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And, you know, therein began, I think the unraveling and, and a little bit of the, the loss of that, you know, cultural juice that had kind of historically made that firm special. Barry Ritholtz : And you, you mentioned the investment in technology and people and the ability to scale at your size. I don’t wanna experience loss.
Yeah, you have to, you know, the conceit of finance is that basically the math is all there is to it. So you mentioned half math, half Shakespeare. Let’s talk about the math side. Ivanka said, oh no, you don’t have to be able to do math to do real estate 00:20:13 [Speaker Changed] Or investing for that math.
Capital One reported a robust second-quarter performance as the bank had increased spending and lowered losses in its credit card business. Chairman and CEO Richard Fairbank said the company showed strong year-over-year growth in pretax income, driven by revenue growth and significant improvements in provision for credit loss.
Michael: So, it sounds like part of the challenge was, you live in a large company environment where, as is common for a lot of them, they organized study groups of top advisors, of top producers, of those that are doing well and growing well, and driving the business profitably. In fact, we probably would have been much more profitable.
Perhaps the most glowing of reviews is related to the iris scanning technology that eliminates the need to have a fingerprint unlock the phone. Authenticating the consumer to mobile banking apps and payments give this technology the potential to unleash a lot of commerce opportunities. Iris Scanning. Dynamic Pricing Algorithms.
I — I loved math, but really, I was going to go down that literature route more than anything else and — and study Spanish literature. And the last piece of it, which I’ve become really passionate about over the past really kind of five to 10 years of my career is the technology and platform. I was econ and kind of geeky.
He’s a loss leader.” Again, if you’re thinking 60 or 90 prospects, and if you only convert 20%, and if you just think the average case being $500,000 to $1 million, you can quickly do the math and go, “Well, this makes money.” ” Michael: And so, then what was the whiteboard flow? Terry: Panic.
.” RITHOLTZ: So people also should realize, for those of you who’ve never traded futures, it’s not like options where essentially you could put up your losses in advance and all they could do is go to zero. RITHOLTZ: Put up your losses in advance. And so it’s one of these things that math works.
Because a lot of the Stanford MBA graduates tend to find their way into technology, not finance. It’s a matter of making better decisions and being more profitable. That’s an amazing lesson in life, right, to take failure and losses as business as usual. Is it technology, market structure? MIELLE: Right.
00:03:14 [Mike Greene] So that was actually an outgrowth from my experience coming out of Wharton and you mentioned the, the, you know, the transition of people who tended to be skilled at math or physics into finance. So the actual source of profitability in that trade is not the level of the vix, but the shape of the vol surface.
So I think that resiliency piece, never giving up, never giving in, redefining, Barry, success as going from failure to failure without loss of enthusiasm, I think that’s everything. And like every business, they want revenue and they’d like to have a surplus profit. BRYANT: So money, unlike math, money is highly emotional.
Barry Ritholtz : Erika Ayers Badan : So you end up going from ad agencies to technology, you’re at Microsoft, you’re at a OL, you’re at Yahoo. So I got my first taste of using technology and content and a user interface to deliver something to a consumer and also to pay, pay off a brand marketing message.
So I, I did a math degree at Oxford, which is more pure math. You know, pure math can be very theoretical and detached from the real world, and it’s getting worse. And they go on longer and longer and obviously more profitable for the states that run the lottery. And then I was looking for something more applied.
But as a private equity owner, again, first of all, you do invest heavily of your own money in the transactions, plus you have additional ownership through, you know, the carried interest, the profits interests. You got 60 percent of losses ahead of you. And it was considered one of the first grade kind of technological deals.
And I was a math nerd as a kid. They announced a $640 million loss and ouch. But if, if it has a history of not being profitable, you you really want to exclude that. The visibility on earnings they grew but they stayed profitable as, as they grew. So big loss. So I took that. That was real money. Real money.
I’m good at math and science and you know, I always had an idea what go into business, but I felt that electrical engineering would be a good foundation. You know, I, it always, I I see different numbers all the time, so it’s always kinda like, who’s math if you will? 00:02:16 [Speaker Changed] Me too.
The ability to use an anonymous single currency to power a decentralized, permissionless distributed ledger operating over the public internet where miners compete to solve the math problems that enable the processing of transactions is a remarkable innovation. They buy tokens at a discount and resell them for big profits almost immediately.
And so, so we sort of felt pretty stupid for a while because we did a lot of losing trades in 2006 that were the, you know, that obviously didn’t come to fruition until the actual people could see the losses. So in mortgages, the borrower can stop paying maybe a year to two years before the lenders actually book a loss.
Because to me, what was interesting about crypto at that point was, I mean the technology’s interesting. Because he was all sure he was a totally isolated math. So, so he’s brilliant at math. He goes to m i t to study, study physics and math. But in math camp, he’s not the best. Of course he did.
Jeffrey Sherman : Well, what it was was, so I, as I said, with applications, there’s many applications of math, and the usually obvious one is physics. Barry Ritholtz : It seems that some people are math people and some people are not. The, the math came easier. And I really hated physics, really. It’s so true.
So when I was at this very fancy private school that I was at as a kid, I did math because it gave me a huge amount of free time to do the things I really cared about. But when I got to Cambridge, you know, the math was sort of serious there. So, you know, I took my math into statistics and things. Am I getting right?
You’re doing a lot of math in your head on the Fly. I’m doing, I’m doing an awful lot of math in my head on the fly. He knows how to manage risk, and he knows how to trade for a profit for a p and l. And occasionally people are gonna argue about, Hey, who has this loss? Or who has this profit?
And I, and I really like the application of math and statistics and computer science to markets. You learn the math that can help you with, with market making operations. You learn the technology. It’s just not smart on a math basis to do that. And I just caught the bug. It’s a really broad field.
Colin Camerer : So I, some of it was when I was in college at Johns Hopkins, I, I studied physics and math. And there was people, Physics didn’t have, people, psychology didn’t have math, economics was kind of the right mix. The math doesn’t math. That was too abstract. Yeah, I’m gonna vote.
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