[HN Gopher] Jim Simons proved the textbooks wrong, almost
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Jim Simons proved the textbooks wrong, almost
Author : paulpauper
Score : 58 points
Date : 2021-01-17 12:19 UTC (1 days ago)
(HTM) web link (www.bloomberg.com)
(TXT) w3m dump (www.bloomberg.com)
| boyesm wrote:
| https://archive.is/wsmVU
| deandree_ wrote:
| Textbooks have nothing to do with reality of the markets. Those
| who believe in EMH - please check out what happened to price of
| Zoom in March 2020.
| probe wrote:
| I've found RenTech to be fascinating over the years and highly
| recommend the book on it "Man who solved the market"
|
| Two big takeaways for his success -
|
| 1) He was pretty early, and quite contrarian, in betting on
| computer and quant strategies and thus took the "low hanging
| fruit" early on (def wasn't low hanging back then when no one
| knew or believed in computer trades strategies)
|
| 2) From the book, Rentech's main strategy was based on "reversion
| to the mean" - I.e "We make money from the reactions people have
| to price moves". Trading on how you think OTHERS will trade and
| systemizing it (ex vol and momentum) is powerful but clearly
| doesn't scale when you become the market yourself
|
| And a bonus one - despite being a math genius, he basically was
| failing till he brought on others. He hired the right people (ie
| those interested in math not finance), created the right
| environment, took care of logistics, and pushed on a key insight
| (model to trade). He couldn't have done it by himself.
| hogFeast wrote:
| I actually found the last part was my main takeaway.
|
| Even in the early 1990s, Simons had basically checked out of
| the fund and was mainly doing venture stuff. He clearly made
| some good hires pre-1990s (I can't remember but the data guy
| clearly seemed to give them a huge edge over the competition,
| they clearly had data that no-one had) but it was that sequence
| of hires after this point that really elevated things: Peter
| Brown, Nick Patterson, Robert Mercer, etc. Very humbling. Of
| course, everyone will continue to think the strategies are the
| secret sauce.
|
| Also, I think it highlights that quant investing starts out
| being very scalable but stops scaling quite quickly (and most
| similar firms hire people that, on paper, are very smart and
| get nowhere...so RenTech is the best example of scalability).
| At the top end, fundamental investing is still more scalable
| (which is what common sense would indicate).
|
| As an aside, the article is totally pointless. Finance
| professors are engaged in an argument with themselves. They
| know they believe things that make no sense, and so spend all
| their time grappling with facts to fit them into their model.
| Humans do not reason perfectly, when you put a trade on you
| move the market, effects can last for ages (you have pure arbs
| that take years to close)...the whole discussion is just non-
| sensical, and any academic examination of finance should start
| from reality, not what theories are fun to teach. It is kind of
| tragic to see intelligent people do this to themselves...but
| some people just prefer Haskell to Python.
| nightski wrote:
| Not sure what Haskell has to do with it. I've written
| algorithms that take in 2D images and produce depth maps with
| live visualization in OpenGL using Haskell. It's incredibly
| practical once you learn it.
|
| But I also disagree from the point that if physics did what
| you suggested we'd be no where at all. If they had to start
| with reality before producing useful models then we would of
| skipped pretty much all of modern physics today.
|
| All models are wrong, but some are useful as they say.
| hogFeast wrote:
| "once you learn it"...yes, everything is incredibly
| practical once you remove all the disadvantages. The point
| is: some people prefer complexity for complexity's sake,
| and this doesn't work well in a team environment (where the
| "once you learn it" part becomes quite relevant, one person
| who prefers complexity for complexity's sake will take down
| the whole group, not understanding when something should be
| simple is an indication of ignorance...finance professors
| rarely have any understanding of actual finance, their
| ignorance on this is total).
|
| These models aren't useful. Also, the saying is wrong. The
| reason why is that close to 100% of finance professors will
| quote that saying (srs, I think I have heard this 20-30
| times now) because they use models that are wrong and not
| useful but this model seems to give them an intellectual
| reason for doing so: any "wrong" model could actually be
| good, according to this idea. But wrongness is neither nor
| there because wrongness for a model is utility, they are
| identical. The only point is utility. And the reason why
| these models aren't useful, as I have said already, is that
| they aren't used outside of academia. Their only utility is
| giving finance professors something fun to teach. And
| again, the solution is to build models from the way the
| world actually is (and btw, these are numerous...almost
| every successful investor, fundamental or quant, has a
| systematic process...but these models aren't fun to teach).
| nightski wrote:
| Are you implying software isn't complex? Or that
| imperative languages have low complexity? Haskell takes
| the complexity of software and provides useful constructs
| to generalize and abstract some of these complexities.
| Does it take time to learn? Absolutely. Is it easy for
| newbies to understand? Definitely not, because it's hard
| to appreciate their value until you have encountered
| these issues time and again in software. But it's most
| definitely not complexity for complexity sake. It can
| vastly simplify software in practice by restricting the
| domain in which you are working with a very powerful type
| system. That is the entire point of it all after all.
|
| I'm not sure which models you are talking about - but
| models such as Modern Portfolio Theory, or Black Scholes,
| while inherently flawed have been _massively_ useful in
| the real world. Claiming they aren 't useful is simply
| not true. But again, you don't mention any specific
| models so it's hard to even know what you are talking
| about.
| hogFeast wrote:
| You have demonstrated my argument.
|
| I mean all of them. Black-Scholes was used in industry
| before academia, and is only used in a heavily adjusted
| form (for example, option MMs have never used it as the
| only pricing input). MPT isn't useful: volatility doesn't
| describe risk to any degree (possibly as you move to the
| limit of retirement age...but then, not really), the
| empirical relationship is actually the inverse of that
| predicted by MPT (i.e. the model is not only wrong, it is
| misleading and will cause you to lose money), and it is
| easy to construct superior models that beat MPT models in
| every way (and even those aren't very good because they
| often use the same theoretical underpinning...again, most
| of these models exist because the subject needs to be
| taught in universities and needs to build on stuff
| learned earlier...the practical use is zero, which is why
| no-one really uses these theories...the only place I have
| seen them used at scale is in investment consultancies,
| and most of these places are clueless).
| WalterBright wrote:
| > but clearly doesn't scale when you become the market yourself
|
| Any market-beating strategy will no longer work when the market
| adopts it. I.e. if you have such a strategy, keep it to
| yourself as long as practical.
| fractionalhare wrote:
| That's not necessarily true, it depends. For example risk
| parity is common knowledge but it still beats the market. You
| don't really need any secret sauce to use it effectively. You
| could do it, personally, and you would probably do well.
|
| However if your strategies are well known people typically
| won't pay you much (if anything) to manage their money,
| because a bunch of shops will be offering comparable results
| with the same thing.
| effie wrote:
| > _"...with an open, freewheeling atmosphere more like a
| university department than a company. "_ This gave me a pause.
| Which university department has "open, freewheeling atmosphere"?
| ironSkillet wrote:
| Mathematics departments are known for this. In my experience it
| is accurate. People take intellectual detours all the time to
| discuss interesting problems with colleagues, potentially
| unrelated to their main research focus.
| omaranto wrote:
| That's my experience of every university math department I've
| ever been at. I always assumed that's also how non-math
| departments are but don't actually have any first-hand
| experience.
| soniman wrote:
| Nobody knows how Rentech makes money. The most likely explanation
| for the success of Medallion is that Rentech assigns ex post the
| best strategies to Medallion, which is run for the benefit of
| insiders. For instance the fund Bluecrest was charged and fined
| for doing exactly that. We also know, because it appeared in a
| Senate report, that Rentech is a massive tax fraud and owes over
| $5 billion in unpaid taxes. Is it so unreasonable that a massive
| tax cheat would also cheat his investors? The press is far too
| credulous towards Rentech. For instance Zuckerman in his book
| devotes just one paragraph to a discussion of the tax fraud and
| the Senate report. Noah Smith himself worked at SUNY Stony Brook,
| which is heavily funded by Simons.
| beagle3 wrote:
| No, that's not the most likely explanation - it's actually very
| unlikely.
|
| Medallion is not unique, there are other firms with comparable
| win record (Virtu, a Czech one, an Israeli one and a couple of
| British ones at the very least) but only 5-10% of the size; of
| all these, only Virtu is public and verifiable, the others
| aren't but you can find people who will confirm it off the
| record.
|
| People were begging Simons to take money. He wouldn't let them
| into medallion (why should he share?) but he did start a
| higher-risk, lower-reward business and let's people into that.
|
| As far as I can tell, the commonality among those always-
| winning firms is high frequency low latency algorithmic
| trading. These days it takes millions of dollars per month just
| to pay for the infrastructure you need to be able to be
| competitive - and then you also have to have some nontrivial
| edge, without which there isn't all that much profit in having
| low latency.
|
| What's Virtu's or RenTexh's/Medallion edge? I don't know. In
| the past, they seemed to like people with speech/hmm
| background. But that was before the DNN / differential
| computing revolution. I have no idea where there edge is now
| (and actually whether hmm was their edge in the past - but it
| did seem to be quite common background among their recruits)
|
| That said, they may or may not be tax frauds as well - I have
| no idea. But I don't see any reason to suspect they are doing
| retroactive allocation of successful trades.
| hogFeast wrote:
| Virtu is a market-maker. Comparing their win record to
| RenTech makes no sense. They have a high win-rate but so did
| brokers in the 70s...Virtu is doing the same thing as them
| (they are also APs for ETFs...again, the innovation there has
| really been able to make markets at very low cost).
|
| There are hundreds of other quant firms with public records.
| RenTech has better numbers because they stayed smaller. It is
| difficult to generalise but firms either grow assets to a
| point where the market moves against them when they
| trade/returns drop or they go into strategies with lower
| returns at scale (btw, both things are common outside of
| quant too). They aren't doing HFT. Some quant strategies are
| tangential to HFT, for example front-running news was a big
| strategy in the early 2010s...it is somewhat latency-based
| but is still distinct from HFT, which tends to refer more to
| making markets.
|
| The book says they tried hmm/speech stuff and it didn't work.
| It is likely they are doing more complex things now but Nick
| Patterson said they were using linear regression for most of
| the 90s. Generally speaking, this is a common misconception:
| people believe that because the results are good, the model
| must be more complex. This reflects how university courses
| are organised but the real world isn't like that (one big
| advantage that RenTech had was data, they had data that no-
| one else had for a very long time, another big factor is
| execution...these kind of practical edges are far more
| important than people think).
|
| Also, they use a ton of leverage...their returns actually
| compare pretty well to what fundamental managers can achieve
| outside of a public fund. Having investors is a significant
| limitation because they will often force you to behave in a
| way that reduces returns (i.e. redeeming at the worst time,
| asking for risk reductions at the worst time). The structure
| is very kind to gross returns.
|
| Retroactive reallocation of successful trades is very old.
| The SEC cracked down on this in the 80s, it is very easy to
| prove, and it is very unlikely that someone doing this would
| hire a bunch of scientists and then give them a bunch of
| equity in the fund...it doesn't make any sense.
| beagle3 wrote:
| Indeed, but it's important to differentiate between model
| execution complexity, and model optimization complexity.
|
| A linear model, if the inputs are e.g. squares and variable
| products, is a quadratic equivalent.
|
| A logistic regression yields a linear model; you could tell
| people it's linear regression and they'll likely believe
| you, but won't be able to replicate.
|
| There's a huge issue with itrelevant inputs and how to
| identify them - Emanuel Candes has done a lot of work on
| that, as did Rob Tibshirani.
|
| Saying "linear models" is saying little more than "using
| math", even if that's true, and even saying "linear
| regression" doesn't give much information about what is
| actually being done.
|
| The bottom line is that the decision boundaries are usually
| simple and often have linear form - but the variables in
| that linear form are not raw data, but rather nonlinear
| transformations of it (e.g. order imbalance)
| hardwaregeek wrote:
| Yeah in the Zuckerman book they mention an employee who
| worked on getting and cleaning data for decades, far before
| data science techniques were common in finance. I could see
| RenTech having good quality data going back decades being a
| serious advantage.
| hntrader wrote:
| What are the names of the Israeli, Czech and British firms?
| beagle3 wrote:
| The Czech is called RSJ, the israeli is called Final. I
| can't find the british ones now. Here's a list for you if
| you want more names:
| https://www.planetcompliance.com/2017/03/26/introduction-
| hft...
| darawk wrote:
| There are tons. I don't know which ones he's thinking of,
| but off the top of my head: PDT, Jump Trading, Domeyard,
| Two Sigma, DE Shaw, Jane Street, Citadel.
| inthewoods wrote:
| "As far as I can tell, the commonality among those always-
| winning firms is high frequency low latency algorithmic
| trading. These days it takes millions of dollars per month
| just to pay for the infrastructure you need to be able to be
| competitive - and then you also have to have some nontrivial
| edge, without which there isn't all that much profit in
| having low latency."
|
| I don't believe Medallion would be classified as a high
| frequency trading operation.
| btilly wrote:
| _As far as I can tell, the commonality among those always-
| winning firms is high frequency low latency algorithmic
| trading. These days it takes millions of dollars per month
| just to pay for the infrastructure you need to be able to be
| competitive - and then you also have to have some nontrivial
| edge, without which there isn't all that much profit in
| having low latency._
|
| And that is why I like the idea of a "trade arbitrarily
| slowly with limited price change" market versus the current
| approach of "trade fast with an arbitrary price change"
| market.
|
| See https://news.ycombinator.com/item?id=24760841 for an
| explanation of how the trade arbitrarily slowly market could
| work. Under normal conditions, it would look a lot like the
| current market does. Except that you're paying less to the
| HFT folks.
|
| What I didn't describe there is that you could even have a
| chain of slower and slower markets. With a maximum rate of
| price change varying from 1% per day to 1% per minute. With
| the idea that ordinary folks would trade on the 1% per minute
| market while large institutional orders would be likely to go
| in the 1% per day market. (And when the price of two markets
| cross, open orders on the one can match as open orders on the
| other.)
| lixtra wrote:
| What happens if your slow market has to coexist with other
| fast markets?
|
| My understanding is that
|
| a) either there is a huge price lag to the fast market and
| say you offer some good cheaper that the fast market. Then
| the HFT would come and buy your stuff and sell it more
| expensive on the fast market. Until
|
| b) your market becomes illiquid.
|
| In both cases there is little incentive to use your market.
| It would only make sense for huge trades (similar to take
| over offers, etc).
| skipants wrote:
| Is this similar to Investor's Exchange?
| https://iextrading.com/
|
| Similar principle... IIRC it delays execution to try and
| prevent HFT. A big part of Flash Boys by Michael Lewis was
| chronicling the history of what led to this exchange being
| created.
| ironSkillet wrote:
| Rentech trades on extremely reliable (but constantly evolving)
| price movement patterns and levers them up to the hilt in order
| to generate their returns. This is one reason why they are
| capacity constrained and can't just compound their returns.
| When the coronavirus first knocked US markets out of orbit,
| because of this leverage, the medallion fund was actually close
| to losing all of their money due to many previously established
| patterns evaporating too quickly for their algorithms to
| adjust. I have heard this from someone with first hand
| familiarity with ren tech. As others have mentioned, they also
| understood at a very early stage the importance of solid data
| ingestion and infrastructure. They vacuum up _anything_ that
| could plausibly be related to price movements.
| [deleted]
| Spinnaker_ wrote:
| The Medallion fund had 17 years of incredible performance
| before their other funds existed. So that's not a good
| explanation.
|
| The $5 billion in unpaid taxes is a small fraction of their
| total returns. So again, not a great explanation.
| esoterica wrote:
| > The most likely explanation for the success
|
| Mostly likely based on what grounds? Rentech was very
| profitable for decades before they ever started their public
| funds.
|
| > Nobody knows how Rentech makes money
|
| There's nothing extraordinarily special about Rentech's
| returns, they just employ short-term stat arb type strategies
| that require relatively little capital to execute, so if you
| express their returns as a percentage of invested capital you
| get an eye-popping number. But it's not comparable to the
| returns that a traditional buy-and-hold fund makes (in
| particular because those returns don't compound). There are
| plenty of other quant shops and prop trading firms that would
| make huge (>Rentech) annual returns if they attempted to phrase
| their earnings in those terms, but they typically don't,
| because if you don't need a lot of capital then you don't need
| to raise money from the clients and outside investors (can just
| trade the partners' money) and you don't need to brag about
| your returns in public.
| hogFeast wrote:
| Their IP address is also the largest downloader of Form 4s.
| [deleted]
| darawk wrote:
| Can't believe a comment this ignorant is so highly upvoted.
| Quant funds that do well are a real thing. Many people here
| work at them. Renaissance used a technicality to try to avoid
| taxes, and they are in a dispute over it with the IRS. That has
| absolutely nothing to do with the legitimacy of their primary
| fund. Medallion predates their public funds. They launched
| their public funds because Medallion was capacity constrained,
| and they thought they could cash in on its reputation. It's the
| public funds that are the afterthought, not Medallion. They are
| not moving the strategies around ex-post. You're just
| completely making things up here. Anyone with any knowledge of
| the history of Renaissance knows that that doesn't even make
| chronological sense.
| kolbe wrote:
| If I'm interpreting your allegation correctly, that would be a
| serious crime. I could conceive of that happening in the early
| days, but Jim has tens of billions of dollars now. I don't know
| why he'd risk spending the rest of his life in prison for an
| extra 1-3b a year.
|
| Also, you've misunderstood the charges on Bluecrest. Platt may
| also have been doing the scheme you described, but that is not
| what the SEC fined him for. He would be in prison had he been
| charged with what you allege.
| chrisgd wrote:
| You could have said the same about Madoff.
| kolbe wrote:
| Except Madoff had to conceal an accounting hole. If he ever
| stopped, his investors would ask for their $x back, and he
| would have to give them $0.5x. I know there's a lot of room
| for cynicism in the financial world, but you still need to
| know what is happening for each type of fraud or misdeed or
| good action.
| nabla9 wrote:
| Pretty good article. It explains almost everything that is known
| about Medallion fund_
|
| 1. Very research oriented
|
| 2. Their strategy does not scale. Fund has limited size.
|
| 3. They use some kind of arbitrage. No high-frequency trading,
| but longer.
|
| 4. Their current strategy must be kept secret for it to make
| money and it changes over time.
|
| This is why "I have discovered fool proof way to beat the market"
| sales pitch is always a hoax. If someone has it, they keep it
| secret and make money. If everyone has it, it has no value.
| fakedang wrote:
| I don't know where the whole HFT thinking came from?
| Renaissance wasn't known for HFT, it was known for using
| erstwhile new technologies such as data analysis and some
| machine learning to find patterns between uncorrelated data
| (like the weather in Paris affecting LSE trades).
|
| I think all of those points are the same for all Quant shops.
| All of them are at stagnant AUMs now for a reason. I mean this
| article seems like even GPT-3 could have written it.
| concreteblock wrote:
| 2. No strategy can scale indefinitely.
|
| 3. Every strategy can be viewed as a sort of 'arbitrage'.
|
| 4. Applies to every strategy.
| qeternity wrote:
| > 3. Every strategy can be viewed as a sort of 'arbitrage'.
|
| No, it can't. This is a bastardization resulting from the
| proliferation of "stat arb" to mean mispricing and is truly a
| misnomer.
| twic wrote:
| We have a running joke at work that our attempts at making
| money are "probabilistic arbs".
| bradleyjg wrote:
| Not arbitrage in the literal sense. The article claims only a
| small edge over thousands of equal risk positions which means
| no trade, or pair of trades, is risk free.
| finnh wrote:
| The non-compounding aspect is critical: you can think of the
| Medallion fund as a business that, with a capital base of (say) 5
| billion dollars, produces an annual profit of 2 billion dollars
| ... but cannot grow, and so distributes all of that profit every
| year. Kind of like a very profitable but geographically-isolated
| monopoly, telco, etc.
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