Harin de Silva on Portfolio Management (Podcast)

does and doesn't work and when and why. I find a lot of quants tend to be UM a little more singularly focused, and he's a pretty broad based, holistic sort of guy. He He's quite a fascinating background and really interesting set of hobbies. UM. So, with no further ado my conversation with Wells Fargoes horind Da Silva. This is Mesters in Business with Very Reholts on Bloomberg Radio.

My special guest this week is Horirenda Silva. He is a leader and portfolio manager at the Analytic Investors Group of Wells Fargo Asset Management. His team runs a variety of quantitative strategies with assets of over twenty billion dollars. Harin is known as a pioneer in both low volatility and factor based investing. He has won numerous awards, including multiple CFA Institute, Graham and Dot Awards, as well as multiple Bernstein Fabosi Awards from institutional investor Harendra da Silva.

Welcome to Bloomberg. Thanks to having me on, Barry. I had to chat with you. Yep. I've been looking forward to talking to you because you have such an interesting background and your career has taken so many interesting paths. Tell us about your life a bit. How did you get into the financial services business? How do you go from Sri Lanka to UC Irvine. Well, apart from watching that episode of The Graduate as a kid, we had the advice to the guy who was go West young

man um that was kind of the original inspiration. But I really you know, growing up in Sri Lanka, it was traditional for people to go to school or the university in the UK. And so I studied as an engineer undergrad and had the misfortune to graduate which was the height of a recession. And uh, you know, at the time, I had two choices. I could go onto

graduate school. Why could go back to Sri Lanka, and you know, Sri Lanka was in the middle of a civil war at the time, so the choice was not difficult, and I made the decision to go to graduate school at the University of Rochester to study finance. And I was interested in finance because I saw a lot of similarities between finance and engineering, which was, you know, the ability to kind of design products, design strategies, and the idea that you could build something and actually put it

to the test really appealed to me. So that's why I initially went to the University of Rochester to study finance and study finance for several years and then started working for a consulting firm called Analysis Group, and I was had by another stroke of good fortune and got assigned to a project for Merrill Lynch in the mid eighties where we were taking managers to go into the Marylands Consults program and if you remember remember that program,

but it was one of the first rap programs. And so I was twenty five years old and I got to visit something like money managers in person. So you go to the money manager, you'd listen to their story and you try to capture in a quantitative way what

they were doing. And that's when I first got really kind of interested in factor investing because I realized that, you know, you go and talk to, for example, a bunch of growth managers, and talking to them, you realized that all the ones that were doing well at that particular time well focused on a particular factors, and not only were the growth focused then maybe for example, focused on earning the acceleration, and those were the guys who

are doing well at that time. And then you'd go talk to the value managers, for example, and you realize, well, the only ones that are doing really well are the ones who are f for example, divident deals. And that's when I realized, wow, you know, the factors actually explained a lot, and I kind of asked myself the question, which obviously wasn't related to the project I was working on.

Is it the manager or is it the factor. I'm hearing a parallel between what you described in your background with mechanical engineering and the ability to test that in the real world with factor investing and being able to quantify what's driving returns. Am I reading too much into that? Or is there some parallel there? No? I think there is a parallel. I think it's the same idea of

kind of what makes this work. And you know it maybe even a biased view because in an engineer, you think there's always there's a way to there's a formula, or there's a way to quantify something. So obviously if I had a history background, that would not think are you thinking was a manager or the process as opposed to something they were doing that was focusing on the factor. So I think the engineering aspect really kind of affected the way I looked at the problem. Very very interesting.

And some of the factors that you cover include not just the traditional factors um, but you spend a lot of time focusing on low volatility. Tell us a little bit why that factor is significant, what what are the

common elements in the factors that that you find intriguing. Well, that factor, to me was probably the one that was I call it the most neglected factor because I was working on my PhD thesis in the early nineties when Farmer and French came out with this paper that basically said, if you want to describe what they what academics kind of called the cross section of returns, In other words,

which stocks go up and which stocks to go. That value book to market and far Camp were very good at explaining it, and that data did a really poor job, and that high data stocks had the same return as low beata stocks. To me, everybody when they read the paper in nine two focused on, oh yeah, the value

premium and a small cap premium. And what I found really curious was, Wow, you can build a portfolio of Lottle better stocks that's going to have a way better returned risk profile than a portfolio of high data stocks or beta one portfolio. And I was really fascinated by why a no one focused on it, and most people

didn't think it was really that interesting. So what I call, you know, what's now referred to in our team as a low all anomaly is this idea that if you build a portfolio a little beata stocks, you get a much better shop ratio, a much better return risk ratio than the market portfolio. Translate that for the lady listener, what are loval what are low beta stocks? And how

do what is the significance of the sharp ratio? Typically a little bit of stock is what we mean by a little bit of stock is a stock that doesn't move a lot with the market moves in the mark, it will go up less in the market. It will go down less in the morning, go down less in the market exactly. And what if you put them in a portfolio. The portfolio obviously, if you buy a portfolio of a little bit of stocks and be it as a point eight, they'll actually move less than the market.

So portfolio will go up less in the market and go down lest in the market. But what it also means is that the because you're invested in equities, you get the equity of risk premium. So the long run return of equities with a lot less volatility so on a risk of the dropacious, it's better than traditional portfolios, right right. And what the Farmer, all the work the Farmer and French did showed was that low beta stocks have actually the same return over the very long run

as HIGHBERDA stocks or better one stocks. And what's really fascinating is if you look at a little bit of stocks. You know, when you first tell people, they tell you, oh, yeah, a little bit of stock. Oh yeah, that's just that's Amazon. Sorry, that's that's electric utility, And you go no, no, no, no, that's not electric utilities. A little bit of stock is

the stock that doesn't move with the market. So early on in its cycle, Amazon was indeed a little bit of stock because what was driving it was this idiot think credit returned related to doing business in a very unusual way. As the company evolved, it became increasingly a Beta one stock, and now it's a bet at one point to one point three stock because it's a very, very large cap company. It's the very large component of

the economy, and it's no longer very geosyncratic Richard. So if you look at our portfolios very you find that companies like that are now very high data. For example, even Tesler was actually in a little bit of portfolio four years ago. It's no longer in a little bit of portfolio because it's megacap and it moves so much

with the market. But when people think of a little bit of portfolios, you know, the other thing you see often in a little bit of portfolios that you've got to be very careful with is biotech companies, right, because the biotech company will often have two or three patterns, and it's going through a process for regulatory approval after the drug, so it's not really moving. The moving in the market at all, So stuff like that very often

you see those in a little bit of portfolios. So it really is kind of it's kind of fascinating to to watch this and if you look at sectors, for example, spent more of my life studying this anomaly and anything else. But if you look in the sixties, energy was low BEATA. Nobody really cared about it. It was almost utility. Went through the oil crisis in the seventies, it became very high data because it was the fact it sort of

started moving the market. Through the seventies and eighties, oil companies were very HIGHBATA, you know, when the market was dominated by the Seven Sisters. Then it became LOWBATA, and as we went through this last crisis with energy consumption falling, they became high BEATA once again. So it really is sounding a little bit geek like, but it's fascinating to watch the evolution of companies and industries because it's not as simple as oh yeah, a little bit of stocks

are different paying utilities. So let's talk a little bit about factor investing, and in general, we've seen many factors significantly underperformed over the past decade. Why is that? What are your thoughts here, Well, when you say factors under perform, you know you're saying the return to the factor was not the expected. Sign is that the well, you know, the granddaddy of underperformance. The past decade has been value versus growth, but there has been some other factor surprises

to the downside. I guess um when when we had the big blow up in in volatility a couple of years ago, that seemed to affect some factor performance and small cap has dramatically lagged for for quite a while. It's starting to catch up over the past year, but

the past decade was not kind two small caps. When you look at the world of factors, and I know there are many, many more factors than just you know, the three or six that most people are familiar with, how do you look at what's doing well, what's doing poorly? And how do you contextualize that? Yes, so I really look at it from two dimensions. One is the does the factor matter? Right? So does the factor describe what's

going on in the market? And when I mean by describe, if you look at the factor, can I tell you whether a group of stocks either out performing on the performing? So that to me the sign doesn't really matter when in the first dimension is is this factor meaningful? So just to pick up, you know, a random factor. You could pick a factor as where the name of the

company is in the alphabet, right, that's a factor. You'll find that that study is actually completely useless in explaining whether a group of stocks went up or down, right, because it's just random. On the other hand, small camp as you mentioned, is actually really useful in terms of people are running away from risk. Usually small cap companies do really poorly if they're running towards risk, as they've done a little bit in the last three to six months.

Small cap companies really generally do well. The correlation isn't one, but generally, regardless of the environment, there is a difference in performance in large cap companies with the small cap companies, and the same versus value the same in sort of

quality related factors. Now, the expectation that people form on these factors is they look at the long run return, you know, whether it's from a Farmer French study or elsewhere, and then they say, wow, you know, this factor on average has been positive, so I expected to be positive going forward, And that I think is one of the misunderstandings with factor investing because you know when you when you pace the quantitative back, the first thing that goes

through my head is what's the hit rate? Right? Because when I when I tell you something is going to outperform, the first thing you need to be doing, is an investor, is to say, Okay, how often is that going to happen. My conjecture is that even the best factors will outperform six or seven out of out of ten times. So you can think of that in meaning it's going to miss three or four out of ten times. Yeah, so

the underperformed three or four at ten times. So you think of a coin, if you have a sixty percent chance of winning, you can get a bunch of classes in a row even with a sixty percent chance of winning. So so the degree under performance and the length of

periods and the performance can be really, really long. And that I think has not been adequately communicated to people who are investing in these strategies because the other things is factors of momentum, and this is only recently coming to the four where people are talking about it, and this is something so you're not let me interrupt you a second or and you're you're not talking about momentum itself as a factor. You're talking about the momentum of

other factors impacting that factor exactly. And I think that is probably probably one of the most least appreciated things in investing, and it's something to be really really aware of. And I noticed this when I first got into investing, because I look at these investment firms and you know, they'd look growing like gangbasters because their performance was great. You know, the head of the firm was viewed as

a genius. And I look at it really closely as a you know, ex engineer, and go, it's not what's blading up on this one and this factor with its earnings acceleration or undeliveraged companies, whatever. The fact is that's been in favor for the last five years, and as long as it's in favor, they're going to do really, really well. And then suddenly the factor starts under performing and the managers say, as well, you know, my style is out of favor, but it's going to come back.

So cynically, you know, if you're an investor, you know this right, because if you're doing well, you're a genius. But if you're doing coolly your styles out of favor. Um, it's an asymmetrical bet. Yeah, it's an asymmetrical bet. So beyond momentum, factors have persistence that tends to continue to exist. Are some factors more persistent than others that we can to really get into wonky geek territory here, But how

consistent does persistence apply to different factors? Is it similar or or some factors do they tend to enjoy that momentum for longer periods than other factors. It's remarkably consistent. I mean I in all the work I've done, the work, the time and effort I put into modeling each factor individually has not been fruitful. What I see very consistently is that factors tend to the factors that I worked

in the last year tend to continue to work. The ones that have worked in the last two to three years, they tend to work well, but a little less. So. The persistence is very strong over one year, less strong over two to three years. And then after three years you actually start to see some mini version. When you look at manager cycles, you will really really stop saying that, but I mean they managed cycles. Is the tendency for

certain types of managers to perform. And so I think when you're when you're thinking about factor investing, it's really important to actually weigh the factors that have been working well, not only recently, but also think about the mean reversion factor. Right, So if you think about, you know, value factors right now, right now, it's kind of a nice time for value right because the last six months have been very strong.

So the fact that has momentum not great momentum because it's only been strong for three to four months, maybe six months, but the mean reversion aspect of it is actually quite strong. So what's really fascinating about this? When I first started running money using this tract of momentum approach, I was doing it for a uh the US client using US stocks, and it was a client was based out of Japan, and they came to me and said, hey,

what this work in Japan? And you know, being the typical quant, I said, yeah, well, let me check, right, So I collected all this data in Japan and I found that the same fact exists for Japanese stocks that you see this same factor momentum and then you know, subsequently repested it in in emerging markets and in Europe and you see the same. So I think what you're seeing is really and you can depending on which camp you fall into. I dated the economic cycle. Oh, it's

just human behavior, right. If you think about the way our decision making process sense to work, is we tend to like things, so we tend to focus on things that are work recently. So that recentcly bias, I think, is there in the way we buy stocks and the way we think of fads coming in and out of favor, and that's what's driving That's what something you need to take into account when you're tractor investing, because I think the idea that yeah, value work, small cap works, quality works.

So you take these you know, five words, six factor tilts, and you're going to beat the market regardless of what happens. Well, that's going to work if you have a very long or a reason. But if those factors out of favor for the last three years, you're in for a little bit of pain for the next two or three years. So Horne, let's talk a little bit about the idea of managers expressing their philosophy in their portfolio. I I can't help but think that you're a part lo val,

part value sort of quant. Is that a fair just ryption? Yeah, I would say it's it's part global active quant active quant because I really think, I mean, love all is an anomaly. But as a manager, you can express a lot more views than just having a low Boll view in the portfolio. I want to talk to you about some of the funds you guys specifically manage, but before I do, I have to ask you a question. What

is the fundamental law of active management? Well, that is actually a formula, and the idea behind the formula is that you can relate your investing success to really three things. So if you think about investing in US lodge cap stocks, the first thing that's going to matter for you in terms of your relative success of investing is how big

your universe is, so what we call brand. The second is your bill lead forecast, which is as a quant, measured by the correlation between your predictions and what actually happens. The quants called that your information coefficient, how much information you have. And then the third thing is how effectively you transfer your information into your portfolio, So you overweight the stocks you like, and are you underweight the stocks don't like. And that's what quants referred to as the

transfer coefficient. So the three decisions that are the three inputs to determining your success is one is how big the universe? You know, what the breadth of your investment decisions. The second is how well are you forecasting? And the third is how effectively are you transferring all your information into the portfolio? The transfer coefficient, and that's a formula that was very useful when you think about how much

our performance you can get from a portfolio. And it's a formula that my colleagues Steve Sali and Roger Clark and I developed um in the nineties and then published a paper in the two thousand timeframe. That's where that question came from. So now let's talk about some of the specific funds that that you manage over at Wells Fargo, starting with the Global Dividends Opportunity Funds. From the name, I'm going to guess that it is both global and

dividend focused. Um, what do we make of the trend of falling dividends at least here in the US over the past call it a few decades, Yeah, I mean that's been kind of a corporate trend right because of the tendency to have buy back as a methodology forgive beturning money to to shareholders. So I mean it's a challenge from a form divid and focused strategy in that particular portfolio. The other thing we do is use covered calls. So Analytic got it start as a firm in doing

covered call strategies. So we actually use a vault of the forecasting model to identify overvalue call options and then use that to generate additional income for the portfolio. Interesting, it's a little bit unusual, but this is typical quant approach in that you're not just using one way to generate income. You're using dividends as well as covered calls

as a way to generate income for the portfolio. So historically, covered call writing was always a challenge because you're balancing, um, the risk of a stock that's working out getting cold away versus the versus the income you get from selling the calls. I'm going to assume giving your background and low vall that um you managed to offset that because you're going to have a lower beta group of names.

They're they're less likely to get called away when the stock starts to run up or I should say less likely to run up and therefore have the stock called away. Yeah, so that I mean that portfolio is team managed, so it's actually uses some of the other skills within Wells frougu as well, So we're not the only manager. So we just manage the option portflio. And the reason the way we avoid the stop getting called away is by

using index calls. Because if you use the index calls, all you're susceptible to the market run up, not the individual stocks themselves going up, right, right, you still run the risk of having to buy in to replace the the the underlying right well, the underlying wouldn't get called away because you're selling the calls on the SMPI index very example, so you would have to be you'd be on the hook for the payment. But the key with call writing that most people don't think about is you

have to have a way to value the call. Right, So if volatility is over priced, you know, as it was at the start of this year, for example, that's a great time to be selling calls. Then you're getting

paid for exactly getting paid for the risk. But having a call writing strategy where you're always selling the same call that is usually not going to be as successful as something that is actually constantly looking at you know, one month, two month, three month horizon and different strikes and trying to figure out where's the most amount of

miss pricing coming in the marketplace. Now, for example, as we are in sitting here in you know, in the and the may longer dated calls actually more miss priced than shot it calls. So you really need to be thinking about increasing the tenor of your call if you're in a call writing strategy. Very very interesting. What about the Low Volatility US Equity Fund? What what's the philosophy behind that? So that's a fairly vanilla fund um from if you think about everything that we do, because it's

long US stock. The idea is to have a bottlatility of about seventy percent of the equity market and and a similar return. The fund itself is new, but we've run that strategy now since the early two thousands. So it's you know, I'm going to show my age because it's I've been involved with that type of for sixteen years and we're building a portfolio that has that has a low beta, so the average beata for all the stocks in the portfolio is around point six point seven.

But at the same time, we're tilting towards the characteristics that are in favor. So if you look at the portfolio right now, you'll see that it has a very big loading on price to sales as a characteristic. That's a factor that has really really been rewarded in the marketplace. Investors are really focusing on that right now. Trading earnings is not useful as because any trailings earnings number contains the pandemic. So using forward looking numbers like forward pe

price to sales are really really important. Asset turnover is a factor that is really important right now as well, so you'll see a lot of stocks with high asset turnover um in that portfolio. So we tend to look at a very broad range of factors, not just sort of you know, value, growth, quality, small cap, but really kind of try to capture the pross section of factors that fundamental investors look at. Let's talk a little bit

about where we are in this market cycle today. Do you look at us as sort of late cycle or was last year a reset and this is a relatively young market, or do you not care about any of those things I do care um from the perspective of looking at things in a historical context, because that's often a kind of a useful guide as you're trying to figure out which factors too blobal weight and underweight, and

you know, does it make sense? And I would say, given the way factors are behaving right now, it's much more of a really early cycle. There's a huge focus on in the US and globally on estimate revisions. So stocks with high being revised upwards are doing incredibly well, so people are really focused on that as a factor. Small cap is doing well, Low price to sales stocks are doing well. Those are all that associated early in

the fact in the cycle. If you look at interest rate sensitivity as a factor, you know that is something really people are really focused on because there's concerned that there's going to be a rise in rates. And you should think about equities having duration. Most people don't, but equities do have duration, and different equities have different types of different levels of duration. So that's a measure managing newport fill. So when you say duration, harand let me

interrupt yourself. When you say duration, most people think in terms of fixed income and bonds is having a duration. Hey, this is a ten year bond, of twenty year bond and nine bond, what have you. What does duration mean when it comes to equity. I'm assuming there's some sensitivity to changes in interest rate policy. What do you mean by duration, he said to me. The duration of a stock is how sensitive a stock is in the tenure yield.

So if it's insitive, then you'll see that it's it's insensitive. You'll see that it's not affected by changes in rates. And you know, when you look at individual companies, it's really fascinating. You stop. When you look at them carefully from that perspective, you'll see that some companies, for example, have a lot of floating rate debt, so as rates rise there interest payments are going to rise. So those companies tend to be more interest rate sensitive than others. Huh,

that's really that's really interesting. So much has happened since you started in the industry today. What do you think are the biggest differences in asset management relative to years ago or so? Well, there's a lot been a lot of good developments, I think, you know, on the positive side, um fees have come down, the trading costs have come down, so your ability to trade a portfolio mo uh, you know, to have higher turnover to capture factor rotation. That's become

a lot easier. The costs of data um have come down, but at the same time, the amount of data available for purchase has gone up. So if you look at us as a group as a team, you know our data costs is millions, but it seems to always go up, not come down. What are your thoughts on some of these alternative data sources. I know people are buying satellite data where you can see movement of tankers and ships that are I've even seen some people say we could tell how loaded the ship is by how low it

sits in the water relative to its waterline. Do you do you have anything it's on these alternative data sources? Yeah, I think those that type of data is really useful in terms of updating your earnings estimate forecasts, because that's ultimately what it comes down to. The challenge with that data is that it's really really time sensitive. So when I think of data quality, I'm always trying to think about what horizon do I need to invest with to

actually use that. Now that's really useful for me in a short run trading model. But that's not the sweet spot for from our size because we can't turn those portfolios over enough to capture that. So I I prefer data, for example that looks at you know, um. Just to pick up example of something I'm working on now, is what's the carbon footprint of a company and how can it be measured? Right? Because we know the cost of emitting carbon is going to go up in the future.

That's going to be a big factor in the profitability of companies and their behavior, and they need to invest in terms of new plants, encuipment. So what data can be used to capture that. That's kind of a moment intermediate, long horizon factor. And the more data I can collect on that dimension, the better if I am. But it doesn't rely on me getting to some information quicker than somebody else and the information kind of dying at the next learnings announcement that you know that makes a lot

of sense. In fact, since you mentioned low carbon I'm going to jump ahead to another question. What are your thoughts on E s G. On environmental, social and corporate governance as potential factors. I've I've heard people describe them as risk screens. What do you think of E s G. I think they're really important as risk screens. I think if you what we've found is that if you use E s G related factors actually incredibly important in describing

the future return volatil the of a start. The thing that's most important is governance, and you'll find that companies with poor governance the returns are very very fat tailed and as a portfolio manager, you need to account for that because most risk models missed that. Right, a poorly government company has a significant chance of a really negative return, but it doesn't happen very often. It will happen once

every fifteen years, once every thirty years. So in a typical risk model it actually doesn't show up, but it does show up if you look at you know, long time series of data and beef. I find these E s G factors are really really important in risk forecasting.

They're not useful in return forecasting because I think you can make the case that people like these stocks or the like these stocks for other reasons, you know, just like you have people like since some people like sin stocks, right, that's where there's a sin stock etf um So I think the return aspect for me, is less important than the volatility aspect. Huh. That's really interesting. It's it's sort of the Charlie Manger approach, which is, don't be more smart,

be less stupid. In other words, and I love phrases it, but you're you're looking to screen out potential disasters with E s G rather than screen in additional alpha. Right. That's to me, that's exactly the way to think about because these companies have something in their behavior where there's going to be a chance that they have a bad

outcome in the next twenty years. Right. But if you have a portfolio of poorly government companies and suppose you have a hundred stocks in them, there's a significant chance that one of them is going to have a bad outcome next year. So that they is a really key dimension in using E s G in a portfolio because

most people think don't think about it that way. But I found that with D s G factors, and increasingly with environmental factors like carbon or water pollution, or you know, even something is like plastics, the company's plastic emissions, is there a way to measure that and quantify and incorporate in the portfolio Because that's increasingly going to be something that investors care about and something that the company will have to care about in the way people assess their

future profitability. That's really that's really kind of kind of intriguing. So so here we are, the economy is just starting to reopen. People are more concerned with inflation than they are with unemployment. It's means, what factors do you see really taking advantage of the post COVID reopening, anything stand out in particular, and what do you think is um the wrong factor for this phase of the recovery. Well, I would stay away from anything that uses recent accounting data.

So just to just to give you something tangible, you know, people focus on things like r o E and r o A right return on equity return and affect those numbers are really have been affected by the company's performance in COVID. So that's those are factors I would focus on. I mentioned trailing learning zeal as a fact that you should not look at, so that anything that uses trailing

accounting data you've got to stay away from. But if you want to look at the valuation, which I think there's a lot of evaluation factors that are you should be looking at looking at the ratio of price to sales is a really excellent factor right now given where we are in the cycle. Staying away from companies with a lot of debt, especially debt that is floating rate as opposed to fix rate, is something that's that you should be looking at doing. Going towards companies that have

high operating margins in terms of their business model. That's a little bit difficult to do because of the accounting data problem for the last year. Uh, that's something that you should be incorporating into your portfolio. And the other thing that I would really emphasize in the current cycle because of the change we're seeing in the way companies do business, is staying away from companies where there's a

lot of disagreements about their future earnings. So one thing people don't have attention to is looking at analyst dispersion.

So if you look at an earnings forecast, everybody looks at the mean, but you should also look at is look at the difference between the high and the lower or the spread between analysts, because whenever they has a big spread, that means there's a lot of disagreement as to the future profitability of the company, and that factor is something that's going to be really important in this stage of the cycle. Really interesting. I have one curveball question to h to throw at you. Um, what sort

of motorcycle do you like to ride? Oh? My goodness, how much time do you have? Well I did read that you have bite pretty much all over the world. How much of an exaggeration is that? Uh? No, that that that is true. I mean motorcycle is reatively speaking, are cheap. Um. And one of my hobbies is exploring the world on a motorcycle. So I like to keep bikes at different out of the world. I can you know, I can show up, I leave my clothes on the

bike and can hop on and ride. But my my daily rider, because I ride to work, is an electric Hollie Davidson, which is actually a wonderful bike. It's a called Hallie Davidson Live Wire. Um. It's quiet, it's fast, um. And when I leave early morning for work, I don't disturb my neighbors. Um. And we have so solar panels at home so it doesn't cost me anything to run. Um. My favorite bike to ride on the weekends is to have an obscure Italian bike called the bi motor, the Due,

which is a two stroke, very light sport bike. And then my favorite bike for touring is you know BMWs because you can get them service anywhere in the world, and there it's almost like a train. They almost never takedown, right, They're big, they're solid, they're comfortable, and they could go on and on and on. Do you find I asked this question as a kid who used to write dirt bikes and and some of the smaller one fifties do you find like traffic is so heavy these days and

people are just not paying attention. It's a little more challenging to to be on a motorcycle. There is considerably more distracted driving um in southern California. Actually, in California, it's legal to filter or split lanes, So when you're driving down the middle of lanes, what you'll often see is the you know, the person next to you and

driving a car has their phone in their lap. And I don't know why, there's a tendency if you're look if you're texting, you always put the phone in your lap and then you look down away from where you're driving and you text, and I see that probably you know the time in the in the morning, so that it is a hazard that one has to deal with, and it does make it um so that usually when I get to work in the morning, I'm really awake because my adrenaline is flowing to see, to say the

very least, And you have a trip planned later for parts of Asia. Where are you heading to this year? Well, this is actually a continuation of a trip that was got canceled last year because of COVID. So last year I left the motorcycle. I was writing in Riga in Latviere, and I'm writing this year. The plan is to write from Riga to Saint Petersburg to Moscow and then next year to ride from Moscow all the way to the east coast of Russia to Ladivostok, which is right next

to Tokyo. Right, I've never been to Moscow, but St. Petersburg is an amazing city and you can spend weeks there. It's just an unbelievable amount of things to see and do. Yeah, I'm really looking forward to that. I've put lots of wonderful things about that city. All right, So I know I only have you for a couple more minutes. Let's jump to our favorite questions that we ask all of our guests, starting with what are you streaming these days?

Give us some of your favorite Netflix, Amazon Prime podcast entertainment. So I'm I'm going to be a disappointment on that dimension because I don't think I watched Netflix in over a year, so I'm not. I didn't grow up with televisions in Sri Lanka or Scream, so I'm I'm almost never watched them. Well, all right, listen, I would be more productive if I wasn't if I wasn't watching. I'm a big reader. I mean I read more, I more than anybody else I know, so I'm probably got the

world's biggest Amazon books built. So so let me let me jump to that question. Then tell us about some of your favorite books. What if some are your all time favorites, and what are you reading now? Well, what I'm reading now? There's two books that I'm really enjoying. One is called The Well Gardened Mind, m Um. It's a book on how gardening and nature affects the way we think. And this book, I think, to an investor is really fascinating because it talks about how you exposure

to nature affects your decision making. So if we take two people, for example, or two groups of students and they're about to take the exam, one of them books through an urban environment, are the group box to an arboretum, so they exposed to nature. The one that boxer an arboretum will have higher test case. And that's because of

something that's called attention restoration. Because we are also focused in such short time periods now that after a while we get attention fatigue, so you have to figure out where to restore that. And if you're involved in trading or building portfolios, this is something that that's really really critical.

So this book is a really fascinating book from st from that standpoint, because I think, especially in the COVID environment, we're all working longer hours and you have to figure out a way to restore your attention during the day. And that's kind of one of the big things that got out of this book. Um. But the other book

I'm reading is I'm a I'm a total Formula one fanatic. Um. I'm reading this book by one of my favorite designers, Adrian Newey, and he wrote a book last year called How How to Build a Car and Adrian Nui, I think is one of the b he's the design of a red bull. If we didn't know, but he's one of the best card designers ever to go through Formula one.

And the book goes through his designed philosophy and how his philosophy evolved over time and all the different cars that he designed, but it also decided describes his career. And you know, if most people don't realize it, but Adrian was, you know, one of the key partners that Williams, which is now one of the worst Formula one teams, and it was a disagreement with the owners of the

company that left him. They do him leaving, So if not for that disagreement, Williams would probably be continue to be the number one team in UH in Formula one. So it kind of highlights to me one of the importance of realizing that teams are really important to a business and if you let key team members go UH, that's going to have a big impact on your business.

So there is a really strong tide of how to build an effective team in a very high performance environment in this book Give us Another the last one m The most other book I read more recently, which is a little more academic, is annoyed. Sure, yeah, and I think you've talked about that. I think I've seen that

in your podcast. Um. The other one that I really liked that I read recently was actually by one of the people who was one of the founders of Analytic, were involved in its founding, which is a book called A Man for All Markets. Sure, and I think it's a book that anybody going into quantity financial really by at Top was definitely one of the smart st guys I've ever met, UM, and so that I really really

enjoyed reading. UM. So, I you know, pretty pretty wide array, but I'm really fascinated by this interaction between the how, what what we have faced with effects our decision making. And another book I read recently that I really liked is called The Nature of Fear about Survival Lessons in the while that's how we what happens to us when we are fearful, because if we think about investors, you know, one of the issues that's happened is with for one case,

and people having to manage their own portfolios. I don't think people realize how they're environment affects their decision making, and that's why it's really important to show kind of average investor investing, you know, having exposure in for one case, not to make decisions very often. You know, generally they say look at it once a year. But also realize what type of mood you're in when you're making that decisions.

And I think that's really underappreciated. To make sure that you're not in a fearful state or what can cause you to be in a fearful state when you look at that. So you know, do some all things like download your statement, look at it, you know, wait a month, then make the decision, but don't be in a hurry and allow yourself time to think about the decision you're

going to make getting put on the decision. But you know, if I can think about this team, it's this broader team of thinking about how your state of mind affects your decision and how can you manage your state of mind? Really interesting. Tell us about any mentors you might have had, who who helps guide your career. I was pretty lucky, I think when I went to the University of Rochester.

So there was a gentleman by the name of Paul McAvoy who was the dean of the Business school, and I was making a living at the time, you know, in addition to going to school programming, and he hired me as a programmer for some research projects. And Paul was a very well known economist. He was on the

President's Council of Economic Advisors. So working with them, I really learned that kind of think about how to sell problems, but also think about applying economics mhm, you know, much broader context than major policy or interest rate policy, and thinking about you know, the whole Kansian world of animal spirits and how they affect markets. So that was he was probably I think one of the most instrumental people to me. Uh. And then also Shin Kasu, who was

the founder of Analytic. He was the head of the con department at the University of California at Irvine. It was very fortunate to work with him. And then also I would say the gentleman who was my PhD advisor and also kind of a well known figure in in finance, professor Robert Howgen, who wrote a book called The Inefficient

Market Hypothesis and the Incredible January Effects. A very very color a full character, but somebody was always willing to question markets and do unusual things to build portfolios in terms of using at the time large scale optimizers and building large scale factor models in the world where everybody in the eighties we were convinced that markets were perfectly etician,

and now we know that's not the case. To say the very least, what sort of advice would you give to a recent college grad who was interested in a

career in either factor investing or quantitative finance. I think the hardest thing in starting in the business right now is figuring out whether you're invest actually invests interested in investing all your interested in what you think is investing, because investing is really about doing research to figure out what's going on in the market and then figuring out way to exploit that for the benefit of your clients. Right it's not about frequent trading or moving faster than

somebody else. And what I find when I talk to younger people is they're really focused on trying to get an edge by getting this short run informational advantage, and that's not that's not sustainable. And you also can't use that to invest institutional money because people tend to have

longer horizons. So my piece of advice to them is understand what type of investing you're interested in, and whether you like doing that type of research, because the hardest thing about doing research is eight percent at the time, it's a dead end. So if you don't enjoy the journey, it can be really frustrating, right, I mean, think about it.

Think about it this way. You're souted like being a chef, but of the dishes you make taste absolutely horrible, for four out of five get sent back to the kitchen. Really really interesting, and in our final question, what do you know about the world of research and portfolio management today that you wish you knew back in the nineties when you were really first getting started. Without a doubt Bory. For me, it would be the impact of human eimations

and sentiments on markets. I think by the time I did not appreciate how much that mattered, and now I see that it matters a great degree. And I think something I worked very hard at is trying away to build a way to quantify that. But I didn't have an appreciation for how much emotion and people's attitude and sentiment matters in the way assets are price and I think that is not taught enough in schools. Huh. Really quite quite interesting. Thank you her In for being so

generous with your time. We have been speaking with horendraw to Silver. He is the leader of Wells Fargoes quantitative strategy group known as Analytic Investors. They manage over twenty billion dollars and assets. If you enjoy this conversation, well, be sure and check out all of our previous UH interviews. There are nearly four hundred of them, and you can find them at iTunes or Spotify or any of your

favorite podcast sites. We love your comments, feedback and suggestions right to us at m IB podcast at bloom Berg dot net. You can sign up from my daily reads at Reholts dot com. Check out my weekly column on Bloomberg dot com slash Opinion. Follow me on Twitter at rit Holts. I would be remiss if I did not thank the crack staff that helps put these conversations together each week. UH Tico val Bron is our project manager. Tim Harrow is my audio engineer. Michael Boyle is my producer.

Michael Batnick is my head of research. I'm Barry Ridholts. You're listening to Master's Business on Bloomberg Radio.