Speaker 1: This is mesters in Business with very Renaults on Blueberg Radio.
Speaker 1: This week on the podcast, I have a special guest.
Speaker 1: His name is Gary Kropovka. He's the president of World Quants,
Speaker 1: a highly regarded quantitative investment firm. UH. Gary has a
Speaker 1: fascinating background, really insightful UH twenty years at ge Sam
Speaker 1: and Goldman Sachs Asset Management, where he was co head
Speaker 1: of the quantitative investment Strategies team. Ge Sam runs a
Speaker 1: ton of capital UH, and last year he moved over
Speaker 1: to world Quan, which in and of itself was spun
Speaker 1: out from Millennium Management in two thousand and seven. Millennium
Speaker 1: Management is another giant quantitative hedge funds, and World Quan
Speaker 1: runs a nice lug of capital for them. As innovative
Speaker 1: as so many different quantitative approaches are, World quant Is
Speaker 1: really stands out. They're an unusual shop. They do a
Speaker 1: lot of really interesting things that read led by UM,
Speaker 1: a very a kind of clastic and brilliant founder and
Speaker 1: CEO UM And really this is just a very intriguing
Speaker 1: and fascinating conversation if you are at all interested in
Speaker 1: quantitative investing, understanding one of the key drivers of markets
Speaker 1: today or just to get a sense of what people
Speaker 1: with advanced computer and mathematical degrees think about UM, the
Speaker 1: financial engineering that's taking place in the markets these days.
Speaker 1: You're going to find this to be a fascinating conversation. So,
Speaker 1: with no further ado, my interview of Gary Krapovka of
Speaker 1: World quant This is Mester's in Business with very Renaults
Speaker 1: on Bloomberg Radio. Our special guest this week is Gary Propovka.
Speaker 1: He is the president of World Quants, a highly regarded
Speaker 1: quantitative shop spun out of Millennium Management back in two
Speaker 1: thousand and seven. Gary has a BA in mathematics and
Speaker 1: a master's degree in financial engineering from Colombia. He's also
Speaker 1: on the board of trustees of Rutgers University. Gary Kropovka,
Speaker 1: Welcome to Bloomberg. Thank you so much, Barry. Great to
Speaker 1: be here. So I'm I'm kind of fascinated by your background.
Speaker 1: You you spend time UM at the quantitative investment strategies
Speaker 1: co heading that at Goldman Sachs, and you have your
Speaker 1: financial engineering degree from Colombia. Any overlap with Emmanuel Derman,
Speaker 1: you seem to have followed his footsteps. Yeah, I actually
Speaker 1: I think I predated Emmanuel Derman because I I was
Speaker 1: in the program when it first start bit back in
Speaker 1: the early two thousands. UM I did follow em Manuel,
Speaker 1: I guess to to Goldman facts UM. You know, after
Speaker 1: he had he was there, but separate paths, but there's
Speaker 1: definitely a correlation among the two UM A share. I
Speaker 1: went to Columbia, you know, after I joined the quant
Speaker 1: group at Goldman UM, there was you know, looking looking
Speaker 1: around the space, there were a lot of folks with
Speaker 1: some pretty advanced degrees, and decided to try to marry
Speaker 1: the computer science as well as the engineering with some
Speaker 1: of the business side to uh, you know, to to
Speaker 1: be better trained in the in the quant field. So
Speaker 1: so you eventually become co head of quantitative Investment Strategies
Speaker 1: at ge SAM. What what was that experience like? So,
Speaker 1: I would say I spent at over twenty years in
Speaker 1: the same group, and you know, I it really drove
Speaker 1: what I love about, you know, my job, which is
Speaker 1: fun dative investing. It's something that I have a huge
Speaker 1: passion for. I love, you know, dealing with data and
Speaker 1: figuring out problems. And you know, there were certainly a
Speaker 1: lot of investment problems that we dealt with in that
Speaker 1: in that group, and you know, really compelled me to
Speaker 1: go and join World Quant for for you know, even
Speaker 1: other opportunities. But you know, while I was at Goldman,
Speaker 1: did a number of different things on the research side,
Speaker 1: on the portfolio management side, on the product development side,
Speaker 1: the client side, and so had a had a host
Speaker 1: of experiences that I cherished, had a great experient, great
Speaker 1: time there, learned a ton and uh and now I'm
Speaker 1: here at the World Pants for the last roughly six months.
Speaker 1: So we're going to talk more about World Quant in
Speaker 1: a in a few minutes. Let's let's stick with the
Speaker 1: big data you referenced at Goldman and elsewhere. You know,
Speaker 1: big data is almost a cliche these days. How is
Speaker 1: it used in quantitative investment? Yeah, I would say, you know,
Speaker 1: when I think about big data, and you know, it's
Speaker 1: a it's a large term. But I would say, you know,
Speaker 1: we're all consumers, not just in the investment or in
Speaker 1: the quant group, but this whole concept around big data
Speaker 1: is affecting each and every one of our lives. We're
Speaker 1: all trying to have a have an information edge, We're
Speaker 1: trying to make better decisions, we're trying to you know,
Speaker 1: utilize as much data to make informed decisions of where
Speaker 1: we're spending our time, whether it's things like going on
Speaker 1: vacation or you know, figuring out where you what restaurant
Speaker 1: you want to go to. And so, you know, the
Speaker 1: world has moved beyond things like zag. It's um and
Speaker 1: really trying to understand the idea. There's a lot of
Speaker 1: things that will provoke what you want to do or
Speaker 1: where you want to spend your time and where do
Speaker 1: you want to invest in. And so this whole concept
Speaker 1: of big data is really to take you know, anything
Speaker 1: and everything that may be applicable to a company and
Speaker 1: try to learn from it. And so, you know, there's
Speaker 1: just this massive amount every time we click on something,
Speaker 1: time we move, there's all this data that's being captured.
Speaker 1: And really, you know, one of the great things about
Speaker 1: being a quantitative investor is that we have tools and
Speaker 1: techniques to take all this awesome amount of data which
Speaker 1: comes in many forms and I could touch on that,
Speaker 1: but it comes in many forms and convert that into
Speaker 1: some insight or some informational edge that helps us predict
Speaker 1: companies or particular asset class. So this whole concept of
Speaker 1: big data absolutely here to stay I'd say it's much
Speaker 1: broader than the investing business. It's happening, you know, all
Speaker 1: of our lives. We're all sitting with you know, the
Speaker 1: phones in our pockets that have massive amounts of information
Speaker 1: and so really the goal of all this big data
Speaker 1: is to create an informational edge to know something that
Speaker 1: maybe somebody else doesn't or um in order to be
Speaker 1: able to leverage that in in pursuit of learning something else.
Speaker 1: So give us, give us an example, how can you
Speaker 1: use a data set, uh, specifically to identify opportunities that
Speaker 1: other people that aren't looking at that data might miss. Sure,
Speaker 1: So I think there's there's tons of data out there
Speaker 1: that you know, one can glam that. We could take
Speaker 1: an example of, you know, looking through analyst reports and
Speaker 1: you know a lot of people read analysts reports, and
Speaker 1: so you know, things you can do is try to
Speaker 1: pick up on their sentiment and so how we're analysts
Speaker 1: starting to change their mind about a particular company. You know,
Speaker 1: it is a pretty common example of you know, figuring
Speaker 1: out how you know, you can train a computer to
Speaker 1: read all of these words that some of these analysts
Speaker 1: are putting together. UM. That might be one example, UM
Speaker 1: looking at you know, what's in the newspaper and trying
Speaker 1: to gauge sentiment around you know, what's popular and maybe
Speaker 1: what topics are interesting and what companies may be related
Speaker 1: to those topics, and or those topics trending positively or negatively.
Speaker 1: Those are some examples of of ideas where you know
Speaker 1: there's something out there that you know not as company,
Speaker 1: may not be coming out of a company's financials, but
Speaker 1: it's something that's happening around the company that might be impactful.
Speaker 1: So you know, those are two examples of of items
Speaker 1: that you know you'd constitute as big data because you're
Speaker 1: looking at massive amount of whether it's research reports or
Speaker 1: news articles, to kind of get a gauge of can
Speaker 1: I have a better picture of that company's fortunes? And
Speaker 1: I would say, you know, one of the things that
Speaker 1: we do at work Pond is you know, there's not
Speaker 1: just three ideas or five ideas. There's millions of ideas
Speaker 1: of ways to to navigate and have a view on
Speaker 1: a company, and big data forwards us the opportunity big
Speaker 1: data along with some you know, some great analytical tools
Speaker 1: to be able to kind of have views on particular companies. Huh,
Speaker 1: so so how does that play into things like smart
Speaker 1: data or factor based approaches. Is that something that you
Speaker 1: can apply um large data sets towards identifying new variations
Speaker 1: on absolutely? And I think you're touching on an important
Speaker 1: component if we think about the quant industry, you know,
Speaker 1: really started with a lot of these kind of let's
Speaker 1: call them smart betas or traditional measures of factors. So
Speaker 1: thinking about things like value or momentum, value being a
Speaker 1: cheap company relative to its book value as an example, momentum,
Speaker 1: So if the stock is starting to trend in a
Speaker 1: favorable direction, will it continue that particular trend? And so
Speaker 1: you know, the whole idea around analyzing all the data
Speaker 1: you know as quants. For the original quants, you really
Speaker 1: wanted to play off the law of large numbers, and
Speaker 1: so you had a lot of a lot of data
Speaker 1: yet information on each and every company, thousands of companies,
Speaker 1: and you try to rank companies by these particular metrics
Speaker 1: price to book or some measure of momentum. And you'd
Speaker 1: create a portfolio around those kind of quote unquote smart datas.
Speaker 1: And you know that tried and true works over time,
Speaker 1: and I think you know, as the industry is evolved,
Speaker 1: the smart data strategies, Um, there's now more interesting other
Speaker 1: ways of evolving and utilizing things like big data to
Speaker 1: be able to similarly look at those look at factors.
Speaker 1: So very similar to rank companies. So quants always want
Speaker 1: to play the breath game, meaning spread out their bets,
Speaker 1: have a lot of different views on particular companies. But
Speaker 1: what the alternative data and big data allows us to
Speaker 1: do is really play the depth game, so know a
Speaker 1: lot more about a particular company as opposed to just
Speaker 1: their price to book. So you know, back to your
Speaker 1: original question. The smart data strategies you know, which are
Speaker 1: largely common um implementable, absolutely use large amounts of data, um,
Speaker 1: you know in a pretty uh academically proven, you know,
Speaker 1: well thought out, but have been around for many decades.
Speaker 1: So one of the phrases I've been reading about is
Speaker 1: variation and of that customized data. What what is comdomized data? Yeah,
Speaker 1: so it is an interesting topic customization, I would say
Speaker 1: when we think about when you think about customized data
Speaker 1: in the industry, Um, you know, there's there's really two
Speaker 1: things that are happening. One is, um, what types of
Speaker 1: i'll call it bets would you like to make? So
Speaker 1: you know, do you want to bet on value stocks,
Speaker 1: do you want to bet on companies that are um
Speaker 1: have higher dividend payers, And you're able to customize what
Speaker 1: you want to place a wager on UM. The other
Speaker 1: part of the customization, which continues to be a pretty
Speaker 1: interesting trend in the industry, is there are certain E
Speaker 1: s G. Factors that one may want to hold near
Speaker 1: and dear and want to have companies in their portfolios
Speaker 1: that express their the beliefs that they, you know, have
Speaker 1: and want to express. So for example, you know, I
Speaker 1: don't want to invest in tobacco stocks, or I don't
Speaker 1: want to invest in, you know, something that is going
Speaker 1: to negatively impact the environment, and so you can, you know,
Speaker 1: with quant tools, you can figure out, okay, what are
Speaker 1: those companies or how do they fall into those categories,
Speaker 1: whether it's an industry or the percentage of revenues that
Speaker 1: company is going to get from you know, let's say
Speaker 1: emissions UM and then be able to create a portfolio
Speaker 1: to identify, you know, whether it's a factor bet around
Speaker 1: value or momentum and or um you know, different types
Speaker 1: of exposures that they want. So for example, things like
Speaker 1: tobacco or or emission, so you can customize the what
Speaker 1: your equity portfolio looks like relative to a benchmark or
Speaker 1: just an absolute. So let's talk a little bit about
Speaker 1: what you do at World Quants. What does the president
Speaker 1: of the firm's jobs responsibility look like? Great barrier. Yes,
Speaker 1: So so as as president, which I'm extremely fortunate to
Speaker 1: have joined such an incredible team, you know, I'd say,
Speaker 1: really three things that I focus on. You know, one
Speaker 1: is overall business strategy, help with the operating of the
Speaker 1: operating of the firm, and then add some leadership on
Speaker 1: the investing on the investing side, and it really that
Speaker 1: breaks down into kind of four key elements that you know,
Speaker 1: in terms of my role, and I work very closely
Speaker 1: with our CEO, Igor Tolchinsky, UM and really thinking about
Speaker 1: the following four things. One is vision, so you know,
Speaker 1: where where should we be spending our time? I would say, interestingly,
Speaker 1: we've got you know, roughly all over six hundred quantitative people,
Speaker 1: and so you know, we feel like we could solve
Speaker 1: a lot of interesting problems. UM. And really one of
Speaker 1: one of our jobs is to ensure that we're focusing
Speaker 1: on the right ones to solve and so you know,
Speaker 1: the you know, setting out that vision, UM, keeping people focused, UM,
Speaker 1: making sure that incentives are aligned, were allocating resources to
Speaker 1: tackling the right problems and and remaining focused on those
Speaker 1: types UM. Speed and one of the things that you know,
Speaker 1: in an organization that has over six people, you want
Speaker 1: to make decisions quickly. UM Igory does a terrific job
Speaker 1: of you know, of of of leading in attempt to
Speaker 1: help him with that in terms of making decisions, making
Speaker 1: sure things escalate very quickly, UM, so that we can
Speaker 1: continue our focus and our vision. And then the last
Speaker 1: thing I spend a decent amount of time on is talent.
Speaker 1: And you know, how do we acquire talent? How do
Speaker 1: we promote a culture of collaboration? UM? Intellectual stimulation. You
Speaker 1: know a lot of quants in general, we like to
Speaker 1: be intellectually stimulated. So how do we continue to do
Speaker 1: that and create a culture where ideas can be shared
Speaker 1: and collaborated across the firm? So those are those are
Speaker 1: where I've been spending my time over the last six months.
Speaker 1: What sort of programs do you have to incentivize your staff? Sure? So,
Speaker 1: so we have many different ways that we try to
Speaker 1: incentivize our people. UM. In terms of the you know,
Speaker 1: what we do for our for our researchers, and so
Speaker 1: we have real different challenges that we have around around
Speaker 1: the world to you know, to to incentivize people's work.
Speaker 1: And so, you know, that's just yet another piece of
Speaker 1: the puzzle where um, you know, we're trying to promote
Speaker 1: a particular activity or particular research and be able to, um,
Speaker 1: you know, incentivize them, call them out, reward them for uh,
Speaker 1: you know, for for doing some some really good work.
Speaker 1: And so you know, we have many of these, and
Speaker 1: I think one of the unique things about this firm
Speaker 1: is that we have many different competitions where uh, you know,
Speaker 1: where people can our our teams can be incented to
Speaker 1: uh to do different things and to use their mind
Speaker 1: a little differently and have the right uh incentive structure
Speaker 1: to be able to to to be rewarded for those
Speaker 1: So so you're creating these um for lack of a
Speaker 1: better word, competitions internally to solve an investing problem or
Speaker 1: equation or issue, and everyone who works in the firm
Speaker 1: can basically throw the hat in the ring and say
Speaker 1: this is the way I think we can solve this problem,
Speaker 1: and then you run the tests and figure out who's
Speaker 1: the winner on that or is it real time and hey,
Speaker 1: this is the best results based on your suggestion. Yes,
Speaker 1: so we we did. You have we have several competitions
Speaker 1: around around the firm UM with you know, set incentives
Speaker 1: for each of them, and we kind of have a
Speaker 1: group of people that try to tackle this and instead
Speaker 1: of it being relative to others in the firm, they're
Speaker 1: we're saying, okay, here's a particular UM strategy that we
Speaker 1: want to spend some time on. Let's see what you
Speaker 1: can develop UM. And so that's you know, that's an
Speaker 1: area where you know, we have projects that you might
Speaker 1: not fit into the core research that we do on
Speaker 1: a daily basis, but you know, maybe a little more um,
Speaker 1: you know, a little more out there. Maybe we're trying
Speaker 1: to look at a different asset class and we want
Speaker 1: to uncover. So we realize, you know, the the upfront
Speaker 1: R and D or the research is going to take
Speaker 1: a little bit longer, and so we want to incentivize
Speaker 1: them to go out and um, you know, and really
Speaker 1: think creatively about about capturing and we incentivize them accordingly
Speaker 1: because they're taking time out of their kind of core
Speaker 1: to really push the envelope a little bit more in
Speaker 1: terms of um, you know, in terms of figuring out
Speaker 1: something unique. One of the questions I was going to
Speaker 1: ask you is, hey, how is World quant differentiated from
Speaker 1: other firms? But but things like the accelerated platform, these
Speaker 1: sound somewhat different than what we typically hear about at
Speaker 1: a at a lot of shops. Are these common in
Speaker 1: the worlds of quant or is this a little more
Speaker 1: unique to what you guys do? Yeah, I think I think,
Speaker 1: Um sometimes people may do this, um, you know, for
Speaker 1: you know, to try to recruit people, and I've heard
Speaker 1: of people doing that, but putting it as a systematic way,
Speaker 1: you know, internally, I think is something quite unique. I
Speaker 1: would say when we think about our you know, our group,
Speaker 1: and really one of the compelling opportunities that is I
Speaker 1: had when I when I thought of of joining and
Speaker 1: fortunate enough to join World Font is you know, we've
Speaker 1: got over six people around the globe. We operate in
Speaker 1: twenty three offices thirteen countries. UM. So we've got unbelievable
Speaker 1: global diversity. And so I think that's you know, one
Speaker 1: thing that makes us UM quite unique. UM. So we
Speaker 1: operate in many different places we have many different opinions. UM.
Speaker 1: We've we've always promoted diversity, diversity of thought, UM, diversity
Speaker 1: of alpha's or drivers of return when we invest. And
Speaker 1: so you know, having programs that can continue to incentivize
Speaker 1: people UM and really create a collaborative and you know,
Speaker 1: I would say competitive in a in a good way, UM,
Speaker 1: where where people continue to be intellectually stimulated. I think
Speaker 1: that's really what you know, really drives the firm, the collaboration. UM.
Speaker 1: We just recently did a a research tour, a virtual
Speaker 1: research tour, and myself and Igo and a few other
Speaker 1: the senior folks kind of did a did a tour
Speaker 1: around and and you know, it's unbelievable when you know
Speaker 1: people can promote the collaboration they're sharing with us some
Speaker 1: of the research and the first thing they say is,
Speaker 1: I'd like to acknowledge the four or five people that
Speaker 1: helped with this with this research project. And so you know,
Speaker 1: just the idea around true collaboration, true appreciation for where
Speaker 1: you're getting assistance from. You know, I think it was
Speaker 1: really makes makes this place a pretty unique, unique uh
Speaker 1: neque place to be. World Tom was spun out of
Speaker 1: Millennium by Igor Tolchinsky, who is the founder and CEO.
Speaker 1: Tell us a little bit about your boss. Yeah. So,
Speaker 1: so when I first met Igor Um, he's just so
Speaker 1: intellectually stimulating. I mean, a brilliant, brilliant investor, brilliant man. Um.
Speaker 1: You know, extremely charitable. Um. Some of the things that
Speaker 1: he's done, UM. You know, so we are just a
Speaker 1: really spectacular and you can see a lot of those
Speaker 1: on the web. He's written some really interesting books and
Speaker 1: just his vision, his ability to articulate, um, you know
Speaker 1: where we're going, uh, and and and collaborate very well. Uh.
Speaker 1: To the other thing that is just very impressive is
Speaker 1: his decision making. And I think I've observed a lot
Speaker 1: of quants over the years. You know, you kind of
Speaker 1: get into the analysis paralysis. UM. You know, the there's
Speaker 1: always another test you can run on something. You know,
Speaker 1: Igor to his credit, is a decision maker. UM. And
Speaker 1: it is. You know, it's just great to be able
Speaker 1: to partner with him for six months of the last
Speaker 1: six months and you know, look forward for for many
Speaker 1: many years and decades to come. But he is, you know,
Speaker 1: someone who really does make decisions, takes in all the
Speaker 1: information um, and you know, has really built an unbelievable business.
Speaker 1: Uh here at will on. So when I normally speak
Speaker 1: to a firm and I say, hey, what's your firm's
Speaker 1: investment philosophy? Usually I get a sentence that sums everything
Speaker 1: up in in one nice little SoundBite. I get the
Speaker 1: sense that you're operating a whole lot of different approaches.
Speaker 1: It might be a little harder to pin you down
Speaker 1: to one philosophy of of the firm. What is World
Speaker 1: Quants investment philosophy? So, so World World Plants investment philosophy
Speaker 1: is really, you know, pretty pretty simple global leverage our
Speaker 1: people and provide them the tools and technology two to
Speaker 1: make returns for our investors. I mean that's really you know,
Speaker 1: in a nutshell, you know what we're trying to do. Um.
Speaker 1: We we have a very systematic way in which we
Speaker 1: do it. We try to leverage the law of large
Speaker 1: numbers and have millions of different alphas that we can leverage.
Speaker 1: We put them together in a portfolio and then we
Speaker 1: execute and make them a reality through trading. So, you know,
Speaker 1: the investment processes is quite simple and straightforward. But the
Speaker 1: uniqueness of our philosophy is that we are extremely global
Speaker 1: in terms of our people. Um, we do believe in
Speaker 1: in playing the breath game. We have we have a
Speaker 1: lot of alpha's, a lot of ways to look at
Speaker 1: companies and we try to leverage that throughout our process
Speaker 1: and create portfolios that driver turned for our clients. So
Speaker 1: let's talk a little bit about the past year, which
Speaker 1: was some people have called it unprecedented. When you are
Speaker 1: crunching numbers to try and find a pattern, how can
Speaker 1: you deal with the possibility of events which have simply
Speaker 1: never occurred before. Yeah, Berry, that's a terrific question. Um.
Speaker 1: You know, that really separates the you know, the quantz
Speaker 1: quote unquote and the quant investors. And so, you know,
Speaker 1: one of the things that makes our jobs so interesting,
Speaker 1: I find is the ability to adapt and really to
Speaker 1: to be market practitioners as well as as quants, and
Speaker 1: I think that really makes great quant investors. So, you know,
Speaker 1: if we think about two thousand twenty and also in
Speaker 1: two thousand twenty one thus far, you know we've seen
Speaker 1: you know, obviously unprecedented events. Um. You know, whether it's
Speaker 1: around COVID or you know other types of you know
Speaker 1: of of events that that have happened over the last year,
Speaker 1: which which ramifications have caused very large moves in you know,
Speaker 1: kind of common let's call them factors or expressions or
Speaker 1: buckets of particular stocks or characteristics of stocks. You know,
Speaker 1: for example, you know, things like momentum we talked about
Speaker 1: before value. UM, these have had some pretty unprecedented moves. UM.
Speaker 1: You know, there's been you know, for value, about fifteen
Speaker 1: UH standard standard aviation moves that are that we're above
Speaker 1: two in two thousand and UM. You know, one just
Speaker 1: massive moves. When you think about a simple five center
Speaker 1: deviation move means that that happens once one day every
Speaker 1: approximate fourteen thousand years. So to your point, there's been
Speaker 1: no shortage of massive moves UM, you know, largely because
Speaker 1: there's been such a big shift. And so I think
Speaker 1: as quant investors, the way we try to approach it
Speaker 1: is to I is to adapt as quickly as we
Speaker 1: possibly can for some unforeseen event. Obviously we try to
Speaker 1: predict whatever we can in advance. UM. But to the
Speaker 1: extent UH you know you have something like uh COVID,
Speaker 1: you know, you want to think about companies that are
Speaker 1: going to be largely affected because of that, And there's
Speaker 1: two approaches. One is you can try to risk manage,
Speaker 1: which is usually what we would do, which is, you know, listen,
Speaker 1: this is a once in a life time events. Let's
Speaker 1: try to immunize our portfolios from those. So, whether you
Speaker 1: know it's a it helps or hurt stocks, let's try
Speaker 1: to immunize ourselves. And the other is to say, okay,
Speaker 1: let's try to get a sense whether there's going to
Speaker 1: be some type of trend here or there's some you know,
Speaker 1: ability to to create alpha or some excess returns UM
Speaker 1: when these events happen. So you know, you can think
Speaker 1: about binary events, so things like elections that have happened
Speaker 1: UM and what the ramifications are. You can think about
Speaker 1: things like trade UM. You could think about companies exposure
Speaker 1: to you know, things like bitcoin when they announce and
Speaker 1: what do you do about it? And so, you know,
Speaker 1: we think about the world in characteristics. So we call
Speaker 1: them factors, and so you can create these quote unquote
Speaker 1: factors and say I want to have a portfolio that
Speaker 1: whether those factors do well or poorly, I'm my portfolio
Speaker 1: will not be affected. So that's really the way we've
Speaker 1: We've thought about a lot of two thousand, twenty and
Speaker 1: twenty one and our investment team has just done a
Speaker 1: terrific job of being able to navigate that and identify
Speaker 1: some of these risks that they haven't seen before. We
Speaker 1: try to codify it in a systematic way and then
Speaker 1: focus our attention on, you know, on really where we
Speaker 1: believe we can make money UM, and that's a lot
Speaker 1: of these millions of alphas that we believe have been
Speaker 1: contested for for years. So that's how we think about,
Speaker 1: you know, dealing with some of these unprecedented moves that
Speaker 1: we've seen in you know, things like short interest and
Speaker 1: momentum and value that have happened over the last twelve
Speaker 1: months or so. Huh So. So I'm intrigued by the
Speaker 1: concept of of something UM that's so many standard deviations
Speaker 1: away from the norm that it's really a one in
Speaker 1: a fourteen thousand year events, those sort of tail risks.
Speaker 1: How can we anticipate them on a quantitative basis? And
Speaker 1: and more specifically, UM, think back to January six and
Speaker 1: the attempted insurrection in the US capital. How can you
Speaker 1: quantify that? And we've learned since that that actually came
Speaker 1: pretty close to I don't know if I would call
Speaker 1: it successful, but but pretty close to having the rioters
Speaker 1: access UM, various people in Congress, maybe even the Vice president.
Speaker 1: How do you factor that into to your UM analyzes. Yes,
Speaker 1: as I would say, you know, I'll take it up
Speaker 1: a step in terms of just in general how we
Speaker 1: think about it. But it's really about, you know, trying
Speaker 1: to identify things that will impact UM companies and you know,
Speaker 1: what are the ramifications and and I think that's really
Speaker 1: the way we try to think about that. So you know,
Speaker 1: in that specific case, in terms of what would happen
Speaker 1: to particular companies UM, you know, those those events are
Speaker 1: relatively UM you know, quick moves. We try to be
Speaker 1: very diversified in many different ways. And you know, that's
Speaker 1: probably one of the first times I've used that term,
Speaker 1: but I would say the diversification point is so critical
Speaker 1: in investing UM, whether you're a quant investor or you're
Speaker 1: any type of investor. It's it's definitely an extremely helpful
Speaker 1: UM attribute when you have events like this occur. And
Speaker 1: so you know, creating you know, different ways to look
Speaker 1: at risks UM as quickly as you possibly can, and
Speaker 1: adapting a portfolio, you know, we think leads to very
Speaker 1: successful outcomes in the long run. How did you guys
Speaker 1: look at what was taking place with things like Robin
Speaker 1: Hood and read it to me that was reminiscent of
Speaker 1: you know, late nineties action, although it certainly was faster
Speaker 1: and maybe more powerful than we've seen in the past.
Speaker 1: How do you look at these sort of group behavior
Speaker 1: that that social networks can foster. Yeah, again we um so,
Speaker 1: I think we look at in terms of, you know,
Speaker 1: from a from a liquidity standpoint, what what are the
Speaker 1: know how is this affecting the amount of the amount
Speaker 1: of ability to trade our securities? Um? You know, we
Speaker 1: really do try to minimize that I mentioned earlier. We
Speaker 1: try to minimize the amount of risk we take from
Speaker 1: any particular factor and things like you know, short interest
Speaker 1: is something that you know is a is a pretty
Speaker 1: common factor that you know, folks UM like us would
Speaker 1: would try to identify and minimize. Um. Are you know
Speaker 1: how much our our stocks will move because of that? UM,
Speaker 1: I'd say, you know, big picture thinking about liquidity, obviously,
Speaker 1: there there is a big retail you know, retail input
Speaker 1: um to liquidity. They tend to you know, trade it
Speaker 1: trade you know, stocks that are that are relatively cheap
Speaker 1: in priced um. You know, and I think there's some
Speaker 1: you know, some pretty interesting data around that I would say,
Speaker 1: for you know, for our purposes. You know, we look
Speaker 1: at things like liquidity and depths of market and how
Speaker 1: that's being impacted. And I would say, over the last
Speaker 1: twelve months, you know, interestingly that the world of market
Speaker 1: micro structure has gotten pretty complicated, you know, to the
Speaker 1: extent you could trade you could trade you know, ABC
Speaker 1: stock in forty different venues in the US is interesting enough,
Speaker 1: you know, across sixteen different exchanges, or roughly about sixteen
Speaker 1: different exchanges. And so you know, we spend a lot
Speaker 1: of our time looking at things like volumes and spreads
Speaker 1: and and overall liquidity UM. And so that's really where
Speaker 1: we see um, you know, those effects. And I would say,
Speaker 1: you know, it looks like over the last twelve months
Speaker 1: it's been a pretty rocky um, you know, rocky area.
Speaker 1: But you know we're pretty much back to you know,
Speaker 1: kind of pre pandemic levels when I think about quote sizes,
Speaker 1: bid ask spreads, UM, you know for for SMP type names.
Speaker 1: So it looks like things are kind of getting a
Speaker 1: little bit back to normal in terms of of market liquidity,
Speaker 1: depth and spreads. So you mentioned value earlier. I think
Speaker 1: this is up until this quarter. I think the underperformance
Speaker 1: of value versus growth, it could be the longest run
Speaker 1: we've seen of growth dominating value since since at least
Speaker 1: since the CRISP database goes back to nineteen seventeen or
Speaker 1: something like that. How do you think about something that's
Speaker 1: rather unusual in those terms. How does the FED factor
Speaker 1: into this or is that even an input to to
Speaker 1: what you're building in your models. Yeah, no, it's it's
Speaker 1: it's exactly. It's very consistent with again thinking about it
Speaker 1: as a as a very diversified portfolio, and you know,
Speaker 1: value investing over the long term has done reasonably well. UM.
Speaker 1: I'm very impressed that you went back to the CRISP database,
Speaker 1: So kudos to you. UM. When I think about you
Speaker 1: value again, value on itself, we tend to take an
Speaker 1: approach where we want to be more diversified. We don't
Speaker 1: want to just bet on value. We want to have
Speaker 1: things that have growth at tributes and really have some
Speaker 1: you know, we call it idiosyncratic or some specific type
Speaker 1: of return where we think that's our edge. And and
Speaker 1: in terms of other types of factors like value or
Speaker 1: growth or low volatility. UM, those are something that we
Speaker 1: want to have a very modest amount of exposure or
Speaker 1: you know, we really don't want to We don't necessarily
Speaker 1: make a lot of money on that particular aspect because
Speaker 1: it's very common and it's also subject to very sharp moves,
Speaker 1: and so you know, we aim to have a little
Speaker 1: bit more consistent, persistent results. But to your point, you're right,
Speaker 1: this is it's been an unbelievable um challenge for Value.
Speaker 1: We've we have seen a little bit of a turnaround, um,
Speaker 1: you know, since since the election, UM, and so you know,
Speaker 1: value that start us to do a little bit better.
Speaker 1: But your point is well taken, But I think it
Speaker 1: just speaks to our philosophy of you want to have,
Speaker 1: you know, many different ways of looking at the fortunes
Speaker 1: of a company and diversification. Diversification, diversification is key and
Speaker 1: at World Plant we that with millions of alpha's, we
Speaker 1: have many different portfolio managers, many different ways of combining
Speaker 1: our alpha's, and so you know, we kind of live
Speaker 1: and breathe from diversifying of our people to our alpha's,
Speaker 1: to our portfolio managers, and then to our execution. So again,
Speaker 1: I think you know, your observation is spot on, and
Speaker 1: I would say we as a as a group try
Speaker 1: not to take too many bets in one place. Huh. Interesting.
Speaker 1: You know you mentioned certain strategies are popular, and I
Speaker 1: can't help but think back to the um quant quake
Speaker 1: that took place about eight years ago, where a lot
Speaker 1: of quantitative strategies were very similar at different shops, and
Speaker 1: we saw what had become a fairly crowded trade. Maybe
Speaker 1: maybe it's a decade ago, it's even longer ago. What
Speaker 1: what do you make of that crowded trades? Yeah, so
Speaker 1: so it was more than a decade ago, is you
Speaker 1: know if I think it was almost eight thirteen and
Speaker 1: a half years ago? Okay, I think I think there
Speaker 1: was a huge lesson learned for for Kuant investors. Um.
Speaker 1: I think it was a period where, uh, you know,
Speaker 1: there was you know, some some shops had a fair
Speaker 1: amount of complacency where they didn't continue to use their research.
Speaker 1: There was more into there was you know, there there
Speaker 1: should have been a lot more pushing in terms of
Speaker 1: research and and I think you look back and you
Speaker 1: saw events that you know, for a number of reasons.
Speaker 1: One is there was a fair amount of leverage in
Speaker 1: the system, and so you're able to amplify your returns
Speaker 1: with leverage UM and leverage is great if you're always
Speaker 1: going to have high, high positive returns, but when you don't,
Speaker 1: you know, leverages is a you know as a very
Speaker 1: big challenge because people call up and ask you for
Speaker 1: money and you need to pay them. So I think
Speaker 1: you know that that really was one of the biggest
Speaker 1: issues of of oh seven UM. But I'd also say
Speaker 1: there was crowded traits, as you correctly point out. And
Speaker 1: so I think one of the goals that we have
Speaker 1: at World pant is continue to differentiate, continue to create
Speaker 1: unique ways of making money for our clients investing in
Speaker 1: our almost three hundred researchers, to try to continue to
Speaker 1: innovate and be much less crowded than other people. Again,
Speaker 1: we want to be unique. We don't want to be
Speaker 1: susceptible to those large movements in terms of those quote
Speaker 1: unquote crowded trades. And that's really a huge goal and
Speaker 1: frankly was a big lesson learned for I believe the
Speaker 1: quand industry. UM that happens, you know, almost fourteen years ago.
Speaker 1: So let's talk a little bit about the future of
Speaker 1: quant investing. You mentioned previously that the industry has learned
Speaker 1: from past mistakes. It's involved UM. Tell us a little
Speaker 1: bit about the direction the industry is in evolving towards,
Speaker 1: Sir Barry, I think the you know, the quand industry
Speaker 1: will continue to evolve in in places like data, in
Speaker 1: places like storage, in places like analytics, UM and the
Speaker 1: tools that are that one can use to try to,
Speaker 1: you know, figure out the fortunes of a company have
Speaker 1: increased exponentially, and so you know, the amount of data
Speaker 1: that's out there, amount of data that can be stored,
Speaker 1: amount of data that can be analyzed, the simulations that
Speaker 1: one can run has grown, like I said, absolutely exponentially,
Speaker 1: and really for a quant investor, it's terrific because you know,
Speaker 1: the world is kind of coming in our direction. The
Speaker 1: amount of data. We think, you know, one of our
Speaker 1: edges to be able to take data, synthesize it and
Speaker 1: create information and drive returns. And you know, we think,
Speaker 1: here a world point, we're extremely well positioned to be
Speaker 1: able to do that. And so, you know, honestly, I
Speaker 1: think it's a you know, it's an absolute golden age
Speaker 1: for us as Kuan investors UM in terms of kind
Speaker 1: of where the industry is evolving really interesting. Any of
Speaker 1: this evolution surprised you what what has taken place that um,
Speaker 1: either you didn't see coming, or you saw coming and
Speaker 1: didn't think would happen, and it happened anyway, right, I
Speaker 1: would tell you know, one of the surprises is is
Speaker 1: the adoption of you know, more and more quantitative investing
Speaker 1: strategies in general. Um. Just given uh, everyday people's thoughts
Speaker 1: on you know, the use of computers and use of
Speaker 1: your phone to drive information, It's happening across most every industry.
Speaker 1: I guess I'm surprised, happily surprised that more and more
Speaker 1: kind of investment folks aren't employing more and more quantitative strategy.
Speaker 1: Good for us from where we sit, but I'm just surprised.
Speaker 1: You know, I think everybody wants to you know, if
Speaker 1: you're at a dinner party, you're you're asked, you're getting
Speaker 1: asked a question, it's got to be empirically back that
Speaker 1: You're gonna look it up as quickly as you possibly can,
Speaker 1: and you want to test that there whatever someone said,
Speaker 1: whatever hypothesis, um, you know, and there's there's a lot
Speaker 1: of skeptics and they can be proven yea or nay
Speaker 1: very quickly. And I'm just you know, I guess I'm
Speaker 1: I'm surprised that that's not happening more and more in
Speaker 1: the in the investment industry. So that would be one
Speaker 1: of the I would say, my my biggest surprises. But
Speaker 1: I'm but I'm okay with that. Huh. You mentioned earlier
Speaker 1: trying to read sentiment data from analysts reports. I've read
Speaker 1: about firms trying to actually scrape market wide sentiment data
Speaker 1: off of social networks like Twitter. What what does that
Speaker 1: look like? And can you really find an investable edge
Speaker 1: from the characters of millions of people who know um
Speaker 1: relatively little, although they may not know that they know
Speaker 1: relatively little? What what signal is in all that noise? Sure, Marry,
Speaker 1: I think you're you're touching on a really important components.
Speaker 1: You think about all this alternative data, you know, it's
Speaker 1: it's what do you do with it? And and how
Speaker 1: do you utilize it? And I think you know, a
Speaker 1: diversified approach of you using things like satellite images, using
Speaker 1: things like social media, um, you know, can be quite impactful,
Speaker 1: you know, some of which might be very very short run.
Speaker 1: Some of it might have more longer term ramifications, things
Speaker 1: like credit card transactions, web clicks. I mean, there's so
Speaker 1: much alternative data out there that you know, if you
Speaker 1: can think about how best to utilize it. Again, it's
Speaker 1: that whole concept of marrying kind of technical acumen and
Speaker 1: so you understand data, you understand uh something about you know,
Speaker 1: putting data together to create some type of expected return,
Speaker 1: but also marrying that with some business acumen. You know,
Speaker 1: I think is is really exploding. And so you know,
Speaker 1: whether it's social media, where it's at allite imaging, whether
Speaker 1: it's you know, clicking on you know, getting vendors that
Speaker 1: that provide some of this data all anonymized to be
Speaker 1: able to have a view of where company's fortunes maybe
Speaker 1: is certainly something that the industry is seeing. Um, there's
Speaker 1: a massive amount of data vendors out there. There is
Speaker 1: some content validation and some of those data vendors, but
Speaker 1: there's a lot of data out there to be able
Speaker 1: to employ not just social media, but other types of
Speaker 1: of data that you know, can be informative of a
Speaker 1: company's fortunes. Yeah, I've been kind of fascinated by the
Speaker 1: satellite data and how granular it can get not just
Speaker 1: tracking ships carrying goods or oil around the world, but
Speaker 1: how deep the ships are sitting in the water. That
Speaker 1: gives some insight as to how are they traveling? Full
Speaker 1: half full? Three corps. That's just astonishing stuff. Yeah, I
Speaker 1: mean it's it really is. And I think you know, listen,
Speaker 1: I think we all we all have our phones and
Speaker 1: and you know I could I could kindly tracked my
Speaker 1: kids on on Life three sixty and figuring out where
Speaker 1: they are. Um, you know this is happening. It's part
Speaker 1: of our everyday lives, um and uh. And you know
Speaker 1: it's it could be insightful information. You know certainly helped me,
Speaker 1: you know, with my kids and and you know other parts,
Speaker 1: whether it's uh, you know, tankers or whether it's uh,
Speaker 1: you know, clicks. Uh. You know, these are insights that
Speaker 1: you know, can be you know, potentially telling. Again, I
Speaker 1: would go back to my other common about diversification. So
Speaker 1: in isolation, these you know, will you know almost for
Speaker 1: certain will not work all the time. Um, But if
Speaker 1: there's some level of insight that you can gain from
Speaker 1: a piece of this data or a way to look
Speaker 1: at this data, and then you marry that with millions
Speaker 1: and millions of other things. You know, you can have
Speaker 1: a pretty good sense of that company's fortune. So you know,
Speaker 1: again it's it's really about diversification and not thinking about
Speaker 1: you know, these pieces of data in isolation. UM. You know,
Speaker 1: we had talked a little bit about value and other
Speaker 1: types of factors. Again, I think you know, the approach
Speaker 1: that that one that most quants take UM is really
Speaker 1: to think about diversification um as as a really helpful
Speaker 1: way to produce UM you know, consistent results for clients.
Speaker 1: And I think that's really, you know, the key to
Speaker 1: how most wants and at World want you know, we
Speaker 1: think about diversification at pretty much every step of the way.
Speaker 1: But it's our people, whether it's the expected returns that
Speaker 1: we try to generate or portfolio managers and how we
Speaker 1: go about executing and making that a reality. So you
Speaker 1: talked several times about how gigantic these data sets are
Speaker 1: and how fast they're growing, How how big can these get?
Speaker 1: And at what point do they become unmanageable? I mean,
Speaker 1: when is too much data too much? Yeah? UM, we
Speaker 1: certainly have not found that out yet. UM. You know,
Speaker 1: the nice thing about it is there's the amount of data,
Speaker 1: you know, is increasing exponentially. There's some unbelievable stats on
Speaker 1: just that massive amount of growth UM. And I think,
Speaker 1: you know, frankly, we've spent an enormous amount of time
Speaker 1: figuring out how to take in that data, how to
Speaker 1: collate it, how to check that data. Um. You know,
Speaker 1: again it's the gory details of data, but it's um
Speaker 1: but it's fascinating. I know, I d C I d
Speaker 1: c UM. You know reported a quote them more than
Speaker 1: five billion consumers interact with data every day. Five billion
Speaker 1: consumers interact with data every day. By they say that
Speaker 1: number will be six billion, or three quarters of the
Speaker 1: world's population. So data is getting created again exponentially. I
Speaker 1: think this is the thing that we spend a lot
Speaker 1: of time on is how do we ingest that, How
Speaker 1: do we come up with processes to be able to
Speaker 1: you know ingest it, how do we store it, how
Speaker 1: do we analyze it? Again? And that's that's really, uh,
Speaker 1: you know, one of our integral parts of what we
Speaker 1: do and how we do it. And you're seeing this
Speaker 1: in the investment industry. You're seeing this in many different industries.
Speaker 1: But I think that's one of the exciting parts um,
Speaker 1: you know, and it's a lot of data. But again
Speaker 1: I think that's really you know, we've been waiting for
Speaker 1: these times for for a long time. To continue to
Speaker 1: have more and more data, it allows us a huge
Speaker 1: opportunity to drive an edge because we think we know
Speaker 1: what to do with that type of data. Um, to
Speaker 1: pair that with some of our you know, smart researchers
Speaker 1: and figuring out what are the insights. So, you know,
Speaker 1: I think the other challenge that we face in terms
Speaker 1: of your comment about too much is again signal to noise?
Speaker 1: All right, What's what's a signal? Meaning what what gives
Speaker 1: you insight? And what's just noise? And so part of
Speaker 1: our jobs as researchers and portfolio managers, as good quants
Speaker 1: at worklan is is to kind of distinguish between the
Speaker 1: signal meaning does this have some value, does it provide
Speaker 1: me insight? Or is it really just noise and you know,
Speaker 1: not really worthy of of of allocating any investment to it. Huh.
Speaker 1: Quite interesting. Let let me change gears on you a
Speaker 1: little bit. We recently heard rumblings about possible changes in
Speaker 1: tax policy coming out of the new administration. I know
Speaker 1: at Goldman, I know a gam You did a lot
Speaker 1: of work on UM tax efficiency from from your new perch.
Speaker 1: How do you think about things like tax efficiency in investing?
Speaker 1: Is that something that's still within your bailiwick or or
Speaker 1: is it more institutional and you're you're less focused on
Speaker 1: tax Yeah, so, I mean the way we think about it,
Speaker 1: and I'm happy to spend some time on just generally
Speaker 1: tax efficient investing. I think it is. It's you know,
Speaker 1: it's a very useful piece and I've had some prior
Speaker 1: experience in it, but more substantively on you know, kind
Speaker 1: of what we do now at work on you know,
Speaker 1: if there is a change to tax policy, we're gonna
Speaker 1: you know, figure out how it's going to impact a
Speaker 1: particular company. You know, our corporate tax is going to
Speaker 1: go up or down UM, and how will that impact
Speaker 1: you know, cash flow or you know something on on
Speaker 1: a company's statements. UM. So that that's really how we
Speaker 1: would tackle it, and you know, we'll we'll understand how
Speaker 1: we should you know, update our accounting UM for for
Speaker 1: those types of events and adapt accordingly, like like you
Speaker 1: would expect most in sters to do. UM. You know,
Speaker 1: in the ray of tax efficient investing, you know, I'm
Speaker 1: happy to spend a few minutes there, but you know,
Speaker 1: we don't, uh, that's really not one of our core
Speaker 1: focuses at world point. You're you're looking more as to
Speaker 1: how the changes in taxes impact either the bottom line
Speaker 1: for the companies or their position relative to their competitors
Speaker 1: UM and what the tax code means, uh to their valuation.
Speaker 1: Is that is that a fair description? Like, I know,
Speaker 1: you guys aren't tax loss harvesting the way a traditional
Speaker 1: UM advisor would. You're you're running a very different portfolio
Speaker 1: for for a different audience. So your perspective is what
Speaker 1: does this mean to the companies that we may or
Speaker 1: may not own, and and how does it affect them
Speaker 1: relative to their competitors? Is that a fair statement? Yeah?
Speaker 1: I think that's a that's a fair statement. Again, we
Speaker 1: want to see as as Biden you know, institutes new policies,
Speaker 1: how that will affect corporations and frank we that goes
Speaker 1: you know beyond you know, tax policy, other types of policies,
Speaker 1: and so you know, if there's international policies that will
Speaker 1: affect trade or or any type of you know of
Speaker 1: of things that come out of Washington or Frankly, any
Speaker 1: any other government around the world. Given we are a
Speaker 1: global organization, you know, we're gonna attempt to take that
Speaker 1: into account, um, to try to understand it, understand what
Speaker 1: the ramifications are two companies and being able to position
Speaker 1: our portfolios accordingly. And that's that's you know, we do
Speaker 1: that whether it's a regulatory issue or an event that
Speaker 1: we talked about again. Our ability to adapt and understand
Speaker 1: what's going on in markets, what's going to affect companies
Speaker 1: or particular asset classes is really you know, one of
Speaker 1: the fun parts of the job as being a quantitative investor. Huh,
Speaker 1: what what are other fun parts of the job? What
Speaker 1: what do you enjoy doing most? Um, as presidents of
Speaker 1: world want so, I will tell you I've had such
Speaker 1: a great time of of walking out of meetings action steps. Uh,
Speaker 1: it's been you know, seeing seeing people intellectually stimulated around
Speaker 1: you know again where a lot of it is on
Speaker 1: zoom and so you know, we sit there and and
Speaker 1: just you know, watching how people dialogue has just been
Speaker 1: you know, so incredibly exhilarating. Um. You know a lot
Speaker 1: of the great ideas and you know, watching how respectful
Speaker 1: people heard of each other and challenging them in in
Speaker 1: thoughtful ways and almost hearing them think, uh, you know
Speaker 1: right in real time. Is it's just been been incredible.
Speaker 1: Uh in terms of uh, you know, the the organization,
Speaker 1: it's it's just highly productive, highly collaborative. Um, there's just
Speaker 1: a lot of great decision making that goes on. We
Speaker 1: just recently did a research off site where we just
Speaker 1: walked through and have many, many decisions. We pride ourselves that,
Speaker 1: you know, we're very action oriented, and so you know,
Speaker 1: that's been you know, some of the fun things that
Speaker 1: that I've been fortunate enough to uh, you know, to
Speaker 1: observe in my in my six months. Let me jump
Speaker 1: to my favorite questions that I asked all of my guests,
Speaker 1: starting with what are you streaming these days? Give us
Speaker 1: your your favorite Netflix or Amazon Prime show or any
Speaker 1: podcast you might be listening to. What's keeping you entertained? Sure? Um,
Speaker 1: I would say been a fan of House of Cards. Um,
Speaker 1: My daughter and I watched Million Little Things. Um. Joe
Speaker 1: Rogan's interviews with Elon musk Are are pretty pretty impressive.
Speaker 1: And I would have to say, you know, one of
Speaker 1: my favorite videos is a four minute and thirteen second
Speaker 1: Jason Garrett speeches. He talks about one World Trade Center.
Speaker 1: It's just it's an amazing video that you know, all
Speaker 1: my friends, uh get a text from me on a
Speaker 1: pretty regular basis, just just level sets. It's a great video.
Speaker 1: H really interesting. Uh tell us about your mentors who
Speaker 1: helped to shape your career. Sure, I would say my
Speaker 1: dad had unbelievable work ethic. Um it was a six
Speaker 1: day a week guy. Um. One of my my first
Speaker 1: bosses was was a guy named Gustic Conomos, who unfortunately
Speaker 1: passed away at nine eleven. Um. But you know, was
Speaker 1: was was able to balance enormous credibility or industry credibility
Speaker 1: with a sense of humor. And uh, you know, us
Speaker 1: always used to tell me I may have taught you
Speaker 1: everything you know, but I didn't teach you everything I know.
Speaker 1: And I always always think that's a pretty funny, uh
Speaker 1: funny quote. But uh, you know, And and the last
Speaker 1: one I would say on the quant spaces two gentlemen
Speaker 1: and Bob Jones and Don Mulvehill. Bob was the founder
Speaker 1: of the g Sam uh you know chront equity business
Speaker 1: back in the day, and you know, taught me a
Speaker 1: lot and really helped shape my career and my interest
Speaker 1: in quantitative investing. And then Don was you know, an
Speaker 1: age old colleague and boss of mine that really taught
Speaker 1: me a tremendous amount about UM investing, in dealing with
Speaker 1: clients and you know to too great early role models
Speaker 1: that I had had in the industry quite quite interesting.
Speaker 1: Tell us about some books? What do you what are
Speaker 1: you some of your favorites and what are you reading
Speaker 1: right now? Sure? So, uh, some of my favorite especially
Speaker 1: since I had a decent amount of time between between
Speaker 1: taking on the role at at World quand UM. You know,
Speaker 1: I was able to read David Rubinstein's How to Lead,
Speaker 1: which I thought was just terrific. Um Sartin to Tella
Speaker 1: had the hit Refresh, which I thought was quite good.
Speaker 1: I was also able to read our books from our CEO,
Speaker 1: who has two good ones, Finding Alpha's and The Unrules,
Speaker 1: So I gotta plug those two. Those were quite quite
Speaker 1: good and just interesting ways of thinking. UM. And then
Speaker 1: the one I'm reading now, which I think is a
Speaker 1: pretty cool book. It's called Outrageous Good Fortune. It's about
Speaker 1: a guy named Michael Burke, UM football hero you penn
Speaker 1: c I agent overthrew Communist government um Ran Intelligence for
Speaker 1: Eastern Europe Ran Ringling Brothers Circus. He was the executive
Speaker 1: at TBS Sports, president of the Yankees, and president of MSG.
Speaker 1: So talk about a pretty packed life, but that books
Speaker 1: called outrageous good Fortune. I'm in the middle of that
Speaker 1: and it's, uh, it's pretty amazing, really really quite interesting.
Speaker 1: What sort of advice would you give to a recent
Speaker 1: college grad who was interested in pursuing a career in
Speaker 1: quantitative finance? UM, I would say to those that are
Speaker 1: uh their First of all, they're welcome. We'd love to
Speaker 1: see them, UM to enjoy the journey. UH, substantively network.
Speaker 1: I think you learned so much from asking a lot
Speaker 1: of questions about what people do and how they do it. UM.
Speaker 1: Be a sponge. UM. Surround yourself with some really smart
Speaker 1: people UM that are equally driven UM. And then you know,
Speaker 1: the last thing I would say, for particularly for Kuan investors,
Speaker 1: is you know, marry the how and the why. And
Speaker 1: what I mean by that is, you know a lot
Speaker 1: of people either have the correlation understanding or the causation
Speaker 1: understanding correlation and they understand the math behind it causation,
Speaker 1: they understand the practical effects. So it could work again. UM.
Speaker 1: Marrying those two I think really makes for UM, you know,
Speaker 1: a phenomenal quantitative investor. Uh, quite quite interesting. And our
Speaker 1: final question, what do you know about the world of
Speaker 1: quantitative investing in trading today that you wish you knew
Speaker 1: years ago when you were first starting out UM. But
Speaker 1: I would say, besides buying UM it was a monster beverage,
Speaker 1: which I think is up about six hundred thousand percent.
Speaker 1: The SMP is only a less than a thousand percent UM,
Speaker 1: and I would say, I would say, there's there's really
Speaker 1: nothing I would want to know in advance. And it
Speaker 1: might sound a little weird, but I think it spoils
Speaker 1: the excitement. I'm one of the great things about being
Speaker 1: in this quantitative business that really finance in general, is
Speaker 1: just the expert exploration and the quest for learning. That's
Speaker 1: something that has driven me, you know in my career
Speaker 1: that I've I've truly enjoyed and and knowing you know stuff,
Speaker 1: would you know what would kind of spoil that journey?
Speaker 1: And so, you know, I the hiccups that I've had
Speaker 1: across the around the years and and the successes I
Speaker 1: think have made the journey awesome. And I'd say respectfully,
Speaker 1: No thanks on on you know the other pieces, because
Speaker 1: it wouldn't have made the journey is fun. We have
Speaker 1: been speaking with Gary Kropovka. He is the president of
Speaker 1: World Quantz. If you enjoy this conversation, well please check
Speaker 1: out any of our previous almost four hundred prior conversations.
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Speaker 1: your podcast fix. We love your comments, feedback and suggestions
Speaker 1: right to us at m IB podcast at Bloomberg dot net.
Speaker 1: Sign up for my daily reads at ridoltz dot com.
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Speaker 1: audio engineer. Michael Boyle is my producer. Attika Valbrunn is
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Speaker 1: I'm Barry Ritholtz. You've been listening to Master's Business on
Speaker 1: Bloomberg Radio.