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Hedge Fund Uses Algae to Reap 21% Return

211 points by chollida1 9y ago

computerex 9y ago
A 3 year sample does not prove anything.
- monochromatic 9y ago
  A 3 year sample with only one impressive year.
- dsacco 9y ago
  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 9y ago
    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.
deleted 9y ago
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habosa 9y ago
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.
- alexandercrohde 9y ago
  I agree, I don't believe this would pass a test for statistical significance (of outperforming the market indices). Unless there is a way to break this data down much more finely (by 6-day window, by individual asset) in which case it's possible there's a high p-value but low-power effect. Even so, if there are more than 100 experimental firms, a single one with p-value .01 isn't evidence enough to jumping to big conclusions.
- frozenport 9y ago
  Well 1.05x0.85x1.30x1.10x1.00=1.27 Wow, so they are ~27% off the mean! The part that isn't clear is how this compared to typical performance variation - then we can run our p-tests. But I suspect its pretty good, given the news worthiness of the article.
  - rockostrich 9y ago
    Wouldn't 1.27^0.2=~1.05 be a better indicator?
    - CreepGin 9y ago
      Yes. 1.05 over the mean. Also for the actual return: 2013 +22% 2014 -2% 2015 +33% 2016 +22% 2017 +10% (til June) (1.22 * 0.98 * 1.33 * 1.22 * 1.1) ^ 0.2 = 1.16 Or for the 4 whole years: (1.22 * 0.98 * 1.33 * 1.22) ^ 0.25 = 1.18
- mholmes680 9y ago
  Also, hasn't been tested under bear market conditions... I'm skeptical that past returns prove future gains here. I can take any small subset of something and say its beating the market.
- zeteo 9y ago
  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.
gnaritas 9y ago
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 9y ago
  Importantly, he'll make plenty in fees in the meantime!
Jabbles 9y ago
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
chollida1 9y ago
> 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 9y ago
  > 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 9y ago
    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
m777z 9y ago
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).
b_ttercup 9y ago
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.
pliny 9y ago
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.
frgtpsswrdlame 9y ago
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 9y ago
  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 9y ago
    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).
platz 9y ago
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 9y ago
  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 9y ago
    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 9y ago
      isnt there already research to show that the stock and bond market behaviours are theoretically impossible to predict?
      - icebraining 9y ago
        It's disputed: https://en.wikipedia.org/wiki/Efficient-market_hypothesis https://en.wikipedia.org/wiki/Efficient-market_hypothesis
    - gaius 9y ago
      See http://www.independent.co.uk/news/business/comment/simon-english-stockbroker-beats-cat-and-fund-manager-6948428.html http://www.independent.co.uk/news/business/comment/simon-eng...
  - ZeroCool2u 9y ago
    Okay, I know you're joking, but this is exactly how I interpreted the title and I was so excited to see a picture of some suits staring at some green water and trying to read it like tea leaves.
sixhobbits 9y ago
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".
vanderZwan 9y ago
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).
anovikov 9y ago
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 9y ago
  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.
pxndx 9y ago
https://xkcd.com/1831/ https://xkcd.com/1831/
- gaius 9y ago
  Or "data science" Also https://xkcd.com/1570/ https://xkcd.com/1570/
tlb 9y ago
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.
koyote 9y ago
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 9y ago
  Stability maybe?
blahblah3 9y ago
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-investment-advisors/ http://keplerianfinance.com/2013/07/alpha-and-evaluating-inv... 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.
l5870uoo9y 9y ago
> 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-funds/ http://paulmerriman.com/10-reasons-brokers-dont-like-index-f...
- pvitz 9y ago
  See also [1]. Let's have a look at him again in 7 years. [1] https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc4a4 https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc...
joelthelion 9y ago
Can someone point me to a more technical description of the methods he uses?
- mathperson 9y ago
  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 9y ago
    I was hoping it would be part of a larger family of methods some of which would be public.
    - mathperson 9y ago
      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
csomar 9y ago
Wait a second. The average hedge funds is underperforming the SP500 index every year and by important returns? How are they still in business?
- pitaj 9y ago
  Beats me, man. My economics teacher in HS was telling us to invest in index funds years ago. It boggles the mind that hedge funds are so popular.
- encoderer 9y ago
  Diversification.
  - ceejayoz 9y ago
    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.
- cirenehc 9y ago
  to provide diversification
- dkural 9y ago
  Hope sells well, against reason. It's a soft way to gamble. Gambling also sells well.
- justadeveloper2 9y ago
  It's the same reason why companies buy licensed software even when decent open source alternatives exist--they know they can pick up a phone and yell at someone when something goes wrong. Also, there is a ton of folklore built up around the market and telling your golf buddies you are with 'so and so' is just another kind of name dropping.
- cat199 9y ago
  Many hedge funds invest in lots of things other than publically traded stocks e.g. local bonds, property companies, etc.. if you have some expectation the market will tank ala 2008, you probably don't want to keep all of your money in the market, even if you get lower returns overall.. Also, not sure about hedge funds, but alot of mutual funds exist with a specific focus - one country, sector, asset class, etc. They try to do well within that category... Just because the 'average' does worse, doesn't mean there aren't a few that do far better if you pick the right one.. Whether you think it is good to invest in that sector over the short or long run and why is up to you based on your portfolio and expectations for the market over the holding period.. As others have said - diversification.
msla 9y ago
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.
dkural 9y ago
Puff piece.
synaesthesisx 9y ago
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"
austenallred 9y ago
Let's see how Algae does when we're not in an outrageous bull market.
zitterbewegung 9y ago
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.
guelo 9y ago
Bullshit, it doesn't use algae.
deleted 9y ago
[deleted]
EGreg 9y ago
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!
0xbear 9y ago
All you had to do this year to reap a 20%+ return is not watch fake news. No algae required.
perseusprime11 9y ago
For a second, I read this as Hedge Fund uses Agile to Reap 21% Return and thought what the...
BeetleB 9y ago
5 year windows are practically noise: http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-invest/ http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-in...
deleted 9y ago
[deleted]
anesmike 9y ago
fooled by randomness
osrec 9y ago
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?
wtfz 9y ago
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?
- pgwhalen 9y ago
  I love that kind of thought experiment! In practice, at hedge fund scale, no one is going to sell you options with that risk/reward profile I think.
  - noddy1 9y ago
    There are ways to achieve this though - using a martingale betting strategy where you take small, high risk bets and basically keep doubling up until you win or bust, you can achieve the same risk-reward profile on most high risk markets
- xchaotic 9y ago
  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 9y ago
    > 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.
nodesocket 9y ago
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&chvs=Linear&chdeh=0&chfdeh=0&chdet=1500670535207&chddm=500089&chls=IntervalBasedLine&q=NYSEARCA:SPY&ntsp=0&ei=RGpyWbGuFYPrjAH01KboBg https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&... [2] - 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 https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&...
module0000 9y ago
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 9y ago
  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 9y ago
    > an average of Does this exclude outliers? What's the median duration?
    - scott_karana 9y ago
      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.
crb002 9y ago
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 9y ago
  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.

211 points by chollida1 9y ago

computerex 9y ago

A 3 year sample does not prove anything.

monochromatic 9y ago
A 3 year sample with only one impressive year.
dsacco 9y ago
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 9y ago
  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.

deleted 9y ago

[deleted]

habosa 9y ago

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.

alexandercrohde 9y ago
I agree, I don't believe this would pass a test for statistical significance (of outperforming the market indices). Unless there is a way to break this data down much more finely (by 6-day window, by individual asset) in which case it's possible there's a high p-value but low-power effect. Even so, if there are more than 100 experimental firms, a single one with p-value .01 isn't evidence enough to jumping to big conclusions.
frozenport 9y ago
Well 1.05x0.85x1.30x1.10x1.00=1.27 Wow, so they are ~27% off the mean! The part that isn't clear is how this compared to typical performance variation - then we can run our p-tests. But I suspect its pretty good, given the news worthiness of the article.
- rockostrich 9y ago
  Wouldn't 1.27^0.2=~1.05 be a better indicator?
  - CreepGin 9y ago
    Yes. 1.05 over the mean. Also for the actual return: 2013 +22% 2014 -2% 2015 +33% 2016 +22% 2017 +10% (til June) (1.22 * 0.98 * 1.33 * 1.22 * 1.1) ^ 0.2 = 1.16 Or for the 4 whole years: (1.22 * 0.98 * 1.33 * 1.22) ^ 0.25 = 1.18
mholmes680 9y ago
Also, hasn't been tested under bear market conditions... I'm skeptical that past returns prove future gains here. I can take any small subset of something and say its beating the market.
zeteo 9y ago
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.

gnaritas 9y ago

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 9y ago
Importantly, he'll make plenty in fees in the meantime!

Jabbles 9y ago

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

chollida1 9y ago

> 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 9y ago
> 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 9y ago
  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

m777z 9y ago

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).

b_ttercup 9y ago

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.

pliny 9y ago

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.

frgtpsswrdlame 9y ago

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 9y ago
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 9y ago
  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).

platz 9y ago

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 9y ago
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 9y ago
  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 9y ago
    isnt there already research to show that the stock and bond market behaviours are theoretically impossible to predict?
    - icebraining 9y ago
      It's disputed: https://en.wikipedia.org/wiki/Efficient-market_hypothesis https://en.wikipedia.org/wiki/Efficient-market_hypothesis
  - gaius 9y ago
    See http://www.independent.co.uk/news/business/comment/simon-english-stockbroker-beats-cat-and-fund-manager-6948428.html http://www.independent.co.uk/news/business/comment/simon-eng...
- ZeroCool2u 9y ago
  Okay, I know you're joking, but this is exactly how I interpreted the title and I was so excited to see a picture of some suits staring at some green water and trying to read it like tea leaves.

sixhobbits 9y ago

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".

vanderZwan 9y ago

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).

anovikov 9y ago

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 9y ago
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.

pxndx 9y ago

https://xkcd.com/1831/ https://xkcd.com/1831/

gaius 9y ago
Or "data science" Also https://xkcd.com/1570/ https://xkcd.com/1570/

tlb 9y ago

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.

koyote 9y ago

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 9y ago
Stability maybe?

blahblah3 9y ago

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-investment-advisors/ http://keplerianfinance.com/2013/07/alpha-and-evaluating-inv... 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.

l5870uoo9y 9y ago

> 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-funds/ http://paulmerriman.com/10-reasons-brokers-dont-like-index-f...

pvitz 9y ago
See also [1]. Let's have a look at him again in 7 years. [1] https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc4a4 https://www.ft.com/content/e555d83a-ed28-11e5-888e-2eadd5fbc...

joelthelion 9y ago

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

mathperson 9y ago
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 9y ago
  I was hoping it would be part of a larger family of methods some of which would be public.
  - mathperson 9y ago
    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

csomar 9y ago

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

pitaj 9y ago
Beats me, man. My economics teacher in HS was telling us to invest in index funds years ago. It boggles the mind that hedge funds are so popular.
encoderer 9y ago
Diversification.
- ceejayoz 9y ago
  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.
cirenehc 9y ago
to provide diversification
dkural 9y ago
Hope sells well, against reason. It's a soft way to gamble. Gambling also sells well.
justadeveloper2 9y ago
It's the same reason why companies buy licensed software even when decent open source alternatives exist--they know they can pick up a phone and yell at someone when something goes wrong. Also, there is a ton of folklore built up around the market and telling your golf buddies you are with 'so and so' is just another kind of name dropping.
cat199 9y ago
Many hedge funds invest in lots of things other than publically traded stocks e.g. local bonds, property companies, etc.. if you have some expectation the market will tank ala 2008, you probably don't want to keep all of your money in the market, even if you get lower returns overall.. Also, not sure about hedge funds, but alot of mutual funds exist with a specific focus - one country, sector, asset class, etc. They try to do well within that category... Just because the 'average' does worse, doesn't mean there aren't a few that do far better if you pick the right one.. Whether you think it is good to invest in that sector over the short or long run and why is up to you based on your portfolio and expectations for the market over the holding period.. As others have said - diversification.

msla 9y ago

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.

dkural 9y ago

Puff piece.

synaesthesisx 9y ago

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"

austenallred 9y ago

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

zitterbewegung 9y ago

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.

guelo 9y ago

Bullshit, it doesn't use algae.

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EGreg 9y ago

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!

0xbear 9y ago

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

perseusprime11 9y ago

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

BeetleB 9y ago

5 year windows are practically noise: http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-invest/ http://blog.nawaz.org/posts/2015/Dec/pay-down-mortgage-or-in...

deleted 9y ago

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anesmike 9y ago

fooled by randomness

osrec 9y ago

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?

wtfz 9y ago

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?

pgwhalen 9y ago
I love that kind of thought experiment! In practice, at hedge fund scale, no one is going to sell you options with that risk/reward profile I think.
- noddy1 9y ago
  There are ways to achieve this though - using a martingale betting strategy where you take small, high risk bets and basically keep doubling up until you win or bust, you can achieve the same risk-reward profile on most high risk markets
xchaotic 9y ago
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 9y ago
  > 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.

nodesocket 9y ago

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&chvs=Linear&chdeh=0&chfdeh=0&chdet=1500670535207&chddm=500089&chls=IntervalBasedLine&q=NYSEARCA:SPY&ntsp=0&ei=RGpyWbGuFYPrjAH01KboBg https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&... [2] - 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 https://www.google.com/finance?chdnp=0&chdd=0&chds=0&chdv=1&...

module0000 9y ago

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 9y ago
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 9y ago
  > an average of Does this exclude outliers? What's the median duration?
  - scott_karana 9y ago
    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.

crb002 9y ago

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 9y ago
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.