The Science and Art of Investing | AWM Insights #174
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Episode Summary
Over the past 150 years, data on markets has been collected, analyzed, and an optimal investment process has been discovered. This process has been shown to reward investors over long periods.
It includes taking advantage of diversification, flexibility, the efficiency of markets, and technological advancements that help markets function.
Even with the rigorous, science-backed methods of investing, there is still an artistic and emotional side that can’t be ignored.
The rewards of investing are founded on the principles of commitment and consistency, so managing your emotions, incorporating investments that matter to you, and being able to weather turbulence are just as important as the fundamentals.
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Episode Highlights:
0:00 Intro
1:55 Diversification and reducing unrewarded risk in your portfolio
2:29 Flexibility improves purchase prices
3:15 Active management is more of a friction than a value-add
3:50 How technological advances and market forces penalize active management
6:43 The Art of Investing
8:32 Investing as a practice
10:33 Text us!
+ Read the Transcript
Brandon Averill (00:03): Hey everybody. Welcome back to another episode of AWM Insights. We're continuing down this path of really talking about the experience of being an investor, a successful investor, and really how it relates back to your life in its totality. We've talked a lot about priorities and how it fits in as money as a tool is something we commonly say, and I think today what we wanted to talk a little bit about was how do some of these things come together. At the end of the day, investing is an art, there's an art aspect to it. It's certainly a practice. It's something that we have to continually tend to, otherwise we won't be good at it.
(00:45): But scaling all the way back, it is a science. There is a science to how we actually go about this. And so how did all these things come together? And I think one place would be really good to start, Justin, is investing as a science. Maybe go through a little bit of the history of the science of investing. How do we actually look at this instead of just having the crystal ball that we're going to read the tea leaves and figure out where things are going.
Justin Dyer (01:15): We know after years and years and decades of academic research that we can really boil down the science to a couple key tenets. There's a lot under the hood, so I'm trying to simplify it for the purpose of this podcast. But the science piece of it took many, many years to really develop. But again, since really the sixties, it is been a, I would say, a commonly accepted list of items here that distill what truly the science of investing is. There's lots of interpretation, we'll get in that in the art piece of it to an extent, but diversification reduces risk. Number one, I think we all know that, but it's often forgotten, let's call it. Uncertainty creates opportunity, so uncertainty in the market is one of the reasons why you should expect to earn something more than holding cash or holding a treasury bond. Something that has a lot less risk. Uncertainty you can almost define as risk. There's ways to diversify that risk, see above, but uncertainty does create opportunity. It's one of those reasons why we have a higher expected returns.
(02:25): Flexibility is a great one. Flexibility truly adds value. Instead of just taking a market price, or the great analogy I think we've used time and time again here is if you go buy a car, if you're more flexible and you're like, no, I don't want the white car, I want the pink car. Just to be extreme on that, you're probably going to pay a higher price for that specific, very detailed item you want. Whereas if you're like, no, I just want a car, I'm going to find the best price, you're going to get some additional value to it. So that's a way of thinking about flexibility.
(03:00): And then this is the big one, I think, conventional active management isn't really worth the cost. It's been proven time and time again, there's reams and reams of data, yet people still try and do it. So I think that's the core tenets of this idea of investing as a science.
Brandon Averill (03:16): And I think at the end of the day, you mentioned the 1960s, really technology is a big reason behind this science that we can make some of these statements, right? It was the 1960s that computers really came about and started to become powerful enough to go back and study the information of stock pickers, of investors from previous generations. And then if you think about it, as time has gone on, the power of computers continues to get better and better. The synthesizing of information and what continues to be proven out is exactly what you're talking about. And something that's been raised, I think interestingly by a lot of our clients, that you guys that are listening, but also, I mean, it's a question we've been asking ourselves. We seem to be in this next technological movement potentially with AI and all the different large language models. How do we think about this in investing?
(04:14): There was a great article in the Financial Times that David Booth, the Founder of Dimensional Fund Advisors wrote, and he had some pretty fantastic zingers. But I think the thing that really stuck out to me the most is that really the market is the best AI machine. When you think about what machine learning is and what AI is actually designed to do, at the end of the day, the whole purpose of AI is to take a ton of information, distill it back into a language, into a text that seems like it's written by a human, but it's not designed to predict anything, it's to take historical information and distill it. So when you actually put that in context, I mean the market is largely a big AI machine. And so I thought that was fascinating.
Justin Dyer (05:05): Oh, it is. It's a perfect analogy. You're taking reams and reams of data, information, putting it into some sort of system. There's a digestion of that information. In the case of the market, it's typically humans. There's a lot of computer assisted digestion there, but it is then coming up with the next best answer, which essentially is what a large language model or AI or machine learning is effectively doing. And so it is, it's a perfect comparison. And in that article you referenced, there's a great example, if anyone's interested or has ChatGPT on their phone, go ask it. Is it safer to trust the market price than rely on an AI model to find mispricing in stocks and bonds? And guess what? The short answer is that AI even says don't trust AI, trust the market, trust market pricing.
(05:56): And it is for the reason, we say that kind of tongue in cheek and poke fun at it, but it is for the reason. It's because there's all sorts of information coming into the market, being reflected by multiple people, and then the price comes out. And that's generally speaking the next best answer that you should rely on.
Brandon Averill (06:12): So at the end of the day, science really does prove out that, hey, we can't beat the market from a stock picking perspective. We go into other podcasts and we talk about our philosophy and really taking the large swaths of information that are provided, participating in the market, and then using science really to get to areas of the market that will outperform, or at least are expected to outperform over time. So really kind of taking that science piece though, so maybe turning to the art of investing, Justin, maybe hit on a few things that we look at there as we start to marry these together.
Justin Dyer (06:51): So, I kind of alluded to it at one of my comments previously, but there is this commonly accepted science aspect of investing, but you can interpret that data in wildly different ways. The way to think about this is investing is more like medicine than it is like traditional mathematics. Math has proofs. There's a right and a wrong answer, unless you get into some crazy theoretical math. But generally speaking, there's a right and a wrong answer. In investing, the science is subject to interpretation, the art of the science, if you will. And in that sense, it is similar to medicine, right? You will go get a second opinion because two physicians, two surgeons can look at a set of x-rays or MRIs and have two different opinions around it. They're interpreting the science or what they see in a little bit of a different way.
(07:48): But the execution and engineering and interpretation is critical to a successful outcome. There's a great quote by this gentleman, Myron Scholes, I believe he's a Nobel Laureate. "Ideas are cheap. What matters is how you execute." So this is where the industry, I think, does a lot of disservice to ourselves and to the end investor. They take that information and they will manipulate it or "interpret" it in a way that really enriches themselves more so than doing what's best for clients at the end of the day, through a really rigorous set of requirements or expectations or just leading with what is truly best. That fiduciary standard I think is often overlooked.
Brandon Averill (08:33): And I think that's a huge point. And then the last piece is investing as a practice. So how does this all come together? You mentioned the health aspect of the art side, and really it comes back to this as well. Good health requires good attention, good habits, et cetera. And investing is really no different.
Justin Dyer (08:51): No different at all. I mean, you mentioned this at the outset. These are daily practices. Investing is not this static, set it and forget it. Although having that kind of general mindset is pretty good, because this is a very long-term endeavor, but you need to constantly care for it, constantly remind yourself why you're doing something. And that's where, I think, we're really hoping that this series of last few podcasts that we've done helps in that endeavor. There is the pure, Hey, here's what the data says, here's what you should do.
(09:22): Then there's the behavioral side, and we need to blend these two things together to come up with what the practice, the daily practice, or the monthly, yearly, et cetera, practices are to keep you on course so that you can do what you want to do. It's no different than, hey, you want to pitch at the highest levels, you want to go for a [inaudible 00:09:42], you want to run a marathon. Choose your physical endeavor. Investing has the exact same endeavors, and that's you meeting your priorities, you being able to accomplish what is important to you in life. And the practice aspect of investing is really where the rubber meets the road to give you that assurance.
Brandon Averill (09:58): And I think practice, everybody listening that is an athlete, or even successful in business, at the end of the day, we know that practice is all about the process. It's all about controlling the controllables. And I think that goes back to the investing side. Sometimes the habit is to do nothing. It's to not tinker. It is to control the controllables, control your process. And if you control the process, that generally is going to lead to really good outcomes.
(10:23): So hopefully this is helpful, just kind of marrying some of the science, the art, the practice into a really successful client investment experience. And so we welcome your questions, shoot them on over. You guys know the text number by now, 714-504-7689. And until next time, own your wealth, make an impact, and always be a pro.