Gary Chropuvka on Financial Engineering (Podcast)

of the quantitative investment Strategies team. Ge Sam runs a ton of capital UH, and last year he moved over to world Quan, which in and of itself was spun out from Millennium Management in two thousand and seven. Millennium Management is another giant quantitative hedge funds, and World Quan runs a nice lug of capital for them. As innovative as so many different quantitative approaches are, World quant Is

really stands out. They're an unusual shop. They do a lot of really interesting things that read led by UM, a very a kind of clastic and brilliant founder and CEO UM And really this is just a very intriguing and fascinating conversation if you are at all interested in quantitative investing, understanding one of the key drivers of markets today or just to get a sense of what people with advanced computer and mathematical degrees think about UM, the

financial engineering that's taking place in the markets these days. You're going to find this to be a fascinating conversation. So, with no further ado, my interview of Gary Krapovka of World quant This is Mester's in Business with very Renaults on Bloomberg Radio. Our special guest this week is Gary Propovka. He is the president of World Quants, a highly regarded quantitative shop spun out of Millennium Management back in two thousand and seven. Gary has a BA in mathematics and

a master's degree in financial engineering from Colombia. He's also on the board of trustees of Rutgers University. Gary Kropovka, Welcome to Bloomberg. Thank you so much, Barry. Great to be here. So I'm I'm kind of fascinated by your background. You you spend time UM at the quantitative investment strategies co heading that at Goldman Sachs, and you have your financial engineering degree from Colombia. Any overlap with Emmanuel Derman,

you seem to have followed his footsteps. Yeah, I actually I think I predated Emmanuel Derman because I I was in the program when it first start bit back in the early two thousands. UM I did follow em Manuel, I guess to to Goldman facts UM. You know, after he had he was there, but separate paths, but there's

definitely a correlation among the two UM A share. I went to Columbia, you know, after I joined the quant group at Goldman UM, there was you know, looking looking around the space, there were a lot of folks with some pretty advanced degrees, and decided to try to marry the computer science as well as the engineering with some of the business side to uh, you know, to to be better trained in the in the quant field. So so you eventually become co head of quantitative Investment Strategies

at ge SAM. What what was that experience like? So, I would say I spent at over twenty years in the same group, and you know, I it really drove what I love about, you know, my job, which is fun dative investing. It's something that I have a huge passion for. I love, you know, dealing with data and

figuring out problems. And you know, there were certainly a lot of investment problems that we dealt with in that in that group, and you know, really compelled me to go and join World Quant for for you know, even

other opportunities. But you know, while I was at Goldman, did a number of different things on the research side, on the portfolio management side, on the product development side, the client side, and so had a had a host of experiences that I cherished, had a great experient, great time there, learned a ton and uh and now I'm here at the World Pants for the last roughly six months. So we're going to talk more about World Quant in a in a few minutes. Let's let's stick with the

big data you referenced at Goldman and elsewhere. You know, big data is almost a cliche these days. How is it used in quantitative investment? Yeah, I would say, you know, when I think about big data, and you know, it's a it's a large term. But I would say, you know, we're all consumers, not just in the investment or in the quant group, but this whole concept around big data

is affecting each and every one of our lives. We're all trying to have a have an information edge, We're trying to make better decisions, we're trying to you know, utilize as much data to make informed decisions of where we're spending our time, whether it's things like going on vacation or you know, figuring out where you what restaurant you want to go to. And so, you know, the world has moved beyond things like zag. It's um and

really trying to understand the idea. There's a lot of things that will provoke what you want to do or where you want to spend your time and where do you want to invest in. And so this whole concept of big data is really to take you know, anything and everything that may be applicable to a company and try to learn from it. And so, you know, there's just this massive amount every time we click on something, time we move, there's all this data that's being captured.

And really, you know, one of the great things about being a quantitative investor is that we have tools and techniques to take all this awesome amount of data which comes in many forms and I could touch on that, but it comes in many forms and convert that into some insight or some informational edge that helps us predict companies or particular asset class. So this whole concept of big data absolutely here to stay I'd say it's much

broader than the investing business. It's happening, you know, all of our lives. We're all sitting with you know, the phones in our pockets that have massive amounts of information and so really the goal of all this big data is to create an informational edge to know something that maybe somebody else doesn't or um in order to be able to leverage that in in pursuit of learning something else.

So give us, give us an example, how can you use a data set, uh, specifically to identify opportunities that other people that aren't looking at that data might miss. Sure, So I think there's there's tons of data out there that you know, one can glam that. We could take an example of, you know, looking through analyst reports and you know a lot of people read analysts reports, and so you know, things you can do is try to pick up on their sentiment and so how we're analysts

starting to change their mind about a particular company. You know, it is a pretty common example of you know, figuring out how you know, you can train a computer to read all of these words that some of these analysts

are putting together. UM. That might be one example, UM looking at you know, what's in the newspaper and trying to gauge sentiment around you know, what's popular and maybe what topics are interesting and what companies may be related to those topics, and or those topics trending positively or negatively.

Those are some examples of of ideas where you know there's something out there that you know not as company, may not be coming out of a company's financials, but it's something that's happening around the company that might be impactful. So you know, those are two examples of of items that you know you'd constitute as big data because you're looking at massive amount of whether it's research reports or news articles, to kind of get a gauge of can

I have a better picture of that company's fortunes? And I would say, you know, one of the things that we do at work Pond is you know, there's not just three ideas or five ideas. There's millions of ideas of ways to to navigate and have a view on a company, and big data forwards us the opportunity big data along with some you know, some great analytical tools to be able to kind of have views on particular companies. Huh, so so how does that play into things like smart

data or factor based approaches. Is that something that you can apply um large data sets towards identifying new variations on absolutely? And I think you're touching on an important component if we think about the quant industry, you know, really started with a lot of these kind of let's

call them smart betas or traditional measures of factors. So thinking about things like value or momentum, value being a cheap company relative to its book value as an example, momentum, So if the stock is starting to trend in a favorable direction, will it continue that particular trend? And so you know, the whole idea around analyzing all the data

you know as quants. For the original quants, you really wanted to play off the law of large numbers, and so you had a lot of a lot of data yet information on each and every company, thousands of companies, and you try to rank companies by these particular metrics price to book or some measure of momentum. And you'd create a portfolio around those kind of quote unquote smart datas.

And you know that tried and true works over time, and I think you know, as the industry is evolved, the smart data strategies, Um, there's now more interesting other ways of evolving and utilizing things like big data to be able to similarly look at those look at factors. So very similar to rank companies. So quants always want to play the breath game, meaning spread out their bets,

have a lot of different views on particular companies. But what the alternative data and big data allows us to do is really play the depth game, so know a lot more about a particular company as opposed to just their price to book. So you know, back to your

original question. The smart data strategies you know, which are largely common um implementable, absolutely use large amounts of data, um, you know in a pretty uh academically proven, you know, well thought out, but have been around for many decades. So one of the phrases I've been reading about is

variation and of that customized data. What what is comdomized data? Yeah, so it is an interesting topic customization, I would say when we think about when you think about customized data in the industry, Um, you know, there's there's really two things that are happening. One is, um, what types of i'll call it bets would you like to make? So you know, do you want to bet on value stocks, do you want to bet on companies that are um have higher dividend payers, And you're able to customize what

you want to place a wager on UM. The other part of the customization, which continues to be a pretty interesting trend in the industry, is there are certain E s G. Factors that one may want to hold near and dear and want to have companies in their portfolios that express their the beliefs that they, you know, have

and want to express. So for example, you know, I don't want to invest in tobacco stocks, or I don't want to invest in, you know, something that is going to negatively impact the environment, and so you can, you know, with quant tools, you can figure out, okay, what are those companies or how do they fall into those categories, whether it's an industry or the percentage of revenues that company is going to get from you know, let's say emissions UM and then be able to create a portfolio

to identify, you know, whether it's a factor bet around value or momentum and or um you know, different types of exposures that they want. So for example, things like tobacco or or emission, so you can customize the what your equity portfolio looks like relative to a benchmark or just an absolute. So let's talk a little bit about what you do at World Quants. What does the president

of the firm's jobs responsibility look like? Great barrier. Yes, So so as as president, which I'm extremely fortunate to have joined such an incredible team, you know, I'd say,

really three things that I focus on. You know, one is overall business strategy, help with the operating of the operating of the firm, and then add some leadership on the investing on the investing side, and it really that breaks down into kind of four key elements that you know, in terms of my role, and I work very closely with our CEO, Igor Tolchinsky, UM and really thinking about the following four things. One is vision, so you know,

where where should we be spending our time? I would say, interestingly, we've got you know, roughly all over six hundred quantitative people, and so you know, we feel like we could solve

a lot of interesting problems. UM. And really one of one of our jobs is to ensure that we're focusing on the right ones to solve and so you know, the you know, setting out that vision, UM, keeping people focused, UM, making sure that incentives are aligned, were allocating resources to tackling the right problems and and remaining focused on those types UM. Speed and one of the things that you know, in an organization that has over six people, you want

to make decisions quickly. UM Igory does a terrific job of you know, of of of leading in attempt to help him with that in terms of making decisions, making sure things escalate very quickly, UM, so that we can continue our focus and our vision. And then the last thing I spend a decent amount of time on is talent. And you know, how do we acquire talent? How do we promote a culture of collaboration? UM? Intellectual stimulation. You know a lot of quants in general, we like to

be intellectually stimulated. So how do we continue to do that and create a culture where ideas can be shared and collaborated across the firm? So those are those are where I've been spending my time over the last six months. What sort of programs do you have to incentivize your staff? Sure? So, so we have many different ways that we try to

incentivize our people. UM. In terms of the you know, what we do for our for our researchers, and so we have real different challenges that we have around around the world to you know, to to incentivize people's work.

And so, you know, that's just yet another piece of the puzzle where um, you know, we're trying to promote a particular activity or particular research and be able to, um, you know, incentivize them, call them out, reward them for uh, you know, for for doing some some really good work.

And so you know, we have many of these, and I think one of the unique things about this firm is that we have many different competitions where uh, you know, where people can our our teams can be incented to uh to do different things and to use their mind a little differently and have the right uh incentive structure to be able to to to be rewarded for those So so you're creating these um for lack of a better word, competitions internally to solve an investing problem or

equation or issue, and everyone who works in the firm can basically throw the hat in the ring and say this is the way I think we can solve this problem, and then you run the tests and figure out who's the winner on that or is it real time and hey, this is the best results based on your suggestion. Yes,

so we we did. You have we have several competitions around around the firm UM with you know, set incentives for each of them, and we kind of have a group of people that try to tackle this and instead of it being relative to others in the firm, they're we're saying, okay, here's a particular UM strategy that we want to spend some time on. Let's see what you

can develop UM. And so that's you know, that's an area where you know, we have projects that you might not fit into the core research that we do on a daily basis, but you know, maybe a little more um, you know, a little more out there. Maybe we're trying to look at a different asset class and we want

to uncover. So we realize, you know, the the upfront R and D or the research is going to take a little bit longer, and so we want to incentivize them to go out and um, you know, and really think creatively about about capturing and we incentivize them accordingly because they're taking time out of their kind of core to really push the envelope a little bit more in terms of um, you know, in terms of figuring out

something unique. One of the questions I was going to ask you is, hey, how is World quant differentiated from other firms? But but things like the accelerated platform, these sound somewhat different than what we typically hear about at a at a lot of shops. Are these common in the worlds of quant or is this a little more

unique to what you guys do? Yeah, I think I think, Um sometimes people may do this, um, you know, for you know, to try to recruit people, and I've heard of people doing that, but putting it as a systematic way, you know, internally, I think is something quite unique. I would say when we think about our you know, our group, and really one of the compelling opportunities that is I had when I when I thought of of joining and fortunate enough to join World Font is you know, we've

got over six people around the globe. We operate in twenty three offices thirteen countries. UM. So we've got unbelievable global diversity. And so I think that's you know, one thing that makes us UM quite unique. UM. So we operate in many different places we have many different opinions. UM. We've we've always promoted diversity, diversity of thought, UM, diversity

of alpha's or drivers of return when we invest. And so you know, having programs that can continue to incentivize people UM and really create a collaborative and you know, I would say competitive in a in a good way, UM, where where people continue to be intellectually stimulated. I think

that's really what you know, really drives the firm, the collaboration. UM. We just recently did a a research tour, a virtual research tour, and myself and Igo and a few other the senior folks kind of did a did a tour around and and you know, it's unbelievable when you know people can promote the collaboration they're sharing with us some of the research and the first thing they say is, I'd like to acknowledge the four or five people that

helped with this with this research project. And so you know, just the idea around true collaboration, true appreciation for where you're getting assistance from. You know, I think it was really makes makes this place a pretty unique, unique uh neque place to be. World Tom was spun out of Millennium by Igor Tolchinsky, who is the founder and CEO. Tell us a little bit about your boss. Yeah. So, so when I first met Igor Um, he's just so

intellectually stimulating. I mean, a brilliant, brilliant investor, brilliant man. Um. You know, extremely charitable. Um. Some of the things that he's done, UM. You know, so we are just a really spectacular and you can see a lot of those on the web. He's written some really interesting books and just his vision, his ability to articulate, um, you know where we're going, uh, and and and collaborate very well. Uh. To the other thing that is just very impressive is

his decision making. And I think I've observed a lot of quants over the years. You know, you kind of get into the analysis paralysis. UM. You know, the there's always another test you can run on something. You know, Igor to his credit, is a decision maker. UM. And it is. You know, it's just great to be able to partner with him for six months of the last six months and you know, look forward for for many

many years and decades to come. But he is, you know, someone who really does make decisions, takes in all the information um, and you know, has really built an unbelievable business. Uh here at will on. So when I normally speak to a firm and I say, hey, what's your firm's investment philosophy? Usually I get a sentence that sums everything up in in one nice little SoundBite. I get the sense that you're operating a whole lot of different approaches. It might be a little harder to pin you down

to one philosophy of of the firm. What is World Quants investment philosophy? So, so World World Plants investment philosophy is really, you know, pretty pretty simple global leverage our people and provide them the tools and technology two to make returns for our investors. I mean that's really you know, in a nutshell, you know what we're trying to do. Um. We we have a very systematic way in which we

do it. We try to leverage the law of large numbers and have millions of different alphas that we can leverage. We put them together in a portfolio and then we execute and make them a reality through trading. So, you know, the investment processes is quite simple and straightforward. But the uniqueness of our philosophy is that we are extremely global in terms of our people. Um, we do believe in

in playing the breath game. We have we have a lot of alpha's, a lot of ways to look at companies and we try to leverage that throughout our process and create portfolios that driver turned for our clients. So let's talk a little bit about the past year, which was some people have called it unprecedented. When you are crunching numbers to try and find a pattern, how can you deal with the possibility of events which have simply

never occurred before. Yeah, Berry, that's a terrific question. Um. You know, that really separates the you know, the quantz quote unquote and the quant investors. And so, you know, one of the things that makes our jobs so interesting, I find is the ability to adapt and really to to be market practitioners as well as as quants, and I think that really makes great quant investors. So, you know, if we think about two thousand twenty and also in two thousand twenty one thus far, you know we've seen

you know, obviously unprecedented events. Um. You know, whether it's around COVID or you know other types of you know of of events that that have happened over the last year, which which ramifications have caused very large moves in you know, kind of common let's call them factors or expressions or buckets of particular stocks or characteristics of stocks. You know, for example, you know, things like momentum we talked about

before value. UM, these have had some pretty unprecedented moves. UM. You know, there's been you know, for value, about fifteen UH standard standard aviation moves that are that we're above two in two thousand and UM. You know, one just massive moves. When you think about a simple five center deviation move means that that happens once one day every approximate fourteen thousand years. So to your point, there's been no shortage of massive moves UM, you know, largely because

there's been such a big shift. And so I think as quant investors, the way we try to approach it is to I is to adapt as quickly as we possibly can for some unforeseen event. Obviously we try to predict whatever we can in advance. UM. But to the extent UH you know you have something like uh COVID, you know, you want to think about companies that are going to be largely affected because of that, And there's

two approaches. One is you can try to risk manage, which is usually what we would do, which is, you know, listen, this is a once in a life time events. Let's try to immunize our portfolios from those. So, whether you know it's a it helps or hurt stocks, let's try to immunize ourselves. And the other is to say, okay, let's try to get a sense whether there's going to be some type of trend here or there's some you know, ability to to create alpha or some excess returns UM

when these events happen. So you know, you can think about binary events, so things like elections that have happened UM and what the ramifications are. You can think about things like trade UM. You could think about companies exposure to you know, things like bitcoin when they announce and what do you do about it? And so, you know,

we think about the world in characteristics. So we call them factors, and so you can create these quote unquote factors and say I want to have a portfolio that whether those factors do well or poorly, I'm my portfolio will not be affected. So that's really the way we've We've thought about a lot of two thousand, twenty and twenty one and our investment team has just done a terrific job of being able to navigate that and identify

some of these risks that they haven't seen before. We try to codify it in a systematic way and then focus our attention on, you know, on really where we believe we can make money UM, and that's a lot of these millions of alphas that we believe have been contested for for years. So that's how we think about, you know, dealing with some of these unprecedented moves that we've seen in you know, things like short interest and momentum and value that have happened over the last twelve

months or so. Huh So. So I'm intrigued by the concept of of something UM that's so many standard deviations away from the norm that it's really a one in a fourteen thousand year events, those sort of tail risks. How can we anticipate them on a quantitative basis? And and more specifically, UM, think back to January six and the attempted insurrection in the US capital. How can you

quantify that? And we've learned since that that actually came pretty close to I don't know if I would call it successful, but but pretty close to having the rioters access UM, various people in Congress, maybe even the Vice president. How do you factor that into to your UM analyzes. Yes, as I would say, you know, I'll take it up a step in terms of just in general how we

think about it. But it's really about, you know, trying to identify things that will impact UM companies and you know, what are the ramifications and and I think that's really the way we try to think about that. So you know, in that specific case, in terms of what would happen to particular companies UM, you know, those those events are relatively UM you know, quick moves. We try to be

very diversified in many different ways. And you know, that's probably one of the first times I've used that term, but I would say the diversification point is so critical in investing UM, whether you're a quant investor or you're any type of investor. It's it's definitely an extremely helpful

UM attribute when you have events like this occur. And so you know, creating you know, different ways to look at risks UM as quickly as you possibly can, and adapting a portfolio, you know, we think leads to very successful outcomes in the long run. How did you guys look at what was taking place with things like Robin Hood and read it to me that was reminiscent of you know, late nineties action, although it certainly was faster and maybe more powerful than we've seen in the past.

How do you look at these sort of group behavior that that social networks can foster. Yeah, again we um so, I think we look at in terms of, you know, from a from a liquidity standpoint, what what are the know how is this affecting the amount of the amount of ability to trade our securities? Um? You know, we

really do try to minimize that I mentioned earlier. We try to minimize the amount of risk we take from any particular factor and things like you know, short interest is something that you know is a is a pretty common factor that you know, folks UM like us would would try to identify and minimize. Um. Are you know how much our our stocks will move because of that? UM, I'd say, you know, big picture thinking about liquidity, obviously, there there is a big retail you know, retail input

um to liquidity. They tend to you know, trade it trade you know, stocks that are that are relatively cheap in priced um. You know, and I think there's some you know, some pretty interesting data around that I would say, for you know, for our purposes. You know, we look at things like liquidity and depths of market and how

that's being impacted. And I would say, over the last twelve months, you know, interestingly that the world of market micro structure has gotten pretty complicated, you know, to the extent you could trade you could trade you know, ABC stock in forty different venues in the US is interesting enough, you know, across sixteen different exchanges, or roughly about sixteen different exchanges. And so you know, we spend a lot of our time looking at things like volumes and spreads

and and overall liquidity UM. And so that's really where we see um, you know, those effects. And I would say, you know, it looks like over the last twelve months it's been a pretty rocky um, you know, rocky area. But you know we're pretty much back to you know, kind of pre pandemic levels when I think about quote sizes, bid ask spreads, UM, you know for for SMP type names. So it looks like things are kind of getting a little bit back to normal in terms of of market liquidity,

depth and spreads. So you mentioned value earlier. I think this is up until this quarter. I think the underperformance of value versus growth, it could be the longest run we've seen of growth dominating value since since at least since the CRISP database goes back to nineteen seventeen or something like that. How do you think about something that's rather unusual in those terms. How does the FED factor into this or is that even an input to to

what you're building in your models. Yeah, no, it's it's it's exactly. It's very consistent with again thinking about it as a as a very diversified portfolio, and you know, value investing over the long term has done reasonably well. UM. I'm very impressed that you went back to the CRISP database, So kudos to you. UM. When I think about you value again, value on itself, we tend to take an approach where we want to be more diversified. We don't

want to just bet on value. We want to have things that have growth at tributes and really have some you know, we call it idiosyncratic or some specific type of return where we think that's our edge. And and in terms of other types of factors like value or

growth or low volatility. UM, those are something that we want to have a very modest amount of exposure or you know, we really don't want to We don't necessarily make a lot of money on that particular aspect because it's very common and it's also subject to very sharp moves, and so you know, we aim to have a little bit more consistent, persistent results. But to your point, you're right, this is it's been an unbelievable um challenge for Value.

We've we have seen a little bit of a turnaround, um, you know, since since the election, UM, and so you know, value that start us to do a little bit better. But your point is well taken, But I think it just speaks to our philosophy of you want to have, you know, many different ways of looking at the fortunes

of a company and diversification. Diversification, diversification is key and at World Plant we that with millions of alpha's, we have many different portfolio managers, many different ways of combining our alpha's, and so you know, we kind of live and breathe from diversifying of our people to our alpha's, to our portfolio managers, and then to our execution. So again, I think you know, your observation is spot on, and I would say we as a as a group try

not to take too many bets in one place. Huh. Interesting. You know you mentioned certain strategies are popular, and I can't help but think back to the um quant quake that took place about eight years ago, where a lot of quantitative strategies were very similar at different shops, and we saw what had become a fairly crowded trade. Maybe maybe it's a decade ago, it's even longer ago. What

what do you make of that crowded trades? Yeah, so so it was more than a decade ago, is you know if I think it was almost eight thirteen and a half years ago? Okay, I think I think there was a huge lesson learned for for Kuant investors. Um. I think it was a period where, uh, you know, there was you know, some some shops had a fair amount of complacency where they didn't continue to use their research.

There was more into there was you know, there there should have been a lot more pushing in terms of research and and I think you look back and you saw events that you know, for a number of reasons.

One is there was a fair amount of leverage in the system, and so you're able to amplify your returns with leverage UM and leverage is great if you're always going to have high, high positive returns, but when you don't, you know, leverages is a you know as a very big challenge because people call up and ask you for money and you need to pay them. So I think you know that that really was one of the biggest issues of of oh seven UM. But I'd also say

there was crowded traits, as you correctly point out. And so I think one of the goals that we have at World pant is continue to differentiate, continue to create unique ways of making money for our clients investing in our almost three hundred researchers, to try to continue to innovate and be much less crowded than other people. Again, we want to be unique. We don't want to be susceptible to those large movements in terms of those quote

unquote crowded trades. And that's really a huge goal and frankly was a big lesson learned for I believe the quand industry. UM that happens, you know, almost fourteen years ago. So let's talk a little bit about the future of quant investing. You mentioned previously that the industry has learned

from past mistakes. It's involved UM. Tell us a little bit about the direction the industry is in evolving towards, Sir Barry, I think the you know, the quand industry will continue to evolve in in places like data, in places like storage, in places like analytics, UM and the tools that are that one can use to try to, you know, figure out the fortunes of a company have increased exponentially, and so you know, the amount of data that's out there, amount of data that can be stored,

amount of data that can be analyzed, the simulations that one can run has grown, like I said, absolutely exponentially, and really for a quant investor, it's terrific because you know, the world is kind of coming in our direction. The amount of data. We think, you know, one of our edges to be able to take data, synthesize it and create information and drive returns. And you know, we think, here a world point, we're extremely well positioned to be

able to do that. And so, you know, honestly, I think it's a you know, it's an absolute golden age for us as Kuan investors UM in terms of kind of where the industry is evolving really interesting. Any of this evolution surprised you what what has taken place that um, either you didn't see coming, or you saw coming and didn't think would happen, and it happened anyway, right, I would tell you know, one of the surprises is is the adoption of you know, more and more quantitative investing

strategies in general. Um. Just given uh, everyday people's thoughts on you know, the use of computers and use of your phone to drive information, It's happening across most every industry. I guess I'm surprised, happily surprised that more and more kind of investment folks aren't employing more and more quantitative strategy. Good for us from where we sit, but I'm just surprised.

You know, I think everybody wants to you know, if you're at a dinner party, you're you're asked, you're getting asked a question, it's got to be empirically back that You're gonna look it up as quickly as you possibly can, and you want to test that there whatever someone said, whatever hypothesis, um, you know, and there's there's a lot of skeptics and they can be proven yea or nay very quickly. And I'm just you know, I guess I'm I'm surprised that that's not happening more and more in

the in the investment industry. So that would be one of the I would say, my my biggest surprises. But I'm but I'm okay with that. Huh. You mentioned earlier trying to read sentiment data from analysts reports. I've read about firms trying to actually scrape market wide sentiment data off of social networks like Twitter. What what does that

look like? And can you really find an investable edge from the characters of millions of people who know um relatively little, although they may not know that they know relatively little? What what signal is in all that noise? Sure, Marry, I think you're you're touching on a really important components. You think about all this alternative data, you know, it's it's what do you do with it? And and how

do you utilize it? And I think you know, a diversified approach of you using things like satellite images, using things like social media, um, you know, can be quite impactful, you know, some of which might be very very short run. Some of it might have more longer term ramifications, things like credit card transactions, web clicks. I mean, there's so much alternative data out there that you know, if you

can think about how best to utilize it. Again, it's that whole concept of marrying kind of technical acumen and so you understand data, you understand uh something about you know, putting data together to create some type of expected return, but also marrying that with some business acumen. You know,

I think is is really exploding. And so you know, whether it's social media, where it's at allite imaging, whether it's you know, clicking on you know, getting vendors that that provide some of this data all anonymized to be able to have a view of where company's fortunes maybe is certainly something that the industry is seeing. Um, there's

a massive amount of data vendors out there. There is some content validation and some of those data vendors, but there's a lot of data out there to be able to employ not just social media, but other types of of data that you know, can be informative of a company's fortunes. Yeah, I've been kind of fascinated by the satellite data and how granular it can get not just tracking ships carrying goods or oil around the world, but how deep the ships are sitting in the water. That

gives some insight as to how are they traveling? Full half full? Three corps. That's just astonishing stuff. Yeah, I mean it's it really is. And I think you know, listen, I think we all we all have our phones and and you know I could I could kindly tracked my kids on on Life three sixty and figuring out where they are. Um, you know this is happening. It's part of our everyday lives, um and uh. And you know

it's it could be insightful information. You know certainly helped me, you know, with my kids and and you know other parts, whether it's uh, you know, tankers or whether it's uh, you know, clicks. Uh. You know, these are insights that you know, can be you know, potentially telling. Again, I would go back to my other common about diversification. So in isolation, these you know, will you know almost for

certain will not work all the time. Um, But if there's some level of insight that you can gain from a piece of this data or a way to look at this data, and then you marry that with millions and millions of other things. You know, you can have a pretty good sense of that company's fortune. So you know, again it's it's really about diversification and not thinking about you know, these pieces of data in isolation. UM. You know, we had talked a little bit about value and other

types of factors. Again, I think you know, the approach that that one that most quants take UM is really to think about diversification um as as a really helpful way to produce UM you know, consistent results for clients. And I think that's really, you know, the key to how most wants and at World want you know, we think about diversification at pretty much every step of the way. But it's our people, whether it's the expected returns that we try to generate or portfolio managers and how we

go about executing and making that a reality. So you talked several times about how gigantic these data sets are and how fast they're growing, How how big can these get? And at what point do they become unmanageable? I mean, when is too much data too much? Yeah? UM, we certainly have not found that out yet. UM. You know, the nice thing about it is there's the amount of data, you know, is increasing exponentially. There's some unbelievable stats on

just that massive amount of growth UM. And I think, you know, frankly, we've spent an enormous amount of time figuring out how to take in that data, how to collate it, how to check that data. Um. You know, again it's the gory details of data, but it's um but it's fascinating. I know, I d C I d c UM. You know reported a quote them more than five billion consumers interact with data every day. Five billion

consumers interact with data every day. By they say that number will be six billion, or three quarters of the world's population. So data is getting created again exponentially. I think this is the thing that we spend a lot of time on is how do we ingest that, How do we come up with processes to be able to you know ingest it, how do we store it, how do we analyze it? Again? And that's that's really, uh, you know, one of our integral parts of what we do and how we do it. And you're seeing this

in the investment industry. You're seeing this in many different industries. But I think that's one of the exciting parts um, you know, and it's a lot of data. But again I think that's really you know, we've been waiting for these times for for a long time. To continue to have more and more data, it allows us a huge opportunity to drive an edge because we think we know what to do with that type of data. Um, to pair that with some of our you know, smart researchers

and figuring out what are the insights. So, you know, I think the other challenge that we face in terms of your comment about too much is again signal to noise? All right, What's what's a signal? Meaning what what gives you insight? And what's just noise? And so part of our jobs as researchers and portfolio managers, as good quants at worklan is is to kind of distinguish between the signal meaning does this have some value, does it provide me insight? Or is it really just noise and you know,

not really worthy of of of allocating any investment to it. Huh. Quite interesting. Let let me change gears on you a little bit. We recently heard rumblings about possible changes in tax policy coming out of the new administration. I know at Goldman, I know a gam You did a lot of work on UM tax efficiency from from your new perch. How do you think about things like tax efficiency in investing?

Is that something that's still within your bailiwick or or is it more institutional and you're you're less focused on tax Yeah, so, I mean the way we think about it, and I'm happy to spend some time on just generally

tax efficient investing. I think it is. It's you know, it's a very useful piece and I've had some prior experience in it, but more substantively on you know, kind of what we do now at work on you know, if there is a change to tax policy, we're gonna you know, figure out how it's going to impact a particular company. You know, our corporate tax is going to go up or down UM, and how will that impact you know, cash flow or you know something on on

a company's statements. UM. So that that's really how we would tackle it, and you know, we'll we'll understand how we should you know, update our accounting UM for for those types of events and adapt accordingly, like like you would expect most in sters to do. UM. You know, in the ray of tax efficient investing, you know, I'm happy to spend a few minutes there, but you know, we don't, uh, that's really not one of our core

focuses at world point. You're you're looking more as to how the changes in taxes impact either the bottom line for the companies or their position relative to their competitors UM and what the tax code means, uh to their valuation. Is that is that a fair description? Like, I know, you guys aren't tax loss harvesting the way a traditional UM advisor would. You're you're running a very different portfolio

for for a different audience. So your perspective is what does this mean to the companies that we may or may not own, and and how does it affect them relative to their competitors? Is that a fair statement? Yeah?

I think that's a that's a fair statement. Again, we want to see as as Biden you know, institutes new policies, how that will affect corporations and frank we that goes you know beyond you know, tax policy, other types of policies, and so you know, if there's international policies that will affect trade or or any type of you know of of things that come out of Washington or Frankly, any

any other government around the world. Given we are a global organization, you know, we're gonna attempt to take that into account, um, to try to understand it, understand what the ramifications are two companies and being able to position our portfolios accordingly. And that's that's you know, we do that whether it's a regulatory issue or an event that

we talked about again. Our ability to adapt and understand what's going on in markets, what's going to affect companies or particular asset classes is really you know, one of the fun parts of the job as being a quantitative investor. Huh, what what are other fun parts of the job? What what do you enjoy doing most? Um, as presidents of world want so, I will tell you I've had such

a great time of of walking out of meetings action steps. Uh, it's been you know, seeing seeing people intellectually stimulated around you know again where a lot of it is on zoom and so you know, we sit there and and just you know, watching how people dialogue has just been

you know, so incredibly exhilarating. Um. You know a lot of the great ideas and you know, watching how respectful people heard of each other and challenging them in in thoughtful ways and almost hearing them think, uh, you know right in real time. Is it's just been been incredible. Uh in terms of uh, you know, the the organization, it's it's just highly productive, highly collaborative. Um, there's just

a lot of great decision making that goes on. We just recently did a research off site where we just walked through and have many, many decisions. We pride ourselves that, you know, we're very action oriented, and so you know, that's been you know, some of the fun things that that I've been fortunate enough to uh, you know, to observe in my in my six months. Let me jump to my favorite questions that I asked all of my guests,

starting with what are you streaming these days? Give us your your favorite Netflix or Amazon Prime show or any podcast you might be listening to. What's keeping you entertained? Sure? Um, I would say been a fan of House of Cards. Um, My daughter and I watched Million Little Things. Um. Joe Rogan's interviews with Elon musk Are are pretty pretty impressive. And I would have to say, you know, one of my favorite videos is a four minute and thirteen second

Jason Garrett speeches. He talks about one World Trade Center. It's just it's an amazing video that you know, all my friends, uh get a text from me on a pretty regular basis, just just level sets. It's a great video. H really interesting. Uh tell us about your mentors who helped to shape your career. Sure, I would say my dad had unbelievable work ethic. Um it was a six day a week guy. Um. One of my my first bosses was was a guy named Gustic Conomos, who unfortunately

passed away at nine eleven. Um. But you know, was was was able to balance enormous credibility or industry credibility with a sense of humor. And uh, you know, us always used to tell me I may have taught you everything you know, but I didn't teach you everything I know. And I always always think that's a pretty funny, uh funny quote. But uh, you know, And and the last one I would say on the quant spaces two gentlemen

and Bob Jones and Don Mulvehill. Bob was the founder of the g Sam uh you know chront equity business back in the day, and you know, taught me a lot and really helped shape my career and my interest in quantitative investing. And then Don was you know, an age old colleague and boss of mine that really taught me a tremendous amount about UM investing, in dealing with clients and you know to too great early role models that I had had in the industry quite quite interesting.

Tell us about some books? What do you what are you some of your favorites and what are you reading right now? Sure? So, uh, some of my favorite especially since I had a decent amount of time between between taking on the role at at World quand UM. You know, I was able to read David Rubinstein's How to Lead, which I thought was just terrific. Um Sartin to Tella had the hit Refresh, which I thought was quite good.

I was also able to read our books from our CEO, who has two good ones, Finding Alpha's and The Unrules, So I gotta plug those two. Those were quite quite good and just interesting ways of thinking. UM. And then the one I'm reading now, which I think is a pretty cool book. It's called Outrageous Good Fortune. It's about a guy named Michael Burke, UM football hero you penn c I agent overthrew Communist government um Ran Intelligence for

Eastern Europe Ran Ringling Brothers Circus. He was the executive at TBS Sports, president of the Yankees, and president of MSG. So talk about a pretty packed life, but that books called outrageous good Fortune. I'm in the middle of that and it's, uh, it's pretty amazing, really really quite interesting. What sort of advice would you give to a recent college grad who was interested in pursuing a career in quantitative finance? UM, I would say to those that are

uh their First of all, they're welcome. We'd love to see them, UM to enjoy the journey. UH, substantively network. I think you learned so much from asking a lot of questions about what people do and how they do it. UM. Be a sponge. UM. Surround yourself with some really smart people UM that are equally driven UM. And then you know, the last thing I would say, for particularly for Kuan investors,

is you know, marry the how and the why. And what I mean by that is, you know a lot of people either have the correlation understanding or the causation understanding correlation and they understand the math behind it causation, they understand the practical effects. So it could work again. UM. Marrying those two I think really makes for UM, you know,

a phenomenal quantitative investor. Uh, quite quite interesting. And our final question, what do you know about the world of quantitative investing in trading today that you wish you knew years ago when you were first starting out UM. But I would say, besides buying UM it was a monster beverage, which I think is up about six hundred thousand percent. The SMP is only a less than a thousand percent UM, and I would say, I would say, there's there's really

nothing I would want to know in advance. And it might sound a little weird, but I think it spoils the excitement. I'm one of the great things about being in this quantitative business that really finance in general, is just the expert exploration and the quest for learning. That's something that has driven me, you know in my career that I've I've truly enjoyed and and knowing you know stuff, would you know what would kind of spoil that journey?

And so, you know, I the hiccups that I've had across the around the years and and the successes I think have made the journey awesome. And I'd say respectfully, No thanks on on you know the other pieces, because it wouldn't have made the journey is fun. We have been speaking with Gary Kropovka. He is the president of World Quantz. If you enjoy this conversation, well please check out any of our previous almost four hundred prior conversations.

You can find those at iTunes, Spotify, wherever you feed your podcast fix. We love your comments, feedback and suggestions right to us at m IB podcast at Bloomberg dot net. Sign up for my daily reads at ridoltz dot com. Check out my weekly column on Bloomberg dot com slash Opinion. Follow me on Twitter at Ritholtz. I would be remiss if I did not thank the crack team that helps put these conversations together each week. Nick Falco is my

audio engineer. Michael Boyle is my producer. Attika Valbrunn is our project manager. Michael Batnick is my head of research. I'm Barry Ritholtz. You've been listening to Master's Business on Bloomberg Radio.