
A new sort of hedge fund relies on crowd-sourcing - miobrien
http://www.economist.com/news/finance-and-economics/21721946-amateur-coders-write-algorithms-compete-funds-new-sort-hedge-fund
======
stcredzero
Here's my "Tom Clancy movie plot" evil fund. Someone starts a fund that's
actually based on figuring out the portfolios of Senators, moderately high net
worth congresspersons and other Washington insiders. However, instead of
duplicating the entire portfolios of the whole populace, you first filter for
IQ, an age range where people are starting to be very well connected but still
making their fortunes, and develop another filter based on a quantitative
proxy for riskiness of each investment.

This is what the fund will really be based on, though there will be a fig leaf
fictional method advertised. The purpose of this is to piggyback on the
(technically-not) insider trading such people will manage to do while still
staying within the letter of the law. (Somehow, the collective portfolios of
US representatives manage to greatly outperform the stock market indexes.)

~~~
inputcoffee
This (insider trading by representatives) was common practice till the STOCK
act:

[https://en.wikipedia.org/wiki/STOCK_Act](https://en.wikipedia.org/wiki/STOCK_Act)

Check out the amendment in the last paragraph for more ideas for your Tom
Clancy movie.

~~~
ksherlock
it still is common practice.

[http://www.politico.com/story/2017/05/14/congress-stock-
trad...](http://www.politico.com/story/2017/05/14/congress-stock-trading-
conflict-of-interest-rules-238033)

------
chollida1
We've been seeing these quantopian fund stores for years now.

Where are the numbers? I mean at some point you have to produce right?

[https://news.ycombinator.com/item?id=12171843#12173142](https://news.ycombinator.com/item?id=12171843#12173142)

[https://news.ycombinator.com/item?id=12950276#12952666](https://news.ycombinator.com/item?id=12950276#12952666)

[https://news.ycombinator.com/item?id=12335272#12336086](https://news.ycombinator.com/item?id=12335272#12336086)

THe biggest issue I see for a quantopian fund is the "skin in the game" rule.
All of the successful fund managers I know have a very unhealthy portion of
their net worth in their own funds.

It's not clear to me that the quantopian algo designers will be able to, or be
forced to, put their own money into their strategies. I find "skin in the
game" to be one of the most promising alpha signals that still persists to
date.

~~~
zeppoleppo
This is an interesting comment as we have no way of validating how much money
designers are putting into their own algorithms.

I started building algorithms on Quantopian 2.5 years ago, using it as a way
to teach myself how to code because I come from a finance background and had
no coding experience. I now have a portfolio of algorithms that consistently
produce alpha (so far). My favorite algorithm does valuations and then buys
and holds for long periods of time. I don't actually invest any money into
this algorithm but rather use it as a prescreener for my own personal
investments. I have a significant amount of 'skin in the game' because of the
amount of time I have invested in developing my algorithms in addition to half
of my (very little) net worth being allocated based on the suggestions of my
algorithm.

I wouldn't be surprised if other designers were in the same boat. This is
purely anecdotal but I hope it helps.

~~~
Danieru
Do you know if there is something similar which can run against stocks traded
on the Japanese markets? I would love to write a pre-screener for myself.

------
creeble
Uh, isn't "the market" just the ultimate crowd-sourced fund?

~~~
jonbarker
The market is like a giant voting machine but not really a fund, since nobody
is managing it.

~~~
kgwgk
Index funds exist since the seventies.

~~~
jonbarker
Index funds actually still have a manager, whose only job is to rebalance
periodically and accurately.

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inthewoods
I'll repeat what I've said before about these platforms - I don't see why any
institutional money would ever flow to them. Most startup funds require at
least 5 years of audited history before any capital allocator will touch them.
They might get some small quick money from fund-of-funds, but I think they'll
be hard-pressed to keep it. Given the relative short history on these
platforms and the likely churn in algos, I can't see anyone putting serious
money into them.

One of the other problems I see with these platforms is that there is nothing
that stops me, as far as I can tell, from pulling my algo from that platform
once it is successful. Now there are lots of reasons why I could see people
not doing that (running your own fund is hard, raising capital is difficult),
but I don't see why anyone that is successful wouldn't immediately exit the
platform in order to maximize their return.

~~~
Houshalter
For numer.ai you can't leave. The data you get is private and encrypted. So
even if you come up with a great algo, you depend on them to do anything with
it.

~~~
klipt
Unless some other fund buys the same expensive data?

------
quantgenius
The problem with Quantopian, many current robo-advisors (including some with
large valuations) and other market-related fintechs is that by and large they
don't seem to have anyone who has had real success actually trading automated
quantitative strategies at a serious hedge fund or tier-1 proprietary trading
group on their founding teams. I've seen successful VCs, well-known academics,
market gurus, people with a background in some aspect of running a mutual fund
and all manner of other people who seem like they should be good, but nobody
with an actual track record. I've seen people who worked on technology at
hedge funds but the technology group at a hedge fund builds what amounts to
plumbing like clearing, reporting etc, not the actual trading technology,
certainly nothing that can actually impact PNL.

Jonathan Larkin at Quantopian comes closest to what is needed and since he
joined Quantopian has certainly had good success, but even his experience was
more along the lines of recruiting and risk-managing portfolio managers, not
actually running a large book. He certainly helps Quantopian but Quantopian is
coming from a place where when it was founded, I personally had to explain
what selection bias meant to John Fawcett and despite Jonathan Larkin being
there, they still seem to be making some pretty basic mistakes in how the
platform is setup.

Spending a few years working on a tier-1 automated trading desk is absolutely
essential because, what is deployed at those firms (and what you are competing
with) is years if not decades ahead of academia and the rest of the industry
and you learn more in a week of working on a successful trading desk (which
only happens if you demonstrate a lot of not just academic aptitude), with
people sharing knowledge available nowhere else than in a decade in academia
or anywhere else, even other groups at the same firm, potentially sitting 10
feet away from the trading group. I'm not suggesting people steal IP or
anything like that but you do have to have sone sense of what the state-of-
the-art actually is if you are going to claim to have developed something
state of the art.

I suspect it's going to end up like the search space, where the space will be
taken over by the second generation of firms that nobody has heard of who
decide to do things differently from how investment management is currently
run offline taking advantage of their knowledge of how mutual funds including
index funds are picked off by sophisticated traders.

Interestingly, Igor Tulchinsky at Worldquant and his team who are a tier-1
trading shop have basically been running a very successful version of what
Quantopian hopes to become without a lot of hoopla or publicity for years,
decades if you include the time they were doing this as an independent team at
Millenium.

~~~
tanderson92
> how investment management is currently run offline taking advantage of their
> knowledge of how mutual funds including index funds are picked off by
> sophisticated traders.

This is news to me, I was not aware that most index funds are being front-run
to such a large degree. I understand it was possible with the Russell 2000
index at some point. But e.g. the Vanguard Total Market fund (CRSP index) has
almost identical performance to the Fidelity Total Market index fund (Dow
Jones Total Market). And both funds replicate the performance of e.g. the
Ibbotson book.

How is it possible that this is occurring if the index funds are being picked
off? Or do you mean style / sector index funds, not broad market?

~~~
quantgenius
I don't mean to be snarky but I fail to understand why you believe that the
fact that the Vanguard Total Market Fund has almost identical performance to
the Fidelity Total Market fund and that both funds replicate the performance
of e.g. the Ibbotson book is an argument either for or against my statement
that sophisticated traders are able to make lots of money due to the actions
of index funds. I don't mean to be snarky and I would really like to give you
a meaningful answer but I'm not sure how to proceed and I'd like to understand
why you believe the two have anything to do with each other so I can give you
a higher quality reply.

~~~
tanderson92
they follow different indices and have similar returns. Please explain how
this is possible while still underperforming what they 'should' be returning.
Are both indices being front-run? But if they reconstitute at different times
how is this possible.

And yes, you do sound snarky.

~~~
quantgenius
> they follow different indices and have similar returns. > Please explain how
> this is possible while still > underperforming what they 'should' be
> returning.

They are both equity indices and equities are highly correlated to each other.
The first principal component of global equity returns explains over 50% of
the variance.

> Are both indices being front-run?

Yes! If a stock is getting added (or dropped) from an index, this is typically
announced (depending on the index) between 3 days and a month before the date
on which the change to the index is made. The index itself is calculated
assuming you bought (or sold) precisely at the close on the day of the
reconstitution. Index fund managers are incentivized to match the index. They
actually do worse personally if they modestly outperform the index and
potentially get fired if they underperform. So every index fund manager wants
to buy (or sell) the stock entering (or leaving) the index at precisely the
same time on the same day. This means you could potentially have as much as a
few months trading volume wanting to transact on the same side at precisely
the same time. Smart traders take advantage of this by a) Buying (selling
short for deletes) the stock over time before the index is reconstituted. b)
Selling what they bought and short selling more (or buying) stock to the index
funds at the close and c) Covering their shorts (or selling the excess stock
bought) over the next few weeks. The fund managers don't care because even
though a typical proprietary trading desk makes tons of money doing this, as
far as their clients are concerned, they are matching the index. You could
move a stock 50% in the rebalance but you wouldn't notice if you were
comparing a fund's returns relative to the index.

This is fairly obvious if you simply take a look at price charts of stocks
entering and leaving indices around index reconstitutions. Academic studies
(use google scholar for a few dozen references) estimate that the typical
index addition or deletion to the S&P 500 index moves between 2-4% between
announcement and reconstitution. This is an underestimate of what actually
happens because adds/deletes are predictable and stocks start moving long
before the announcements are made. S&P 500 stocks are the most liquid stocks
on the planet and the effect is much larger for other indices. The Russell
indices are not much more or less gameable than other indices per add or
delete but the effects are concentrated since all Russell Index rebalances
happen on a single day (fourth Friday in June) which creates massive jumps in
PNL for proprietary trading desks right around that time.

It's also fairly obvious if you look at the data carefully that in recent
years with the increasing popularity of index funds, the indices are
understating the potential returns available in the stock market. The market
has done "better" than the oft-quoted returns on the indices would have you
believe.

> But if they reconstitute at different times how is this > possible.

Why would the timing of the reconstitution have anything to do with why this
is possible or not?

~~~
tanderson92
I explicitly avoided mentioning the S&P500. Why did you bring it up? It makes
your point nicely but I'm not talking about the S&P500 or the R2k as examples
where front running of any significance is happening. The index
additions/deletions in the Total Market indices happen at the margins: micro-
cap stocks (and IPOs). Hard to argue much happens of any effect with micro-cap
stocks.

I don't necessarily disagree with you on the S&P500 or R2k, but it's much
harder to make the same argument for total market indices.

Please justify how you are saying the market returns understate potential
market returns. If it is not an index you are using, what is it?

> Why would the timing of the reconstitution have anything to do with why this
> is possible or not?

Because they have similar returns and add/remove stocks at different times. If
Vanguard's total market fund adds a stock after Fidelity's, then any jump
("front-running") in share price due to Vanguard's purchases would be captured
in a higher return for Fidelity since it already owned the shares.

------
DennisP
Numerai is also doing this: [https://numer.ai/](https://numer.ai/)

------
theprop
I think I found a new interview question: write an algorithm that outperformed
the market for the past ten years...you have 35 minutes...

~~~
dx034
That's easy and doesn't take 35 minutes. Here's the algorithm:

If year < 2009: short stocks

else: buy stocks

Add some leverage to this and you made a lot of money. Doesn't mean it'll work
in the future, though.

------
nether
One of Quantopian's studies shows that backtesting poorly predicts live
trading results: [https://blog.quantopian.com/using-machine-learning-to-
predic...](https://blog.quantopian.com/using-machine-learning-to-predict-out-
of-sample-performance-of-trading-algorithms/). From the forums, it looks like
90% of the effort is devoted to getting a good backtest, a yardstick which
might not have any bearing on reality. How do real quant traders deal with
this discrepancy?

~~~
akrymski
Real firms use tick data to backtest, not the 1 minute bars that Quantopian
uses, and spend a lot of time simulating network characteristics such as data
and order latency. They also use machine learning, which isn't possible on
Quantopian, to build models, which requires downloading lots of data (and not
just equities). No serious quant will ever use such a tool. You might as well
go to the casino.

~~~
akrymski
Edit: tick data is usually collected over time, because data sources have
different characteristics, and you should be testing over the same realtime
data that you'll be using to trade live. You need to know the bid/ask prices
and volumes, in order to know where to place limit orders. Otherwise you are
just paying commissions and spreads to brokers and market makers.

