tools and technology to be able to deliver that to different folks. And again, unfortunately, you know, we were in the middle of global financial crisis in 2008 that basically put a stop to every activity across, you know, New York and Wall Street and everything else. And that gave me the opportunity to go back to my academic roots and start working at Financial Engines with a lot of Stanford academics, you know. headed by Bill Sharp. Speaker 3 (6:25) To say nothing, right, of the Nobel laureate at Bill Sharp. I just want to clarify one thing. Lehman Brothers, the... quant research you were doing, was that for alternative investment management or for public equities? It was Speaker 1 (6:37) dedicated to both. The building asset allocation models for the private bank. And it was the first time that we were able to build a set of strategies that included alternative investments. So we had private equity, private real estate, fund of hedge funds. And that was the whole concept of what we wanted to do for wealthy clients back then. Speaker 3 (6:58) And then at Financial Engines, it's $40 billion in defined contribution plan sponsors. I'm fascinated by Bill Sharp's work. I was fortunate enough to interview him about 10 years ago. How did his thinking influence your approach to portfolio management and retirement Speaker 1 (7:17) planning? Well, you know, going back to this concept of behavioral economics, you know, Bill and the economics of Stanford have been at the forefront of merging this concept of how do we create markets and invest in markets that are not necessarily. efficient in the short run, but in the long run, they are. The sort of bill has always been in this idea of capital efficiency in the long run. It's better to do the buy and hold and stay put at a low cost as opposed to try to go in a market. The whole concept of market timing and avoid market timing was sort of the premise of everything. And that fits very, very good for 401k, for retirement assets, for pensions, where strategic asset allocation is what really drives your long-term results. So that was at the core of what we did. financial engines. And it's still at the core of the philosophy that we have at Schwab. So Speaker 3 (8:09) I recall one of the most fascinating things of many really interesting things Sharpe had said was the question of the annual 4 % drawdown in retirement as the thorniest problem in all of finance. I've read that you've said 4 % for many people doesn't make any sense. Do you want to address that? Yeah. Well, Speaker 1 (8:32) we've done and we did a lot of research. And, you know, the needs for income is not a static number. And it's not necessarily something where you can rely specifically about one thing. And what we have become is, you know, the 4 % rule became just like a number that somebody picked out of the hat and said 4 % works as long as you can generate those. And a lot of that had to do because if you think about it, Depending on the level of interest rates, you know, you can actually, you know, 4 % may be, it is right now, probably less than the risk-free rate. So there is no reason why you have to stay with 4%. So it is really a dynamic process that depends on the needs of the moment, inflation numbers, real growth, and the level of rates that may affect, you know, what is the drawdown that you need to survive. Speaker 3 (9:21) To say nothing of when 4 % was picked, the longevity. projections were so much less than they are today. If you're 68 and relatively healthy, you got a good shot at another 15, 20, 25 years of living on that pile of capital. That wasn't true 30 plus years ago. Speaker 1 (9:41) Absolutely, Barry. And a lot of the challenges that we face, and this is something that we work on financial engines, is getting into the habit of early saving. Because, you know, in the generation for Gen X and any of these generations, there is no pensions that were like back in the day. So people rely on 401k. So the ability for people to use that savings and the matching of the companies is critical for them to get to a point where they can retire. Speaker 1 (10:12) Unfortunately, you know, during all the research, we realized that the majority of Americans don't have enough to retire for this. Precisely what you said. It's more than 25 years of, you know, liabilities that they will have ahead. And with 4 percent drawdowns, they will run out of money very quickly before they can actually get there, especially when you have inflation impacting. Speaker 3 (10:34) So what's really so fascinating about your background. You're not only a quant, but somewhat unusually, you're a big follower of behavioral finance and thinking about decision making. You lead Schwab's BFI program for advisors, including diagnostic coaching tools, and you run the BFI barometer study. How does someone who's that mathy and a longstanding statistics, probability, and quant student fall into behavioral finance? Speaker 1 (11:07) Well, it is a great story because the area of statistics that were part of my dissertation, it's an area of statistics that's called Bayesian statistics. And Bayesian statistics is based on a theorem called by Reverend Thomas Bayes way back when. What it does, it basically combines information that you have today that is called a prior that could be your experience. and then uses all available data to update your experience, which is really our life. If you actually just think about it without necessarily creating a model, just think about it. You have an experience. You know what you need to do. I always give the example of trying to get to the airport. So you have your prior knowledge about how you and your own utility function, how early you want to get to the airport, how difficult that may be, the potential problems, the probability you'll miss the plane, and everybody has a different way to approach it. You know, two people with the same background, everything else. One may actually want to get there three hours ahead. The other person may want to get there like just five minutes before they start planning. They both take different types of risks. Updating that information over time, that's basically how decision process is. And that's probability and its core. And that's pretty much what Bayes-Tiorin does. I Speaker 3 (12:24) wonder if Bayes... how he would have thought about this if he was married to my wife, who she doesn't want to miss a plane, will get to the airport two hours later, bring a book. That's just how it is. But it's interesting that, you know, people have very different approaches to that. How much time do they want to waste versus the headache of missing a plane? So I'm curious, how does your education and decision science shape the way you think about the big issues like markets, risk? and investor behavior. Yeah, Speaker 1 (12:56) well, you know, I have always been passionate about, you know, providing tools and services to investors to help them enhance their financial lives. That's at the core of Schwab Values. That's at the core of what we do in asset management. And a big part of that, Barry, includes the fact that, you know, we want to provide information to clients so that they can make better decisions on their process. So again, the whole idea of try not to time the market, try to look at your long-term investments, try to stay calm, you know, when things are. All that goes back to the core of their behavior because we're all humans. You know, all of us, you know, have evolved over time with two parts of our brains. One that is the amygdala, which is the more private, you know, primitive, you know, version of us that allows us to react and, you know, go fly to safety whenever we see a problem and allows us to just, you know, be emotional about things. And then the other part, which is the part of the front of the... of the brain that allows us to be rational and allows us to use data to make decisions. That combination, which sounds very familiar to the base TRM, one that is more gut feeling, the other one that is more analytical and more brain oriented, and they get combined. And every day they're battling with each other. So for us, Being able to provide the context for clients that are more emotional with the information they need to adapt to their investment strategy so that they don't panic when the market goes down or they don't have and give them a process that is quantitative in nature so they can stay the course is very important. On the other hand, we have other clients that are more analytical in nature. They think they can outsmart the market. They think they know the answers. And we give them information and data so that they can inform and update their own beliefs so that. they can have better decisions. So arming clients with the tools and products and solutions to make them and help them make better decisions is the core of what we do. A Speaker 3 (14:50) little bit of thinking fast and slow. Bill Bernstein, neurologist, had said, you mentioned the amygdala, our whole limbic system is what underlies fight or flight. If we don't get that under control, we will die poor. And it really is... quite quite fascinating in in actual usage when you're in in the real world when you're advising clients and investors about their various behavioral foibles and and errors how do you get them to stay on the straight and narrow what tools to schwab use to prevent investors from shooting themselves in the foot well Speaker 1 (15:35) Two things we do is first we we do a lot of education through our Center for financial research We also provide a lot of training to our wealth advisors and our financial consultants was precisely the tools that you mentioned at the beginning We call it is very cute name by gnostics, which is supposed to diagnose your biases in a way That's you know, our marketing was smart enough to put it together So it is a diagnosis team for your biases and the reality is that all of us have biases one way or another So the tools that allow financial consultants to get to know their clients better. You know, we have data that basically says that the more information we get from the client or their biases allow us to build longer relationships with them. And at the core of what we do, we simplify it by saying, well, we have to balance their needs with what they want. There's a lot of clients, they tell you what they want. And you as a financial professional, you know what they need. And we need to put them together. If you think about in the world of AI, you know, the need is basically what the computer is going to tell you. The computer is going to tell you this is the right allocation. This is what you need to do. But the want is what the client, you know, wants to have. And merging those two is the critical part to maintain and have a sustainable long-term investment strategy. Speaker 3 (16:53) Really, really interesting. Coming up, we continue our conversation with Omar Aguilar, president, CEO and CIO of Schwab Asset Management, talking about how he helped build the asset management group to over a trillion dollars in client assets. I'm Barry Ritholtz. You're listening to Masters in Business on Bloomberg Radio. Speaker 6 (17:15) Hi, I'm Carol Masser with a helpful tip to keep you plugged in throughout the market day. Subscribe to the Stock Movers report from Bloomberg. These are short audio episodes, five