
Hedge Fund Uses Algae to Reap 21% Return - chollida1
https://www.bloomberg.com/news/articles/2017-07-20/hedge-fund-quant-posting-21-return-says-biology-is-secret-sauce
======
habosa
In the chart, this is how the fund has compared to an S&P index over the past
5 years:

    
    
      * 2013 - 5% over
      * 2014 - 15% under (and negative overall)
      * 2015 - 30% over
      * 2016 - 10% over
      * 2017 - About even
    

One exceptionally strong year, and pretty uneven otherwise. Hardly proof that
these biology-derived algorithms are the secret to market-beating returns.

~~~
zeteo
Also there's a question of how many new hedge funds are using machine
learning. If you have enough different attempts, one of them will beat the
market by sheer game of chance. Picking out their specific quirks afterwards
(algae etc.) is just survivor bias.

~~~
dsacco
_> If you have enough different attempts, one of them will beat the market by
sheer game of chance._

How do you define an "attempt", and how many "attempts" do you need to beat
the market (consistently) by chance?

~~~
zeteo
Get 25 monkeys to throw darts at S&P 500 stock symbols on January 1st of each
year. The chance that at least one monkey outperforms 5 years in a row is
about 55%. (The target areas need to be proportional to market capitalization
etc.)

~~~
dsacco
That's if you have one trade per year. How would you model this if you have 25
monkeys throwing, say, 300 darts at the board per day, for every day that the
market is open (252 days), for five years?

If you're going to quantify survivorship bias, you can't use entire years as
data points, because that doesn't properly represent the amount of activity
that occurs. We should reason about each event, because if consistency emerges
on an event basis we might not even need more than one year for our sample.
The decision-making that is being empirically examined here (i.e. acumen
capable of beating the market beyond chance) ostensibly functions on trading
events, which means years are not the correct data point to use (and will
provide an incorrectly pessimistic sample).

~~~
zeteo
> That's if you have one trade per year. How would you model this if you have
> 25 monkeys throwing, say, 300 darts at the board per day, for every day that
> the market is open (252 days), for five years?

If the data is reported on a yearly basis then it's pretty much the same
thing.

~~~
dsacco
No it isn't, because each firm doesn't have a 50% chance of beating the market
each year. Unless you're postulating that that _is the case_ , it's not at all
the same.

I can quibble about the odds of each individual trade resulting in profit or
less being binary, but for the sake of argument it'll do. But a 50% chance of
beating the market _each year_ isn't supported by anything.

The grouping of data reporting doesn't suggest anything about the underlying
data if it doesn't also share the same probability distribution. The _trades_
are the events which determine if a fund will outperform on an annual basis,
and we can group those trades by day, week, month, year, etc.

~~~
zeteo
Strategy A: buy one random stock per year.

Strategy B: buy two random stocks.

If the expected payoffs were mathematically different then you'd have an
arbitrage opportunity. Then apply induction.

------
platz
Was disappointed because title is misleading; I had hoped the fund was using
actual Algae (i.e. computation in biological medium) to produce market
decisions. Instead it is just biologists that are creating algos with their
existing machine-learning knowledge. Apparently deep-learning and algae are
the same thing.

~~~
makmanalp
I was hoping that it like that situation when Caligula replaced a senator with
a horse, but rather the hedge fund replaced quants with algae :-)

~~~
Bartweiss
Didn't the monkey win when they tried that instead?

I'm holding out for a 4-way contest of quant, horse, monkey, and algae. I
won't be betting on the winner, either.

~~~
vikascoder
isnt there already research to show that the stock and bond market behaviours
are theoretically impossible to predict?

~~~
icebraining
It's disputed: [https://en.wikipedia.org/wiki/Efficient-
market_hypothesis](https://en.wikipedia.org/wiki/Efficient-market_hypothesis)

------
frgtpsswrdlame
Here's the important part of the article:

 _There are skeptics, too. Emanuel Derman, who was among the first physicists
to work on Wall Street, doubts that biologists possess secret sauce for
investing. Derman rose to lead the quant risk strategies group in his 17 years
at Goldman Sachs Group Inc. He found that as physicists applied their
expertise of the laws of motion, atoms and mathematics to investing, their
models didn’t work nearly as well as they did in a lab.

Newton’s law of gravity hasn’t changed for eons, Derman said, but human
behavior in markets changes all the time, wreaking havoc on even the best
models made by scientists.

“I’ve developed a lot of skepticism about anyone bringing their expertise from
one field to another,” said Derman, author of the book “Models.Behaving.Badly”
and a Columbia University professor of financial engineering. “They say stocks
are like atoms, or like genes. But stocks are not atoms or genes. There is a
resemblance, but ultimately they are very different.”_

~~~
redroot9
This is essentially a certain type of cognitive bias I think (halo effect?),
where people take someone's high skill or talent in one area and assume it
carries to another field. For example, assuming a chess grandmaster will be
good at business strategy, or a great mathematician an automatically great
engineer. These examples are convaluted but anecdotally I've seen it in action
in recruiting.

Also 'the map is not the territory', all models will be unable to deal with
all possible behaviours of the reality they are dealing with in a correct way.

~~~
dsacco
I don't think the cognitive bias you're describing matches this scenario very
well, because that bias appears to result when people don't acknowledge
specialization versus overall intelligence.

Your first example seems like it maps well to that cognitive bias - someone
assumes that a chess grandmaster has catch-all capability because they
demonstrated expertise in one area, and then they flare out in an orthogonal
area.

Mathematics and engineering (at least, computer science) overlap in many
areas. If someone excels at mathematics it doesn't _prove_ that they'd be good
at programming, but I'd bet a significant amount of money that the mean
mathematics major is more capable of programming than the mean population in
general. If that holds, there's no bias in trying to cross-pollinate
expertise, even if it ultimately doesn't work out.

A lot of the work that occurs in finance is legitimate mathematics and has
very close ties to physics. The heat equation is directly used in Black-
Scholes; securities can be modeled as stochastic processes, which means that
much of the models that apply to Brownian motion also apply to them. Outside
of quantitative derivatives pricing (and more recently), hedge funds can apply
the same scientific computing techniques used by physicists and computational
biologists to analyze vast amounts of data (more than they know what to do
with).

~~~
computerex
And yet: [http://fortune.com/2016/05/11/warren-buffett-hedge-fund-
bet/](http://fortune.com/2016/05/11/warren-buffett-hedge-fund-bet/)

~~~
dsacco
1\. That doesn't meaningfully respond to my point about cross pollinating
skillsets, because we aren't distinguishing between amateurs, novices who
become professionaks after expertise in other fields, and core professionals
in finance/economics.

2\. That bet is paraded more than it should be. Buffett bet against a "fund of
funds", which is the aggregate performance of the industry. We didn't need a
decade long bet to tell us most hedge funds are a poor return of capital, just
as we don't need a bet to realize that the greatest _n_ participants in many
fields are mediocre.

I would have gladly taken that bet with Buffett _and won_ if I could have
chosen a single firm. But Buffett wouldn't have taken _that_ bet, because (to
his credit) he understands this point already as a savvy investor. The bet
proves that the industry overall is mediocre, but it says nothing about the
top firms that mostly don't even take outside capital anymore because they're
so successful.

~~~
computerex
I was being cheeky when I responded to you. I agree with you on the first
point.

But I think you are downplaying the significance of the bet. If it was an
obvious wash like you are making it seem then why was the bet even placed?
What top firms are you talking about?

~~~
dsacco
1\. The bet was placed because Buffett's thesis is fundamentally true - you
have much better odds of receiving a good return through passive index fund
investing than you do through active management. However, this bet is often
used (unempirically, though not necessarily _strictly inaccurately_ ) to
justify the idea that active management _cannot_ beat the market consistently.

2\. Firms like Baupost or RenTec would have handily won that bet against
Buffett. But like I said, Buffett wouldn't have made that bet, because Buffett
is a smart better and already knows all of this. Buffett has _never_ argued
that the market is perfectly efficient and resistant to alpha harvesting; in
fact, he has publicly taken the opposite position in letters to shareholders.

------
module0000
They are overthinking this... with sufficiently low latency to your exchange,
all your "quant"(and I use this term loosely) needs to do is watch the order
book. When either side's inside bid/ask is about to crack, you join the
opposing side with a market order, and place a stop on the next tick in your
direction.

This is what 99.99% of consistently profitable quants do. It's boring,
unexciting, and VERY profitable. The crux is...you must have that low latency
connection to the exchange, and you must have priority routing for your
orders. Bonus point if you have market maker status(but if you have that, why
are you doing this in the first place?).

The deep learning craze seems to be infiltrating the minds of a few
algorithmic funds, but it doesn't stay long(either they stop trying it, or
they blow up their fund). Positions of any reasonable size(such as that
required to move the market) are opened by human beings. Human beings operate
on emotion and mob mentality in the market, so that is what you capitalize on
when designing your algorithm.

Disclaimer: I'm looking at this with an ultra short term timeframe, such as
5-15 seconds being the maximum time in market per position. If these guys are
targeting longer term positions, then all bets are off. The algorithms I
create and maintain work in this timeframe, and the majority of my competitors
algorithms are in the same timeframe.

~~~
scott_karana
I agree with your general assessment of HFT, but if the article is correct,
this fund doesn't fit that mold:

> said Lun, whose computer holds trades for an average of _six days_

~~~
namuol
> an average of

Does this exclude outliers? What's the median duration?

~~~
scott_karana
Even though "average" is a statistically non-rigorous term, we should be out
of the "5-15 second _maximum_ " holding times mentioned by GP by at least one
order of magnitude.

~~~
module0000
It's average as determined by the statistics from my own algorithm's
licensees, and from my competitors. I'm sure there are plenty out there that
don't fit that mold, but all I can report on is what I see - and those
statistics are what I see day in and day out.

Another disclaimer, the markets I'm quoting these averages from are the ES and
ZB.

------
blahblah3
It's hard to know if the returns are statistically significant given annual
returns, but I'm sure he's providing more granular statistics to investors.
Kinda annoying how the articles hypes this by distinguishing it from
statistical models since he is obviously running some sort of statistical
model as well.

In general, people have a poor understanding of how to evaluate an investment
manager. It's not enough to just look at absolute returns and compare them to
the S&P, you need to correct for market exposure (the beta). Even then, it is
not that straightforward: this is one of the best overviews I've seen (the
author of the blog, Robert Frey, was a former managing director at Renaissance
Technologies, the most successful hedge fund of all time)

[http://keplerianfinance.com/2013/07/alpha-and-evaluating-
inv...](http://keplerianfinance.com/2013/07/alpha-and-evaluating-investment-
advisors/)

To make the "correcting for exposure" aspect concrete, suppose you have the
opportunity to invest in a poker player that generates a 10% return on capital
per year. It wouldn't really make sense to compare this return to the S&P 500
returns, because the beta is very close to 0.

------
chollida1
> As the genome project produced reams of data, Lun saw an opportunity to
> break ground in computational biology and in 2006 joined the Broad Institute
> of MIT and Harvard, a crossroads for scientists and hedge fund managers.
> There Lun met senior computational biologist Nick Patterson, a former
> cryptographer who had spent a decade at Renaissance Technologies making
> mathematical models. Another Lun colleague, genomic researcher Jade Vinson,
> left Broad for the same pioneering quant hedge fund for 10 years.

Well he is certainly surrounded by some impressive people.

I think at this point in the search for alpha, wall street has employed
applied mathematicians, physicists, code breakers, engineers, economists,
chemists, computer scientists, sociologists, and now computational biologists.

Each one of them brought some new/novel mathematical techniques to the field.
Do Medieval Historians learn any specialized math?

Maybe he can beat the market reliably but he's only managing $20 million. The
big question every quant fund asks is can this strategy provide alpha at a
salable level of investment.

A 3 year track record is plenty long enough to prove out a system and provide
a track record. It's a troubling sign that there is only $20 million in his
fund if.

~~~
dsacco
_> A 3 year track record is plenty long enough to prove out a system and
provide a track record. It's a troubling sign that there is only $20 million
in his fund if._

I'm curious as to why you say a 3 year track record is long enough to prove a
system. I don't necessarily disagree (though I think number of trades executed
in that timespan and the type of trading strategy might be as important as the
timespan itself), but I'm interested in your reasoning.

~~~
chollida1
Sure, great question.

It's important to note that 3 years doesn't mean 3 data points. It really
depends on the funds average trade horizon. Which is, I think, exactly what
you were referring to.

An HFT firm trades at such small scales that it can use its daily returns such
that each year actually provides 252 data points.

On the other side of the coin, Berkshire Hathaway would need benchmark times
longer than a single year.

I'm assuming the fund has holding times of around a week based on intuition
and prior knowledge of alto of different fund investment structures.

The thing to understand about hedge funds is that most of them change
investment strategies at some point in their lifetime such that historical
records no longer really apply. This can happen for a number of reasons:

1) markets get crowded and force people to search for alpha somewhere else

2) funds get larger and existing strategies don't have the capacity to manage
the new money.

3) traders leave and new traders have new ideas.

3 year is an industry goldilocks mark for comparing hedge funds. Not too long
to take into account old strategies that are no longer employed and not too
short that it doesn't allow the strategies to play out.

I cant' remember the exact number but Victor Haghani of LTCM fame talked about
this and said it would be something like 143 years of data to know if a biased
coin that comes up heads 60% of the time is biased to a 95% confidence level.

Obviously this isn't workable and as such we have to use smaller time frames.

See:

[http://labs.elmfunds.com/pastreturns](http://labs.elmfunds.com/pastreturns)

[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2856963](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2856963)

~~~
dsacco
Yeah, that all makes sense, thanks. I figured you were using that 3 year
figure with an implicit acknowledgement that it would provide greater or
lesser rigor depending on the number of trades and the holding time. Thanks
for the resources as well.

------
sixhobbits
The article is pretty hyped and low on actual details. From what I can figure
out, he used the same models that he used to predict stuff about Algae to
predict the market.

No information about what these models are is given. But it seems more "I
created a system which can predict cell changes and stock market movements"
than "I used Algae to predict the stock market".

------
anovikov
Better this guy would continue working on algae to finally invent that
(definitely possible) strain that would be useful to produce cheap fuel from!
He tried to play that eternal zero sum game instead... sad

~~~
thablackbull
It sounds like he is doing both (managing investments and doing research)
simultaneously. From the article,

> Lun, who was born in Hong Kong, splits his time between his firm in
> Pennsylvania and lab at Rutgers, where he’s undertaken an ambitious long-
> term project: creating computer models that predict how cells behave, using
> data from blue-green algae and other sources. The models allow Lun to re-
> engineer genes for useful purposes: he has modified E. coli for production
> of bio-fuel for transportation.

------
wtfz
Question for investing people.. say I started a hedge fund, put all the money
in vanguard to achieve s&p500 benchmark return, then once a year did an
options bet with a roughly 97 percent chance of a 3 percent return and a 3
percent chance of ruin. I do this for 10 years, outperformng the s&p 500 by 3
percent consistently. I have 70 percent odds of not being ruined, and I
consistent outperform most hedge funds. I have good alpha and there is no way
to see that my beta ain't great. Would I become a wealthy hedge fund manager?

~~~
xchaotic
It's a good strategy, if you can afford not to withdraw from the fund on the
year (and for several years after) you 97% bet turns sour - there was an
article somewhere, which showed that options on S&P singe the great depression
almost a hundred years ago, would have only slightly outperformed the index,
due to losing in the bear market.

~~~
random28345
> It's a good strategy, if you can afford not to withdraw from the fund on the
> year (and for several years after) you 97% bet turns sour

If the bet turns sour, you close the fund. The idea is that you grow the fund
and take your two and twenty while your bets are winning, and you keep your
prior years' two and twenty after your fund collapses.

------
l5870uoo9y
> In John Bogle's “The Little Book of Common Sense Investing,” he notes that
> the average U.S. equity fund compounded at 10 percent from 1980 through
> 2005, while the Vanguard 500 Index Fund made 12.3 percent. Actively managed
> funds did worse than average, not better as the brokers would have you
> believe.[1]

Lets see how it performs longer term (10 year period).

[1]: [http://paulmerriman.com/10-reasons-brokers-dont-like-
index-f...](http://paulmerriman.com/10-reasons-brokers-dont-like-index-funds/)

~~~
pvitz
See also [1]. Let's have a look at him again in 7 years.

[1]
[https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc...](https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc4a4)

------
tlb
It's sad to see people with potential to create worthwhile things, get sucked
into zero-sum financial games.

* Not everything financial is zero-sum, but this sounds like it is.

------
Jabbles
From the chart in the article:

    
    
        Year Market Algae
        2013  +16%  +22%
        2014  +14%   -2%
        2015  +2%   +33%
        2016  +12%  +22%
        2017* +9%   +10%
    

*Til June

------
msla
This guy looks young. Usually, it's the older Ph.D.s who veer into
crackpottery.

I'm reminded of Linus Pauling: He made amazing, fundamental breakthroughs in
chemistry and quantum physics, but when he applied his genius to medicine, we
got orthomolecular medicine and mega-dose vitamin C as a cure-all, something
which has been roundly disproven by actual evidence.

That said, investing in algae could be a good idea. It has potential as a
cheap, high-volume input to synthetic food production.

------
vanderZwan
Aside from whether this actually works reliably already or not, from a
principal point of view it makes sense that computational biology adds
something to the mix.

For the last year I've only been a glorified webdeveloper working for
molecular neurobiologists at the Karolinska Institute, but from what I
understand it is all about untangling vast quantities of high-dimensional
data: data sets of tens to hundreds of thousands of individuals cells, where
for each cell the expression levels of tens of thousands of genes are being
measured (in what stage of development in which tissue was the cell
harvested).

If you can find algorithms that somehow make sense of how these cell
populations and genes interact and develop over time, I think it is not out of
the question that the same algorithms could make some sense of the aggregate
behaviour of the stock market, give a decent data set as input of course.
Especially given that most of these algorithms are forms of machine learning,
so don't necessarily require an a priori model of what is happening (I mean,
if I understand correctly, uncovering that model is precisely what the
biologists are after).

------
synaesthesisx
This looks like satire - these guys are literally underperforming the S&P. My
own personal investing returns as an individual surpass theirs!

Where can I sign up to gamble with other peoples money with my black-box AI
algorithms based on fungal evolutionary genomics?

“It’s hard to explain simply why and how it works"

------
gnaritas
Boo, he basically got lucky twice, once on Brexit and once on Trump's
election; he'll raise a bunch of money for his fund, lose much of it and be
out of business in a few years when his model fails because luck isn't a
strategy.

~~~
isolli
Importantly, he'll make plenty in fees in the meantime!

------
zitterbewegung
I think what he is doing is modeling equities as an interaction model and
performing clustering and or community detection on a dynamic graph. On the
bottom you see a bunch of triads graphs. When they say "A quant tries to make
sense of time-series price data that at first look chaotic because we don’t
know the different parameters and their relations. So you try to piece that
together, as one would do with biological data." you could accomplish this by
taking the time series data and when one equity interacts with another within
some type of time series window you would compute a set of graphs and see how
they cluster together.

------
b_ttercup
I can't tell if this suggesting he uses models that were made to predict algae
growth or if he is using algae/bio/genetic inspired optimization algorithms.
But either way he is certainly not "using" algae.

------
m777z
I guess I'm a bit skeptical. The article doesn't address how the fund managed
to lose 2% in a year when holding an S&P 500 index fund would've gotten a 10+%
return, and in general we just need more data before we can conclusively say
that this has an edge on the market.

I also did not understand why cells specifically provide such good insights
for markets, as compared to any other complex natural system (like weather or
ecological systems).

------
osrec
Based on the title and the summary, I thought the guy was plugging wires into
algae in a Petri dish and getting some magical output that lets him beat the
market. Turns out, he's crunching numbers with a computer using a mathematical
model borrowed from computational biology. This doesn't sound all too
different to what quant hedge funds do currently, unless I'm missing
something?

------
crb002
I think this would be the paper behind his algorithm:
[http://crab.rutgers.edu/~dhong/Papers/fBm2014.pdf](http://crab.rutgers.edu/~dhong/Papers/fBm2014.pdf)

~~~
crb002
Or this one:
[https://arxiv.org/pdf/cs/0605067.pdf](https://arxiv.org/pdf/cs/0605067.pdf)

Find non-diversified asset pools based on mutual information of prices. Avoid
too much exposure to any pocket, but do arbitrage within a pocket.

------
EGreg
I thought this was going to be about how a hedge fund makes money by
increasing algae in the world.

If we all planted trees and algae then we'd increase carbon sinks and solve
the greenhouse gas problem in a sustainable way.

I am surprised more money - or at least ink - isn't funneled into this!

------
BeetleB
5 year windows are practically noise:

[http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-
in...](http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-invest/)

------
nodesocket
Moral of the story... Just buy $SPY[1] or $BRK.B[2] and sit back. Hedge funds
struggle to beat or even match the S&P.

[1] -
[https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&...](https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&chvs=Linear&chdeh=0&chfdeh=0&chdet=1500670535207&chddm=500089&chls=IntervalBasedLine&q=NYSEARCA:SPY&ntsp=0&ei=RGpyWbGuFYPrjAH01KboBg)

[2] -
[https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&...](https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&chvs=Linear&chdeh=0&chfdeh=0&chdet=1500670579360&chddm=500089&chls=IntervalBasedLine&q=NYSE:BRK.B&ntsp=0&ei=cGpyWfH1EsaA2Abdx5S4CA)

------
pliny
Just from eyeballing the chart it looks like they made a few million more than
the index, over those five years, which pays for 3ish engineers if they're
taking half the performance over index and no management fees.

------
austenallred
Let's see how Algae does when we're not in an outrageous bull market.

------
koyote
Slightly off topic:

In the graph hedge funds have performed very badly against the S&P. Given the
massive fees a lot of hedge funds charge: what is the incentive?

~~~
pitaj
Stability maybe?

------
dkural
Puff piece.

------
csomar
Wait a second. The average hedge funds is underperforming the SP500 index
every year and by important returns? How are they still in business?

~~~
encoderer
Diversification.

~~~
ceejayoz
I mean, you could have a "throwing money into an incinerator" ETF and call it
diversification, but that doesn't make it a good call. There are plenty of
other ways to diversify if an index fund with hundreds of stocks isn't already
diverse enough for you.

------
computerex
A 3 year sample does not prove anything.

~~~
dsacco
Not if you group all trading events into single data points by year it
doesn't, but that's a silly way of analyzing them if you have extraordinary
performance consistency on a day by day (or trade by trade!) basis.

~~~
BeetleB
In the end, all that we care about is the effective annual rate of return. It
doesn't matter if you did 200 trades that year or 1 - the money is the same if
you have the same RoR.

The number of data points is important when looking for trends, or for
cleanness of data. However, they're not showing us the data. It could be
hugely volatile, or fairly linear.

------
guelo
Bullshit, it doesn't use algae.

------
perseusprime11
For a second, I read this as Hedge Fund uses Agile to Reap 21% Return and
thought what the...

------
joelthelion
Can someone point me to a more technical description of the methods he uses?

~~~
mathperson
It probably doesn't exist. Most funds of this type are very very paranoid
about publicizing the methods they use because 1\. Another firm could exploit
what they are doing. 2\. Another firm could trade the signal and remove their
ability to profit. 3\. They think being opaque makes them cool and mysterious.
Which it does.

~~~
joelthelion
I was hoping it would be part of a larger family of methods some of which
would be public.

~~~
mathperson
Ah I see. There is typically gossip on quant blogs? Like Wilmott and Nuclear
Phynance. That might help. Or you can look at

1\. Options/Futures etc by Hull

------
pxndx
[https://xkcd.com/1831/](https://xkcd.com/1831/)

~~~
gaius
Or "data science"

Also [https://xkcd.com/1570/](https://xkcd.com/1570/)

------
anesmike
fooled by randomness

------
0xbear
All you had to do this year to reap a 20%+ return is not watch fake news. No
algae required.

