Rebecca Hotsko (03:21):

In order to set the stage for today’s discussion, I think it’d be helpful to start off with you just explaining what factor investing is for our listeners that don’t know. And what is the empirical rationale behind why companies with exposure to these certain factors have historically generated higher expected returns over the long run?

Pim van Vliet (03:44):

Maybe going a bit back on my background. I have a PhD in finance. And it started as a master’s student where I stumbled on an article saying that if you systematically buy stocks which a low fall, a good value, profitability momentum, you can beat the market. And I was young and eager. And I was like, “Can it be this easy to be to market?” Because we’re all trained in that markets are pretty efficient and it’s not that easy.

Pim van Vliet (04:10):

Yeah. I use those factors, these company characteristics in my PhD. I continued to see, could it be maybe that these alphas are not real. Maybe it’s downside risk, it’s something else. Because if markets are inefficient, this has huge implications. I studied, spent four years of my life. The answer was a little bit, there’s some tail risk in some of the factors, but at best, a partial explanation, which means there is alpha.

Pim van Vliet (04:35):

And then I went to the industry to Robeco, where I am still today 17 years later. I found out that these factors can be turned into real life strategies and you can harvest them in practice. Now then, your question is, yeah, why do they work? The first question is, do they work? Because yeah, is the evidence strong enough? There is global evidence for factors to work. There is US evidence. It works within sectors, cross-sectors, within countries, across countries. The evidence is pretty overwhelming.

Pim van Vliet (05:05):

Interestingly, on that note, we also did an older sample, going back to the 19th century to test factors. Again, they work. That means that the chance that it’s just noise or data mining or p-hacking is extremely small. That’s a good thing. But then the second question is, yeah, how can these alphas be there if it’s not risk? What is it?

Pim van Vliet (05:24):

If it’s not risk, it’s not data mining, it must be behavior or other explanations. Then you go to behavioral finance to think about why do these factors give you such an alpha. And therefore, finance really gives good answers to that question. For in general, our behavior has been pretty constant over time.

Pim van Vliet (05:45):

There’s famous work by Kahneman on psychology as humans, we are much driven by emotions, which is often good, but when it comes to investment decisions, it’s not always good. These emotions, when they relate to factors are usually over-reaction and under-reaction combined with overconfidence. I would call these the three big explanations for why factors work. The question is also how will this go forward? I think, and we believe that these factors, these explanatory factors have even increased recently.

Rebecca Hotsko (06:15):

I’m curious on the piece where you said the risk-based argument. I’m pretty familiar with that, where one argument is that these factor premiums work because they’re riskier. Are you saying that that is actually an outdated argument?

Pim van Vliet (06:31):

Yeah. The thing is anything you want to harvest, going for factors is not risk free. Yeah. There is variation in returns. When I talk about risk, I talk about more the academic notion of systematic risk. That’s in a Shaworld in an efficient market, there’s only one or a couple of price risk factors, which is market risk, maybe some liquidity risk. And that’s it.

Pim van Vliet (06:52):

It’s not related to death or distress risks. Fama French, for example, they say there’s a value premium and it might be distress risk. They say it’s a risk premium. And then they vaguely say that it’s distress maybe. But this research is falsified. The counter arguments are that value, for example, is not a reward for risk. Because if you take out the distressed companies from a value strategy, so the ones which do have higher risk, you still get access to the value premium without higher risk.

Pim van Vliet (07:21):

But to clarify, if you enter a quant strategy, there is risk involved and that’s more relative risk. Yes, because you deviate from the market, you can have periods of under-performance and periods of out-performance, but it’s not systematic risk. It’s a specific risk you enter in any active strategy. But that cannot be the academic or the theoretical explanation for why something works, because there are many, many other strategies.

Pim van Vliet (07:46):

For example, if you take the opposite of the quant strategy. You not take a low fall value momentum stock, but you do the opposite. Then you also get risk. You also deviate from the market and then you lose money. It’s not that if you take risk and deviate from the markets that you will get a premium for that. That’s not how risk works. It’s not like karma.

Pim van Vliet (08:05):

Maybe it’s good to explain it with, if you enter the streets with blindfolded, you take lots of risk. Or when I want to become an influencer on yoga and, I don’t know, biological food, I take risk, because I don’t know what I’m doing. But it’s not that you get rewarded for that. And when it comes to investing, some people say, “Hey, I take risk so there must be a reward.” The answer is no, that’s not the case.

Pim van Vliet (08:28):

Only in exceptional cases, when you really know what you’re doing. Like with equity market investing, you take risk, but you also get a reward for that. And the same with some active strategies. You take a risk and then you might get the reward. Most cases, you take risk, you don’t get the reward. And that’s an important lesson also for starting investors who think that risk is like karma. You take risk and then you get a return. That’s not the case.

Rebecca Hotsko (08:53):

A lot of our listeners are well familiar with value investing. And the value premium is maybe one of the most well known factors. Can you talk a bit about what the difference is though, between picking stocks, being a value investor versus implementing a factor-based approach?

Pim van Vliet (09:12):

Maybe it’s good to elaborate on another factor, which is less well known among investors, which is the low volatility approach, the low volatility factor. Which clearly is not a risk factor because you get less risk, but you get a higher return. That by definition cannot be a risk factor.

Pim van Vliet (09:29):

That’s the most clear example about what we just discussed about risk being priced or not. With value companies, you systematically buy cheap stocks and you don’t buy expensive stocks. With low-vol investing use systematically buy stocks which have a low beta or a low volatility or a low addition credit volatility. As you just mentioned, because high edition credit volatility is not priced. Volatility is also not priced. beta is not priced. In fact, it’s even negatively priced.

Pim van Vliet (09:56):

If you take lots of risk on the stock market, you lose money in the end. And that goes against anything we’ve learned in finance because there it means that higher risk is lower return. There’s an inverted compensation of risk. And that’s, for me, still amazing that that’s the case on such a large scale. And the reason for that is that investors tend to be overconfident. If you become a stock picker, you tend to buy high vol stocks, which move a lot.

Pim van Vliet (10:24):

But if everybody thinks they’re a good stick stock picker, on average, we all think we are above average, but that’s not the case. Then you drive up to prices of those risky stocks and you overpay for it because of your own confidence. It’s collective. And therefore, these stocks do very poor. It’s like the lottery. If you buy all lottery tickets, you will win the million dollar for sure. But you lose money because the lottery company, they make money. And it’s the same with stock. If you buy all the most volatile stocks, all of them, you will have the next Amazon for sure because that’s often where those growth companies can be found. But you will also have so many stocks which don’t make it and lose out.

Pim van Vliet (11:07):

That’s on average. And that’s with factor investing it’s on average. You have to do it on great scale and great breadth. Then you lose out. Then you start to build into factor investing, as you said. Value investing is well known. You systematically buy cheap stocks, which go for low multiples, high dividends, low PE.

Pim van Vliet (11:26):

The second thing is with risk, then you add risk components. You say, “Oh, I will also want stocks which are systematically less risky.” Then you already have two factors for which you can screen your universe. And then it starts to build out, where you also then add momentum, which is also a common factor. That’s playing sentiment and playing in the reaction.

Pim van Vliet (11:46):

And that’s how you start building a multifactor approach. Can be defensive if you add low volatility to it. And then, if you apply this in a systematic and rules based manner and you diversify across 200, 100 stocks. Not just picking one or two or 10, then you will get something which we call our quantitative factor-based strategy, which in the long run is able to beat the markets.

Rebecca Hotsko (12:10):

I want to touch on your low volatility strategy, more in detail in a little bit because I want to break down a few more topics first. A lot of our listeners pick individual stocks. And so, you’re talking about how to apply these certain factors. First I want to go back to the factors. Fama French popularize their five factor model, which includes market risk, a relative price, size, profitability, investment. They didn’t recognize momentum, but that’s also one that is widely recognized, I guess, between academics. But I’m just wondering which factors do you think will perform best going forward or you think are just more relevant going forward?

Pim van Vliet (12:57):

Fama French, if they’re first a three factor model, they expanded to five. The three factors you can say that’s markets at a active premium. I think most of us believe in that. Although the outlook for that tends to be somewhat weaker after an extreme good decade, fueled by a ultra loose monetary policy and that’s ending. But the first equity factor is maybe less strong going forward than it was.

Pim van Vliet (13:20):

Then there’s the second factor. It’s the size factor of Fama French. The evidence is mixed. As I said, if you slice and dice and you have clean data, you do across countries and it’s mixed. If there’s a premium, it’s a compensation for risk. It’s one of the weaker ones. Then you go to value. We just discussed, well known value is back. It had a tough decade, but the last two years, it’s strong again. And the value investors stayed in and now they’re rewarded.

Pim van Vliet (13:46):

And then Fama French added two factors, as you mentioned, profitability and investment. These are loosely labeled combined as quality. They don’t call it quality, but then you bring it more narrow to quality. And that’s a good factor. It’s also relates to other reaction of investors. A company’s doing great, but people think, “Yeah, it’ll mean revert.” But it’s a good factor. It has had a strong, recent performance.

Pim van Vliet (14:09):

That also means that the quality has become a bit more expensive. That’s then on the outlook an issue. And then you mentioned momentum is not in the Fama French model. That’s a strong factor, a very strong evidence everywhere placed in the reaction. It’s difficult to pinpoint because momentum is every year, it’s different. It’s value investing, you can easily pinpoint to companies with momentum. It’s changing all the time. Fama French don’t like it because you have to trade a bit more and it cannot be explained by risk because it’s not a style. It’s more of a trading strategy.

Pim van Vliet (14:41):

And then the last factor is low vol. We will discuss a bit more about that. Also Fama French don’t recognize that. They are from Chicago, which is more from the rational, efficient market school. And low vol can never be a risk that you cannot have risk. Sorry for that. At least not in the classical sense because there is risk in low vol investing, but it’s a totally different risk than what Fama French talk about.

Pim van Vliet (15:04):

Summarizing that back, you can say there’s the good old equity premium. A bit less size. It’s a bit, yeah, is it there? And then there are the big four, that’s quality, value, momentum and low vol. That would be the summary of 50 years of academic empirical asset research. Some people talk about hundreds of factors, factors use. But these are usually variations around these common styles, you could say. To keep it simple these are the big four, which we think work besides of course the mother of all premiums, the equity premium.

Rebecca Hotsko (15:40):

So then you mentioned not all factors have performed well and some have actually performed really poorly for many years. Some of your research refers to a lost decade for some of these traditional Fama French factors. Can you talk a bit about which factors have maybe lost their premiums or performed poorly over the past few years?

Pim van Vliet (16:01):

It also relates to the academic evidence. Our factor premiums also real going forward. Because if you look at the Fama French three and five factors, and you look at the out of sample evidence, it’s not that strong. It’s positive. Some have done somewhat poorer and we’ve done research. And we see that exactly the two factors, which they didn’t include being local and momentum, they have basically held up pretty strong in the last decade and last two decades.

Pim van Vliet (16:29):

Of course, both with their own cycles and value, especially in the US has been particularly hard hit. Pure Fama French approach. Would’ve been a bit disappointing. Add its low vol and momentum, which have been pretty good, especially outside the US. That’s also something to mention. In emerging markets, in international markets.

Pim van Vliet (16:48):

And finally, there’s also the move of what we call the move into signals. Or beyond Fama French, that’s using quicker trading signals like short term reversal patterns, seasonal patterns. Which also adds a lot of value on top of classical Fama French factors.

Pim van Vliet (17:05):

And these are even more difficult to harvest. Because I think if you look at the development of quant and factory investing that 20 years ago, it was an academic thing. And then the big institutions started to invest with using quant approaches. And then 10 years ago, the Indies fest came up and then also followed by ETFs and mutual funds.

Pim van Vliet (17:23):

And nowadays, especially in the US, also retail investors have a great opportunity also to have exposure to quant factors without doing it all themselves, because it’s quite, you need technology data, you need discipline. And if you buy an active or some vehicle, you can get access in many ways to quant strategies. And that’s really different than it was 10 or 20 years ago.

Rebecca Hotsko (17:48):

Yeah. I want to touch on that because the small cap premium in particular has seemed to have dwindled over the years. And so, I read a research paper that said that the premium for small cap stocks was not statistically different from zero.

Rebecca Hotsko (18:05):

I guess I have two follow ups on that. I’m just wondering, like you mentioned, as these strategies have come more popular and packaged into ETF products and demand for it from institutional investors. Maybe has that driven up the price and that interest in these products in the wider adoption? Has that factored into reducing the premium for certain factor premiums like the small cap perhaps?

Pim van Vliet (18:31):

Yeah. That could be an explanation that small caps have become more popular, driving down expected returns. Yeah. There are two things to that. One is first, you should think why would there be a premium? With small caps, why would small caps earn more return? Because if a big company chunks itself in 10 pieces, do you then get a higher expected return simply because they’re smaller?

Pim van Vliet (18:53):

But that’s something to consider. Usually from the fear of the firm, you would say, “Oh, if you combine them, you’ve got scale internal efficiencies.” Then you create value. That’s pure, fundamentally driven. Why would that be a small cap premium? That’s a tougher one. Some say it’s liquidity. If you’re less liquid, you should have a higher return. But that’s also not a given. If I run a mutual fund and I make it less liquid, it’s not that the return should be higher because it’s less liquid.

Pim van Vliet (19:20):

That’s also doubtful. Your explanation, that’s the third one, that if it was there, maybe is there not anymore. That’s a good explanation for why the size premium would be smaller. There’s only one but, is that the rise of index investing really goes into big caps, like S&P 500 and Shaworld, basically ignoring the small cap.

Pim van Vliet (19:39):

Small caps have become more cheap over time. The cheapness of value. If you believe in value investing, it’s related to small cap. And there you see that’s the evaluations of small cap is pretty low. If you compare Apple with 1,000 small caps. And then you pay basically the same amount. And then you can say, yeah, there’s so much opportunities in all those companies with their patents, whatever they do. Maybe their materials, their buildings, their personal. That, yeah, from that perspective, small cap should not be dismissed.

Pim van Vliet (20:10):

I would not be surprised if the next decade, small caps handsomely outperform because more of tactical reasons. In an environment where you need to be more resilient and also given evaluations. In our quant strategies, which we run, there’s a lot to say about small caps. It’s not as simple yes, no. What we do like about small cup is that there’s so many of them. And like you have 10 mega caps, but you have thousands of small caps.

Pim van Vliet (20:34):

And in a quant approach, you need breath. You need to go through all those stocks and select the best ones. All our quant strategies tend to end up with the small cap bias. Not because we like small caps, but because there’s so many of them and they’re not all created equal. That’s why most of the time you see, when you look at a quant strategy, they tend to have small cap bias.

Pim van Vliet (20:55):

And then it’s not per se because small cap might be attractive, but more because small cap might be cheap. There might be some local small caps. And then, simply by being long only, you will have more likelihoods of having more small caps. Then it’s an outcome.

Rebecca Hotsko (21:12):

I also want to get your thoughts on this because I also read a research paper that said when you filter small caps by growth, low profitability, and then by high asset growth stocks and you remove them from the small cap universe, the size premium does become significant again. Doing this, however, eliminates about 15% of small cap stocks.

Rebecca Hotsko (21:33):

It just seems to me like achieving the expected premium from small cap stocks is increasingly challenging over the year. Given the additional filters, you need to layer onto small cap stocks. I guess my question is, what do you think is the most optimal way for retail investors to get exposure to the small cap premium?

Rebecca Hotsko (21:52):

Because if we try and buy just one of the traditional small cap ETF, small cap value something, it might not be filtering for those additional layers. And then, are we just overpaying for this product that we think we’re getting a premium when it might be implementing the strategy inefficiently?

Pim van Vliet (22:11):

Yeah, that’s a good one. You mentioned the filter. If you go… I know that that research it’s good. I agree. We come to the same conclusions. If you filter only, you can also take it differently. If you only filter 10 or 15% out, you already get a sizeable premium.

Pim van Vliet (22:25):

What happens if you filter 50% out? You get huge premiums because there’s so much breadth. In that sense, I wouldn’t see the filtering as something negative. And then, if you do small caps, you mentioned small value, then you already have your filter that you take out the small, expensive stocks, because you do small value. That’s a very good filter.

Pim van Vliet (22:46):

The only thing there is that it’s fundamental on value. Ideally, you would like to have other filters, like volatility, just mentioned. Momentum and possibly, quality. Asset growth or a possibility. That would be the best way to get access. And I think there are also even some indices out there who offer that kind of strategies.

Rebecca Hotsko (23:04):

You also mentioned value stocks. They underperformed growth stocks for much of the past 10 years when looking at traditional metrics like price to book. They’ve recently recovered a bit over the past two years, but I’ve heard some argue that this is because using price to book is an outdated value metric. I’m just wondering, has your approach changed at all over the years in the way that you characterize and define what value companies are?

Pim van Vliet (23:31):

Value comes in many forms. You can have price to book, price to earnings, even price to anything works. And that’s also, I saw some funny papers on that. Price cash flow, price dividend. What we’ve always done in our strategies is not spin it down to one exact definition. Like this is the best one. We always to value as a multiple dimensional thing, approaching the value of company from multiple angles, including these ones, but also enhanced versions.

Pim van Vliet (23:59):

Because what we find is that, for example, if you do price to book, maybe you do not recognize the investments made on R&D. Then maybe that should be added to the book value. And then you need to adjust certain metrics or dividends. You should also be aware that some companies have to pay dividend, like Reids that you are aware of that. And for each value variable, you can have adjustments. Price earnings, you can also take a look at expected earnings instead of trailing earnings.

Pim van Vliet (24:28):

What we find is that you’re doing multiple dimensional and also enhanced value definitions, you gain something much better than simply price book or price earnings. Having said that, price book is the kid at school who was kicked around, bullied. Price book has been really an easy target for many, how do you say it, quants or market pundits because it’s outdated.

Pim van Vliet (24:52):

However, the funny thing is, although standalone not that strong, it is a factor which adds value in a value strategy. It’s better to repair it than just to throw it away. And then interestingly, Rebecca, is that’s with book value you can even argue that the book is usually more traditional firms with assets. With inflation rising, if you have any tangibles. There’s lots of talk about intangibles, which are important. But in a soaring inflation environments, yeah, having some trucks, having some buildings, having maybe a real site could be something good in a totally different regime if we move from globalization to localization.

Pim van Vliet (25:28):

And also recently, price to book was doing pretty good. However, having said that, it’s you never should go into one extreme. When it comes to value, we have always had, we believe in a balanced approach. And also taking out some obvious flaws of the simple metrics and enhancing them to a higher level.

Rebecca Hotsko (25:45):

You mentioned that you can pretty much use any price multiple that you want when looking at value. Do you have a preferred one that you look at when searching for these companies? Or do you look at them through a lens of comparing multiple different price multiples?

Pim van Vliet (26:02):

Depends on your purpose. If you only have to rely on one, then like income yields is shareholder yields where you take share buybacks. Dividends is a very robust one because it’s a bit more defensive, which is good.

Pim van Vliet (26:14):

It is also comparable across industries because it’s cash in hand, no dependence on any way accounting standards or those kind of things. If you want to one have one, then that’s a pretty good one to start with.

Pim van Vliet (26:27):

That’s also the one I mentioned in my book, which I wrote for mom-and-pop investors. I wrote it for my dad. In fact, he’s not a C of A or PSD, an entrepreneur. And in that book, the value factor which I use is then share buybacks with dividend, which is the shareholder yield or the income yield variable.

Rebecca Hotsko (26:47):

Then I’m curious to know what your views on technology stocks are. Particularly the FAANG companies, which are thought of as large growth companies. Following a traditional value-based investment approach, these companies often look very expensive and probably wouldn’t make the cut for just using those traditional price to book metrics. I’m wondering what you think about these tech companies from a factor-based investing approach.

Pim van Vliet (27:16):

With the factor investing, I mentioned, it’s good to look at multiple angles. And also, we control our risks often. You don’t want concentrated portfolios. When it comes to FAANG and large cap growth stocks, usually within technology, there are always stocks which are not that expensive, but are attractively priced.

Pim van Vliet (27:35):

You can find stocks which don’t have a high risk, but are more a medium risk. Profitability is fine, of course. And then we go to momentum and that is also has been pretty strong over the past decades. With a factor approach, you would end up with pretty some exposure to those technology stocks because they score pretty well on several factors some of the time. Overall, you have been somewhat over underweight. Yeah. That’s the outcome because of what you say value from the valuation perspective, that was really holding some of them back.

Pim van Vliet (28:06):

That’s a pretty nuanced view on technology. And also, in our strategies, we see that many technology stocks pop up and come through our screens only when they satisfy our criteria. The good thing about a quant approach is that you only look at stocks through the factor lens and do not get emotions on this is maybe a tech stock or not. You just follow it’s data driven, pretty clean and objective. And then we have some relative sector limits, of course, which make sure that you’re not going to move into one country or one sector with a huge part of your portfolio.

Rebecca Hotsko (28:39):

Do you have any examples or that you could walk us through an adjustment that you make, such as like R&D maybe, that shows that it is still a value strategy for these companies?

Pim van Vliet (28:51):

That’s one example. R&D patents can be used. They’re usually an expense and then you can bring them back and adjust your value metric. That’s what we call an enhanced definition. Another one is carbon emissions. If you assume that there is a price to it, now there’s not a tax yet on it. But if it becomes more and you can look at carbon price data. How much would it cost if there would be a price on it?

Pim van Vliet (29:17):

We can make adjustments to your valuation multiples. We’ve done a research on that. And then we find that you can take this risk out, which is in price. That means if it’s in price is good, because then you still get the full value premium without having these unwanted risks or exposures. These are two examples of R&D and carbon adjustments.

Rebecca Hotsko (29:38):

Now I want to move onto your low volatility investing strategy. Many investors might think that the only way to increase their returns is by taking on more risk. And lower risk means lower returns. And you’ve done some incredible work on the topic. You published a book titled High Returns From Low Risk, a Remarkable Stock Market Paradox. Can you explain why high risk does not always mean higher returns? And then how can we actually get higher returns from taking less risk?

Pim van Vliet (30:10):

That’s a remarkable paradox or something which puzzles me big time. And also, when I started the fins, I told my mother, “Yeah, we’ve got a low risk strategy with a high return.” And then, she was obviously skeptical like, “How can it be?” Because we all have learned if you take more risk, you get more return.

Pim van Vliet (30:27):

This is very exceptional and you shouldn’t directly believe me if I say that buying high risk stocks gives you lower returns. And if you buy low vol stocks, you get higher returns. That’s really a puzzle mark paradox. Now the reason, first, it’s about the evidence. Is this really true? Now, the thing I mentioned we’ve done during my PhD, I did research it’s there in the US. We looked at pre-crisp data. Really going to the 19th century is there. It’s of all the factors out there, basically the most proven and strongest one out there.

Pim van Vliet (31:01):

And also, it requires little data. It is simply return volatility. You can test this without relying on any other data than price data. The degrees of freedom are limited. It’s simple and effective. The evidence is there. It is extremely high T-stats, especially if you take long samples. And then the question is, what horizon are we talking about? Because if you look at a daily basis, so you’re a day trader, then any data market goes up, then high risk stocks also go up or higher. And low risk stocks don’t go up.

Pim van Vliet (31:33):

On a short term basis, the market is pretty efficient. It’s not that on a daily basis, low risk stocks outperform. It depends on where the market is going. The same way on a year, if the market is really up in a year, so 20%, then usually high risk stocks are up more and low risk stocks are up less. Then again, you would say, “Hey, markets look pretty efficient.”

Pim van Vliet (31:53):

The puzzle becomes more and more prominent and visible if you zoom out and out and out and go to a three year, five year, seven year, 10 year horizon. A full cycle, which includes bulls and bears. What you don’t see appearing is that every day, every month, every year, the market is off a little bit because they overpay for risk, they under pay for low risk. Meaning that low risk stocks lose less. They are winning by losing less. That’s the catch phrase of low vol investing. Winning by losing less.

Pim van Vliet (32:22):

And if you compound it over this 3, 5, 7 years period, then you see suddenly, “Wow, these low vol stocks are beating the market.” I spent my brains on cracking this. How can this be? Why would this be the case? Now one is, of course the horizon. The longer you look, the bigger it gets. And then academics, they often use a one month horizon. On a one month horizon, the anomaly is not that big. And so the puzzle is smaller when you are looking at a short term horizon.

Pim van Vliet (32:49):

For any listener who says, “Hey, my horizon is longer than one, or three, or five years,” it becomes more and more interesting. If you only are looking for short term traits, then low vol is less of an appealing. That’s part of the explanation. What’s your horizon? If it’s longer than a month, then it already starts to be very interesting.

Pim van Vliet (33:08):

The second is the risk explanation. I was cracking my brains, could it be downshift risk, tail risk? And lots of econometrics needed. And then the answer was no, not really. That’s not really the case. But then I came in the industry. And then I learned something else about risk, which we call tracking error, benchmark deviation, active risk. And only the word is trackinge error means you’re making a mistake, while you’re just deviating from the market. It’s not wrong to take an active view.

Pim van Vliet (33:37):

And there it comes. If you have a stock which hardly moves and gives you every year 10%, I think all the listeners would say, “Give me something which yields 10,” or even, for sure, just every month, 1%. That’s 12% per year. Then an active manager who has to beat the benchmark, S&P 500 and Shaworld. This person is looking at the stock and saying, “Hey, but I think I need to outperform the S&P. If the S&P is doing 20%, then even 10% is not giving me my out performance.”

Pim van Vliet (34:07):

The second thing is, if a stock doesn’t move, the tracking error is extremely high because anytime the market goes up or down, you are just, the stock doesn’t move. From a relative perspective, low risk stocks are extremely high risk stocks. And then, I found out just after a couple of weeks, I’d studied risk, I studied low vol. I found out that, Hey, the way our industry is organized, especially the institutional part of the market, that’s becoming bigger and bigger. That’s a relative investment world, aiming to beat benchmarks and outperform.

Pim van Vliet (34:38):

While low volatility investing is not to deliver stable out-performance, but to stable performance. It’s an absolute perspective. From an absolute perspective, you say, this is great. I’m growing my capital and protecting my downsides. Capital growth and capital protection. But if you say I want to beat S&P 500, then it’s not a good idea. It is a high tracking error and not so much out performance. And this is one of the big explanation for why low vol investing works. It’s all about comparison.

Pim van Vliet (35:10):

I also write in the book, my mother told me, “Pim, don’t compare too much with others. Because if you compare, you usually become unhappy because of you.” And that’s what we do in our industry, we compare all the time with benchmarks. And again, a bit of comparison is fine. How am I doing compared to peers? That’s fine. But if you take it as a starting point of your investment procedure, where you say, “Okay, I take the index as a starting point and I need to beat it.” Then it becomes normative thing and often a disappointing thing.

Pim van Vliet (35:38):

Yeah, first we think there’s very big. It’s one of the biggest and strongest anomalies out there. We do all the data checks, all the scrutinization, what you should do in an academic context. And then why? Why does it work? We think it’s the compounding, which is often ignored. And then this relative investors’ perspective where investors are also overconfident.

Pim van Vliet (35:59):

Because if you want to be the market, if you want to be the smart guy in the party, then of course, you’re not going to buy some boring utility stock because it’s not going to make you rich. You want to have to school this. You love volatility. You have a volatility preference, because you are a good stock picker and that’s where you should be.

Pim van Vliet (36:15):

But if we are all above average, which is technically not possible, because we are not all above average, about half is above and half is below, it’s healthy to be self-confident so that we all move to this part where you can beat the market. You can beat your friends, your day trading friends. And then, individually it might be a rational thing, a micro base. But on a macro level, it doesn’t add up.

Pim van Vliet (36:39):

And on a macro level, you can say, “Okay, when I see this happening, like game theory, I see everybody individually doing this. Maybe I should take another standpoint and be skeptical here and say, ‘Hey, let’s move to the low part. Let’s buy this through an ETF or active event or do it myself.'” And then you get rewards of this approach where you profit from the others people’s over confidence. Again, yeah, you need also to have this horizon for at least a year or more to see the benefits of this approach.

Rebecca Hotsko (37:09):

I want to just touch on this quickly. How would you define what low volatility or low risk is just for our listeners? Are you just saying that is beta less than one? Or how do you define what a low risk stock is?

Pim van Vliet (37:25):

This is the most simple way is what you just said. beta below one or below 0.8 or something, because one is, it’s always one if it’s market lag. That’s very easy. Volatility is more, can be higher, can be lower, but there are rule of thumb is, yeah, lack of volatility less than 20% is low. If it’s above the high. But again, that depends more on the market’s circumstances. beta is a simple one for retail investors and listeners.

Rebecca Hotsko (37:51):

Then for our listeners wanting to adopt this strategy and improve their returns by buying these lower risk stocks, what else should they be looking for in these companies? I’ve read a paper. I think it was 2016, Richard Novy-Marx, that said that low volatility stocks, when you control for size, relative price and profitability, then that anomaly goes away. Are we needing to look for these additional factors in addition to the low volatility one?

Pim van Vliet (38:23):

Yeah. That’s a good interpretation of these results. Like I said, you should never go single factor. I will also not recommend just to simply screen on beta and that’s it. You should definitely look at those other things as well, like profitability.

Pim van Vliet (38:38):

If it’s low risk, but it is unprofitable, maybe don’t do it. If it’s low risk, but it’s expensive, don’t do it. If it’s low risk, that momentum. That’s what I would favor. In the book, present a formula based starting from low risk. And then we add income yield, as just discussed, as a value metric. And also price momentum. We call that the conservative formula. It’s a bit similar to Greenblatt’s Magic Formula.

Pim van Vliet (39:02):

And there are screeners who apply it and they can apply this formula to your screens. And it should be multidimensional for sure because if you only do one of them, then you might have some issues as you just discussed.

Rebecca Hotsko (39:15):

I’m curious on the momentum piece. There’s a lot of different ways that investors implement momentum strategies. Are you looking at performance over 12 months? Or what do you think is the most optimal way to get that momentum premium or benefit from it?

Pim van Vliet (39:31):

The starting point would be six to 12 months past price return. That’s the staple of momentum. It’s also pretty good, robust over time. Then you should skip the last month because prices tends to mean revert on a short term basis. That’s already one.

Pim van Vliet (39:47):

Then another thing, yeah, then you can expand. Also the listeners, if you Google, for example, local investing and there’s Wikipedia on it. There’s also lots of background material also for momentum. With momentum, there is lots of expansions. One is to residualize your momentum? Risk adjusted because some of the past price return is driven by the style. If all value stocks go up, yeah, that momentum starts to buy value.

Pim van Vliet (40:10):

Maybe that’s not what you want. Maybe you want to control for this. Or when all high beta stocks go up, then momentum is buying high beta. Maybe you want to control this and we call that more stock specific momentum. You need a bit more technology to do that, but you can take those systematic parts out and then you get a more pure form of momentum.

Pim van Vliet (40:29):

It’s a company momentum, high idiosyncratic momentum you can call it. They’re different names. And that’s also a very good one. And also one which crashes less. You are less sensitive to market reversals. That’s one example to, yeah, move on beyond the classical six, 12 months. But again, for retail investors also a show in the book, it’s pretty good, six, 12 months

Rebecca Hotsko (40:50):

Momentum seems to have a different time horizon than the other factor premiums. Can you talk a bit about, I guess how long investors should think about holding these stocks with these factor exposures to get the premium? How long does it typically take for these factor premiums to show up?

Pim van Vliet (41:09):

There’s a difference between the duration you have your stocks in portfolio and about the performance. Momentum is a strategy which tends to give positive results on a five year basis, but you change the portfolio every six months. It’s a high turnover strategy. With value and low volatility investing, you hold the stocks for about four years. Pretty stable.

Pim van Vliet (41:30):

And there are also those factors tend to work on a five year basis. But the five is not a given. Value really tested us because it went in the US to a 10 year basis in which it was flat or negative. If you do a multiple factors, so that’s what we believe in, then you shorten this horizon to five year or beyond. You most of the times, beat markets with lower risk. Again, this is not a 100% case. The stocks you hold in portfolio are more changing over time.

Rebecca Hotsko (41:58):

I guess that touches on my next question about rebalancing. These different factors also have different rebalancing assumptions then as well. Momentum, like you mentioned, is shorter. But then the value in size and profitability or quality factors. How often should we think about rebalancing those and what should be looking for to indicate that we need to rebalance?

Pim van Vliet (42:22):

If you do cell factors, so these are more the slower ones. That’s low vol value quality, one year could do it. If you go to the quicker one, like momentum, you need at least a quarterly basis or a monthly. But therefore, yeah, it’s more labor intense to do it.

Pim van Vliet (42:39):

If you combine them, then a quarter is fine, especially if you have momentum in. It’s also in the conservative formula takes, for example, quarterly horizon. And if you’re a professional investors. What we do for institutions, but also in our mutual funds, that’s why we do look at markets at a daily basis and also take trade signals into accounts. But there you have, of course, the technology and the people and the platform to really do this basically 24/7, where you can always be ready to move in or out. If you do it yourself at home with your broker, then a year could work, or several, or a quarter.

Rebecca Hotsko (43:13):

You also talked about before, how you shouldn’t just apply one factor, you should apply multiple. But are more factors, always better? How many factors should we be looking to get exposed to for each of our picks? And how do you think through that?

Pim van Vliet (43:32):

I mentioned the big four factors besides the market, which is five. Four is not always better because if you add 10 more which are all momentum, then it gets out of balance. Also, when you add more, you also have to better understand why you are adding them. Like we discussed about size, why would it work? You also need an economic rationale for each factor.

Pim van Vliet (43:54):

More is certainly not always better because the chance that you throw in something bad, because it’s spurious or just it’s nothing, increases if you are basically throwing in too many. Now when it comes to signals, I also mentioned, so we discussed about the factors a lot. I said, we also see movements beyond Fama French, going more into now more next gen level signals where you use machine learning, alternative data. Often those signals are also quicker.

Pim van Vliet (44:22):

And also there, we see more is not always better. Many of those very promising signals prove not to work that good. Also there, it’s goods to have a multidimensional view and multiple angles. But also don’t overdo it. There’s this sweet spot we find between certainly not one, but also certainly not 100 or 50.

Pim van Vliet (44:41):

And then there’s semantics to factors versus variables. Because if you talk about value, I call it one. But of course, it’s consists of 10, 20 different angles of value. Then it’s also semantics. Yeah. What are we talking about? When I say four, five, I’m not saying variables, but I’m saying themes or groups of variables.

Rebecca Hotsko (45:02):

The last thing I want to ask you is just a practical takeaway for our listeners. I guess, what do you think is the best way that our listeners can get exposure to these factors? One camp of investors might be stock picking or the other camp might be just wanting to get exposure through ETFs. What do you recommend is the best way for the average retail investor?

Pim van Vliet (45:27):

Depends really on the jurisdiction. Many of your listeners are US based. There you have pretty high sophistication levels. If you look at Europe, it’s pretty much the opposite. Institutions are very state of the art, lots of access, while on the retail space is really fragmented among cross countries. Let’s go to the US. There are several ways. You can do it yourself, where you apply screens and you have to do this systematically. It’s requires some work. I describe it in my book as well, how you could do this.

Pim van Vliet (45:55):

If you say, “Hey, let’s not do my own cooking. Let’s hire a chef.” Then you go to a mutual fund, for example. There are different mutual funds. Are there Morningstar can help you or other consulting investment. Maybe you’re an advisor or maybe you just check out on the internet where you post questions. Like “What’s a good….” You can find your way on good mutual funds.

Pim van Vliet (46:15):

There’s ETFs and active ETFs coming up, which also have various degrees of factor exposure. Direct indexing coming up. If you have some money, you can also ask. That’s a hybrid between do it yourself and having an advisor doing it. That’s pretty advanced in the US. The same goes to Europe, but there you are a bit more limited to what your broker offers and what you can do.

Pim van Vliet (46:37):

Also trading internationally. In the Netherlands, for example, there are not so many stocks in US, so you have to go international. You have some more boundaries. And also there in Europe and Asia and the rest of the world, there’s access to mutual funds and ETFs. Because maybe that’s also something to mention, Rebecca, that sustainability is also by some considered as a factor or at least as a preference.

Pim van Vliet (46:58):

A very common, not political view on sustainability is that if you talk about efficiency, if you treat your people well, like governance or social, then that’s good for a firm and stakeholders and shareholders. If you are resource efficient, no matter whether you’re progressive or conservative, if you take one barrel of oil and you make lots of products with it, more than a competitor, that’s good. That’s good for the planet, but also good for profits.

Pim van Vliet (47:23):

ESG is also moving in with quant. It’s also emerging there where lots of fascinating things happening. Where you can also have a quant approach to ESG in a shareholder friendly way. That’s also the G part of ESG, so governance. The S part happy people produce good profits. The E part being resource efficient, all can add to alpha and also can deliver outperformance. And that’s also a good thing to mention here.

Rebecca Hotsko (47:51):

Touching on the different themes, ESG and sustainability. From a quant perspective, I could have a whole nother conversation With you on that one, for sure. I guess my one last question and then I’ll let you go, is a lot of our listeners might have heard of smart beta investing strategies. Can you just speak about maybe what the difference is between factor investing and these smart beta products. And are they an efficient way to get exposure to factors?

Pim van Vliet (48:21):

Smart beta is a way of getting exposure to factors, usually through indices, which are then static. They’re defined. The technology in these indices is often static and it’s written down. It’s also makes it a bit vulnerable because it’s very open. It’s pretty transparent, in some cases too transparent.

Pim van Vliet (48:43):

But yes, it’s an efficient way. The smart betas can give you exposure to factors. And of course, some smart beta products are of course, better than others. And it’s again, very good for listeners today. If we would’ve had this talk 10 or 20 years ago, then your final question, what can they do with it? Trading would’ve been more expensive, smart beta ETFs wouldn’t be there or mutual funds.

Pim van Vliet (49:06):

And now, it’s really a rich offering and also very competitive. That means that the best quant strategies and the best factor based products are available to anyone, especially in the US. And that’s I think good news, Rebecca.

Rebecca Hotsko (49:21):

Well, thank you so much, Pim. I want to be mindful of your time today. We covered so much. Before we close out the episode, where can the audience go to connect with you, learn more about you, your work and everything you do?

Pim van Vliet (49:36):

One way is through LinkedIn. You can follow me there. Then I’m on Twitter called @paradoxinvestor and the paradox of how can this be, these high alphas? And also, we’ve got a website to the book it’s also called paradoxinvesting.com. If you’re native in German, we also five translations in other languages, including Chinese. That’s multiple language availability. I also speak multiple languages. If you reach out in English, German, Dutch, well, it’s all fine.

Rebecca Hotsko (50:07):

Perfect. Thank you so much again, Pim.

Pim van Vliet (50:09):

It was my pleasure.

Rebecca Hotsko (50:13):

All right. I hope you enjoyed today’s episode. Make sure to subscribe to the show on your favorite podcast app so that you never miss a new episode. And if you’ve been enjoying the podcast, I’d really appreciate it if you left us a rating or a review. This really helps support us and is the best way to help new people discover the show.

Rebecca Hotsko (50:31):

And if you haven’t already, be sure to check out our website, theinvestorspodcast.com. There’s a ton of useful educational resources on there, as well as our TIP finance tool, which is a great tool to help you manage your own stock portfolio. And with that, I will see you again next time.

Outro (50:49):

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Outro (51:04):

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