The best paid fund managers in 2007

[Shawn]

Originally posted in Guardian.co.uk

Manager's Name, City, Firm, Estimated Income

1. John Paulson, New York, Paulson & Co. $3bn
2. Phil Falcone, New York, Harbinger Capital Partners. $1.5bn-2bn
3. Jim Simons, New York, Renaissance Technologies. $1.5bn-$2bn
4. Steve Cohen, Connecticut, SAC Capital Advisors. $1bn-$1.5bn
5. Ken Griffin, Chicago, Citadel Investment Group. $1bn-$1.5bn
6. Chris Hohn, London, The Children's Investment Fund. $800m-$900m
7. Noam Gottesman, London, GLG Partners. $700m-$800m
8. Alan Howard, London, Brevan Howard Asset Management. $700m-$800m
9. Pierre Lagrange, London, GLG Partners. $700m-$800m
10. Paul Tudor Jones, Connecticut, Tudor Investment. $600m-$700m

 

[atreides]

Seems like despite the market downfall, the top shots are still making it big

 

[bigbadwolf]

Seems like despite the market downfall, the top shots are still making it big

Parasites, leeches, and vampires.

 

[dstefan]

I could be wrong, but I remember reading that these numbers include the return on the equity the managers have in their hedge funds.

 

[Dmytro]

i like how casually they treat $1.5-2 b :D
plus-minus $500.000.000

 

[Shawn]

Seems like despite the market downfall, the top shots are still making it big

especially when you think of that there might be more people who earns less than these guys but still over few millions........

 

[Andy Nguyen]

Here is a somewhat different list from Institutional Investor’s Alpha Magazine
http://www.telegraph.co.uk/money/main.jhtml?view=DETAILS&grid=&xml=/money/2008/04/16/bcnhedge116.xml

Alpha estimates managers' earnings based on assets under management, fees, returns, personal investments in the funds and ownership stakes in their firms.


Top 10 moneymakers in the hedge-fund industry in 2007
1 $3.7 billion, John Paulson, Paulson & Co
2 $2.9 billion, George Soros, Soros Fund Management
3 $2.8 billion, James Simons, Renaissance Technologies Corp.
4 $1.7 billion, Philip Falcone, Harbinger Capital Partners
5 $1.5 billion, Kenneth Griffin, Citadel Investment Group
6 $900 million, Steven Cohen, SAC Capital Advisors
7 $750 million, Timothy Barakett, Atticus Capital
8 $710 million, Stephen Mandel Jr, Lone Pine Capital
9 $625 million, John Griffin, Blue Ridge Capital
10 $520 million, Andreas Halvorsen, Viking Global Investors

 

[doug reich]

i like how casually they treat $1.5-2 b :D
plus-minus $500.000.000

Before and after taxes?

In a recent Berkshire Hathaway letter, Warren Buffett observes that Berkshire's tax bill ($4B I think) ran the entire federal government for 5 minutes or so. Take our billionaire earners here, and they each run the government for a minute each... assuming they pay taxes.

 

[IlyaKEightSix]

Sadly the only way to get a job at Renaissance is to get a phD in Math/CS/Physics from an Ivy League university. And with my engineering background, I'm far stronger applied than I am theoretically.

John Paulson I have to say had some steel ones to bet against the housing market way back when. It seems to have made him a kazillionaire overnight, though.

The only question is how the heck can one get a job to learn from these people?

 

[alain]

Sadly the only way to get a job at Renaissance is to get a phD in Math/CS/Physics from an Ivy League university.

This is not true since they use SUNY @ Stony Brook as a talent supply as well. On the other hand, from what I have read, they tend not to hire finance types but just hard science people and engineers.

If you want to learn, you can start like Simons and trade your own account, create a track record. He didn't learn working at an investment bank but doing stuff by himself.

 

[IlyaKEightSix]

This is not true since they use SUNY @ Stony Brook as a talent supply as well. On the other hand, from what I have read, they tend not to hire finance types but just hard science people and engineers.

If you want to learn, you can start like Simons and trade your own account, create a track record. He didn't learn working at an investment bank but doing stuff by himself.

Well this is why I want to trade currencies/control information at Goldman Sachs to have everyone short commodities and to drop oil and food to all time lows using financial engineering.

I'm a math kid at heart--always will be. Though I'm not sure how Simons started out when he had no knowledge. The first ten chapters of Hull's book say "let's say you believe a stock will go up. How can we speculate on that?"

What I want to see is "a stock has a stronger chance of going up than down if factors X, Y, and Z behave in such and such a fashion."

What's the use of all this knowledge if you're missing the most vital part--when to apply it?

I realize that at the same time, if there was a magical formula for predicting which way a security would move, everyone would hop onto it and nobody would make any money. But what do I need to learn in order to make educated bets? I'm taking my first finance courses this coming semester, but I definitely think that the billionaires in hedge funds and the upper echelons of Goldman Sachs know something more than I do about predicting the direction of the markets!

 

[doug reich]

What I want to see is "a stock has a stronger chance of going up than down if factors X, Y, and Z behave in such and such a fashion."

A lot of academic research goes on towards this end. Just today I was pointed to an article from 2000 on short interest and returns.

SSRN-An Investigation of the Informational Role of Short Interest in the Nasdsaq Market by Hemang Desai, S. Thiagarajan, K. Ramesh, Bala Balachandran

The literature review is funny because, like most of these papers, they say "prior researchers have found the exact opposite effect..."

There's plenty more where that came from.

 

[xoxqun]

Challenge to all Quant Modelers: Model This!

John Paulson
George Soros
James Simons
Philip Falcone
Kenneth Griffin
Steven Cohen
Timothy Barakett
Steven Cohen
Stephen Mandel Jr
John Griffin
O. Andreas Halvorsen

Challenge to all Quant Modelers: Model This!

What is the probability of the top-10 fund managers having graduated from a "top"-FE/Mat-Fin program (or having had a PhD in any of the hard science disciplines asked for in today's hedge fund ads)?
(As Mandelbrot notes in (Mis)Behavior of Markets, FE became popular since 1960s, therefore, one should expect to see many of these having FE or Mat Fin PhDs from what may be suggested by anecdotal discussions on these forums.)

[Solution: After you have created and run your model, click on the above links to check the accuracy of your model.]

What is the probability that each of the above top-10 will be in the top-10 next year or the year after?

If as Mandelbrot suggests we may ignore cause and effect and just do 'black box model' that looks at only input and (primarily) output (and not the causal logic Why?), how would one model the above problems?

[Solution: After having run the models, check what NNT says in Fooled by Randomness to answer the question how do we model what is random - what Mandelbrot calls 'rough'? More important question, how do we know that what we are modeling as random (stochastic) is _really_ random.]

 

[IlyaKEightSix]

They're all Ivy League high-powered people. I think that's good enough. Just makes me wonder what kind of a chance anyone else that's not the cream of the crop that couldn't even get into an Ivy has.

 

[xoxqun]

Model Again. Ivy or No Ivy, But ALL self-made.

No, that may not be good enough... model.

Not any Ivies here:

Paul Tudor Jones, Connecticut, Tudor Investment. $600m-$700m
(Read why he chose NOT to go to Harvard Business School)
John Griffin, Blue Ridge Capital, $600m-$700m
George Soros, Soros Fund Management, $2.9 billion
Alan Howard, Brevan Howard Asset Management. $700m-$800m (Chemical Engineering 1986, Imperial College)

Also, someone New York City's own who cleared about $200m in a recent year, was enrolled in college for two years after high school. If dollar figures are what one's interest is in, it may be even more interesting to look at the top 10 in the Forbes 100 / 400, one may find smaller percentage of Ivies among the super-rich. (There are 40% school dropouts in the top-10 in Forbes 100! How does one model that.) Therefore, if we see a correlation or a cause-effect relationship, that may be very well spurious. Despite similar outputs ($m/B) and similar inputs (Ivy, non-Ivy, BA, MBA), there seems to be some other more dominant factor at play here besides inputs and outputs.

Lesson learned: Whatever one's model or trade, ALWAYS carefully check the data and ALWAYS carefully review the assumptions.
Some other day we will revisit the issue of logic, which IMO is even more important than data (input/output) and assumptions, with due respect to Mandelbrot's thesis.

In our model of inputs-outputs, when one considers 'Ivy League high-powered people', one needs to specifically avoid self-confirmation bias. Here are some other data points that can really skew the reliability and validity of your model:
Kirk Wright, Jeffrey Skilling, Theodore Kaczynski, and similar others.

p.s. Here is a question about fractal geometry and all its fans, would appreciate hearing from you in this thread or another. Mandelbrot notes in The (Mis)Behavior of Markets (p. 116): "When a man has a hammer, all he sees around him are nails to hit. So it should be no great surprise that, with our small number of mathematical tools, we can find analogies between a wind tunnel and a Reuters screen." Is it plausible that when one's primary focus is on the tool (hammer or fractal geometry) it may possibly bias one to perceive every problem as a (nail or a fractal to be modeled)? What if one has a hammer, but is faced with what may likely be a screw and not a nail?

 

[IlyaKEightSix]

@ Kirk Wright: Ugh. Disgusting. What a waste of an education.
@ Jeff Skilling: Because apparently you're not rich enough till you break every law.
@ Theodore Kaczynski: This one astounds me. What a shame! He had every right to express his viewpoint, but why with all his knowledge, did he have to resort to what he did to get the attention?

But yes, you're right. I see why they call you devil's advocate. I have much to learn =)