5 ms·
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
by 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 agoI 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 agoWell 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 agoWouldn't 1.27^0.2=~1.05 be a better indicator?
- CreepGin 9y agoYes. 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 agoAlso, 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 agoAlso 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 agoThe whole industry is based on investors not understanding survivor bias and quite often traders not understanding hindsight bias.
- dsacco 9y ago> 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 9y agoGet 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 9y agoThat'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).
- huac 9y agoWe have no idea what the beta of the fund is; it's difficult to talk about performance without knowledge of the fund's underlying risk The other problem is scale - this is pretty evidently an advertising attempt in order to raise more cash. It's a lot easier to return 20% on, say, $100M AUM than it is on $1B AUM. To be fair -- these caveats are true for almost every fund you hear about. I do think that's kind of my big issue with the article though, that this fund is just like every other fund; it's intrinsically an actively managed portfolio with the same shortcomings as any other. It's just got a good publicist!
- ice109 9y agoI don't understand why 100 mil aum is different from 1 bill aum. couldn't you just divide the billion amongst 10 groups that are Chinese walled from each other? then there'd be no problems of market moving or depth or anything.
- huac 9y agoYour strategy means that you need 10x more working algorithms. Harder to find 10 than 1.
- deleted 9y ago[deleted]
- Moshe_Silnorin 9y agoAlso the selection effect of us just being aware of it.
- Bartweiss 9y agoIt seems like you could probably insure some great press coverage by starting several funds with wild-ass prediction mechanisms that don't change much. As long as you pick enough investments to roughly mirror the market, you can spin all the winners as incredible breakthrough techniques.
- dsacco 9y agoIf the winning techniques continue to generate greater risk-adjusted returns than the market for a significant amount of time, you haven't really bypassed the whole, "finding alpha" bit. Unless of course you've spun up a truly absurd number of funds, but I'd find that harder to believe than just beating the market in the first place given the capital requirements. "Fuzzing" for alpha that way would be really inefficient.
- Karissa44 9y agolike Curtis said I can't believe that any body can make $8668 in one month on the internet . > Open this >>>>>>>>>>>http://ow.ly/iBXm30dNtIZ http://ow.ly/iBXm30dNtIZ
- Bartweiss 9y agoI think I was a little unclear. I'm not actually proposing fuzzing alpha, just capitalizing on survivor bias. Basically my idea was that if you're going to spin up a 'normal' managed fund, you'll average tracking the market, with some chance of success or failure beyond that. If that's all you're doing, you might as well go all-out on claiming to have secret sauce that produces your alpha. I'm not expecting you'll get any, just that you might as well have a media-friendly way of picking if you don't have an actually useful one.
- jedberg 9y ago