Posts filed under “Quantitative”

Financials as Percentage of S&P500 Market Cap

Earlier this week, we looked at the impact the financials had on the S&P. Today, I want to bring two charts to your attention that might give you some pause.

The first is from Ron Griess (The Chart Store), showing NYSE market cap as a percentage of GDP. It indirectly relates  stock prices and valuation to 0verall US economic activity. This acts as a ratio: How active are bankers, speculators, traders, etc. relative to other activity?

A more direct version comes from John Roque of WJB Capital. John took the market capitalization of the Financials versus the SPX cap. You can readily see how far above the median we have been since the mid-1990s. (I can only partially blame Alan Greenspan’s easy money for this).

Combine these two charts, and you get a sense of what happens  when Finance is dominant versus other sectors.


NYSE Market Cap vs Nominal GDP


Financial market cap as a Percentage of S&P500

Category: Economy, Markets, Quantitative, Technical Analysis, Valuation

ECRI: Global Slowdown to Hit by Summer


Global Slowdown to Hit by Summer, Even for U.S., Says Achuthan
Stacy Curtin
Yahoo Daily Ticker

Category: Cycles, Economy, Quantitative, Video

First Three Days in May

The equity market has made a little bit history in the first three days in May.  Only four other times in the last fifty years has the S&p500 opened May with three consecutive down days. Bespoke did some great work yesterday analyzing the first two consecutive down days in the new month and we thought we’d add…Read More

Category: Investing, Markets, Quantitative

Birthdays and Investment Risk

Birthdays and Investment Risk By John Mauldin April 4, 2011 > “Tail risk (the risk of large losses) is dramatically underestimated by many investors and the tools we have available to manage such risks are hopelessly inadequate. Financial theory which is taught at business schools and universities all over the world is plainly wrong.” This…Read More

Category: Investing, Philosophy, Quantitative, Think Tank

Soc Gen’s Economic Surprise Indicator

Alain Bokobza of the Société Générale Quant team, writes that their “Economic surprise indicator” suggests risky assets are now technically vulnerable: “After undergoing a massive rally since last September, risky assets are now technically vulnerable: SG Quant sentiment indicator is close to an all-time high, economic revisions have rarely such a high percentage of upgrades,…Read More

Category: Markets, Quantitative, Technical Analysis


SENIOR SOFTWARE ENGINEER / ARCHITECT Skills Required Java/J2EE, MySQL, PHP, Servlets, Apache, JSP, Linux, Financial Algorithms What you NEED for this position: – 7+ years industry professional experience, – 5+ years of recent engineering experience in building J2EE applications with front end components. – 5+ years of recent engineering experience in LAMP stack – Linux,…Read More

Category: Quantitative, Web/Tech

Scraping Twitter to Find the Mood of the Monkeys

Bloomberg reported yesterday that the Derwent Absolute Return Fund was seeded with an initial 25 million pounds ($39 million) and will begin trading in February. Its model? Following posts on Twitter, and tracking emotionally significant words to anticipate the market’s next jag up or down. A recent study concluded that short term market moves can…Read More

Category: Psychology, Quantitative, Technology

History of Atmospheric Carbon Changes

Huge NYT article on Charles David Keeling, the scientist who first measured the increased carbon in the atmosphere. The Keeling curve, as its now known, shows a steady increase in CO2 concentrations in our air over the past century. Keeling also discovered the seasonal variations of CO2 in the atmosphere. I thought the biography of…Read More

Category: Data Analysis, Quantitative, Science

Part II: A Conversation with Scott Patterson, The Quants

Scott Patterson covered the markets as a reporter for the Wall Street Journal during the market run up, credit crisis and collapse.

He details the impact in his book The Quants — a highly readable, very entertaining look at the new breed of mathematicians and financial engineers who got caught in the middle of it all.

I spent some time with Scott chatting about the book, the players in it, and life after the WSJ.

Yesterday, was Part I of our interview; Here is part II


Barry Ritholtz: So if this went in in 2008, the question I was leading up to earlier was…let’s go through some of the characters and find out what happened to them, it’s now two, almost three years later.

Did anybody blow up, did anybody recover? What’s the net takeaway?

Scott Patterson:: Ken Griffin and Citadel is a good example, in late 2008, as I was trying to put the finishing touches on this book, and Ken is a guy that I’ve been following, and he’s really interesting in the arc of this book. Thorp helps set up Citadel, and he actually teaches Griffin some of his trading strategies, he gives him a lot of his own documents and papers, sort of passes the baton.

Q: Does Thorp have a piece of Citadel?

A: He was invested in Citadel from the get-go, so he followed Citadel, and then in 2008, Citadel came a hair’s breadth from imploding, they were totally on the edge, the banks were…

Q: Almost out of capital?

A: Yeah, a lot of it is theoretical, because there’s a lot of derivatives involved, they had exposures all across Wall Street, and they lost billions of dollars, five or six billion dollars. Their main hedge funds, Kensington and Wellington, were down about 55 percent, and these were 15, 16 billion dollar hedge funds. I don’t know if you remember, but there was a time when there were a lot of rumors about Citadel, it was freaking everybody out, because if they went down, they had this massive convertible bond portfolio that would have flooded across the market, it would have been just another domino to fall that would have pushed us closer to that Armageddon scenario that people were worried about.

Q: Long Term Capital Management with a lot more funds sitting right on top of them.

A: Yeah, with leverage, they had 160 to maybe 170 billion in positions, so it was a massive amount. They steadied the ship in ’09, and the convertible bond market had a comeback, and they’re still somewhat wounded, I don’t know if Ken is ever going to get to the top of the heap like he was.

Q: I saw him speak this summer, and I thought he was really interesting and intelligent. There was a bit of an ego between these four guys on the panel at the Saltbridge Conference in Vegas– what was your impression with some of them in terms of dealing with their egos, and why did they want to speak? Most of them don’t want to reveal the secrets and don’t want publicity.

A: Part of it, I guess it’s two things, some people want their story to be told, and I started reporting this book in early 2008 when things were bad, but they didn’t look that bad.

Q: We were in a cyclical recession.

A: Right, Ken Griffin had said that he thought the market would go through a blip in early 2008 and things would come roaring back, which is why they were putting more leverage on at Citadel. Eddie Lampert is the guy who’s not a quant, he was kidnapped…but it’s a mix, and part of it is just being a reporter, like with Pete Muller, he definitely didn’t want to talk to me, but I got enough information about PDT and him and talking to other people that he realized that he should at least try to engage with me. With Pete, it was on and off throughout the whole period.

Q: That’s the Bob Woodward approach.

A: That’s a classic thing, we call it smoke them out of their holes.

Q: That was done in ‘Too Big to Fail,’ where [NYT reporter Andrew Ross] Sorkin seemed to get them on the phone, and say “If you don’t want to tell me your side, we’ll just go with what Jamie Dimon said.” People don’t want to let someone else paint their biography.

Talk a little about Deutsche Bank and Boaz Weinstein. At one time, Deutsche Bank’s trading arm was a monster.

A: And their credit derivatives desk, their bond desk, was one of the biggest in the country, if not the world. At the top of it was this guy, Boaz Weinstein, who’s part of this poker group, he’s friends with Pete Muller and Cliff Asness and other guys who, as I write about in the book, they have this monthly poker game in the city, and he’s part of that. Boaz was positioned perfectly to ride the derivatives boom that started in the late Nineties, he was on Deutsche Bank’s desk when credit default swaps first came out, he was one of the first people to ever trade a credit default swap.

A: Early adopter, loved the asset class…

Q: He helped spread them around the industry, he’d go on these calls to pension funds and banks and say, “We’ve got this cool new thing, credit default swap, you should try it,” because they’re looking for counter-parties to make a market, so he helped create the market, he came up with a strategy called capital structure arbitrage…it’s an arbitrage between the stocks and debt, and he’s using a credit default swap to do the trade.

Q: So it’s a debt equity arbitrage.

A: Yeah.

Q: Amongst the same stock – if you have Lehman, you might be short.

A: He would discover inefficiencies between the price of the stock and the bond and became really good at putting these trades on, so he ended up running Deutsche Bank’s global bond desk at the age of 33, and he was in charge of this other prop trading arm at Deutsche Bank that he called ‘saba,’ which is a Hebrew word for ‘grandfather,’ and he was this incredibly powerful guy making huge bets…

Q: And a kid, essentially.

A: Yeah, but in a way, he was representing the evolution of Wall Street, the older guys who were used to playing vanilla bonds, they had no idea how to use these new derivatives, and to him, it was natural, that’s just how he grew up trading, so it was an evolution of the market, he road that wave, he was very good at it, and when Lehman went down, the CDS market just froze, and it screwed up his trades, because he’d hedged these positions with CDS, and the CDS market just froze, it wasn’t moving, so he ended up having these losses on his books that if the CDS market was working as it should have, he probably would have been OK, but it didn’t, and he was using quantitative formulas to put all these trades together, and it’s just another example of how when things don’t work out in panics, which seems to happen a lot on Wall Street, these very careful, calibrated trades, if you’re using a lot of leverage, which he was, can blow up in your face, and they ended up losing about two billion dollars in the course of about a month or two.

Q: Which, in the scheme of things, is not a huge amount of money relative to what it threw off in profits. Some shops seem to have wiped out previous decades worth of profits.

A: When you add up how much he’d made over the past few years to how much he lost, he ended up kind of flat.

Q: So he gave back all the profits he made?

A: Yeah, it looks like Boaz did not make money for Deutsche Bank over the three or four years leading up to, at least on that prop desk. Now he was also running the flow desk, which can raise questions itself, Chinese walls…he was in charge of that flow desk, which had billions of dollars flowing through it, and I’m sure they were profitable.

Q: I was going to ask about the Gaussian Copula, but I don’t know if you really want to get that far into the weeds.

A: It’s difficult to talk about, it’s the formula that most of Wall Street was using, and the rating agencies, to price these CDOs or synthetic CDOs, more than anything, the bundles of credit default swaps that were designed to mimic cash CDOs, and they were basically, in a nutshell, trying to calculate the correlations between the various tranches of the synthetic CDOs, and it was a very complicated formula. It was also based on correlation, so if one tranche of triple As is trading at 99 cents on the dollar based on historical performance, the triple B tranche is going to be at 92, so you ended up having, based on this formula, a new breed of trader that rose up in Wall Street in the 2000s called correlation traders, and they were making bets on the various tranches of synthetic CDOs, shorting some tranches, going long other tranches, using the model, and that is basically what blew up Morgan Stanley. Morgan Stanley was doing correlation bets on synthetic CDOs.

Q: And heavily leaned into it.

A: Yeah.

Q: How much of what took place…when you trade straight up stocks or bonds, there’s an exchange, the trade is guaranteed to clear, and it’s so liquid, unless you’re trading some of these stupid penny stocks. You want to sell 100 million shares of Cisco, you can. If you need to get out of millions of shares of Apple or Citigroup, you could move billions of dollars pretty easily.

How much of the problems that someone like Boaz ran into is the fact that this is really a bespoke investment, and you’re like, “Let me find somebody…” No one sets up a hedge fund that they’re going to fill with ‘Star Wars’ collectables and Beanie Babies, because the zero liquidity, they have to sell it in a panic, there’s nobody on the other side, as opposed to a market with a market-maker, although since the flash crash, that’s even arguable these days.

But when we’re looking at these credit default swaps and they’re frozen, how do you go from a position where you’re essentially fully-hedged and can’t take the loss, because the worse this gets, the better that gets, to it blows up on you anyway? How do you work around that?

A: I think in a way, you’re talking about how a dealer market works, and it’s a dark market, it’s opaque. The dealers control it, and they know what the prices are, so that’s how the stock market…the NASDAQ market used to be like that, it was controlled by dealers. On black Monday in October 1987, the dealers just walked away from the phones, and you couldn’t trade, so the market froze. That changed with the rise of electronic markets, things became a lot more transparent.

Q: Is this the inevitable outcome of the post-’87 crash, that as we’ve moved to electronics and computers, we’ve made ourselves vulnerable to Skynet setting up a trading system?

A: I think that the electronic markets bring some real positive benefits. The U.S. stock market has become a lot more transparent in many ways, although we have dark pools and high frequency firms, I think things have gotten to a level of complexity that maybe it’s shifting into the dark again.

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Category: Quantitative

A Conversation with Scott Patterson, The Quants

Scott Patterson covered the markets as a reporter for the Wall Street Journal during the market run up, credit crisis and collapse.

He details the impact in his book The Quants — a highly readable, very entertaining look at the new breed of mathematicians and financial engineers who got caught in the middle of it all — it was one of my favorite books of the financial crisis.

I spent some time with Scott chatting about the book, the players in it, and life after the WSJ.

Part II will appear tomorrow.


Barry Ritholtz: I am sitting here with Scott Patterson, author of the book ‘The Quants,’ staff reporter for the ‘Wall Street Journal…’

Scott Patterson: Former staff reporter. I’m on my own, I’m freelancing.

Barry Ritholtz: How do you like that?

Scott Patterson: I kind of love it.

Q: A lot of people have had a hard time making a go of it. I use Dan Gross as the standard-bearer for freelancing for the ‘New York Times’ and Slate and eventually ‘Newsweek,’ and when ‘Newsweek’ imploded, ended up at Yahoo Tech Ticker. Who else are you publishing for if you’re not regular with the ‘Journal’ now?

A: Whoever will take me, basically. Whoever pays the most. I’m mostly working on this new book and focusing mostly on that.

Q: What’s the new book going to be?

A: It’s about the history of electronic trading and markets, high frequency trading and where all this HFT stuff came from. It’s a very fascinating story, I’m learning a lot as I go.

Q: Let’s talk about your background. For a scribe, you have a lot of mathematical-leaning interests. Where did you go to school for undergraduate?

A: Completely no math, I’m an English liberal arts guy, I studied anthropology. I think maybe my connection to this comes from my anthropological background, because I sort of see these quants as being a subculture of Wall Street, they all hang out together, they have their strange little things that they do, their rituals, their language, so in a way, you could see this book as being like my journey into the heart of quant-land.

Q: So the Cro-Magnon essentially pushing aside the Neanderthals who spend their time doing silly stuff like fundamental research.

A: Right, gut traders.

Q: Well, that’s a whole different group. Where did you go to school?

A: I went to James Madison in Virginia.

Q: Did you keep going, any graduate work?

A: I’ve got a master of arts and English.

Q: So zero math…

A: I took math courses, I took statistics and some math in college, but it definitely wasn’t my focus. I can’t say I was really that good at it, but I understand the basics of how these guys operate, and what I find is you just ask them over and over again to explain what they’re doing, and you ask 10 different people and you’ll eventually get it. It’s really not that complicated, although some of the things they do do get so crazy and so complicated that I don’t think anybody really understands it.

Q: In my arc of bailout/crash books, “Quants” is the follow-up to “The Myth of the Rational Market’” — that is the economic, philosophical, “How did we get to this silly belief?” “Myth” approached this from the economic academic perspective, then your book comes at it from the mathematical traders perspective

There’s a terrific data point that James Montier used in one of his books on behavioral investing that says that IPOs are essentially giant money-losers, and yet people are always clamoring for them, and if the market was really rational, this wouldn’t happen, nor would any of these bubbles nor would any of these 100-year collapses that seem to come along every couple years. “The Quants” was a great counterpoint to this.

Q: I think this whole idea of rational markets, from an outsider’s perspective, when you come into the world of Wall Street and you see these theories, the efficient market hypothesis and whatever, you just scratch your head and wonder, “Where did these guys come up with this?” because it’s patently obvious that Wall Street is not about rational mathematical behavior, it’s about the polar opposite of that, it’s about greed and fear, and I think that basically, these quantitative models need to assume a rational market as a starting point, because if the market doesn’t act in some form of predictable, rational, mathematical way, you can throw it all out the window and forget it and go home and do something else.

Q: There’s a spectrum, on the one hand, you have the belief that markets are perfectly efficient and rational. Then there’s a belief that it’s completely and totally random, and the truth, as it often is, lies somewhere in the middle, where there are times that it’s somewhat predictable, the trend continues on. There are times when stuff is just insanely random from day to day, and there are times when you could use history as a guide up to a point, and others where it just veers away from it.

A: It works sometimes, I think a lot of times it’s self-reinforcing. You have these rational models that people started using, and lo and behold, the market starts behaving that way, because so much money is being put in these models, and yes, you can predict it, and smart people say, “This is how the market’s working, it’s rational, it’s efficient, it goes out of equilibrium and comes back into equilibrium.” I had this idea I wrote about in the book called the truth, which is shorthand for this belief that the market is rational, and people have told me, “That’s BS, these guys don’t believe in a truth,” but actually, some of them do, and I’ve had them tell me that, that they believe that there is this mythical truth, underlying how the market works, and that if you can figure it out, then you will be rich beyond your wildest dreams, so that’s not made up.

Q: They’ve drank the Kool-Aid and they ate their own dog food and really believe, as opposed to saying, “Hey, we’re not going to get this perfect, but here’s a way to kind of get an edge over everybody else.” Todd Harrison says this all the time: “Does technical analysis work because the levels matter or do the levels matter because everyone else is watching the same technical levels?” The question is, is it a function of true TA or that it’s the Keynesian beauty contest, you’re not voting for who you think is the prettiest girl, you’re voting for second derivative, who you think everybody else thinks is the prettiest girl.

A: Right, it’s game theory. A lot of these guys are poker players who I write about.

Q: Lets talk about the book. I was looking forward to reading this, and I was ready for something dry and tedious, and you start the book out with the big annual quant poker game, which really just grabs you. Please talk about that poker event, it really sets the table for the parade of characters and everything that comes across. You would think math geeks wouldn’t have quite as many characters, but they’re fascinating guys. How did you come across the big poker game?

A: I loved that scene, because it let me put all of these people in the same room together, which is right up the street here in the St. Regis Hotel (55th & 5th), and I was writing an article for the Wall Street Journal about the quants after the quant meltdown in August 2007 and focusing on this Morgan Stanley group, Process-Driven Trading, which is run by Peter Muller. Peter Muller, as I quickly found out, is a poker fanatic, and I learned just doing some web searches that the previous year, he had been in this poker tournament that is put on by Jim Simons of Renaissance Technologies, and Peter also helps run it, and he played against Cliff Asness, the founder of AQR, another big quant shop, in the finals of the tournament, and everybody had heard of Cliff. Cliff is a famous quant, but nobody’s ever heard of Peter Muller.

Q: Even though he’s running Morgan Stanley’s quant desk?

A: Right, very secretive guy, that’s one of the things that really fascinated me about him.

Q: And Morgan Stanley’s desk is not insubstantial, that’s a couple of billion dollars.

A: They, at the time, were the biggest equities trading desk at Morgan Stanley, they had five billion dollars or something like that, and nobody ever heard of them, I talked to Todd, who worked at Morgan Stanley, Todd Harrison, and I said, “Have you ever heard of PDT?” PDT’s been there since the early Nineties, back when Todd was there, and he never heard of him. Other people I talked to had never heard of them, they were secretive within Morgan Stanley, not just outside of it, but it was a super-secret group. That’s one thing I loved about it, was cracking inside of them. They love poker, and they equate that with trading and mathematizing it.

Q: It’s statistical, rule-driven, with elements of chance and you’re basically making probabilistic bets based on, “What are the odds based of this event occurring,” there’s some emotionality, because in poker, you are also playing the man. In many ways, there are enough parallels that people can say, “This is related…” I’ve heard guys say, “He’s a good poker player, I’ll hire him as a trader.” In reality, the skill set is very, very different. The touch points that are similar in a narrative make you feel like it is, but there are plenty of great traders who aren’t good poker players, and vice-versa. You can see that mano-a-mano competitiveness in the first chapter, you go over that personality-driven attitude.  From “Liar’s Poker” we all know the expression ‘Big Swinging Dick’ (BSD), so there’s a little ‘whose is bigger?’ as they’re sitting down at the table.

A: I wanted to bring the people alive and show that this is about rational mathematical-driven quant strategies, which, like you said, can be really dry, but what I wanted to show is that these are real human beings behind the machine and there is a human element to how all this stuff works. Cliff Asness, I wrote how he gets really, really upset in 2008 when everything is blowing up, he’s punching computers, there’s real human emotion there, and I don’t think there’s anything wrong with that, I think it just shows that we have markets in which people are trying to predict what happens based on these mathematical principles, but at the end of the day, you have the real human elements of fear and greed and all of that stuff mixed in, which leads to blow-ups and a lot of times, this stuff just doesn’t work.

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Category: Books, Quantitative