E427: AQR's Peter Hecht on AI, Market Bubbles & How the Best Investors Build Portfolios

Peter Hecht, Managing Director at AQR Capital Management, explains why diversification has to be measured by underlying risk rather than the number of investments you own. At AQR, diversification is a core principle: thousands of relatively small, uncorrelated investment decisions can collectively create an attractive return for a given level of risk.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00David Weisburd?

  Pete, at AQR, you have $242 billion assets under management. You're one of the largest hedge funds in the world. And one of the things I wanted to start with is, one of my biggest pet peeves in this industry is this concept of a tracking error. Tell me about tracking error, and is it a misnomer?

• 0:19Speaker 01

  We're familiar with concepts like volatility, which sort of gives you a sense of the range of outcomes for an investment's return. Tracking error is the volatility, but it's the volatility of the relative return, your return versus a benchmark. Okay, so let's say the S and P 500. Okay, so tracking error is going to give you a sense of how far a manager's relative return, how different it can be from the S and P 500. So like a tracking error of 3% means if you think it's a normal distribution, right? You're going to have a return that's going to be either 3% ahead of the S and P 500,

• 1:00Speaker 01

  3% behind the S and P 500 with roughly a 66% probability. So it gives you a sense of how much active risk am I taking? And is it consistent with my risk tolerance in terms of my willingness and ability to tolerate lagging the benchmark?

• 1:17David Weisburd?

  Can tracking error be a good thing?

• 1:20Speaker 01

  Yes, because if you want to beat the benchmark, if you want to try to add value, you have to take tracking error. So I always tell people, you can take bad tracking error, right? That's with a manager that does not have a good process for determining what's an attractive security and not an unattractive security. Or you can invest with a manager you think has a good process. You have to take tracking error to beat your benchmark. The more tracking error you take gives you more possibility for beating the benchmark, but it also means you might actually lag the benchmark by more when your manager experiences bad luck.

• 1:56David Weisburd?

  Speaking of the markets, they don't operate in a vacuum. The more passive investing becomes a norm. So now we're still in this era of passive investing. Active investing seems to have more room for alpha. Is that generally true?

• 2:12Speaker 01

  There's a big debate there in terms of whether the rise of passive is distorting prices, making it harder for active managers. I would say from my vantage point, while passive has become more important and it is a large part of the market, I still believe there are enough active managers that are going to take the time to read the information, process the information, and pound that information into prices. And so whether there being more passive or not is good for active managers sort of depends, right? Because it sort of depends on who's getting fired to go passive.

• 2:51Speaker 01

  If it's really bad active managers that are getting fired and should be going passive, right? Now, all of a sudden, the remaining active managers, on average, are higher quality. But if it's actually some good active managers actually getting fired, maybe there's less competition in terms of being able to harvest, identify and harvest alpha. So it sort of depends on what you believe in. So there is no hard set answer.

• 3:19David Weisburd?

  I spoke to former president of Peter Thiel's hedge fund, and he talked about this reflexivity and the volatility that's caused by the passive amount of capital. So now you see, oftentimes in the market, markets go up or down because everybody's making the same trade. Does that make the market inherently more volatile?

• 3:38Speaker 01

  There have been some academic papers, and it's early innings, and there's people who disagree with it, that believe that the rise of passive have made markets more inelastic. More inelastic means flows will actually move prices, even if those flows are for non-fundamental reasons, which would lead to a more volatile stock market, for example. That's possible, that with more passive investors, people who just take prices as given, aren't as sensitive to prices. I can see the possibility that you would see more elasticity and thus, for a given flow, maybe today, maybe there is slightly more sort of market impact, flow-based movements

• 4:21Speaker 01

  in prices than what we saw before, which would lead to more volatility. It's early innings, and in academia, sometimes it takes 20 years to figure out who is right.

• 4:30David Weisburd?

  AQR has $242 billion. You have all these different strategies, but at the core, how would you describe your philosophy?

• 4:37Speaker 01

  First off, we believe in diversification. So we are a systematic fundamental manager. Some people call us quants. I like to actually say systematic, because within quant, there are people who are mathematicians. Like, I have a PhD in finance. Okay? When you're, most systematic managers have a small edge for any single security that they trade. And you might ask, well, then, how do you actually develop strategies that have good returns? Well, like a casino, a casino would never exist if it could only play blackjack against you, one person. They bring in thousands of uncorrelated blackjack customers. That's like bringing in thousands of uncorrelated trades.

• 5:20Speaker 01

  So we believe in diversification. We're militant about thinking about, are these trades correlated with each other? And through that diversification, through that portfolio construction, we can actually achieve an attractive return for a given level of risk, whether that's in a market-neutral implementation, where someone doesn't want any beta, or in an implementation where someone wants full market exposure, beta one. So that is a core tenet, diversification across all of our products.

• 5:51David Weisburd?

  When somebody comes to you and says, does AQR generate alpha? How do you answer that question?

• 5:58Speaker 01

  There are many ways to measuring alpha. It's an art. So first off, finance is a social science. It's not physics. It's not math. So it's always art.

• 6:07David Weisburd?

  Probabilistic in nature.

• 6:08Speaker 01

  Yeah, it's probabilistic in nature. And alpha is always relative to what model? What is your risk model? So, and this was like what Jean Fama taught us in the PhD program at the University of Chicago on the first day of the PhD program. It's all relative to your market equilibrium. If your model of market equilibrium that determines what are the risk factors and those risk factors should be compensated, if one of those risk factors is a value-type factor like book-to-price, going long book-to-price, short book-to-price, Jean Fama would say, if your return can be explained by that, that's not alpha, because it's part of his risk factor framework.

• 6:52Speaker 01

  But other people would debate, why is a book-to-price a risk factor? Maybe it's just something that's picking up the fact that people have over and underreacted to past earnings, and high book-to-price stocks that look cheap have just had disappointing earnings and people overextrapolate. There's behavioral finance stories. So alpha really depends on the risk model you use. So like anything in finance, because it is a social science, treat it like a painting. You're going to do multiple ways of measuring alpha. So the one way might just be, let's control for market exposure only. So there were some very famous models in the 1960s.

• 7:36Speaker 01

  Bill Sharp run, won the Nobel Prize, and other people developed the capital asset pricing model that controls for market beta, something people call, use the word beta all the time. You could just look at it versus beta, a standard market beta. You could then say, hey, Jean Fama and Ken French, they are famous. If it's a stock selection strategy, let's expand controlling for alpha. Let's put in a value factor and some of the Fama-French factors, and if your return can beat those factors, then we're going to call that alpha. And then people would disagree and say, you know what? I'm going to throw in 10 factors that I think are well-known and are associated with the risk factor.

• 8:18Speaker 01

  So from my standpoint, it's always conditional on the model you assume. But you could also sort of just step back. At the end of the day, you might not care whether something's alpha or not in some academic sense. You just want to know, by having it in my portfolio, does it improve my return for a given level of risk? And I can actually measure that by running a regression of the possible new investment that you're considering on the current portfolio you hold.

• 8:53David Weisburd?

  Is there essentially two definitions of alpha? One is risk-adjusted return, and the other one is versus, in the context of a benchmark? Are there really two different definitions?

• 9:01Speaker 01

  They're all related. So alpha is just a very, you know, like I always tell people, if you ask me what I had for dinner, and I said food, you'd say, that's not very specific. And then if I just said fish, that's not very specific. So saying alpha is sort of like saying food. And then saying risk-adjusted return versus a benchmark is sort of telling me, are we talking fish or meat? And so there are many ways of doing risk adjustment. And I would argue, part of the reason why my group exists is because there is that subjectivity, and there is an art to understand what's appropriate, what's not appropriate. But the best way to handle any situation where there isn't a definitive answer is

• 9:46Speaker 01

  to do it multiple ways. A sharp ratio is one way of calculating risk-adjusted return, but it doesn't control for beta.

• 9:54David Weisburd?

  I know you were an assistant professor at Harvard for five years after finishing your PhD, but for you today, the source of truth is the customer. What does the customer want?

• 10:04Speaker 01

  Yeah, so to me, the most potent thing is to actually calculate alpha relative to their current opportunity set, which is the portfolio they hold.

• 10:12David Weisburd?

  The opportunity cost.

• 10:13Speaker 01

  Yeah, so it's, by having access to this, do I improve the return of your portfolio without taking more risk? And that can actually be calculated. It's called an appraisal ratio. It goes by many names, but to me, that's the most important thing I'm trying to do. If some theoretical exercise says it has alpha but doesn't improve your portfolio, it's dead to you, as far as I'm concerned.

• 10:36David Weisburd?

  A mutual friend told me that you're one of two TAs at AQR from Eugene Fama, famous Nobel Prize winner, who popularized this idea of small and value. Today, many people, many very smart people, challenge that small and value still persists. What do you say to that?

• 10:54Speaker 01

  We would have questioned the validity of small decades ago. So I remember some of the early paper that brought the small cap effect to light in the academic literature. First off, had data errors in the paper. So, most people don't know about that. There were like positive signs that should have been negative signs on returns. The second thing is, let's say, small caps beat large caps. Okay. But small caps have higher beta than large caps. So, small caps on average beat large caps, but they're higher beta. Bill Sharp told us, in a rational economy, higher beta stocks should have higher average returns. So, are you just picking up higher beta stocks?

• 11:36Speaker 01

  Once you control for beta differences, we found there was no, there was no small cap effect. So, even before people started saying there was no small in the more recent time period, we would have questioned that. So, while something like size can be a risk factor, we didn't think it was a rewarded risk factor with a positive return associated with it.

• 12:01David Weisburd?

  Said another way, you could have just levered the larger stock to the same beta level and outperformed the small cap.

• 12:09Speaker 01

  Or had the same performance, so that there was no difference whether you were in small or large cap stocks. And to your point on value, obviously, Fama-French made it very famous with their sort of seminal paper where they looked at book to price. Back in the day, we would have said, there were always so many different ways of measuring value, first off. And what made the Fama-French insight amazing wasn't because it was just book to price, it was the larger underlying guiding principle that something that's fundamentals scaled by price might be informative about future returns.

• 12:50Speaker 01

  Even like back in the day, two decades ago, most managers who were doing some type of value inclusion in their process, weren't just using book to price. There are many ways of measuring cheap versus expensive. And I would say today, there are, that process has even evolved. People are using machine learning techniques to come up with better value measures. One thing in Fama-French, and I understand why they did this, they didn't control for industry. So, let's say where someone says, my value measure is a PE ratio. And I'm going to compare a PE ratio of a tech company to a utility company and say, the tech company is expensive because it has a high PE.

• 13:34Speaker 01

  The utility company has a low PE, it's cheap. And it's like, they're different industries. They have different fundamental growth. When we think about implementing value and a lot of thoughtful managers, it's within a peer group where it's apples to apples. It's a utility company versus a utility company. It's a tech company versus a tech. While the simple Fama-French was just across the entire universe. So, all of those types of design choices, managers, thoughtful managers, were doing a decade or two ago. And even today, things have evolved with the explosion of like machine learning. And there's always innovation going on at firms.

• 14:10David Weisburd?

  These memes in the market, even when they're untrue, just persist, could persist for decades, even among some of the most intelligent people.

• 14:18Speaker 01

  One way to protect yourself against that, because it's obviously very hard to try to predict that and to predict how long it will last, is go back to one of my, the sort of guiding principle that sort of is part of all of our implementations is diversification. Right? If you're holding a thousand stocks, long and short, and they all have small weights, then if a couple of them go wrong, even if they go wrong in ways where it's not just like you're short and it was up a couple percent, maybe it was up 10% or 15%, you can really minimize the damage to the overall portfolio. In contrast to like a concentrated manager, who's long 20 names, short 20 names, if

• 15:03Speaker 01

  they're on the wrong side of one of those stocks, that can ruin their entire year. So, our diversification is consistent with us being a systematic manager and having a small edge, but it has the risk management sort of positive collateral benefit. Because that means when one of our longs goes down, or one of our shorts is going up, we can sort of contain the amount of damage.

• 15:25David Weisburd?

  Everyone I talk to on the show is chasing the same thing, an edge. And more and more, the edge comes down to your information, not just having it, but being able to trust it when the stakes are highest. AI is doing more of the information gathering for you every day, and most tools are very good at sounding right. The summary reads clean, but can you trace it back to the filing, the transcript, the specific passage that drove the answer? Or are you just trusting the confidence of the output? For investors, that's not a minor concern. A missed filing, a misweighted source, a context that got lost somewhere in the retrieval chain, those aren't edge cases, they're how decisions go wrong. AlphaSense is the AI market intelligence platform built specifically for this. They own the content, over 500 million curated documents from broker research

• 16:09David Weisburd?

  and expert transcripts, to filings and earning calls, and they own the retrieval layer on top of it. So, every answer links back to an exact verifiable source, because the answer is only as good as what's underneath it. And with AlphaSense, you know exactly what that is. The edge goes to whoever could trust their information and prove it. See it for yourself. Start your free trial at alpha-sense.com/HowIInvest. That's alpha-sense.com/HowIInvest. I've spoken to quite a few quant investors, and they're saying, everyone's just loading information to Claude and following what Claude is telling them. Is that a risk to AQR and AQR's model?

• 16:50Speaker 01

  No. I'm working on a paper that's related to this idea of whether the rise of AI is going to lead to convergence. Right? Oh, everyone has access to the same tools, you guys are all going to do the same thing. So, first off, let's talk about these large language models. So, in terms of, while there's many ways you can use it in investing, there's one way that I'm going to call the prompt-based approach. You literally ask ChatGPT or Claude, is Apple cheap or expensive? Give me your analysis and give me the details why you think it's cheap or expensive. That's prompt. Okay? Then, there's a way of using a large language model where you feed in documents, financial

• 17:30Speaker 01

  documents, broker reports, earnings reports, and you go under the hood of the large language model, and you take what we call a word embedding, which is a numerical representation of the text. So, the large language model converts text into numbers. Okay? Then, once you have these numbers that represents the text, it's like any other signal, you have to now calibrate it to see if it predicts returns. When we use large language models, we're doing the latter, we're not doing the prompt-based approach. All of the special sauce is not in the large language model. The fact that you can get a numerical representation of the data is sort of a commodity.

• 18:13Speaker 01

  The hardest part is, can you find whether that numerical representation of the data can predict future returns? We're using all of our in-house proprietary models to do that. So, the reason why there won't be convergence, because everyone's using Claude or ChatGPT, is, one, prompt-based is very inefficient. Two, even if most managers are doing the numerical representation approach I talked about, all of the special sauce is, once you have that numerical representation, how does it help forecast returns? That is very difficult to do, requires a ton of skill, and it's highly subjective. And that's why I don't think there'll be convergence.

• 18:55David Weisburd?

  It's this taste thing that everyone talks about, taste and judgment.

• 18:59Speaker 01

  Yeah. What separates a good systematic manager from a bad systematic manager? It's not obvious which signals predict returns and how they predict returns. That requires, that's the art component of what separates two people that's on paper look the same in terms of background, oh, they have a PhD, somebody that has those insights to know, this is good judgment, this is, we're overusing and abusing quantitative tools versus we're underutilizing and we're leaving money on the table.

• 19:30David Weisburd?

  How much AI are you using in your process?

• 19:33Speaker 01

  AI, machine learning, it is definitely a material component to our process. But we also use the pre-AI techniques, because it's additive. If we isolate it, and sometimes there's overlap on whether something is a machine learning signal versus did it have some of our old way of doing, I'm calling it the old way, the non-machine learning way. But if you could bifurcate our signals into, this is machine learning-based, this is non-machine learning-based, the non-machine learning-based signals have alpha against the portfolio that's only doing machine learning. Therefore, just like I told you, it only matters what the client's portfolio

• 20:14Speaker 01

  is. If your client's portfolio is only ML, and it's additive to add in these non-ML signals, you should do both. So, ML is, has alpha versus the non-ML signals. The non-ML signals have alpha, that's just saying you should be doing both, and that's what we're doing. Now, ML will always have some limitation, because we actually have small data in finance, unlike image recognition in driverless cars, which will limit whether it will be 100% of the process. We also have competitive markets, like efficient markets, where if I have private information on whether something's cheap or rich, I'll trade on it, and therefore, it will be reflected

• 20:57Speaker 01

  in the price such that future price changes are random and hard to forecast. So, for all of those reasons, while AI, machine learning can be helpful and we utilize it, it, there will be sort of a cap on how much it will be part of our process because of those sort of underlying principles of our marketplace and investing.

• 21:20David Weisburd?

  Ken Griffin from Citadel says that his number one assets is recruiting the next generation of people to build the business. Even Renaissance Technology, everyone thinks of this amazing black box, but it's really all the PhDs that they brought in to build that out. When you think about who you're recruiting today, is that fundamentally different than it was before Claude and before GPT?

• 21:42Speaker 01

  It's similar qualities because you want someone, again, you, we're going to have that economic finance PhD bent. That doesn't mean we won't have PhDs in stats and math, but that's sort of part of our DNA and our process. We want people who are intellectually curious, right? Because that protects you from drinking the Kool-Aid where you run some back test and it works and it was just really due to chance. You have the intellectual curiosity to test it in other markets and test, try to find out of sample data sets and then you realize it actually doesn't work. So intellectual curiosity.

• 22:21Speaker 01

  You do have to have good at empirical applied sort of analysis. You also, depending on the role, you have to be good at communication. Even people who are quants, like most projects involve other colleagues. And if I have a ton of knowledge to give and I can't communicate it, it's trapped in me. One of the things that I think Harvard helped in terms of molding me coming from Chicago is while I thought I was a good communicator before, Harvard really promoted this notion of you're in the boardroom. Now, at first, when I joined there, I sort of thought like, yeah, that's superficial. Isn't it about the engine? And they said, actually, the paint job's important, the communication's important

• 23:05Speaker 01

  because you have ideas that you want to convince people of that they should take on as their own ideas. So yeah, you need to have strong analytics, you need to understand finance and economics, you need to be intellectually curious. Also, we think about making sure we have enough communication skills so that you could work with your colleagues productively. So I think in that sense, it's very similar to what we would have done 10 years ago. But human capital is where it's all at, right? It isn't like, well, you just, we all, we're all widgets, AI is going to force convergence and we just sort of come in and press a button and some model runs. There's so much subjectivity, even in a systematic problem.

• 23:47Speaker 01

  If your asset manager is not innovating, it's not a sufficient condition. If they're not innovative, it's a necessary condition. If they're not innovating, you need to be looking for another manager. So that is core to our business model.

• 24:00David Weisburd?

  How do you go about figuring out what goes into your model and what gets taken out?

• 24:05Speaker 01

  In general, let's talk high level. It's really hard to get in our model. Okay, so we're going to have a very high bar. And so that process-

• 24:15David Weisburd?

  And these are the factors in the model.

• 24:17Speaker 01

  Yeah, they could signals, we think of them as signals, like you can think of, again, a really simple one, we were talking about Fama-French and value book to price is a very simple value signal. Okay? So some things that we tend to have, again, this is not universal, there might be some exceptions with machine learning. Hey, maybe start off with a, an economic thesis on why this signal should predict returns, right? Is there some behavioral finance on a reaction story, et cetera? So that you're not just sifting through the data, trying to find relationships that maybe aren't going to hold out a sample because you were just finding patterns in randomness. Okay, so start off with maybe a thesis.

• 24:59Speaker 01

  And then when you go to the data to test that sort of economic thesis on why it should work, we do stock selection macro arbitrage, let's just keep it in stock selection. Let's say you first test your hypothesis in US large caps and it works. Then we're going to say, all right, but your theory also says it should work in US small caps. Let's test it there. Does it? Oh, it does. Good. Your theory isn't about US domination, it should work in European markets, it should work in Japan. Let's go grab European markets and test it there and in Japan and Australia. It should work in emerging markets. Let's test it there. Again, even signals that work sometimes won't work temporarily in one particular market.

• 25:43Speaker 01

  So you look at the weight of the evidence. So we're looking for out of sample validation. Then we might say, you know what, we can buy a new data set that actually gets a new timeframe that we didn't have access to the data, we could treat it as an out of sample test. We'll test it there. Then some of our signals, if they predict a single name stock, maybe they should also predict country level indices like the S and P 500 versus the FTSE versus the Nikkei. Let's see if it actually works in macro assets like equity indices because it should. So we're always pushing the data with all of this out of sample verification, even though we're starting with sort of an

• 26:26Speaker 01

  economic foundation to try to minimize the chance that we're just finding patterns in randomness. But there's an important point here and we've evolved here. Everyone's always worried about the risk of overfitting. We also now spend time worrying about the risk of underfitting. Machine learning has taught us that there are some complicated relationships between these signals and future returns. So let's take a simple example. Let's say you used to constrain yourself to these simple linear ideas and linear models. Well, maybe there's nonlinear relationships between book to price and future returns.

• 27:06Speaker 01

  And so machine learning techniques have taught us that maybe we're leaving some money on the table by not using more sophisticated statistical techniques to try to find the relationships between those signals and future returns. But that would be a high level understanding of what our process would be, very high bar to get in. And then, once you're in, we're not going to just remove you after you have a bad month, right? Because we recognize, again, if we only, if each signal only has a small edge, there'll be times when it will lose.

• 27:44David Weisburd?

  That's a subjective aspect to it.

• 27:45Speaker 01

  Well, we've actually systematized it where we actually use machine learning techniques that will sort of down weight and up weight signals based on whether they're-

• 27:55David Weisburd?

  It sends some confidence in it.

• 27:56Speaker 01

  Yeah, based on whether they're working and out of sample live trading.

• 28:00David Weisburd?

  It's this theme that I see from podcast to podcast, the importance of the rootedness of the thesis. Coming in, you have to have a really good idea of why you're doing something because it helps you ride out those waves that inevitably come in markets. If you're not rooted in your thesis on the way in, you may still make the same purchase, but you're going to sell at the wrong time.

• 28:20Speaker 01

  Yeah, that could be another, like it gives you the conviction to stay with the trade. Now, that being said, we also want to be open minded, right? It could be that we were wrong. So there's sort of a healthy balance. Our founder, Cliff Asin, has always said, we want to be open minded, but not so open minded that our brain falls out, right? Because there are people where once things just don't go well, they, they bail, but they don't bail and make it sound like bail. They just, no, it's because I'm flexible and I learned something and I actually have a different view. Again, you, that could be true, but again, that's where the subjectivity comes in and whether someone has really good judgment, are they just pulling the plug prematurely or did they come up with rigorous evidence to suggest they need to change their mind?

• 29:04David Weisburd?

  Are you looking for a 51% hit rate, a 55% hit rate, a 90% hit rate?

• 29:10Speaker 01

  In stock selection, the way it ends up working on average is, let's say, if we're right about 55% of the time, we've hit our target return and at that reasonable risk level. So that means 45% of the time we're wrong. And when you look at it, again, there's always exceptions. If you said like, or let's say one year we were 52% right and we hit our target return. And let's say we're having a bad year and you must be like, well, instead of 52%, you must be like at 37%. You're having a bad year. No, we're at 49%. Like the difference between having a, hitting your target return or having a good year

• 29:55Speaker 01

  versus a bad year, it's small, like, right? It's a small edge. So while we're still maybe right 48% of the time or 49% of the time. And again, that's why we believe in diversification. That's why we're doing the innovation to bring in more signals so that we could have that better batting average.

• 30:12David Weisburd?

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• 30:57David Weisburd?

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• 31:15David Weisburd?

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• 31:59David Weisburd?

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• 32:43David Weisburd?

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• 33:28David Weisburd?

  And when you make a sale, you don't have to wait days to get paid. Square gives you fast access to your earnings through Square Checking. They also have built-in tools like loyalty and marketing so your best customers keep coming back. And right now, you can get up to $200 off Square hardware when you sign up at square.com/go/HowIInvest. That's S-Q-U-A-R-E.com/go/HowIInvest. With Square, you get all the tools to run your business with none of the contracts or complexity. Run your business smarter with Square. Get started today.

• 33:58Speaker 01

  But yes, it's not like we're right 80% of the time. It's more like low 50s, mid 50s for our stock.

• 34:04David Weisburd?

  Is trading a place where you seek not to lose any of the alpha that you made through investing, or can you also capture additional alpha on the trade?

• 34:11Speaker 01

  If you're like a market maker, if you're a citadel, they have a whole team that's making money through trading because they're providing liquidity. Okay, they're providing liquidity who want liquidity and they make a liquidity premium. So you can't, for us, the type of investor we are, we are not a high-frequency trader. We are always trying to minimize the impact on our alpha ideas.

• 34:38Speaker 01

  So we're not trying to be a market maker.

• 34:40David Weisburd?

  That's not your business.

• 34:41Speaker 01

  That's not our business. Our business model is we're a fundamental systematic manager. We're thinking about the next month, the next quarter, the next year, not the next tick or the next five minutes.

• 34:52David Weisburd?

  Speaking of your business, you operate with customers, institutional investors, high net worth individuals. What type of strategies are they asking for today?

• 35:02Speaker 01

  There's some commonality. The first and foremost is a multi-strategy. And why is that? Because people have realized that it's hard to pick the single sub-strategy that's going to outperform next year. If you think they're all good over the long run, get the benefits of diversification in the single-line item that does a multi-strategy approach. So it will include stock selection, market neutral, it will include market-neutral macro, it will include directional macro like trend following, it will include corporate arbitrage. So people see that as their core sort of beta-neutral, diversifying hedge fund position or liquid alts position.

• 35:45Speaker 01

  And then from there, that multi-strategy, while it will have trend following, which has some protective properties, the first question most clients ask, or we ask them to see if they should supplement this multi-strat, is do you want more protective properties? And if the answer is yes, you might add in more trend following.

• 36:07David Weisburd?

  So you might put the levers up and down depending on your risk tolerance.

• 36:11Speaker 01

  Exactly. So your multi-strat will be there. It's something that will diversify your stock and bond risk, public or private. It's something that can do well both in a growth shock or an inflation shock. But if you want more protective property, something that can outperform in a challenging market environment, the only hedge fund sub-strategy that has sort of bona fide evidence for that type of a result is trend following. So those are the two popular project, I would say, product, types of strategies, both within institutional and the sort of high net worth channel.

• 36:44David Weisburd?

  I like to keep track of these mistakes that smart people make, or these beliefs that smart people have that are incorrect. And one of the most common ones, I'd probably define as momentum. You see these tweets about, well, if you had just invested in the mag 7, the last seven months, you would be up 2X. Why even buy the market? And then this year, the magnificent 7 is, is underperforming the index. But it's crazy to me that these very smart investors have these recency buys and oversimplify investing in such a way.

• 37:15Speaker 01

  Your point brings up a broader point, tying it back to diversification. Let's say they're even right, like versus they're just ex-post trying to be a talking head on like what's going on and what they should have done. You shouldn't put all your eggs in one signal or one theme like momentum, right? Even if that's a good theme over the long run. So when we're putting together portfolios, when we're trying to determine whether a security, a stock, or a macro asset is attractive or not, we're using multiple themes, multiple signals, and they're not all going to be flashing green and they're not all going to be flashing red, right? It's the weight of the evidence. And I think a more diversified approach would also protect people from putting too

• 37:58Speaker 01

  much weight in momentum, for example, even if momentum is something that should be in your portfolio.

• 38:03David Weisburd?

  Perhaps you could double-click on trend following. It's a strategy that a lot of smart people believe in. How would you explain it to a lame person?

• 38:10Speaker 01

  Trend following is taking advantage of the fact that market participants tend to underreact to news in the short run. They underreact to news. So that's why when prices went down in the recent past, they went down the right direction, but they underreacted. They should have gone down even more. So if I look at past returns and it's negative, I should short with the assumption that eventually the market will catch up for where it should go, just like if there was good news and the price was up, it didn't go up enough, but it'll eventually get there. That was sort of first-generation trend-following signals where they would look at past prices.

• 38:50Speaker 01

  So that type of strategy has delivered attractive returns over the long run, again, taking advantage of this behavioral bias of underreaction, and you do it across hundreds of macro assets.

• 39:04Speaker 01

  It's delivered a diversifying return, i.e. very low correlation to most people's main portfolio.

• 39:10David Weisburd?

  So like a neutral correlation?

• 39:12Speaker 01

  So like a zero correlation. So something, if you think of the main.

• 39:14David Weisburd?

  Half of the trades go up, half the trades go down.

• 39:17Speaker 01

  It's a core, it's just when, if the main risk in people's portfolios is equities. When I say something has zero correlation with equities, that means, hey, the S&P was up a lot, is that good news for trend? I say it's meaningless and has no information. Okay, oh, S&P is down 15%. Is that good news for trend? Meaningless, because it's got zero correlation. They don't tend to outperform together, they don't tend to underperform, it's random. Okay? And that's what you want, because you don't want all your eggs in one basket. The third property that trend following has, so we said competitive return over the long run. Low correlation, so it's a diversifier to stocks. It also, I mentioned before, has these protective properties. Protective properties are different than diversification.

• 40:01Speaker 01

  Protective properties are, do you tend to have an above-average return during challenging market environments like an '08, a '22, the tech bubble burst, et cetera? And trend following has that. And you could sort of make sense of it because if it's a protracted, challenging market environment, prices are going down, a trend follower is shorting, shorting, shorting, and it's protracted, just like if markets are going up, they're going to be going long those asset classes. So trend following, that's the sort of behavioral basis behind it. And that's why people include it in their portfolio for diversifying competitive return that has those protective properties.

• 40:39David Weisburd?

  Is that a smarter version of looking for something that's negatively correlated to the market because you're actually capturing upside instead of just holding money as a hedge?

• 40:47Speaker 01

  So if it's negatively correlated, so let's take like a put on the S and P 500. Negatively correlated tends to have a negative expected return over the long run. So even though, it's like your home insurance. Like when your house burns down, you make a lot of money, right? Because you paid your $5,000 premium and they gave you, let's say you own a million-dollar house, they gave you a million bucks to rebuild your house. But most people are paying $5,000, $5,000, or $10,000, $10,000. They expect to lose money on their insurance policy, but they do it because it's insurance. So I wouldn't call trend following like a hedge in the same way like a home insurance

• 41:30Speaker 01

  contract or put option, but it does have some hedge-like features, but with some basis risk. It's not automatically, because the other thing is like a COVID crash. COVID crashes are fast. It's not a two-week downturn. Trend following is not really designed to do well in that type of environment. Not that it's going to do poorly. It's not a protracted, challenging market environment. So trend following people have for those protective properties, but it is not a negatively correlated asset like a put option, but put options have negative expected returns. People can't hold on to them because it bleeds and bleeds and bleeds.

• 42:08David Weisburd?

  I know you can't give investment advice, but you're constantly dealing with the smartest investors in the world. And when it comes to their public books, the smart investors are managing their own money. How much typically do they have exposed to the market? How much beta do they have in their portfolio?

• 42:22Speaker 01

  Most portfolios, no matter how many line items they have, explicitly have a ton of equity risk or have investments that are so highly correlated with equities, we can just call it equities. Because like that thought experiment I said before with trend following, S and P's up. If I say the S and P's up a lot, what does that tell me about your private credit? And you tell me, oh, it's up. And I tell you the S and P's down a lot, what's up with your private? Oh, it's down. Credit is sort of like mini equities, right? They don't do well when there's massive recessions and they can do well in an expansionary period, for example.

• 43:02Speaker 01

  So most people's portfolios, 90% of the risk can be explained by some type of inequity factor, no matter how diversified it looks like when you look at all the line items. And so that's usually the first thing I'm trying to address when thinking about how on the margin can I improve someone's portfolio? And that's where we were talking about before, adding in a multi-strategy hedge fund or adding in trend following as a supplement if you want more protective properties. One thing we didn't talk about, since I'm going to tie it back to these portfolios are equity-dominated, sometimes I interact with clients or investors who just love their equities, they're not giving it up.

• 43:44Speaker 01

  And that's where a solution like portable alpha comes in. So portable alpha takes that multi-strategy, which is market neutral, and let's simplify, puts on one additional security in S and P 500 futures contract. So now it's beta one equities plus high-quality, special sauce, active return, long, short from the multi-strat. Now this can be in their equity book. So you always have to be thinking about, of course, I always want to try to give people my opinion, but at the end of the day, if it's your portfolio, you know your risk tolerance, you know the types of risks you like and don't like, and I have to work within those constraints.

• 44:25Speaker 01

  Maybe that's going to be a market neutral, uncorrelated hedge fund, like a multi-strat or trend following. Sometimes I'm going to package those with beta one in order to make it a core equity solution that can meet the needs of someone that has, hey, I have an opening in my bench on my core equity team. Your market neutral stuff doesn't have beta and I need beta. So portable alpha solves.

• 44:49David Weisburd?

  I want to get into portable alpha in a bit, but the sharp investors, are they typically one beta? Are they more levered? What is smart investors doing in terms of their equity exposure?

• 45:01Speaker 01

  If I look at their overall portfolio, smart investors are doing different things. There's sort of a crowd that's doing a lot of privates, right?

• 45:11David Weisburd?

  Endowments.

• 45:12Speaker 01

  They might be doing a lot of private investing, private equity, private credit, private real estate, private infrastructure. But then you have other really smart investors that like have this sort of total portfolio approach mindset that are really trying to get the most bang for the buck and trying to maximize capital efficiency and they're doing overlays internally, effectively doing portable alpha. So I think it just depends on the investor. So yeah, I would say the more sophisticated investors do see the role of a diversifier, even in a market environment where equities are crushing it, where it's easy for people to say, why do I need diversification?

• 45:57Speaker 01

  And then I say, but that's what people were saying before '22 and before '07, right? The whole idea is we don't know when markets are going to tank. You don't know when your house is going to burn down, right? Otherwise, you wouldn't get home insurance until the year of your house.

• 46:13David Weisburd?

  And I would say it's not even noble, it's Bayesian, meaning nobody could definitively know that COVID would spread.

• 46:18Speaker 01

  Exactly. No one, so you're always, good risk management, there's many, like one thing is to have a really good imagination of what could happen, right? You're not saying it's going to happen. You're not saying it's probable. You're just saying it could happen. And then you have to ask yourself, what happens to my portfolio? And when we do asset allocation, we do those types of exercises to give people a sense of how bad it could get and are there ways to make it more resilient?

• 46:46David Weisburd?

  I had the former CEO of a trillion-dollar-plus asset manager, he said that the 60-40, it's, there's a lot of correlation, 2022 is correlated. So you, in some ways, you're almost as correlated as if you were 100 and 0. The correlation was almost one-to-one in some portfolios.

• 47:02Speaker 01

  So this is a great point. Most people before '22 thought central bankers got rid of inflation risk. The only risk out there are recessions. And if there's a recession coming, they'll lower rates because they don't have to worry about inflation and they will get rid of the cold of the economy. Okay? And if it's a growth shock like '08, treasuries are going to do well when stocks go down. So treasuries or core bonds, high-quality bonds are a good diversifier to stocks if it's a growth shock. '22 comes around and people are like, oh, actually, if it's an inflation shock, stocks and bonds both get crushed.

• 47:47Speaker 01

  And that's when people would talk about the stock-bond correlation started to get really high and positive. So when inflation news becomes a dominant force in the macroeconomy, stocks and bonds tend to move together. So one of the reasons why we always tell people to have these like market neutral multi-strats or trend following is while bonds might be a diversifier to stocks, they're only a diversifier to stocks if it's a growth shock. You have to think about inflation shocks too. Multi-strat or trend following can do well in either a growth shock or inflation shock. So if you want someone to sort of understand it, you just say, how will your portfolio do in an inflation shock?

• 48:28Speaker 01

  And when they realize a nominal bond paying fixed coupon, if there's inflation, your real payout is much lower, that's why bonds tank.

• 48:37David Weisburd?

  Do you have any bonds in your portfolios?

• 48:40Speaker 01

  Yeah, we believe in bonds. Bonds in terms of like a core, long-only base, it should have global equities, global, so including emerging markets, get the benefits of diversification. You will have global bonds, right? Get the benefits of diversified bonds do, again, are helpful. They provide a risk-adjusted return that's competitive to stocks, risk-adjusted, not total return. And then an allocation to inflation-sensitive assets like commodities and TIPS. So that would be without going sort of long, short, our sort of ideal portfolio would try to get the most out of all of the sort of asset classes that offer a positive average

• 49:24Speaker 01

  return over the long run. And we would sort of risk balance them and we would be thinking about things like, do I have something that can do well if inflation is higher than expected?

• 49:35David Weisburd?

  So you have stocks, bonds, commodities, and you're long-only. Now let's introduce leverage. What are the principles? How much leverage do you put in?

• 49:43Speaker 01

  For that long-only, it would depend on what is the risk tolerance of the client. So a lot of times people say, well, if 60-40 was acceptable and 60-40 has roughly a 10% volatility, we would use enough leverage to get that portfolio to 10% volatility. And the amount of leverage to get there will vary over time depending on how volatile markets are. So that would be, so it's always driven by.

• 50:12David Weisburd?

  Presumably the expected return is higher, but the volatility would be.

• 50:15Speaker 01

  So think of it as we have these global equities, global bonds, and we have this global inflation-sensitive commodities. Unlevered.

• 50:25Speaker 01

  Let's say it has a good risk adjusted return. It's got a better risk adjusted return than 6040. But unlevered, it's got such low vol. Its total return is low, even though it's got a great risk. So we need to boost up the vol. We do that through leverage. So when we use that leverage to get it to 10 vol, it's now 10 vol, just like 6040, but it will have a higher total return base case than 6040 because my portfolio is more diversified than just holding stocks and bonds.

• 50:55David Weisburd?

  It's interesting that you guys use volatility because you could also define risk

• 50:58Speaker 01

  We do other stuff, yeah.

• 50:59David Weisburd?

  as the risk of losing money. So if your expected return is higher, the volatility could be higher if your metric is, can I lose money?

• 51:08Speaker 01

  So I actually wrote a paper about this, about this whole notion of like, is volatility a good measure of risk for people who care about like permanent loss of capital? And I think that gets to what horizon are you measuring volatility? Are you measuring one day vol? Are you measuring one month volatility? Are you measuring one year volatility? If you're a long horizon investor and your horizon's 10 year, you should measure 10 year volatility. And there are ways of doing that. So I do think

• 51:34David Weisburd?

  If you could hold.

• 51:35Speaker 01

  Right. But I'm just saying in terms of like the framework you would use, because one day volatility annualized is not the same as 10 year volatility annualized. Most people are using higher frequency, daily or monthly data and annualizing it. And then people like Howard Marks will come in and criticize it and say, well, that's not a good measure of permanent loss of capital. And he's partly right, but like, that's because people are misusing, they're not measuring the right volatility.

• 52:04David Weisburd?

  There's almost two different use cases. One is if you're cryogenically frozen for 10 years, what would your portfolio be? And two is if you were not cryogenically frozen for 10 years, what would be your ideal? Cause there's a behavioral aspect to it.

• 52:17Speaker 01

  Yes, yes, yes. And again, that, so you need to be mindful of the short run volatility, short run risk levels, because you aren't frozen. Let's say you could put it under your mattress and go to sleep for 10 years. Then 10 year volatility will be a good measure of permanent loss of capital. It won't be perfect, but it'll be a good measure. And some of the criticisms of volatility are really about using the wrong horizon.

• 52:43David Weisburd?

  An investor at Mark Andreessen's family office told me something fascinating, which is, if you have a high expected return over time, even if you have a relatively high volatility, you're going to have a high expected return. In other words, if you have a coin, the best way that I found to explain this is if you have a coin with three sides and two out of every three sides is a positive outcome and only one is a negative, if you flip it enough time, you're going to be doing pretty well.

• 53:12Speaker 01

  Normally, when someone thinks of like a long horizon return. Okay. So let's say I care about my 10 year return. They're not thinking of a 10 year expected return. They're thinking of a 10 year 50th percentile return, the median. What's the most likely? And you might be like, well, isn't the expected return, the 50th percentile, the middle of the distribution? No, because when you have compounding, your distribution gets highly skewed. Okay. So most people care about the 50th percentile. The 50th percentile will be equal to the expected return. And I don't know if you've heard of this concept called volatility drag, some people call it.

• 53:53Speaker 01

  The 10 year base case 50th percentile return will be that expected return that you talked about, minus one half volatility squared. Okay. So that volatility of that asset actually lowers the actual base case 50th percentile return.

• 54:15David Weisburd?

  And what's that equation for?

• 54:16Speaker 01

  Some people, like depending on who you're talking to, again, this is getting a little geeky. It's a difference between arithmetic mean and a geometric mean.

• 54:23David Weisburd?

  And that's essentially if you have a, you own a stock at $10, it goes down 20%, then it goes up 20%, you won't be at $10.

• 54:31Speaker 01

  Exactly. There's that asymmetry.

• 54:32David Weisburd?

  And that's always to the downside. That hurts you.

• 54:34Speaker 01

  If you're interested in the 50th percentile outcome. So I think some of these examples are, they are more difficult, but I would always come back and say, be diversified. Even if you think you got this great asset, I would never invest in that one good trade, thinking that over the long run, I'm automatically going to win. In the same way, people think of like, well, stocks are only risky if you have a short horizon. They have a higher expected return than bonds. Of course, they're going to always outperform bonds over a 30 year period or 50 year period. And the answer is no, they're not. They might be expected to outperform, but I guarantee you there are scenarios where they underperform. And then like, I'll bring up Japan. No one ever thought like the Japan equities would be in this malaise for so long.

• 55:19Speaker 01

  So just because something has a higher expected return with higher volatility, doesn't mean it will eventually outperform over the long run. There will be parts of sort of outcomes that are unfavorable.

• 55:31David Weisburd?

  So is there another aspect to that? You said that it'll be slightly below the 50th percentile. But is the expected return actually higher?

• 55:41Speaker 01

  Yeah, the expected return is higher. Yep. Because of compounding effects.

• 55:46David Weisburd?

  What kind of questions are you asking yourself these days?

• 55:49Speaker 01

  One is, which asset classes should I have if I'm really scared of inflation taking off because of what's going on in the Middle East or what's going on in Ukraine or what's going on with tariff policy? That just reminds me that most people's portfolios are very pro-growth. They want growth to happen because they are equity dominated and they want disinflation, not in inflation. The way really to sort of start making progress on balancing out those macroeconomic exposures is to bring in things like commodities, to bring in things like TIPS, if you're thinking of long only. And like we talked about earlier, some of those long, short strategies. It's not magic.

• 56:33Speaker 01

  It's like, it's because they don't have beta, right? If something is market neutral, either short run and long run or over the long run, it doesn't have the stock and bond beta that's giving those asset classes the macroeconomic exposures. Right? So bringing in those multi-strategy hedge funds and bringing in trend following are ways that I continue to preach can help out if you're worried about inflation or you're worried about tail risk. And then to the other point where we were talking, I brought up portable alpha. A lot of times, people will come to me and say, you improved my risk adjusted return, but you didn't improve my total return. I sort of went into these long, short hedge funds and I pay bills with total returns.

• 57:18Speaker 01

  Like do something for me. And so we've really had to rethink like, that's a capital inefficiency problem. It's not a problem with the hedge funds per se. It's how can I package them to be more capital efficient? So they get more bang for the buck. So I can improve their risk adjusted return and I can improve their total return. And the easy way of doing that is through design of the strategy. And that's taking those strategies and adding in that one additional security. Let's say an S and P 500 futures contract that gives full beta exposure. So people care about inflation, they care about capital efficiency because they know they can't just rely on passive equities because that evaluations are stretched.

• 58:01Speaker 01

  They need active management, but long only active management's been really disappointing. And so we're trying to think through, well, let's take the shackles off. Let's not have it be long only active management. Let's have it be long, short, and let's package it and construct it, construct it properly to solve these foundational problems.

• 58:21David Weisburd?

  How would you explain portable alpha to a person?

• 58:24Speaker 01

  So portable alpha. Normally, when someone wants to go active in an asset class like equities or fixed income, they actually, if that's the beta, that's the benchmark. They go find, let's say for equities, they go find if it's US large cap, I gotta go find a US large cap active manager. So the US large cap active manager gives them the beta plus the alpha. Okay. And they're doing it long only. Portable alpha, the original insight 20 years ago was, why should you, given that alpha is so hard to harvest? Why would you constrain yourself to looking for alpha only in US large cap? Right?

• 59:06Speaker 01

  You need US large cap beta, but why should the alpha have to come from there? You can get the alpha from anywhere where you think there's high quality alpha, then have that manager put on an S and P 500 futures contract. So you're porting, you're making the alpha portable so that you can take the alpha from another market, another strategy, and bring it back and have it sit within your S and P 500 sleeve. And that's where the name portable alpha comes from.

• 59:36David Weisburd?

  And the S and P 500 futures is just giving you the net exposure. So if it's up five, it's up five, if it's down five, it's down five, but you're not taking the 100% of exposure there.

• 59:48Speaker 01

  You would earn the return on the S and P 500 minus the implied financing cost. Right? Cause it's unfunded. So think of it as like T bills plus some financing spread. Okay. So for portable alpha, if you sort of did all the math, you would get the total return of the S and P 500 plus the excess of cash return of your hedge fund alpha strategy minus any frictions.

• 1:00:19David Weisburd?

  So let's put it in dollars and cents. You put in a million dollars into a portable alpha strategy.

• 1:00:24Speaker 01

  Yeah.

• 1:00:25David Weisburd?

  Where does that money go?

• 1:00:27Speaker 01

  So depending on the implementation, right? It could be, let's talk about an integrated solution. So there's a single fund. Let's say you want 7% volatility to trend following as your alpha source. Okay. So you give me a million dollars. I put this million dollars in this fund. It will give you a million dollars worth of S and P 500 exposure and it will give you a million dollars of managed futures trend following exposure at 7% volatility. Importantly, you don't get the total return of both the S and P.

• 1:01:09Speaker 01

  And the managed futures, you get the total return of the S and P 500 plus the excess of cash total return, right? Cause it's when you borrow something, you have to pay a financing rate, right? You can't, you don't get to double down and get, so for your million dollars, you are getting a million dollars of S and P exposure plus a million dollars of managed futures trend following exposure at seven vault.

• 1:01:33David Weisburd?

  It's the cost of treasury plus trend following return plus S and P 500 roughly equals your return.

• 1:01:40Speaker 01

  Yeah, the cost of treasuries plus a little financing spread because people need to make money who are in these markets. Yeah. So that would be part of the frictions. Yes.

• 1:01:49David Weisburd?

  And you mentioned it yourself, trend following has been around for a while. A lot of people blew up in the previous version. I believe it was around 08. Why won't that happen again?

• 1:02:00Speaker 01

  Well, in 08, it actually did well. So that's actually why everyone got in after 08. And so it did really well. And then in the 2010s, it was, the industry was sort of mediocre. And we actually wrote some papers on this. That was because there was actually low macro volatility into 2010s. It was really calm. So if trend following is based on underreaction to news, if there isn't much news, there is very little to underreact to. So after 08, where it showed its protected properties, it did awesome. A lot of people got out of trend following after holding it for 10 years and it was sort of mediocre and they got out in 2021. And in 2022, the industry was up, let's call it 30% or 40%.

• 1:02:46Speaker 01

  So managed futures trend following for people who don't have the patience, right? Cause we don't know when the next crisis is going to come, right? Sometimes holding it with equity beta is a way to force discipline because if managed futures is just having mediocre returns and you have it with S and P 500, mediocre returns plus S and P, you're top decile as a active S and P manager. If you're just holding managed futures standalone and it's just having a two, three percent returns, you're sort of like, ah, is that a good use of my capital? I'm getting these tough questions from my CIO, getting tough questions from my investors, right? So that's one thing, one advantage of something like

• 1:03:31Speaker 01

  portable alpha, it gives the staying power to stick with these diversifiers. And it's sort of funny, these diversifiers, it's a feature, not a bug that they don't track the S and P 500, right? But when the S and P is doing well and they're not tracking it, people lose patience. Cause they forget the fact that they have this in the portfolio because they want it to be different. But they only want it to be different when the S and P is down.

• 1:03:54David Weisburd?

  And the portable alpha helps adjust for those behavioral mistakes.

• 1:03:59Speaker 01

  That's one reason, right? Like portable alpha, if someone came to me and said, so what problems does it solve? One, long only active management is inconsistent because of the long only constraint. It's like being a world-class sprinter and you have cinder blocks in the 100 meter dash, taking, doing portable alpha, using a long short source that's as your alpha source unconstrained, high quality alpha, pair that with beta one, now all of a sudden you can do active management much better in your beta one equity sleeve. So that's one reason. The second reason people love portable alpha is a decade ago, the people who went into multi-strat hedge funds or any hedge fund or liquid alt, they had to sell down stocks and bonds to fund it and stocks and bonds crushed it, right? Stocks

• 1:04:43Speaker 01

  crushed it. So they started to feel like they have egg on their face and they're a little bit worried, like even though equity valuations are stretched, maybe I have to be concerned, what if equities just keep going up? I don't want this funding problem of selling stocks, going into something that maybe hits its base case return, but stocks beat it. So it solves the funding problem because you replace the equity beta one for one. And then the third reason, which is what we talked about, people complaining that sometimes these diversifiers improve risk adjusted returns, but not total returns. Portable alpha solves that capital inefficiency problem.

• 1:05:16David Weisburd?

  And portable alpha in its previous generation did not blow up, it just didn't perform well?

• 1:05:20Speaker 01

  It depends on implementation. So implementation has improved a lot. Some people were doing very risky implementations prior to the global financial crisis and that reared its ugly head. We are big believers in having a single manager who manages the alpha strategy also put on the beta overlay because they then can manage the cash for the derivatives safely. They can make sure your beta one. Sometimes people separate the two functions. They invest in an alpha manager. They either get derivative capabilities in-house or they hire an overlay manager and that works 98% of the time. But there's cash management operational risk.

• 1:06:02Speaker 01

  So there are many turn, what I call turnkey solutions, integrated solutions, single manager solutions that pretty much take implementation risk off the table. And the main risk you face with portable alpha is the risk of active management, right? Which is the risk you signed up for.

• 1:06:19David Weisburd?

  Pete, if you could go back to, you had just left Harvard after doing your PhD at University of Chicago, you could give yourself one timeless piece of advice as you entered the investment world. What would that be?

• 1:06:31Speaker 01

  I was unwilling to share my credentials with other investors and colleagues. And I think that actually hurt my career. So I remember there was a story when I was an allocator and even when we used to have business cards, I don't have business cards anymore. I wouldn't even put PhD at the end of my name because I thought it was sort of like bragging. I didn't want to be a show off. I wanted to be the common person. I don't even remember in high school. I didn't want to talk about I was in honors classes. I was a normal kid. And one of my colleagues, when I was an allocator sort of took me aside. It's like, Pete, what are you doing? Like this gives you credibility. We're in a situation

• 1:07:12Speaker 01

  where people don't know you. You need to signal to them that you actually have an engine because there's a bunch of frauds out there or there's a bunch of people who are willing to oversell their skillset. And the fact that like you were a Chicago finance PhD, you were one of Gene Fama's best students that year, which is why you were his TA. You were a Harvard Business School tenure track professor, taught in the MBA PhD program, and you were actually an allocator managing multi-billion dollar portfolios. That gives you credibility when you're sitting across the table with someone and they're thinking, is this guy the real deal? Is he chat GPT? Is he Claude? I didn't do that. I didn't leverage that enough. And while I still am somewhat humbled, my wife always tells a

• 1:07:56Speaker 01

  story when someone I was at Harvard, someone's like, so what do you do for your profession? And I go, I'm a teacher, which was technically true, right? But my wife's like, what are you doing? Like, what's the big deal? What are you ashamed of? And so I would tell people, if you really have bona fide credentials that signal real talent and you know you're competing against people who have resumes that are inflated, that are sitting in meetings claiming to be knowledgeable about stuff that they're not that knowledgeable about, use these hard credentials, concrete credentials that are bona fide verifiable to signal that you're the real deal. And I try to do that a little bit more today. And I think that

• 1:08:40Speaker 01

  would have helped my career if I would have done it earlier.

• 1:08:43David Weisburd?

  I've struggled with that as well. I understand where you're coming from.

• 1:08:48David Weisburd?

  Well, Pete, this has been an absolute masterclass. Thanks so much for jumping on.

• 1:08:51Speaker 01

  Well, thanks for having me. We really appreciate it.