YouSaid · the spoken record

Michael Recce

lines on the record: 62
first: 2018-06-12
most recent: 2018-06-12
sittings or episodes: 1
sources: podcast

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“Yeah, that's a great question. So I get asked that question by lots of people that'll say, well, credit card data has been out there forever. Everyone has it. So why isn't it just completely commoditized? Why would I spend money on credit card data? And I think the key issue here is data is data and everyone can have data, but information is something completely different. And what you do with that data in order to extract information is key. So there's lots of things you want to do with that data in order to make the information much more rich. So for example, one of the things we think about is, well, let me back up for a second. In my internet company, we measure demographics for free for web pages. That was our free service, and we were an advertising company. It still are, Quantcast. But what we do is take the, you could take all the credit card spend or all the online activity and infer the gender, age, income level, and all these other demographics of the people. And then you can figure out what's happening in this company's customer base. So Lululemon is increasing their appeal to male customers. It used to be just a little blips in Q4 where they'd go buy something for their girlfriend.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“And that gives us a little bit of a wiggle that we can add to our quant strategy. And that's just really easing into it from the quant's view. And from the fundamental view, you could say, well, look, I'm going to hire a super analyst who can go scrape the web for me. He can go find this magic parameter for me. Then I'll manually put it in my spreadsheet. And that's easing into this process, if you want, of using more quant type methods in your discretionary process. But what we're interested in is going right at the middle. Build models of the business automatically with computers and use quants. If you can think of it as a second generation of quant, while there's lots of opportunities just to find mispricing, go for it. But as that disappears, what you want is just to build computers to implement the way that a fundamental person thinks about a business in much more detail.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Based upon data What we're interested in is actually using the data to understand how healthy the company is. And there's lots of reasons why that's a longer term and better deeper strategy, because essentially the nice thing about companies is they're relatively stationary and fluctuations in the market are classically nonstationary. But we can come back to that issue. But the point I would just make is that, let me parody for a moment the two extremes. So typical thought process is you know a little bit about a lot of companies and you have to actually begin lots of companies to avoid tilts of any form that you don't want to predict. And so I describe them as an inch deep and a mile wide. Discretionary folks know a lot about a very small number of companies, but they still make money in their book. And so I describe them as an inch wide and a mile deep. And if you imagine those two axes next to each other, there's lots of different variants that are in between. And so there's some variants which are very close to the quant approach, which is, hey, let's take something like sentiment and analyst reports. Use natural language processing to evaluate it. We have 10 years of history across the whole market.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Other demographics. And so all that type of information we can use the data to get. And a key point which we should talk about at some point is the whole technology stack because essentially this all has to sit on top of a technology stack. So why describe what we want to do is building Zillow for the stock market. You want to essentially build a model. You know, Zillow is implemented sort of a form of automated valuation of property, which people used to do. Maybe it's not as good, certainly not as good as the best valuation person who would value property, but it's automatic. And so what you want to build as a first step something which automatically values companies before you look at the price in the market.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“With businesses, know about mergers and acquisitions in order to figure out what these things are doing in terms of helping a business. And then you want to take that information, put it into a model of the business. Now, I would argue that if all you do is roll that up and try to come up with a top line revenue, why did you need the granular data after all? Essentially, you're just defeating yourself. And so what you want to do is understand the business at the granular level. And the way I think about that is the spreadsheet model of a discretionary investor. So if you populate the spreadsheet model with information you're getting from the real world, in fact, you want it to be even more granular than their typical model. I mean, I would say to a discretionary investor, well, you know, you're a busy guy. It's hard to update your 50 companies, 100 companies. If you had someone updating it for you, how would you even more elaborate your model? Let's elaborate it that way. Or another way of saying it is you're buying a public company, which means you get to see public accounting statements. But if you bought a private company, you get a data room. What would you want to see in the data room? You know, maybe you want to see their online sales. Maybe you want to see their overlap with Amazon. Maybe you want to see how they're spreading.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“So let me talk about the process of starting point to end point of what you do with the data, and then we dig down in some more detail. So there's a data sourcing problem because lots of data in the world, some people think their data is very valuable, some people don't realize the value of their data. So you have to go find the data. The data tends to be transactional. And so think about like a credit card transaction line or a line in your bank statement or one visit to a webpage. And the thing is that some data is more useful than others. So the weather predicts consumer behavior. It's nice in New York today. People will go shopping. If you have their cell phone location, you know they actually went shopping. At least they took their cell phone there. If you have credit card transactions, you know what they spent. So not all data is equally valuable, but you get this data. And then once you get the data, you have to figure out what the businesses that is involved in the process. And so you look at a transaction. It could be that there's no public business in it. It might be interested in private companies too, but it could be that there could be three businesses. You could have used PayPal through Expedia to buy United Airlines flight. And so you have to break down these transactions, know about brands associated with...”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so one example which has been published in blogs by places like Second Measure is when Pluay printed an IPO. And again, if you look at Blue Apron from its IPO documents, it looks like a company that has customers going up into the right and has revenue going up into the right. But if you break it down into cohorts of individual customers based upon when they join the firm, you can look at the cost of acquisition of each of those tranches of customers based upon the advertising.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Who can give you a couple of concrete examples? And largely it has to do with if you think about the high-level financial statement, we're treating lots of things if you want as scalars, as single numbers like the temperature, like same-store sales and things like that. But really, the businesses are much more distributed than that. So it could be that some stores are doing really well or some customers are actually great customers. But there's the long tail of a little bit of commerce from lots of other customers. And what the data allow you to do is to really understand what's happening in the business in enough detail to know what the future of the business looks like.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Would be helpful. The idea is that there's lots of information that's in the world that's not in the market. And a lot of these data are in things like people's navigation. So Mark Zuckerberg was just in front of Congress. And part of the concern was the creatives that were being shown by Russian money. But the other concern was that advertising starting to feel a little bit strange because it's so well targeted. In the period of time that I was in the advertising space, advertising went from just pretty much spray and prey to pretty accurate targeting of advertising. But if I know what ad to show you, then I know what product you're interested in. If I know that across all geographies and all products, I know who's winning in the marketplace today. And I would argue that information is not priced into the market. So it's really all this information, I call it digital residue left over from inexpensive electronics that's laying around in the world that we can sort of scoop up and to figure out who's actually winning in the marketplace.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“All asset classes, not just equities and certainly not just events, and they're a long-term investor. So we get to broaden out how to use data across lots of different types of investing. And the third of employers is Newberg Berman, where I work now, and I've been there about a year, also as chief data scientist. I like to think of it as Goldilocks, so too hot, too cold, and”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“The second business was analyzing people's online activity to figure out what ad to show them. So, in that business, about a million times a second, someone goes to a webpage and you have a tenth of a second to decide what ad to show them based upon their history of their Clickstream activity and how much to bid for it. And so the reason why that's relevant is you'll see that those types of data actually end up being exactly types of data you need to look at. And the machine learning background turned out to be pretty helpful too. But for about 15 years before being recruited from that second business by Steve Cohen to join 0.72, I was working essentially for my student running these firms. And the second firm, we were about 1,000 people when I left. I was running engineering. I used to say at conferences, if you have really good students, they employ you. But then I went to work for Steve Cohen as chief data scientist there. And we were on the discretionary side of the business, essentially trying to use data to help predict the direction of earning surprise. So I was there for 15 months. The second employer was GIC, Singapore Sovereign Wealth Fund, and I was chief data scientist there. And there we're looking across.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay, sure, thanks. Great to be here. So I think it's probably better to start before the investing industry because by happenstance, I ended up doing things which turned out to be very useful. So my initial background was in math and physics. I did graduate work in physics. I abandoned the PhD to go work for Intel. After five years at Intel, I could tick the box, I could earn a living, and didn't really want my boss's job. I was in my late 20s. So I thought, well, what do I want to do? I want to be an AI researcher. I knew enough computer science and engineering, but I didn't know anything about biology. So I did a PhD in neuroscience so I could learn some biology and become a professor teaching medical students about the brain, teaching computer scientists about machine learning, graduated about 12 PhDs, but I missed the impact of being an industry. So I helped my students start a couple of businesses. The first one, we were analyzing bank transactions to find white color crime. So we were looking for anti-money laundering and we're looking for doing some trade surveillance and things like that. We had 18 of the top 25 international banks as customers when we sold the business to Wabri Pinkis in 2005.”
2018-06-12 · Invest Like the Best · Michael Recce – Tim Cook’s Dashboard - [Invest Like the Best, EP.91] · IDENTIFIED FROM THE TRANSCRIPT · source