A review of “The Man Who Solved the Market” (and “the Captain”)
Most systematic hedge funds are a racket; they either got lucky, or have a strategy that only works in one market regime. There’s a couple of hedge funds out there who have beat expectations year after year. Ed Thorpe’s Princeton Newport and its successor TGS Management is collectively one of them. Rentech is the one that lasted the longest, and is best known. They’ve also got the biggest bags and the principals were and are much more admirable people than the TGS principals. It helps that I actually know some of the people in the Rentech story, and people like Jim Simons are friends of a number of friends of mine, so it’s something I know a little bit about on a personal level. Rentech is also remarkable for the sheer density of actual great men involved. People who accomplished great things before and after their Rentech days. Let us name some of the names: Lenny Baum, Nick Patterson, Sandor Straus, Elwyn Berlekamp, James Ax, Bob Mercer, Henry Laufer, Robert Frey, Peter Brown and Jim Simons himself. It’s a lineup of machine learning, statistics and fundamental mathematics rock stars. They’re all very different personalities as well: though they were welded into one of the greatest and most successful firms which ever existed. The story is sort of like the great WW-2 movie, Kelly’s Heroes.
Probably the most important fact about this book is the fact that it was an unauthorized history of Rentech. As such, the people who talked were people with grievances; grievances dating back in some cases to the 1970s. I’m not sure how aware the author was of this psychological dynamic, but it was evident in the extreme to me. There are lots of specific examples I could point out where the history listed is questionable. This is valuable though, as by highlighting the social fractures, we can learn a lot about how Simons managed to weld these oddballs into a money-making machine. Imagine if Kelly’s Heroes was told from the point of view of harvesting anecdotes from Oddball, Petuko, Big Joe, Willard and the German Tank Commander. That’s what we have here. Actual anecdotes from Kelly (aka Jim Simons) and some of the other important characters is missing. And of course old beefs are going to seem more important to some people than they really were to everyone else at the time.
Simons always had hustle; he built a world class mathematics department at Stony Brook mostly through personal charm. He was also always a risk taker; driving a Vespa with a gang of scooter nerds from the East Coast to Columbia (oddly many of the known details of this trip are left out) before he went to grad school.
One of the amusing things about this account is the sepia toned 70s-ish of it the early days. Simons got up in the spirit of the times; being fired from the code-breaker squad for opposing the war in Vietnam, spending time on a psycologist’s couch -later doing primal scream therapy and having an early marriage go spectacularly sour. James Ax was also a stereotypical man of that time; a competitive, angry, genius womanizer-misanthrope living on a boat.
The early experiences of Simons and Lenny Baum are illustrative; they started out with an actual algorithm running on a PDP-11. This in itself was a huge innovation. Baum was one of the creators of the Hidden Markov Model; a tool which has direct applicability to financial problems. I assume they were using something like this, probably looking for trending states. They had problems with it though; one must remember at the time they were inventing a lot of things. Even using data from a database in making trades was pretty innovative, let alone using decent statistical modeling in making the trades. For a while they were just winging it trading on logic and instinct, to varying degrees of success, but ultimately this wasn’t a satisfactory solution for anyone. The stories are familiar to anyone who has ever tried it: discretionary trading is extremely stressful.
The next iteration, Axcom, was with James Ax and Sandor Straus. In this period the models grew more mathematically sophisticated; still using Markov ideas on Straus’ rapidly growing collection of intraday data. I think Sandor Straus deserves credit as the world’s first “data scientist.” His account of cleaning data is probably the earliest one of performing this task. Cleaning data is the fundamental task that defines data science as a role: statisticians and economists buy clean data from somebody. The team also used a lot of Kernel Regression in this era; something I know is still an important part of Rentech and its spinoffs, but which seems to be of little interest to anybody else but me; hell I can’t even get TDA people to look at it. The real breakthrough came, however, when Elwyn Berlekamp showed up, became a majority shareholder in Axcom and moved the firm into the Wells Fargo building in Berkeley. It’s obvious in hindsight Berlekamp treated it as a probabilist involved in error correction codes would; developing a technique for using multiple edges in one unified trading system. Though the book doesn’t say so he also probably added a rational bet-sizing system for optimizing to the geometric mean: a really sweet thing that only someone like Berlekamp would have thought of (to be fair, Thorp definitely thought of it as well). The team also narrowly avoided being caught up in a commodities broker going tits up in this era, which probably would have killed them in those days. It’s good to be lucky as well as smart.
Berlekamp and Simons had a difficult long-distance relationship, as remote work wasn’t a thing back then excepting for frequent phone calls. Frequent phone calls are incredibly annoying to people who are concentrating deeply. Eventually Simons bought him out and moved the rodeo to Long Island. Two important figures from the post Berlekamp days was cryptographer Nick Patterson and mathematician Henry Lauffer who were responsible for various of the innovations that we take for granted today, and a few which people would no doubt like to have access to. Robert Frey was also recruited from the Stab Art world. Another set of key hires in the 90s were Bob Mercer and Peter Brown; a couple of speech recognition specialists from IBM research (there’s that Markov model stuff again), and David Magerman, a programmer also from IBM research. Taciturn saturnian Mercer and talkative mercurial Brown seemed like Castor and Pollux; opposites who meshed well together like a couple of gears, grinding out wonderful results. Brown is still CEO of the company.
Magerman, on the other hand, seemed like an asshat. He converted the company from C to C++ to make himself more valuable (a complete waste of time; 90s era C++ mostly just adds complexity for no obvious benefit over C) and blew up a live trading system by backdooring a computer. Magerman seemed to bring some computer science discipline to a company filled with sloppy-coder mathematicians and he was obviously a crucial guy who solved important problems, but the dude was a jerk. People who are good at programming are often perfectionist mindset types; meticulous people who can track down a subtle bug or manage large amounts of complexity. Unfortunately what you get with that mindset are often …. jerks. People who throw things when they don’t get their way: jerks. People who think 90s era C++ was worth using, despite nobody else in the company being able to use it: jerks. People who raise hell with OSHA because the CEO is a heavy smoker: jerks. People who alienate their boss and benefactor with sperdo like “why don’t you liiiike meeeee” behavior: jerks. People who have the CEO removed because he voted for the wrong political candidate: jerks. I’ve known people like this throughout my career and have endeavored to always see the best in them I possibly could. Frankly his story in this book convinced me to never hire a person like this excepting as contractors. They bring bad luck, bad social interactions and you should banish them from your village. It’s an astounding account in part because it must have largely been told to the author by Magerman himself.
One of the keys to its success: Rentech shared the loot. People who uncovered new alphas were important, but fixing code, cleaning data….. all received big bonuses when the company did well, which aligned everyone’s incentives. Lots of work is necessary, but not so sexy, and this keeps people working on the necessary. The company, at least in the earlier days also seemed to have tremendous mission intensity; just like other type-1 organizations such as the Sidewinder era of China Lake. One of the things that didn’t work so well: new employees shitting on the old employees who to their mind “didn’t do anything anymore.” Not sure if they ever found a way to deal with this. Probably by paying people more. One of the things which stuck out was Simons knowing what his company was worth, and taking large performance fees: Simons had after a long struggle a genuine golden-egg-laying goose, and he wasn’t giving these returns away to goofballs who only wanted to pay 2 & 20. It was also amusing that many thought Rentech to be some kind of Madoff like scam; I have acquaintances who went through the interview process and thought it might have been some weird money laundry for Columbian drug dealers (he did make friends in Columbia from his early scooter trip there). Through the whole arc of Rentech, Simons had an awful lot of terrible luck in his personal life, which is really unfortunate as he seems like a genuinely nice person.
The rest of the history laid out here is boring HR drama, so I won’t talk about it. It’s more interesting to focus on the great years, and how they made it succeed. Big brains working together as a team, with great intensity and great rewards.
Bonus review: During one of the Simons video interviews (with James Ax’s son) he also mentions a book popular back in his day called “The Captain” by Jan de Hertog. This is definitely a period piece; a sequel to a book that was a sensation under the Nazi occupation of Holland, on a young tugboat captain. Very intense, as it involved running German blockades. While it’s a great read for entertainment purposes, it’s also got some important leadership lessons, as he pointed out. It is a very good book for this sort of thing; being decisive, motivating very different groups of people, distracting people who need to be distracted and generally being a combination matador and stage magician. The crew in The Captain were a bunch of non-motivated odd ducks who needed to be convinced to follow the eponymous character, as well as being motivated to do a good job in general. Half of the early drama in the story was dealing with this.
Edit add: Ben Gimpert had a nice review back when the book came out, making notes of a lot of the interesting technical bits: https://blog.someben.com/2019/11/notes-on-man-who-solved-the-market-jim-simons/
Locklin on science 
Do you think it would be worth it to try to break into finance in current year? I’m fascinated with HFT and quantitative finance and such, at least the mathematics is captivating, but it seems like a lot of it is just bullshitting anymore. I’ve read that HFT is nowhere near as profitable as it once was, I saw a video of a conference where Warren Buffett said that hedge funds don’t work, inflation is becoming a severe problem, etc. I really just want a job where I can do statistical magic and make decent money. Seems like there’s nowhere to go anymore these days unless you want to be a part of the problem (referring of course to Silly Con Valley, NSA, basically anywhere with massive data analytics and machine learning). Any advice, or should I move to Idaho and open a tavern or something?
Tavern sounds comfy.
You can make a lot of money on the crypto market. It’s heavily leveraged and trading follows the “rules” of pure technical analysis.
It’s similar to NAS100 trading, just a lot more volatile due to the extremly leveraged positions.
Just to add this: you can analyze order flow and spot ice bergs pretty eaily if you know the basics of program. If you’re also good at analyzing data you will literally *print* money. Don’t be afraid to dive deep. 🙂
Sounds intriguing. I’ve been following cryptos on and off since early 2013 and I still haven’t been able to make heads or tails of whether it’s all a Ponzi scheme, owing to the bubbles like in 2017 and ’18, or if it’s really a paradigm shift in the financial world. If there is really potential for applying quant techniques and amassing a little fortune, then I better get off 4chan and get to it lol.
P.S. if you have any links with more info it would be appreciated. Of course, being a trailblazer means there won’t be anyone there to hold your hand.
Here you go: https://www.tavernateagleisland.com/
Some notes: You are never married to your investments, unless you are doing long-term investments, and then you don’t need maths magic. So it should not matter if paradigm shift. I myself think it is all overhyped bullcrap. Very profitable bullcrap.
Stay on 4chan. Become good at sifting through bullcrap. You’ll hear about all the crap-coins before these astroturfers move to Youtube or Reddit to hype up their bags. That is when you sell to them and get out.
You are not a trailblazer. Automatic crypto trading has matured. But there never will be anyone to hold your hand. When profitable, it is really hard to give away the goodies. Your tips will end up next to some towardsdatascience article using LSTMs to regress on stock prices. Incidentally, those articles also always show a profitable backtest. Now my motivation to talk about bagged ridge regressions for variance reduction is gone.
Close to 10 years, and I had 3 people I could talk shop with. They all had skin in the game, they knew their forecasting, they dug deep where I hadn’t yet. Truly amazing, but not possible to capture in a book or online discussion.
Even when retiring/or yelling full-time “fuck you” to all bullcrap I see, not sure if going to publish. Something about sharing some responsibility for any problems your solution may have caused. And the crypto market being very scummy, so it is inevitable anomaly detection and forecasting algo’s pick up on things like pump-and-dump schemes.
Sure and you can lose a lot also.
But the real problem, from my point of view, is the lack of traction on issues which I consider relevant.
Thanks for the review. I didn’t read it. I think my interest in things like this have waned; or I’ve just read so much over the years I’ve gone numb. I am not sure I know anyone there anymore. I spoke to them in the early 00’s. I recall a comment “you dont’ have a business degree right?” “No, no, I don’t.” and another along the lines of “we contacted you, right? We don’t solicit resumes…” Back then I recall two things. First was talk of order book mining, transaction cost optimization, and tax avoidance as opposed to global macro arb, voice recognition, and brilliant relative value positions. The second, and this would only come into focus years later, was that anyone I knew attached to the place would either talk about very specific software development or very abstract things that was closer to theoretical physics or pure math than running a fund. I say “come into focus” because as I started to work more in trading and capital markets I noticed that my pure quant teams, if not guided, would still be working 60-80 hour work weeks, but on strange and self-guided projects. Oddly still, I learned, years later, that if I applied some good coding standards, wrote up the math in well-organized white papers, had good SDLC, many of these projects had some kind of use in the ecosystem, eventually; but my point is that is how it all struck me, in retrospect. For me, when things were good, we got to work on whatever we wanted and it was fun. When times were lean the fun ended.
The thing with Rentec is it’s not really Rentec, it’s Medallion. Whether or not Medallion was a tax fraud, or alpha built on leverage and a glitch, whether the other funds ported alpha, or diluted the capacity of Medallion is kinda the point: w/o Medallion Rentec is nothing. Without Medallion Rentec is maybe a thing that only quants talk about, like PDT partners or Prediction Company.
I’ve come to think of Rentec as a Robinhood fund. What Jim has done for science is fantastic. Broad science, too, not just SUNY Stony Brook, but all of the various ventures and appointments. Money taken out of the financial system that goes to science versus a rotting shark corpse in formaldehyde for the lobby is a good thing.
I’m sure the voice recognition red herring is just voice recognition people being good at heteroskedastic timeseries. I got the business school thing and “we contacted you” thing as well (at a Straus founded spinoff); I was working on a CFA at the time and they really didn’t like it. They also had a really shitty/weird windowless office in a Walnut Creek shopping center, more or less above a Vietnamese waxing studio, just like the description of early Rentec.
A lot of this sort of thing is also heavily path dependent. In addition to being first at a lot of things, they were kind of in a blessed time where a lot of things in the global financial system were dislocated, making for lots of opportunities.
100%. It’s both completely banal and truly amazing how fast things get efficient. In retrospect some of these strategies are as simple as undergrad chapter 4 problems in Hull. Watching signals evaporate under subatomic decimalization and low-latency in every market as more and more players and money and regulation ebb and flow it’s hard to imagine that anyone under 30 could ever have an appreciation for the opportunities that existed for years for these people.
Agreed. In new markets you can print money but you are also playing with fire since you are almost surely working in a locally stationary favorable period where — if you are successful — you can only pat yourself on the back for being the survivor in “survivor-bias”. Curse of quant work is that when an effect is huge — eg a broken or new market — you do not have the data for building statistically robust models, but by the time enough data has been collected to know the effect is real and will persist everyone will have detected the effect and traded it to small size.
The other reason most fail when moving from STEM fields to finance is the signal-to-noise ratio in finance is extremely poor, and data non-stationary over required observation periods. Most grizzled engineers (like me, cough cough) were trained on problems like NLP, character + image recognition. We missed that despite all we cursed and swore about it being hard, even the most messed up text or speech has an underlying stucture designed for communication and often has error-correction/noise suppression features built in (eg Bark scale matching for almost all spoken languages). Even when we were looking for tanks in camouflage with SAR you pretty much know what you are looking for. And frequently you can condition the signal (as we joked, engineers don’t look for the keys under the light, they take the keys and drop them under the light). Even when looking a fractional Watt transmissions from Voyager you use error correction codes that generate super high SNR (thanks Shannnon). And unsurprisingly, most ML techniques and methods depend on having a reasonable SNR — either explicitly or implicitly by assuming sequences are approximately stationary for sufficient N samples to allow whatever mad Russian mathematician’s bound driving your hypothesis search to converge.
So quant models are often at base simple. Properly handling them is not. Even if you find a Markov chain -like effect in some market, if you think your Matlab Toolbox algos are actually working to fit something useful you are likely more valuable to firms like Rentech trading outside their walls than inside it. If you want to be a successful quant, plan to spend 70% of your time cleaning and understanding data especially where the textbooks ignore stuff, and the other 70% working on these basics and rolling your own math. To deal with, for example, heteroskedasticity. In short there is a reason they hired Baum rather than copy his code for a fraction of the price.
Medallion? As good an explanation as any is that there was a sign error in the first code and they learned something wild which no one else knows or would reasonably suspect, which is why they kept their edge but was unable to do anything near as good in other markets. Probably still running on a PDP11 or VaX since no one has been able to get it to run on floating point hardware 🙂
Tavern is a good idea even if you do start trading. You are likely going to end up drinking your losses away.
For what its worth a friend of mine (Scott also knows him) got interviewed by them. Even by some of the bigger names in the company if I recall it right. He wasn’t horribly impressed and they wanted to force him to leave his mountain village. He was not cool with that :).
Lol, I would have loved to be a fly on the wall for that conversation.
Me too. I will most probably working together with him real soon. Looking forward to it.
Alright, give me a clue, which friend? I assume I know them too. Congrats on the new thing.
He was someone’s literal court mathematician. Not an NP bro.
Like Scott said, not NP related. If I would know who you are, I would be happy to make introductions:),
I enjoyed the book and the color you added in your review. Question: “Robert Frey was also recruited from the Stab Art world.”… should that read ‘stat arb?’
It’s deliberately written that way, like “hodl.”
> the principals were and are much more admirable people than the TGS principals
Anything juicy you could add? I’ve worked in the space for over a decade and it’s the first I’ve heard of this.
None of them distinguished themselves in any way before or after Princeton Newport/TGS. Their charitable works were almost entirely political, and to my mind at least somewhat harmful. Stuff like making the Sierra Club pro immigration(Gelbaum’s doing), donating strings attached money to the ACLU which is now a shadow of its formerly admirable self, investments in pointless and harmful “green” technologies as opposed to things which could actually help the environment, lobbying congress for more tax breaks, and generally not doing anything obviously good in the world (I think one of them funded Huntingtons lymphoma work which is admirable, if not very imaginative). Contrast to the Rentech dudes who had great achievements in science both before and after, and whose charitable work is/was generally unreproachable and fairly creative. For all I know they were/are perfectly nice people, and I’m sure they thought they were doing good in the world with their various initiatives, but they can’t be described as more admirable in any way which is apparent to me.
It’s a familiar type of person: basically classic “type-2 organization” executives who exploit existing innovations. It was Ed Thorp who built the firm where they developed their insights, and the history of Princeton Newport, or Nunzio Tartaglia’s group at Morgan Stanley would be more worth looking into than that of TGS.
In addition to Kelly’s Heroes, Brian Hutton also directed Where Eagles Dare, a year before Kelly’s Heroes, also outstanding.
I met Jim Simons once at his foundation’s auditorium off of lower Fifth Avenue, alone, he was propped up against a hand rail on the ramp leading up to the auditorium smoking a cigarette.
I am in the flooring business and did his floors, strangely enough, Jim Simons dabbled in the flooring business at MIT, he had a laugh about that.
That brief conversation backs up that he was charming and a very nice man.
Nice review and anecdotes. I remember sitting across from the man himself once, just his pack of Merit cigarettes between us.
Apologies in advance for the unrelated post. Long time reader, first time commenter.
Scott I was just re-reading your “automotive memories” piece from 2020. Any chance we could get some another automotive-themed piece? My brother and I are on the repair and used-sales/flipping side of the industry and I suspect we have some very similar thoughts in the direction things are going. We’ve both honed in on 90s-mid 00s cars as our preferred long term daily drivers, as we have a front row seat to the insanity unfolding in modern automotive design from a engineering/control perspective. 50+ black box modules on a CAN bus, increasingly locked down behind pay-to-access manufacturer “secure access gateways” (they introduced wifi connectivity at the level of ECUs/security systems and then realized people would use this to steal cars). Want to change brake pads on a newer Ram? You’ll probably need to pay for an Secure Vehicle Gateway to access the ABS module to retract the calipers “correctly.” I’ve got a 300k mile ’06 Suburban with the wonderful 5.3L LS pushrod V8, one of the last years to predate the horrible cylinder shutoff tech that led to wiped out lifters and cams. Simple, cheap to service and rebuild 4spd automatic. As long as I can keep the rust at bay with annual oil undercoating I think I can just keep servicing/rebuilding this truck for the next 30+ years. In the age of $70-100k new trucks laden with tech, more and more I’m seeing the trend of these 90s-00s trucks being refurbished and prices for them are shooting through the roof. Worse yet I think is the coming age of the EV-pods where you won’t even own it, it will be a lease/subscription, the Tesla style over-the-air updates that can leave you disabled downloading an update, etc. Last summer I picked up a 1991 Buick Park Avenue for $400 that was probably on its way to the crusher, mostly out of mechanical sympathy. Low miles on the venerable 3800 motor, pretty clean car aside from some underbody rust starting to set in. With just a few parts and basic wrenching I had myself a wonderful cruiser that was so much more satisfying to drive than any newer car I’d driven. I could see some kind of collapse scenario where its these basic “analog” cars with simple low compression iron block engines that stay on the roads (junkyards are full of spares), while the module-laden new stuff become paperweights waiting on parts or highly specialized diagnostic equipment.
I myself have avoided new cars because of all the engine-start-stop eco-anemic electronic kudzu. I recently bought a used 2013 ford before the prices took off and they all vanished from the market. I’m driving a 20 year old Honda and will continue to do so until it’s rust and duct-tape. I don’t *want* the newer cars.
I write as the spirit moves me, more or less. SavageGeese are pretty good for car nerding stuff. One thing the new cars do have that the old ones don’t is lots of reliable airbags. It’s a shame that comes with the ability for someone to remotely drive your car into a brick wall, because the whole thing is hooked up to the internet, complete with “collision avoidance” system.
Quantitative finance isn’t really my thing. In fact, outside of some money-and-banking undergrad courses, economics in general hasn’t really been my thing.
But if I wanted to download your brain and get a foot in the door in this world, what would I have to know, and what would I have to read to get it? (I have one graduate stats class under my belt.) Any recommended textbooks explaining the nuts, bolts, fundamental activities in this world?
Learn poker. Study Sklansky. Top hedge-funds play a very similar game to poker.
> In February, The Wall Street Journal broke the story of Magerman’s criticism of Mercer’s support of Trump. The article included an interview with Magerman in which he argued that Mercer was “using the money I helped him make to implement his worldview.” Renaissance Technologies’ billionaire founder and longtime Democratic supporter James Simons publicly stood by Mercer and the hedge firm suspended Magerman.
> Magerman claims his decision to go public was motivated by his alarm of Mercer’s backing of policies that are harmful to the poor and that he felt obligated to speak out against these policies.
> In April, The Wall Street Journal reported that Magerman had gone to a charity poker tournament in New York attended by Mercer, his daughter, and Simons. Magerman told The Wall Street Journal that Rebekah Mercer had been agitated by Magerman’s presence at the tournament and the newspaper reported she called Magerman “pond scum.”
> Magerman, who worked for Renaissance for some 22 years and says the hedge fund has used his algorithms to earn billions of dollars, claims that Mercer had Renaissance fire him the day after the second Wall Street Journal article was published.
and some science written for popsci-media:
> We find that hedge fund managers who do well in poker tournaments have significantly better
fund performance. This effect is stronger for tournaments with more entrants, larger buy-ins, larger
cash prizes and for managers who win multiple tournaments, suggesting poker skills are correlated
with fund management skills.
Like big watches, chess or Go, the poker thing came and went. I date its apex circa 2005-2008, in at least NY and London. I can only describe the zeitgeist as being akin to AI or data science: every junior resume had poker on it. Out of work for the last eight months? Why? Professional poker player. Many listed their stats on their resume. That one hasn’t aged well. All nighters in vegas and AC were the split between the camp of kids that watched rounders and boiler room in a sophomoric attempt to live vicariously (and couldn’t afford to lose their rent money), the quiet midwestern lookyloos, the Doyle Brunson wannabes, and the wall streeters (that could afford to pay for the lesson). The lesson was in bluffing and acquiring the training set after thousands and thousands of reps. The private games in NY and London had buyins that made it interesting enough that everyone took their hand seriously. Staring at a pot of $50k made both the nine figure man and seven figure boy not fuck up the training set like the clodhopper at the 1/2 table at the Borgata that goes all in on the flop because he caught the third spoke of a wheel.
Eventually this all waned and there was this residual slime of celebrity trading (or trading adjacent) and hollywood types. It disappeared from resumes. We ascribe genius to luck (and leverage) all too often. Very few of these egomaniacs consistently made money. One-offs abound and include the mortgage genius (there’s a movie), credit genius (why’d the chess master leave DB and how are things more recently?), rates genius (left GS under investigation, left MS for losses despite huge positions being debated before blaming failure of risk management, and what happened in August at betadone?), global macro genius (punting crypto today between fashion weeks), cash equity genius (well he didn’t go to jail, somehow, but the genius has somehow gone away? How? If you’re a good trader why does it matter if the federal government is watching you more closely?)…. very few people create systematic edge like is done in poker. 50.75% locked and loaded, increase N to capacity, create more capacity and optimize transaction friction, rinse repeat. This is supposedly what happened in Medallion but the nature of whether it was true alpha or not has been debated forever (taxes, order book, and tx isn’t really market related). It’s all still money, though, and people got rich.
It’s just not genius. It’s clever. Some of the most clever people are involved in financial markets. I’d argue, as I have, the PE is the current nexus of clever. Regulators just don’t stand a chance going toe-to-toe; so similar to the concept of force multiplication in warfare, it just has to be authoritarian, and this is undermined by globalism (I’ve set up my fair share of off shore entities). Julian Robertson et al comes to mind as having attractive yoy statistics. When looking at broad hedge fund AUM be sure to normalize for market performance 2010-present, though. I’d also argue that disruption as an asset class is novel and really has no historical precedent for a bunch of reasons that should be obvious. Yapping about leptokurtosis and levy distributions and power laws in the 90’s isn’t the same. The French are still yapping about “what is volatility” like a Deleuze recording on infinite loop. Anyway, I just don’t think poker ever as important as the narrative that supported the idea implied; and, regardless, it’s just not applicable anymore. Maybe studying classics and poetry is? (a la the James Jesus Angleton narrative around deciphering the “wilderness of mirrors”). Hmmm.
Poker definitely has a Panerai watch vibe to it in current year. I’d definitely look at any resume that had some attempt to get good at any kind of probabilistic game though. I fooled around with backgammon and roulette for a while, partly for getting a sense for real world probabilities, but also because I was curious. I guess I also played poker when I was an auto mechanic but it was mostly for fun, and it could as easily have been pinochle. FWIIW I’m also interested in the game hnefatafl, as nobody’s uncorked any math on it, and all those dumb viking TV shows have made it more popular. I wrote some J frameworks to dig into it, but decided my time was better spent in other pursuits for now.
Classics test sounds pretty legit. Good filter anyway.
Yep, ‘poker’ is another resume signal sadly traded into insignificance. The other one which comes and goes is “startup”. Quoting my colleague, a CS Stanford grad, coming back exhausted from recruiting at his alma-mater: “They all come in with a “startup” . In my day we called it “homework”.
Still, some of the skills that help make you good at poker do carry over, and now the shine is off it may be useful again if found in a candidate. Once you start managing a full book – sizing bets, properly evaluating edge while betting on your estimate, being able to take a meta view of your strategy, plus staying in with your own money — and just plain being interested in dealing with uncertainty — still good to have in this business. Shannon, “He Whose Testicles Smoked Unfiltered Camels” , Thorpe and others all had these traits. Rarer than one thinks – many quants working in large firms after years cannot even do the back-of-envelope calculations for their books.
The one about French “volatility” made my day.
“I’d definitely look at any resume that had some attempt to get good at any kind of probabilistic game though…”
“Still, some of the skills that help make you good at poker do carry over,…”
Absolutely. Agree 100%. For me the biggest thing, especially if you’re playing often or for real money/stakes, is keeping the emotions disengaged from fucking up your system (playing) and your apparatus (autopathos v autologos). Inoculation from this fog is crucial to prevent becoming metacognitive bias incarnate spraying (usually) other people’s money all over the trade blotter. I think whatever it is translates well when it has to do with money, though. Like activity specific training in sports, e.g., lift to train lifting and run to train running. For instance, I spent a bunch of time in the mountains and had my fair share of being in the serious shit. That stress inoculation didn’t translate in obvious ways for me in the financial world. It helped during World Trade if that counts. If anything I felt panic being in an office. The larger trading floors were a little more calming. But I digress… the aspect of poker that translates, IMO, is the grind. Being consistent in the system, which is based on decisions made on what I’ll call *wet-filtering*, not letting emotions sway short term tactics in ways that impact the strategy… classic “plan the trade, trade the plan” stuff. You may be Kelly betting your pot or taking advantage of a read of someone short stacked but, over long time periods, it should feel like a disciplined grind, like work, where the pot dynamics don’t irrationally influence your wet-filtering. Occasionally you can achieve states of flow but the body has it’s cycles and you don’t get to pick when there is a game and you gotta perform. Grind and flow, grind and flow. That skill has transferability. What I am taking aim at is when poker became jewelry on the resumes of peacocks. If there was a movie about bridge maybe it would have been bridge, but the movie was about poker. Actually there were a couple of books about bridge – Berkshire and Bear Stearns people – and bridge became a bit of a thing on resumes, but that was before my time. I was in the mountains or grad school then.
I remember hiring video game programmers during that time. They knew dickall about trading or finance but they were amazing problem solvers. Same thing with the protein folding crowd. I don’t have much experience with the astronomer crowd, like the Setauket guys, but it sounds the same. The solutions were orthogonal to the rest of us, so they were always additive, and they were slick. Video game programming and protein folding had cross over.
I don’t care if it annoys you or not and that I am sounding like a breaking record,but the truth is th truth: dude, you can write! And somehow you have profound insights in whatever you decide to write about.
I really really would like to read more of you in a centralized and systematic fashion. Like a blog.
Just saying. I am pretty sure lots of people would agree with me. So please, just think about it.
Assuming this is in reference to chiral3: he would have at least a second blog reader (and I suspect many more). This blog usually has no shortage of interesting comments, but his always stick out as particularly noteworthy in prose and content.
Chiral3 full of interesting ideas. I think he’s enjoying life too much to entertain others though. For me it’s just something I do between coding jags. If I quit coding, probably no more blerg.
Thanks for the kind words. I ride Scott’s coattails and blabber in his comments which I wouldn’t do if Scott and everyone else here wasn’t so interesting; but, like the man, it’s in between jags.
> Marcy Dawson: [to Max] You don’t understand it, do you? I don’t give a sh*t about you! I only care about what’s in your f*cking head! If you won’t help us, help yourself. We are forced to comply to the laws of nature. Survival of the fittest Max, and we’ve got the fucking gun! – Pi (1998)
About the Medallion Alpha, I have a feeling that guessing correctly on that, which net you a knock on your door. So let me hope I am not too creative here:
– NSA justifies economic spying on foreign countries, because some (state) companies use bribes and cheating to get contracts and deals, which do not benefit U.S. economy, this economy being a national interest, and thus defended as such. Say, the NSA stumbles upon insider trading happening in Dubai territory against U.S. companies. Or IP theft from China. They would do right to use this information to safeguard and take back what belonged to the U.S. economy. But you can not trade as NSA hedge fund inc. So you cook up some story where you fire a brilliant code breaker, say it is on peaceful objections to the war, let him build a fantastic team of ML-powered economical top-dogs. When you need cover for a young code breaker, you send them to work there, on real data. When this economic warfare 5.0 powerpoint-slide ever becomes a real thing, you put RenTech and Blackrock to work to protect you from an artificially induced housing crash, or aim all the dirty tricks you learned, but, as good American hedge fund, did not exploit to damage for all ‘Muricans, at the enemy. Game over.
– They really are this smart. They tried explaining to traditional quants, but these just could not get it. They mixed systems theory, gauge theory, and algebraic topology. They bypassed the problem of attribution -as a node in a dynamic graph where you do not have full information on all the edge values and other nodes, it is impossible to know which energies you send out, contributed to your energy inputs. But when you can “shock” the network with smartly chosen energy burst, perhaps when the network is in a calm low-entropy state, then you can get a pretty good idea of the edges, and even how sending energy there, gives you back energy a little bit later. RenTech Medallion is this node and the network is the world economy. They know that charging the “field” of raw materials in one continent, will have profitable influence on a consumer company stock price in another continent. Not so much printing money, as turning the entire world economy into their own printer. One day they went too far, so they had to agree on a hard cap.
– They simply do have the information edge on everybody at the table, and they have mined and processed all the old data, going 100 years back. Their backtests are the most rigorous in the world. Their risk reduction is most solid of all. There are some available tricks when looking far enough back, like cyclical events, or seemingly one-off anomalies, that do pop up again predictably in times of high variance / crisis. Like Phil Ivey would live forever, and you ever expect to get better than him at poker, it is just too late. They first moved the data, and you’d need decades to even get where they were 5 years ago. No catching up, means we see the biggest wins possible for their bankroll. That’s ~40 billion per year?
NSA thing is real, but I’m quite certain that goes to Jeffrey Epstein and Nancy Pelosi types rather than Jim Simons. He was just real early, and compound interest is powerful. He was real early at a lot of things; dude backed a startup that literally invented the e-reader in the 1980s. Wasn’t mentioned in the book, but I knew a guy (who was also early; invented a protonmail thing in the 90s) who was involved with it. All of the ML tools they were using in the 90s are still useful (and rarely used) tools, and their backgrounds were well positioned to squeeze the maximum out of them. Also to understand shit like data mining bias (Sandor Straus made me aware of using the block bootstrap on your equity curves …. this was back in 2008 or so when it was still pretty advanced shit: I assume they were doing it in the 90s).
Scott, did you write the ED article on theoretical physics:
https://encyclopediadramatica.online/Theoretical_Physics
This shit cracks me up every time I read it. I know you’re a part-time denizen of the chans and you’ve gone on at length about the joke that is modern physics, so I’m just curious kek
Wish I had; it’s great
Loved the commentary, particularly your beef with C++. Was a trash language, remains a trash language … (sadly I did have to use for some years)
Late to comment on this review, but I stumbled on it when catching up Simons news (I heard he might be ill). I definitely was a bit of a jerk in my early days (and even later days) at Renaissance. I learned a lot about how much of a jerk I had been as a manager when I returned to the company as a regular employee and got regularly beaten up by managers above me in the org chart who used to work for me when I was a manager. Turns out karma really is a bitch.
I admit that I answered questions Zuckerman asked me about my time at Renaissance. I tried to be honest with him, sharing both the good and the bad of how I behaved while I was there. I was an immature 25-year old when I started, and I got lots of responsibility at a young age. I didn’t handle it so well, but I hope that I learned from the experience and became a better person later in life (I hope). I didn’t expect the portrayal of me to be positive. I expected it to be real, and I think Zuckerman did a good job with that.
The blow-up with Renaissance management that got me fired was both the worst and the best thing that could have happened to me. It was horrible, because it severed almost all of the adult relationships I had in my life. It was great because it taught me that I didn’t really have any friends, and that was on me. I’ve worked since then to be a better friend and a better person to the people around me, so the next time I have a monumental disagreement with a group of people, I’ll still keep them as friends.
And also, I never would have left Renaissance without getting fired, and I wouldn’t have had the opportunity to do something more meaningful with my life. It’s a hard place to leave, but now that I’m out, it’s very freeing.
Sorry my part of the Renaissance story seemed to irritate you so much. My contributions were real, but the bigger story is how Peter Brown and Bob Mercer brought computer science and research discipline to the company and got the most value out of a lot of brilliant minds. I wish that part of the story had been given more prominence.
P.S. – I still love C++.
Appreciate the comment; obviously it’s nothing personal from me since I don’t know you from a hole in the wall, but some of what you brought to the story is a type of antipattern I’ve seen in other ventures. It’s something a lot of people don’t notice or think about, and it was worth pointing out. It’s also something I’m trying to avoid in my own projects. If you can think of something that would have made the younger David a better team player, at least something the management could have done, I’d love to hear about it. Sports really seem to help people with these kinds of issues.
FWIIW I just made a large (for me) angel investment in a HF venture and they also primarily use C++. I probably wouldn’t have if it was Rust.