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A Moneymaking Machine Like Few Others

258 点作者 volodia超过 8 年前

26 条评论

gdne超过 8 年前
I feel sad that so much brain power goes into market arbitrage. They produce nothing usable by anyone else. Imagine if these people built companies that made new advances and new products.
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DrBazza超过 8 年前
I&#x27;m working in the industry, and came from astrophysics, and intend to return to it one day. I would have stayed, but when the salary is 10x or more and you have a family, it&#x27;s an easy decision. A part of me always feels dirty doing what I&#x27;m doing when I see news about Hubble, New Horizons, etc.<p>And as for &#x27;super smart people&#x27;, I&#x27;d just say quants in general are &#x27;super smart&#x27; at the very narrowest of mathematical problem sets, but shouldn&#x27;t be let within a mile of a compiler. And they shouldn&#x27;t be invited to parties either.
mrdrozdov超过 8 年前
&gt; Eventually the scientists went so far as to develop an in-house programming language for their models rather than settle for a numbercentric option such as ASCII, which was popular at the time.
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wslh超过 8 年前
In another article [1] it says &quot;Currently Renaissance has three funds: Medallion, Renaissance Institutional Equities Fund and Renaissance Institutional Futures Fund. The latter two have been open to investors, but losses and withdrawls have left the funds wilted ($30 billion to $6 billion in three years).&quot;<p>[1] <a href="http:&#x2F;&#x2F;www.businessinsider.com&#x2F;bob-mercer-peter-brown-2010-3" rel="nofollow">http:&#x2F;&#x2F;www.businessinsider.com&#x2F;bob-mercer-peter-brown-2010-3</a>
justinsaccount超过 8 年前
<a href="https:&#x2F;&#x2F;www.amazon.com&#x2F;When-Genius-Failed-Long-Term-Management&#x2F;dp&#x2F;0375758259" rel="nofollow">https:&#x2F;&#x2F;www.amazon.com&#x2F;When-Genius-Failed-Long-Term-Manageme...</a><p><a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Long-Term_Capital_Management" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Long-Term_Capital_Management</a><p>&gt; Initially successful with annualized return of over 21% (after fees) in its first year, 43% in the second year and 41% in the third year, in 1998 it lost $4.6 billion in less than four months following the 1997 Asian financial crisis and 1998 Russian financial crisis requiring financial intervention by the Federal Reserve, with the fund liquidating and dissolving in early 2000.
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danielvf超过 8 年前
Two Sigma, mentioned in the article is currently hosting a fun AI programing contest at <a href="http:&#x2F;&#x2F;halite.io" rel="nofollow">http:&#x2F;&#x2F;halite.io</a><p>The learning code is not steep - you can really move up the ranks with simple improvements. I&#x27;ve had a great time.
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qwrusz超过 8 年前
For those questioning the returns, it&#x27;s important to remember this fund&#x27;s strategies clearly have capacity constraints. The article mentions a cap of $10B and a decade ago it was half that amount.<p>Why cap the size? What this means is usually whatever strategies RenTec employees are using in their Medallion fund likely do not work at larger dollar amounts.<p>Even worse, attempting to run a quant strategy above its size constraint can break it (this includes exposing too much about it to others). This would lead to it not ever working again even if they went back to only using small amounts.<p>if it aint broke, dont break it.
sixdimensional超过 8 年前
Once while applying for jobs I had an interview for a dev job with a firm like this. They refused to tell me exactly what they did, or even the company&#x27;s name. I had to sign an extensive NDA before I could even interview (it was weird having to sign an NDA when it wasn&#x27;t clear who I was signing it for)!<p>I was fresh out of school and flubbed the interview, but will never forget the experience. All they told me was, I would work around the clock, but if I came and did my job I would likely make a mint.
rezashirazian超过 8 年前
I&#x27;ve been dreaming about building stuff like this (on a much simpler scale) for a long time.<p>Perhaps a model that takes in past quarterly reports, commodity prices, executive performances and news regarding a company and calculates &#x27;tones&#x27; surrounding a company.<p>(for example appearance of &#x27;good performance&#x27;, &#x27;meeting targets&#x27;, &#x27;vast improvements&#x27; would possibly yield a positive tone where as &#x27;disappointing returns&#x27;, &#x27;failed endeavours&#x27; etc would yield negative). Then gauge past price sensitivities to various tones and see if there is any way to train the machine to speculate merely on these &#x27;tones&#x27;.
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lordnacho超过 8 年前
I&#x27;m a fund guy, and my take on RenTech is this.<p>We&#x27;re lucky to even have heard of them.<p>RT started off as a CTA. If you look at CTAs a good Sharpe is something like 1-1.25. You can buy a book that will get you most of the way there, and it&#x27;s really simple (Author Andreas Clenow, I forget the title). I have actually verified this myself, coding it up in Python.<p>If you simulate a random walk that has a sharpe of 1, you&#x27;ll find there&#x27;s plenty of periods where it&#x27;s down or sideways. So you need investors. They have to pay you management fees so that you can run the thing while it doesn&#x27;t make money.<p>Simons then changed tack. In the early 1990s the fund industry was very different. Most funds were discretionary funds where the boss decided what to punt on, and investors were used to trusting them to do so. So changing tack to another systematic strategy, in equities, could be sold to the investors.<p>Now this is significant, because there&#x27;s a lot more stuff you can do with equities. There&#x27;s industry structure, there&#x27;s individual company information, there&#x27;s analyst predictions for each firm, each firm has its own price series, there&#x27;s corporate actions, and so on for thousands of stocks. Contrast that with CTAs where you have a couple dozen liquid things, maybe 40, in a few categories (bonds, equities, commodities, FX).<p>If you find a strategy that works for a commodity and it gives you some Sharpe, maybe 0.1, and we assume for simplicity they are uncorrelated (which they aren&#x27;t!), you can roughly sum them up to sqrt(n). So there&#x27;s a big difference between 40 and say 2000. This is just a vignette, don&#x27;t take it literally. But the point is you can find strategies that in aggregate are much better in the equities space. Purely my opinion, I don&#x27;t often talk to people about this, so no feedback other that my collaborators.<p>So back to the story, Simons builds this thing and it starts printing money. Now he&#x27;s insanely rich, and the thing never loses money. So what does he need investors for? They are getting a free ride until the fund hits capacity.<p>Now if he had just gone straight to the Medallion fund, the thinking is the same. Why on earth would he need investors? If he didn&#x27;t need investors, why would he have his name out there? He wouldn&#x27;t, and neither would anyone who&#x27;d discovered anything similar. There&#x27;s probably a few groups like that out there. They&#x27;re unlikely to have built out the capacity, because they never became hedge funds. But I&#x27;m thinking they&#x27;re out there.
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nl超过 8 年前
<i>Eventually the scientists went so far as to develop an in-house programming language for their models rather than settle for a numbercentric option such as ASCII</i><p>Wow.<p>It&#x27;s amusing to imagine what the people at the fund told the journalist which ended up being turned into that.<p>A perfect example of the &quot;noisy channel&quot; idea in information theory.
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zump超过 8 年前
I wish I knew about this place as a kid. I would have tried my darnedest to get in.<p>Frustrating how a single bit of information can alter the course of one&#x27;s life.
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scandox超过 8 年前
Super smart people. Financial Alchemy. Computers. Secrecy.<p>What could possibly go wrong?<p><a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Long-Term_Capital_Management" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Long-Term_Capital_Management</a>
nathan_f77超过 8 年前
A few comments:<p>&gt; Eventually the scientists went so far as to develop an in-house programming language for their models rather than settle for a numbercentric option such as ASCII, which was popular at the time.<p>I might be missing something obvious, but this makes no sense to me. ASCII is not a programming language. And although UTF8 has taken over, I think ASCII is still very common.<p>&gt; (To this day the company’s website, rentec.com, looks like it dates from the Netscape era.)<p>That&#x27;s not very fair. I think the design is quite modern and minimalistic, and the website has definitely had some recent updates. It uses jQuery 1.11.3, which was released last year.<p>&gt; When the bill came, they would pull out a special calculator that could generate random numbers. Whoever produced the higher number picked up the tab.<p>I can&#x27;t figure out why the author decided to include this anecdote. I also can&#x27;t figure out why the scientists didn&#x27;t just flip a coin.<p>Another random thought: It&#x27;s interesting to think that whenever I&#x27;ve bought or sold some stock in the past, that little piece of data has made it&#x27;s way through all of their millions of lines of code, and all of their neural networks. They might have even made a few fractions of a cent based on my behavior.<p>&gt; By studying cloud cover data, they found a correlation between sunny days and rising markets from New York to Tokyo.<p>Wow. That&#x27;s incredibly interesting, and that&#x27;s just one example. Alright, their code has probably read all of my tweets, too. And everything else I post about online. Especially on all the subreddits for investments and stocks.<p>&gt; I don’t know, like 90 Ph.D.s in math and physics, who just sit there looking for these signals all day long.<p>Oh geez. Yeah, they&#x27;re looking at everything. Traffic, Yelp reviews, Pokemon Go, Netflix ratings, flight delays. I don&#x27;t know, maybe even newspaper horoscopes. Maybe the newspaper prints something that says Virgos are going to get lucky with an investment. And then they watch all of the online activity of all the virgo investors who still read newspapers.<p>Oh. And all of those companies selling your data? They&#x27;re buying that, too.<p>This sounds like a fascinating place to work. I want to know some of their secrets.<p>One more random thought: They knew Donald Trump was going to win. I guarantee it. And they probably made a ton of money on all those stocks that went up.
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MrJagil超过 8 年前
Here is another Bloomberg story about Robert Mercer, for those interested: <a href="http:&#x2F;&#x2F;www.bloomberg.com&#x2F;politics&#x2F;features&#x2F;2016-01-20&#x2F;what-kind-of-man-spends-millions-to-elect-ted-cruz-" rel="nofollow">http:&#x2F;&#x2F;www.bloomberg.com&#x2F;politics&#x2F;features&#x2F;2016-01-20&#x2F;what-k...</a>
hkmurakami超过 8 年前
Recommended reading: The Quants.
sixQuarks超过 8 年前
How do we know those returns are real? $1 million invested at the beginning would be worth $4.5 billion today at 35% return per year.
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eevilspock超过 8 年前
That we have an article that discusses people providing no value to society yet working the system to extract billions of dollars (and the political power that comes with it) as if it were fascinating and cool rather than obscene tells us how fucked up our society is right now.<p>Imagine reading a newspaper in 1840 reporting on a group of scientists who are making a killing in cotton because they figured out, using statistics <i>Moneyball</i> style, how to maximize profits by buying slaves that nobody else wants. Imagine the article tells it as a story of smart guys who amazingly did what no one else could do, with nary a comment or even awareness about the evil of slavery.
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kriro超过 8 年前
Makes me wonder why they don&#x27;t just invest all the money under management in that fund.<p>Edit: They are capped and take out profits...so I wonder if the cap is the magic or if they use better algorithms for their private fund (only natural since it&#x27;s their own money). They would have the same inputs (their data sets, infrastructure, programming language etc.) so I wonder if they have two very different models (&lt;=10 billion and &gt;10 billion) or how those are linked.
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mdotk超过 8 年前
These guys pay a ton of tax and also have investors like pension funds they take along for the ride.
Rainymood超过 8 年前
In the video they call him Jim Simon, is this a typo?<p>I think his name is Jim Simmons, was this intentional?
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UhUhUhUh超过 8 年前
Somehow this reminds me of LeGuin&#x27;s &quot;The Dispossessed&quot;.
known超过 8 年前
Former D. E. Shaw &amp; Co management
20161113超过 8 年前
What did you do seven years ago?
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sean_patel超过 8 年前
This sounds like the fictitious company in the Series &quot;Billions&quot;. How did these guys make 98.5% in 2000 and 33% in 2001 in the depths of the .com collapse of Wall Street?<p>Something smells fishy.
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riskable超过 8 年前
Note: This is merely my opinion...<p>The only way they&#x27;re making money like this is by cheating the system. I <i>highly</i> suspect they&#x27;re using their public funds to feed data into their private one in order to siphon off profits. It&#x27;s like a pyramid scheme except the mechanism of moving money is a form of market manipulation and this article is playing right into their hands by making them sound like geniuses (&quot;it&#x27;s all scientists!&quot;). Clearly, if this business is run by &quot;smart people&quot; (scientists) then their other two funds--which are actually accessible--must be promising! Right!?<p>TL;DR: The investors in the public funds are likely being scammed.
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