The MOST Important Thing

You DON’T need SNOW BOOTS in July – A GLOBAL Quant Expert

• Ivan Yates & Dr Alan O'Sullivan

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The Future of Quant Investing: Strategies, Factors, and Portfolio Insights with Pim Van Vliet. 

Explore the intricacies of factor investing, risk management, and portfolio construction through insights from Pim Van Vliet, a leading quant expert from Robeco. This episode demystifies how quantitative strategies adapt in evolving markets, emphasizing low volatility and multi-factor approaches to optimize returns and control risks.

Main topics covered:

  • The role of low volatility strategies in turbulent markets
  • Combining multiple factors for stable and outperformance goals
  • The relationship between low volatility and other factors like quality, momentum, and size
  • The importance of simplicity, including Oxum’s Razor, in factor models
  • Risks and realities of long-short versus long-only approaches
  • Portfolio diversification through multi-factor blending
  • Use of forward-looking metrics and machine learning for stock screening
  • Insights into asset classes beyond equities, including bonds and crypto
  • How factors like low volatility perform across various markets
  • Practical advice for young investors and emerging professionals

Timestamps:

00:00 - Navigating a new market regime with low volatility strategies
00:29 - Why blending multiple factors improves stability and returns
01:01 - The impact of low volatility on other factor exposures
01:31 - Emotional factors like FOMO, envy, and the role of Lovel in investment decisions
02:51 - Does low vol leverage benefits from other factors?
03:07 - The debate on whether low volatility "steals" from quality and momentum
03:55 - Explaining correlations between low volatility and other factors
04:24 - Are low-vol stocks inherently cheap and quality-driven?
04:53 - The principle of Oxum’s Razor: simplicity in factor models
05:22 - Differences in academic versus practitioner approaches to sector constraints and long-short strategies
06:18 - The significance of long-only vs long-short in academic research
07:10 - Portfolio construction insights: blending factors for diversification
07:32 - The role of uncorrelated factors like momentum with low vol
09:03 - Stock screening techniques using machine learning and forward-looking indicators
09:50 - Incorporating market information to adapt to changing risk environments
11:16 - The importance of balancing forward-looking measures vs bias in estimates
13:05 - Concepts of conditional vs unconditional expectation in investing
14:01 - The impact of historical data and the importance of expected future returns
15:32 - Bayesian approaches: updating views with new information
16:02 - Market insights from Robeco: funds, strategies, and their performance
17:16 - The thematic focus on conservative low volatility funds and their risk-adjusted returns
19:27 - Evidence of factor premiums across asset classes, including bonds and crypto
22:28 - Strategies in a stagflation environment and the long-term value of equities and stocks
23:41 - How valuation levels influence investment decisions in different regimes
26:41 - The importance of experience, learning, and adapting in investment careers
30:44 - Pim Van Vliet’s key investment principles: don’t lose money, focus, and avoid benchmarking distractions
31:31 - Recommended books: Erik Falkenstein’s Finding Alpha, Jack Bogle’s The Little Book of Common Sense Investing
32:14 - How to follow Pim Van Vliet’s work and learn more about Robeco’s strategies

Resources & Links:

Connect with Pim Van Vliet:

Note:

This conversation provides a comprehensive overview of quantitative investment strategies, emphasizing practical insights and academic debates, suitable for both practitioners and students in finance and investing.

Book a Meeting with Dr Alan O'Sullivan

For individuals, families, and business owners seeking professional wealth management, estate planning, and long-term financial stewardship, please contact Muriel at muriel@priyawm.ie to arrange a private consultation.

 

SPEAKER_03

That's a fundamental point. People if people talk about the equity premium, they look at the past ten years and they see ten percent. Let's say the equity premium is ten, and then we say now the realized return was ten percent. Professor Who explained me very simply, said, you know, unconditional information is suppose you go out and you wanna uh the weather. And so what do what what do you take? And he said if you're an unconditional, you take your umbrella, you take your sunglasses, you take your long shorts, your short shorts. Because snow boots, you don't know what's gonna happen, whether it's gonna snow or rain or if you're a conditional, so you look outside, you know it's uh summertime, then you don't take your snow boots because it's too light.

SPEAKER_01

We're looking out to the next uh 20-30 years where we're in a new regime, and if you're trying to dampen the fear that's going to be there, more or less fear, I would say, it seems to me that a low volatility uh approach would be the way to go. But what would you combine on a multi-factor approach? What would you combine with low vol? I know there's multiple strategies, Pim, but just to my question about if there's lots of fear, what generally might work well there?

SPEAKER_03

Um so yeah, we I I don't believe in single factor investing, so I always believe you should blend uh multiple signals, multiple factors. That is by far better. Yeah, it depends on the objective. If you want to have a stable performance, so benchmark unaware, then you can add uh more defensive value, uh defensive quality. You add momentum. Uh if you combine that, you get the best total return per unit of drawdown, basically. Um in a paper just came out two weeks ago. I uh do some exercise with that, do some optimizations, and that's where this is basically uh simulated and optimized, this outcome. So mostly uh defensive low vol and then blend in return factors as mentioned. If your perform if your objective is to say, hey, I want a consistent outperformance, then basically you should get rid of low volatility uh almost entirely. So you should drop it. And this is really fascinating because if you can you said dampen your emotions, I like that. That's that's what quant factors do, and then the emotion of uh FOMO or comparing, envy, jealousy, you have all those words for it, that's basically the low vol dampener. If you can take that out, so the most important thing is don't compare. My mother says don't compare too much, makes you unhappy. It's true. Uh and low vol is fully tied to that emotion. If you can get rid of it, you can profit from it. But if you say no, uh I need to stay up, keep up with the Jones, I need to uh uh stay close to the market, then uh this one, this factor uh doesn't work. So that's why it's such a special factor, unlike all others. What all others, I think you've got value uh proponents in your in your podcast, maybe you've got quality fans. Yeah, Lowell is a special animal, it it really needs uh a special allocation, and you need to get rid of uh this emotion of comparing all the time with benchmarks, and that's very difficult because Lowville cannot take that away from you. It's it's it has to be your own choice. Um, and then yeah, once you get in, you're in. Then uh don't compare too much.

SPEAKER_01

Does low vol kind of take the best bits of other factors? I mean I think in low vol you're pulling from profitability, you're pulling from quality. You're also pulling from small because if you're low volatility, you're probably not moving around as much, maybe, maybe, maybe less so, as I'm as I'm t thinking. But does it kind of the reason it's it's very interesting to me, and I know I'd be looking at a lot of your funds now uh as a consequence of this conversation, and listeners and viewers should as well. But uh does it does it does it kind of steal from those other factors, take the best bits? Would that be fair?

SPEAKER_03

Yeah, you could say so. Um there's and and then it becomes interesting, and uh you can uh make make this uh soap show because the question is what explains what? Um there is a paper out uh claiming that quality uh explains low volatility. Um and you can also say the other way around. You can also say, hey, but if quality explains low volatility, maybe low volatility explains quality. Now there's fierce debates on that, and that's uh where you can take your popcorn and uh and take a look, but you have to read through the lines because academic fights you don't see it uh popping up from your screen, but it can be uh serious. So is it st is low vol stealing from other factors? Uh yes. Um for example, uh low vol stocks tend to be better on momentum, and high full stocks tend to be really bad on momentum, so they tend to be more loser stocks. Low volatility stocks tend to be a bit more cheaper, two-thirds of the time, and low full stocks tend to be more quality. Now then there are two ways of looking at this. One you uh could say, hey, I can explain low full with these common factors. You need four, four, five, six factors to explain lowful, or you say, Okay, I can explain it, but why don't I just take low vol and then I have them? So it's a matter of perspective that is it good or bad. Uh and that's really fun. So I wrote a CFA blog on this, it's called Oxum's Razor. Oxum was a famous, I think, Irish monarch monk or a British monk, I'm not sure, but uh from the islands, and he said if you can do something simple, it's probably the best solution. So simplicity over complexity as a rule, it's a philosophical rule. And you can do the same with Low Vol, because you mentioned quality, for example. With Lowell, you only need return data. You can go back hundreds of years because you only need returns. Quality is a bit more complex and ambiguous. How do you define it? You need uh uh company profit statements. Um, so there you can say, hey, let's let's go for simple. If it's the same, then uh let's do it. Um then there's another thing is in the academic literature. I mentioned academics don't use sector constraints, where practice practitioners do. Uh another thing academics tend to do is to do long short. They do L factor literature long short, whereas practitioners uh yeah, more than 95% is long only. Also, the fence you've been looking at, these are long only. You can come to different conclusions whether you do long short or long only. And that's also pretty fun. That some of the uh anomalies are only there in the short lag. So they look great. So for example, momentum is uh is great in the shorts. So the the loser stocks are the ones who have a really big negative alpha, but to profit from it, you need to sell it, you need to short sell. And I can tell you that's pretty risky to short sell uh stocks which went down. So uh many of the academic results uh should be looked through that lens. Like, hey, this is as you said, be skeptic, skeptical. Uh wait a minute, if if momentum explains low vol, is it coming from the shorts or not? Because it's from coming from the shorts, it's not a real explanation, because this is just a theoretical exercise. So we also wrote that down uh called uh when factors lose their shorts. What do you see then? Uh you get a different story, you get a different picture, and also low vol looks much better long only than it looks long short.

SPEAKER_01

In terms of portfolio construction, Pim, um have have you seen in your research uh evidence that certain factors do well with other assets? I mean, if we're going to broaden this out to a portfolio construction perspective. Any views on that if if we talk specifically about low low low val?

SPEAKER_03

Yeah. Yeah, so with low vol, uh as we said, uh it steals from other factors, but it also needs other factors. Uh so that's why uh we always do everything multi-factor. So uh having other factors in is really great for diversification. Uh, momentum, uh as mentioned, really helps to improve your up capture, and so uh markets can be trending for a couple of years, and then momentum is great of uh buying into uh those trends while still having a low vol profile. Uh so blending in factors uh is great. Um and combined with sector concentration limits, you can basically keep your high return or your high risk-adjusted return, but you can also then lower your uh relative uh performance risk, your active risk, you can limit that. And uh especially uncorrelated factors are the best. So momentum is pretty uncorrelated with low-value. It's a bit positive over the long run, but in the short term it's uh up and positive and negative. So nowadays momentum is negatively correlated with low-val, and that's great for diversification if you have negative correlation. Uh so that's why it's good to do low-value uh we say, but it's better to do multi-factor defensive, uh, exactly for this reason. Uh to not only steal from artifacts but also integrate them and uh build something better.

SPEAKER_01

So in terms of the screening of of um stocks then so the process, what's feeding you know, in terms of the inputs? An institution research firm that I won't name, but I mean they have a stock screening model, right? And I had a discussion with them recently, and it was okay, we're gonna screen for quality, we screen for size, we screen for profitability, but they have this, you can probably guess who it is, they have this 30-factor model, okay? So then you're thinking, well, okay, this a lot of this is based on historical data, right? Is there any leading indicators within your your your modeling as opposed to just basically looking at historical data?

SPEAKER_03

So also we use multiple, multiple factors. So if you we have huge databases containing uh yeah many, many signals on all those stocks which are screened. Um one technique we use is uh machine learning, uh where you can uh uh integrate those uh signals in an efficient way and also uh use interaction effects to better predict. So that's really pushing the frontier away from simple linear combinations of well-known factors. But the what's what's you you what you mentioned is also to include forward-looking information, and that's where market information can be useful. So uh I mentioned when we measure risk, we look at past volatility, that's looking backwards. We can look at past correlations, past betas, that's also looking bad. And if today uh a stock issues lots of debt, then we know it's it's riskier from today. And that is information you're missing with with a historical risk measure. So, for example, uh distance to default is then a metric, which is more adaptive. One step further is to take uh market information, so credit spreads, where the market basically uh looks forward and says uh says uh yeah, this is this is a risky stock. And then the optimal balance is blending forward-looking uh metrics, and they these are also not the holy grail, but they do contain information on the risk side, on the return sides, you've got the analyst revisions, for example, you've got um that's also uh indicative uh signal um where you can also look more forward-looking uh metrics. There's one cavity with forward-looking measures like forward eat uh price to earnings, that you can then again introduce a bias. So uh analysts can be structurally optimistic, and that's where the the it's a big debate among value investors. Do you look uh earnings to price, past earnings or forward earnings? Then people can say, yeah, it looks expensive on uh past uh PE ratio, but it's cheap on uh on uh expected, and also there the truth is a bit more in the middle. So if you only rely on forward looking metrics, you uh tend also to incorporate the bias, the optimism bias, which tends to be more among certain groups of stocks where there's some sort of uh overestimation. So, yes, good points. You should also in a good multi-factor model, you should also have your um forward-looking data uh points uh information in. And like I said, also with machine learning uh techniques, you can then also find optimal balances between those two. So that's what we're all doing in our strategies we run in our funds, so that's of course also proprietary. The things you read from me are of course far more simple, and uh so that's also do-it-yourself investors can some sort of get the get the main idea of how you could do it, but of course, it's not the full recipe for uh how we actually do it in uh in practice.

SPEAKER_01

I interviewed Professor uh Campbell Harvey and we spoke about conditional and and unconditional expectation. Now, for the ginking that's a bit geeky, right? But it's not really the unconditional expectation is basically the past, the average, the historical data, whereas the conditional expectation is the your expectation of the future based on information today. You know, not tomorrow, because we don't know what tomorrow is, but today. And that feeds into what you said about Antie Ilman as well, because I actually read his book um Investing in Lower Lowern Times, and uh he looks back over hundreds hundred years, but what he found was that you need to be very skeptical of these annualized returns because much of the return is heavily weighted towards the last 20-30 years, and you know, so we just have to be very, very careful uh when we see figures like as you know, annualized and average and and this type of thing. And most investors aren't aware of that, Pim, as you know.

SPEAKER_03

Yeah, yeah, that's a fundamental point. People, if people talk about the equity premium, uh they look at the past 10 years and they see 10%, they say the equity premium is 10%, and then we say now the realized return was 10%. The equity pre conditional equity premium, based on the information we have now, is is much lower. So instead of equating them, you could even say they're negatively related, and that's for many investors very difficult to grasp. About the conditional, uh the professor who explained me very simply, he said, you know, unconditional information is suppose you go out and you want an uh the weather, and so what do you what what do you take? And he said if you're unconditional, you take your umbrella, you take your sunglasses, you take your long shorts, your short shorts, because snow boots, you don't know what's gonna happen, whether it's gonna snow or rain or if you're a conditional guy, so you look outside, you know it's uh summertime, then you don't take your snow boots because it's July. That's in a nutshell uh what is conditional investing is and unconditional. Unconditional would be yeah, putting everything on. It's it's you look stupid, literally. And that's when you only look at past returns and you don't condition, um yeah, then you then you might might be uh the this feeds into this code kind of Bayesian approach then, doesn't it?

SPEAKER_01

I mean in terms of yes, we look at historical data, but we take our views as well, and we combine our views with our with the historical performance to get a more accurate prediction of what's what's likely to happen. I I'd like to talk about um Rabico's um funds as well, uh Pim, in terms of what your offerings are. Um you know, maybe for people that aren't aware of what you do, um I know you're a huge shop, I mean, or nearly 200 billion, uh something like that, and I know you you personally look after close to 80 billion. So maybe give a bit of information on that, please.

SPEAKER_03

Yeah, that's good. So um Rubico offers uh f funds and segregated accounts. So uh funds are available to any investors, so the these are uh domiciled in Ireland or Luxembourg, so usage compliant. Uh let me focus on the equity funds. We do quant equity funds and we do quant fixed income funds. Um, and with quant I mean systematic rules-based as discussed uh today. So these uh equity funds basically uh are groups around two themes: either beating uh market, so market plus. Uh we call that enhanced indexing uh and uh also active quant. We offer that in uh mutual funds, but we also launched uh some uh ETFs, active ETFs. If you uh look at names, it's Rubico Quant Equity, and then uh we also offer regional strategies like emerging markets, Europe, US, global. Uh so also on Rubico.com slash quant. You you there's the information on all the the funds we offer. Then we also offer um uh more the defensive low volatility funds, we call them Rubico conservative funds. So that means we don't only do low vol, but we do it multi-factor, and that's uh strategies have a beta of 0.7, they have proven to be more stable, so they reduce downside risk by around 30%. Uh beta is around 30% lower while still offering equity plus returns, but then uh relative it's not every year outperforming like the other strategies. So we offer both strategies. Um one is an alternative to passive, so suppose you have a passive tracker, you can say, Hey, I want I want some factor tills in it, uh blended in uh very consistently, uh big team 50 quant working on that daily, using machine learning, next-gen signals, all the secret sources, enhanced definitions. Yeah, and that has been very successful. Uh some of our strategies have delivered 1% uh return with 1% active risk. That translates into an information ratio of one. Uh if you do that for 20 years, you've got a T stat, so uh a T value of uh more than uh four, and which is very significant. And the conservative strategies also uh uh added about one percent, uh but then uh by smoothening the cycle. So we outperformed hugely uh during the tariff terminal, for example, we outperformed in uh financial crisis, but then we lag a bit more in uh up markets, so there the root the the right is more smooth with conservative and with enhanced indexing, that's where the access return is more smooth. Well, you just you get beta plus uh very stable alpha, and also that we offer on uh emerging markets, global markets, and also with high sustainability or standard sustainability.

SPEAKER_01

I've heard some of this not just for funds, but some of this uh described as crisis alpha. Maybe you know that uh in uh an environment of mass panic, mass fear that you you cap the downside, and and that's very, very important, obviously. In terms of uh other assets, now I know you mentioned fixed income uh quant strategies, that low-val premium factor that that is consistent through other assets as well.

SPEAKER_03

Yeah, so uh academics uh have been debating factor premiums. Do they really exist? Are they consistent? And one way of finding consistency is looking at other asset classes. Um yes, factors also work in corporate bonds, they work in government bonds, and uh that can be value, momentum, and low risk. Even crypto, we don't offer crypto funds, but uh I'm involved with the research going on, um, and it's not published yet. But there we also look by the factors working in crypto. There's also some literature on that, so we will contribute to that. Cannot uh say about the results yet, but um it looks good. The funds we offer on fixed income is uh also on government bonds and uh high yield. We also have uh ETFs there, uh and we do have funds. So you see that the evidence in favor of factor investing is very solid uh across markets, uh and that basically builds evidence. So every year we add, uh we see more evidence coming up, uh, and also the historical evidence, as I mentioned. You uh we also did some studies, um, not only we, but I've also seen like Belgium corporate bonds in the early part of the 20th century. That was one of the biggest credit markets in the world. The researchers tested factors there, and also there they found factors to offer higher returns. So the evidence is there. And yeah, it really adds to the biggest factors people investors know. That's the equity premium, that's number one factor. We've got the bond premium, that's another factor. And yeah, these other factors, which are less well known to most investors, are really helpful to uh increase your return. Why? Because as we said about conditional information, investing in the world of low returns, if you don't make much on your equity market as a whole, then the alpha or the crisis alpha is really needed for your long-term uh meeting your long-term objective. Especially since your asset is is nowhere safe. If there's financial repression, but even the risk of it means that if you put your money on the bank account, then you c will also lose your money. So that's where uh factors and quant investing offers a way out, that you can uh play it uh more safe, you can reduce your risk without giving up return.

SPEAKER_01

So uh as we draw to uh a close in terms of you know if we if we go into this deglationary environment, as you said, there's very little that works there. Maybe gold in an environment of heightened geopolitical risk and you know uh all that all that brings, and we've seen gold uh astronomical performance in recent years. But couldn't we see a scenario where yes bonds don't work anymore and the word is out on bonds um that equities do work, but the value, the price you pay, is so important because you know you you if you if you look back at a uh a previous regime was post-World War II perhaps, where you had really high government sovereign debt levels and financial repression was used then and uh equities equities that were well uh that were undervalued did really well. But now we're in an environment where equities are extremely valued, overvalued. So again, low low volatility to me, um, that seems to be the way to go. If you have to own equities, which we do, we have to own equities.

SPEAKER_03

And a good point. So if you look at our emerging funds, I mentioned uh different funds, it has a price earnings ratio of 12 uh dividends of uh sure uh of uh five percent per year. Yeah, if you compare this with uh with everything else, uh it it it can be uh really uh an attractive alternative to your saving account, to loans, to regular equities. Um what could happen, what what's happening with gold now is that it's both a FOMO trade and a uh fear of losing money at the same time. So it's a bet against uh uh central banks, uh fiat money being printed, but it's also uh FOMO, like hey, it's going up, so why it's everything's coming together. Uh it the same could happen with some stocks uh which are not exp which are stable, especially if there's an earnings recession coming up. So if because the economic is a cycle, we don't have permanent GDP growth, so suppose we get into a recession somewhere, then uh more the cyclical stocks, uh high beta stocks will suffer most. Uh there are multiples contracts, then people start dumping those stocks. Uh but it could be that they think, yeah, I dump my stock, but what do I buy? Gold is extremely expensive, bonds is financial repression. Oh, let's do rotation and let's buy those emerging stocks, which are you know, telecom company from Malaysia, you know, doing 10 times earnings, not being affected by a US recession or and then those assets could become really scarce, and such a scenario could happen also for defensive stocks where it's both a FOMO trade and uh fear of uh losing money trade. Uh and if that happens, yeah, then uh you can have extreme multiple uh expansion. But yeah, if you start from a level of uh twelve, even if you double, uh you're still at twenty-four, which is not expensive, uh especially in it uh once you also recognize that stocks are more uh providing in the long term at least uh protection against inflation. If inflation stays like at three, four, five percent for the next decade. Stocks uh tend to, not on the short term, there's lots of studies on that, but in the long term, yeah, stocks are sort of incentive to that. Uh whether you trade in bananas, bitcoins, uh, or pounds, British pounds, uh a stock has a profit in the economy, no matter what the currency is, whether it's gold or or euro. And that's that's could happen where uh this combination of financial repression, as you mentioned, maybe an earnings recession, that then uh certain parts of the stock market become really hot. Yeah, and then you get the self-fulfilling prophecy that if stocks go up, people buy them because they go up. Man, that's that's that's also what we've if we if you long in the industry, you know that.

SPEAKER_01

There's gonna be some you know, young graduates, young career professionals starting out, you have got so much experience as a practitioner and as a contributor to you know high-quality academic journals. What kind of advice would you give? You mentioned machine learning there a couple of times, Pim. You know, there is an anxiety amongst young kids today around, you know, am I gonna have a job? Uh, what am I gonna do? What are the skills of tomorrow? What advice would you give them?

SPEAKER_03

Uh make sure you got one thing really good. So I like the T-shape professional so that you're really good at one thing, that's trial and error, but you also are uh that's the the horizontal part that you know a lot of things. Uh AI won't replace your job, but someone who's better at using AI. Uh that's something to to so embrace this new technology. It is very fair, so even if you don't have a uh a high expensive education, you can learn so much yourself. So it has been more fair and democratized. So if yeah uh with yeah with with AI now and the the the knowledge which is under your uh in your computer uh on the internet with tools like AI is enormous. So my advice is yeah uh yeah adapt it, uh embrace it, learn from it, and see the opportunities and don't worry about what I'm gonna do, but follow uh what you're really good at and what is confirmed by others. So if you're creating value, what what mistake sometimes people are doing is that when you're mastering something, people say, Yeah, but it's simple. Yeah, for you it's simple. So make sure that if people give you compliments, like hey you're really good at that, that that's a clear signal that you're creating value and don't discount it, like oh yeah, but that's simple, simple for you. And then maybe see that as a signal to dig deeper there. There you say, okay, if it's simple, then maybe I can become maybe even better. Uh, because maybe this is my alpha, this is what I can contribute to society. Uh and don't waste your time learning something you think you should learn but you're not excited about. Just forget about that and follow uh your talents and develop them, but also let them seek for confirmation. Uh that people say, Hey, you're really good at that you don't do this on your own. That you think hey, I'm really good at something, but nobody cares. You're good at it. And so that's if you if you're gonna go in there, that's where your alpha is gonna be. And if you're young, I can say take a lot of risk. Risk is learning. So sometimes sometimes people think yeah, you're a lowful investor. It's all about not taking a risk. No, risk can be a function where you learn, uh, you learn from your mistakes. And when it's with money, uh also when you're young, suppose you have thousands of euros to invest, yeah, then use it to learn, yeah. Because if you lose half of it, which I did, I wrote it in my book, yeah, that's that's you you're not losing the world. Where if you are 50 years old uh and then you risk your money, then your pension is gone. That's a different thing. So the young people listening take risk, uh see it as a learning opportunity, and uh basically yeah, find your alpha and uh see that confirmed in interaction with others and don't dismiss your own skills, like yeah, that's simple. Uh that's what I would say to the listeners.

SPEAKER_01

It's fantastic advice. Uh I love that that's your alpha. Uh just two more questions. In terms of your most important thing, okay, uh the plate that this podcast is it's kind of unique in terms that it's it is evergreen. We haven't mentioned stocks, we haven't mentioned really uh the future outlook for the economy, but we've had a I think we've had a kind of a deep conversation around what you what you do. Um what is your most important thing, Ben?

SPEAKER_03

Yeah, no, that's uh you shouldn't rule number one of Buffett, I would say, uh don't lose money. That's the most important thing in investing. Uh add to that is uh yeah, don't compare. So don't lose money invest uh because putting it in a savings account you can also lose money, financial repression. Uh putting everything in one single idea is also risky. So navigate those risks and don't compare but focus. Uh don't don't look at others, don't look at uh benchmarks. That's the most important thing. Um to me, don't lose money, don't compare. Invest, focus. That's that's the most important thing.

SPEAKER_01

That's fascinating. F finally, books. Can you give me a couple of books that influenced you and that you would recommend?

SPEAKER_03

Uh yeah, I didn't prepare this one, but top of my head, I like uh Finding Alpha from uh Eric Falkenstein. Um he writes about risk. The book of Hogan I mentioned, uh you will you've also read it. Uh and then of course there's the uh the classics. I I like Bogle a lot. So I think his point is good. Uh by the index is good advice, Golovol is better, I think it's one step better. But uh I can recommend Bogle as well. Um his books like the little book of common sense investing, for example.

SPEAKER_01

If people are interested in following your work, your research, learning more about Rubico, the funds, etc., how do they do that?

SPEAKER_03

Yeah, when you're interested in the funds, you can go to rubico.com slash quant. Uh if you want to follow my work, uh I'm on LinkedIn with my own name, Pim van Vliet. You can follow me on Twitter, it's I'm uh and at Blue Sky, I'm at uh a Paradox Investor. Um then also paradoxinvesting.com. That's where you can find uh also data on Lowval going back to 1929. So I share that. People can play around with that. So these are places where you can uh find me.

SPEAKER_01

No, that's great, and you've been very generous with your time, and I know you've a passion for sharing the knowledge as well. So huge thanks, Pim, um and really appreciate it.

SPEAKER_03

My pleasure, Alan. Nice talking to you.

SPEAKER_00

Alan there in conversation with Pim van Vliet of Robico. Uh the thing I found most interesting is when you go to any investment manager, they will say, Well, what's your appetite for risk? You know, do you want something that has a high upside and is high risk, but you could lose a lot of money? Or do you want a lower return and a more stable investment, but you won't lose your capital? What he seemed to be arguing was that if you get into a low-volve fund, you could actually get better returns and still have less risk.

SPEAKER_01

Yeah, it's it's incredible, really, the insight there, because what he says is that everything we've learned, everything I've learned, I suppose, in 25 years of research and academia is turned on its head. So the basics of portfolio construction, modern portfolio theory, all the way back to Mari Wark Markovitz in 1952 was to get a higher return, you need to take a higher risk. There's a linear relationship between risk and return, just as you said. Even in my own firm, when I model risk, I'll ask for risk questionnaires. And if somebody says that they're uh low risk, they'll go into a low volatility fund, right? No, we try not to do that, but essentially that's that's what the industry does. So what Pym Van Bleed is saying is no, you can actually get higher risk adjusted returns. That's an important word we might talk about, uh, by investing in assets that don't move around a whole lot.

SPEAKER_00

Is is this a glorified version of picking winners? Picking winners, very hard to pick winners, right? So what it's and most investors' advisors, you know, immediately when you say what stock should I, they shy away from it, buy the index or whatever.

SPEAKER_01

Yeah. It's not really a picking winner strategy. What it is is saying it's a probabilistic uh approach, right? So it's what's that mean, right? Well, if you're a quantitative investor, you're basically what's the definition of investing? It's decision making under uncertainty. That's my favorite uh definition of investing. Decision making under uncertainty. So what what the likes of Rabiko try to do is say, we can come up with probabilities, right? We can generate probabilities of outcome, right? There's a higher probability that there'll be less volatility, less risk in my stock if I have a company that pays a consistent dividend, if I have a company with less debt, if I have a company with strong management, good intangibles, strong earnings, good cash flow. So they can screen for all those uh variables through their quantitative methods.

SPEAKER_00

That's the logic. So the quantitative is the allocation of asset resources or the allocation and assessment of risk? It's both.

SPEAKER_01

So the quantitative model would look at a company's fundamentals. Okay, it's debt, it's uh debt equity, it's cash flow yield, dividends yield, but it would also then Ivan though look at the business cycle. You cannot look at a company in isolation. You have to look at a company. Are we in a recession? Are we in an expansion? Are we in a recovery? Are we in a slowdown? So what a low volatility company that and they're they're ranked obviously in terms of uh screening, okay. All that model puts together, from my understanding, uh Pinban Bleat and his team will rank and score those individual equities according to those inputs.

SPEAKER_00

Tell me a little bit more about Robico, its footprint, and how authoritative it is in the context of European investing.

SPEAKER_01

Yeah, I mean it's got a long history. 1929, the firm was established, uh humble enough beginnings. 1929 is an interesting period, uh, the Wall Street crash, uh, but coming up on nearly 100 years, uh, huge manager, over 200 billion in assets. That's big in anyone's language. Uh Pim Van Vliet manages about 75 uh billion, his team uh of quants and analysts. So they're a big they're a big player, but the approach that they take, it's not just low value or low volatility, there's other factors as well, like uh size, momentum, profitability, and we'll be discussing what factor investing is also in the truth series.

SPEAKER_00

Taking his distilled wisdom, and I was very impressed by the fact that he spoke about 150 years, 1870, uh to the 2020s in terms of applying this technology. What can investor take from this distilled wisdom?

SPEAKER_01

Yeah, I mean you picked up on financial history, Ivan, and that's very important because you don't hear Quantz talking about history or philosophy too much. It's all maths. But Pym Van Bliet is different. He has a solid respect for financial history because what we he talks about this notion of financial repression, which we've previously spoken about. And what he says is, okay, I can get data on the individual equities and the funds, but I must be conscious of what's going on in the global macro environment.

SPEAKER_00

What I learned about financial repression as opposed to sexual repression is that it's when governments get overborrowed and the lean and negative effects that has on an economy.

SPEAKER_01

Absolutely. I mean the US government on balance sheet liabilities 37 trillion. You would be a madman or woman not to include that in your analysis or your model. How do you think that's the same?

SPEAKER_00

Sooner or later it will reflect on those stocks.

SPEAKER_01

And maybe Low Val becomes more attractive in that environment.

SPEAKER_00

So does PIM just focus on stocks?

SPEAKER_01

No, the the Rubico uh company, it's not just equities, they all stocks, it's they look at bonds, they apply the same logic uh across assets. So mostly uh known for the Like gold or cryptocurrencies? Not really, no, it's the traditional asset classes, okay? Um equities, fixed income mainly, uh that they approach that they approach, and they're specialist in that in that area.

SPEAKER_00

So finally, uh for Pim van Vliet, what is the most important thing?

SPEAKER_01

The most important thing was interesting from Pim van Vliet after going through all the low volatility, the financial history, the financial repression. He basically said to me, his most important thing is keeping disciplined in his approach and not looking at what other people are doing, not comparing himself to other fund managers or asset managers. And that is very hard to do. It takes patience and discipline, but what it does is says I have confidence in my system, my process, my rules-based approach, and I'm not worried about what the competition is doing. And once I keep focused uh in my approach, it'll work.

SPEAKER_00

Thank you, Alan. So there you have it, one of the finest minds in the world uh in charge of Rubico, uh Pim van Vliet. I hope you enjoyed uh today's interview and got lots of learnings from it. And if you'd like to learn some more, could I refer you to the concurrent series with this, which is a program and a module of e-learning? It's called the Truth Series, which Alan has also curated. So do check that out. But until the next time, from uh Alan and myself, Ivan, uh co-hosting this podcast series, the most important thing. Thank you for joining us and goodbye.

SPEAKER_01

So thank you for listening or watching on YouTube. I sincerely hope you found this episode useful. This podcast is about slowing down the conversation, of focusing on first principles and long-term thinking and the ideas that shape outcomes over time. Because when everything feels important, knowing what matters the most is your age. It is the most important thing. It should be said and important to say that this podcast is for information and educational uses only and does not constitute financial advice. All views expressed are those of the guests and the hosts. Although I am a qualified financial advisor, and I am a certified financial planner. Everyone's circumstances are unique. So before you make any decision in relation to your finances, investing, or financial planning, please seek a qualified financial advisor. There's loads more to come on the most important thing, and we can't wait to see you next time. Thank you.

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Dr Alan O'Sullivan CFP® TEP

Host
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Ivan Yates

Co-host