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BlackRock's Robot Stock-Pickers Post Record Losses
- pizza 10y agohttps://en.wikipedia.org/wiki/Aladdin_(BlackRock) https://en.wikipedia.org/wiki/Aladdin_(BlackRock) Was tickled by the allegory that could be made, upon reading this from https://en.wikipedia.org/wiki/Jinn https://en.wikipedia.org/wiki/Jinn: > The Quran says that the jinn were created from a smokeless and "scorching fire", but are also physical in nature, being able to interact in a tactile manner with people and objects and likewise be acted upon. The jinn, humans, and angels make up the three known sapient creations of God. Like human beings, the jinn can be good, evil, or neutrally benevolent and hence have free will like humans.
- acqq 10y agoI see no connection of that religious book and these particular Arab beliefs based on the myths from around the 7th century with the article about the BlackRock Inc. I guess you're attracted by the part "can be good, evil, or neutrally benevolent" but it's too little for my taste, the rest is more problematic to be related. And can't most things "be good, evil, or neutrally benevolent" anyway?
- semi-extrinsic 10y agoIf you clicked the first link given by GP, you would have seen that BlackRocks investment platform is called Aladdin, who of course has a strong link to the jinn (genie). Thus the connection.
- StavrosK 10y agoMaybe the connection was that the platform was going to be the one that "took the genie out of the bottle"? Any other alternative is more tenuous, I think.
- TuringNYC 10y agoI submitted this article because I was especially intrigued by the high-profile ex-Google ML Researcher hire (and then departure.) Anyone know what exactly the BlackRock ML group was doing? Was it supposed to be a competitor to Renaissance Technologies (https://www.bloomberg.com/news/articles/2016-11-21/how-renaissance-s-medallion-fund-became-finance-s-blackest-box https://www.bloomberg.com/news/articles/2016-11-21/how-renai...)? Was this an NLP-driven fund gone haywire? I'm particularly interested as I was recruited for this group multiple times, so a bit relieved I didn't pursue it. I wonder if there are any lessons (about what to avoid) to be learned here about the way the group was structured...or if it was simple randomness gone wrong.
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- deepnotderp 10y agoWho was the google ML researcher hire?
- hellofunk 10y agohttp://www.reuters.com/article/us-blackrock-hire-google-idUSKBN0OO2C720150608 http://www.reuters.com/article/us-blackrock-hire-google-idUS...
- deepnotderp 10y agoThanks!
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- B1FF_PSUVM 10y agoOne of these days I may finally understand what was the problem we were trying to solve with all these increasingly complicated financial thingamajigs. And what exactly is the benefit we derive from them. Not betting on it, though. P.S. Looking for something simple, e.g. "If you have derivative trading, your GDP will be 5% larger, and the gain is spread across the population in proportion to income." The kind of things you have for engine efficiency, or compiler optimization ...
- pavlov 10y agoI upvoted you because I don't understand the benefit of quant funds either. With short selling, derivatives and high frequency trading, I can at least see the argument for increased liquidity and so forth... But how does society benefit when leading AI research minds spend their time building gambling models that try to predict the sentiment of other gamblers? At the same time, I recognize that forcing any such social logic onto research is a slippery slope towards Soviet-style government-stunted research. So I guess I'll rather have machines gambling trillions of dollars.
- candiodari 10y agoWhen push comes to shove these things determine the allocation of resources in society. How many people does a company making spoons gets to hire or should we put more of them on webforum moderation ? Same for cars/glass/shoes/... The idea is that letting algorithms decide will result in better/more productive allocation of resources, which will result in more and better everything. Of course, is that reality ? I would point out, however, that stock markets resource allocations are far better than royalty/governments allocating resources.
- throwanem 10y ago> The idea is that letting algorithms decide will result in better/more productive allocation of resources Is it? I thought the idea behind HFT was to make a shedload of money for the firms with the most effective algorithms. To be clear, I have no problem with that, and I'm not close to the industry. But it would surprise me to hear that those in it conceive of themselves as optimizing social resource allocation, rather than, say, setting themselves up to retire at thirty with all the money they'll ever need.
- fauigerzigerk 10y ago"He also pointed to the group's longer-term track record of outperformance. [...] The firm doesn't disclose the peer groups or benchmarks it uses for comparison." My track record is much much better!!! Honest!!!
- binaryanomaly 10y agoAs I understand the article the "robots" would have done more or less ok. It was human intervention that caused more losses. This is exactly what not should happen when investing longterm: Being driven by emotions rather than rational facts.
- adwn 10y ago> This is exactly what not should happen when investing longterm: Being driven by emotions rather than rational facts. Putting a limit on one's potential losses is pretty rational, not emotional. Models are not perfect, and you do not want to find yourself with high paper losses when they fail. Of course, if your models don't work well together with stop-loss limits, then that's a problem.
- binaryanomaly 10y ago> Putting a limit on one's potential losses is pretty rational, not emotional. Models are not perfect, and you do not want to find yourself with high paper losses when they fail. At least here they say that it is not a good idea with a quant approach: http://en.swissquote.com/epb/support/faq#node-301 http://en.swissquote.com/epb/support/faq#node-301 The BlackRock example plus the fact that many ETFs beat managed Funds in terms of performance seem to support the position that human interference is in most cases for the worse.
- ohyes 10y agoBut you do that by properly sizing your positions, not by panic selling.
- CoolGuySteve 10y agoAdding a stoploss is common practice. It prevents bugs, over-fitting, and adverse selection from ruining you. You'll have a bad time if you think your model is infallible.
- mrchicity 10y agoIt gives a false sense of security in cases like this. The biggest losses you want to liquidate will always happen in cases where it's impossible or extremely costly to do so: company has merger announcement overnight while you're short, accounting scandal, bankruptcy, earnings surprise, fat finger order takes all liquidity out of the market. You will end up losing many multiples of your designated loss limit in the bad cases. The only way to prevent massive losses is to size your bets sensibly or insure against tail risk using options ahead of time, of course that comes at a cost. By bugs and adverse selection I'm assuming you're talking about something like automated market making. For traders like that, a loss limit makes sense because of technology risk. If your order router has a bug like Knight's did, or your data feed gets stuck, you can lose a lot of money very quickly.
- tonyedgecombe 10y ago"It instructs the team to sell when losses become sizable, regardless of what its mathematical models say, according to a person with direct knowledge of the matter." Hard to blame the robots then.
- tma-1 10y agoMakes sense though, they don't want a repeat of the LTCM crisis.
- Waterluvian 10y agoHow likely is it that a successful model involves _sizable_ losses?
- ceejayoz 10y agoVery? That's Vanguard's entire business model. Buy and hold.
- boulos 10y agoActually, Vanguard just strongly suggests that their customers do so (and provide nudges in the form of limiting sales and exchanges from certain funds to once per month). They don't get to make their customers follow a Buy and Hold strategy (and their ETF products have no restrictions), so I think it's more accurate to say that they do better (for their customers) due to their relentless push towards efficiency, with low turnover being an important part.
- ceejayoz 10y agoI feel like that's splitting hairs a bit. Sure, they can't prevent you from panic-selling or attempting to time the market, but their low expense ratios are possible because they, themselves don't do it. They just follow along with the markets. They've got some pretty good arguments in favor of this, too: https://vanguardblog.com/2016/10/13/when-nothing-is-something/ https://vanguardblog.com/2016/10/13/when-nothing-is-somethin...
- ChuckMcM 10y ago"BlackRock inherited the three-decade-old quant business with its purchase of Barclays Global Investors in 2009. Initially, the group was a big success under new management, delivering outsize returns. More recently, things haven’t panned out quite as well." -- well you know those Barclay's Boys[1] Its an interesting question about machine learning and market returns. But there is a remarkable number of people who seem to just step over the line of legality and pick up the extra profits they need which taints the whole industry. [1] https://www.theguardian.com/business/2016/jul/04/libor-rigging-scandal-three-former-barclays-traders-found-guilty https://www.theguardian.com/business/2016/jul/04/libor-riggi...
- airlust 10y agoBGI was basically a subsidiary and run independently. It was originally part of Wells Fargo (hence the SF HQ) - just pointing out that although it had the Barclays name, it was separate.
- scurvy 10y agoAny thoughts on Blackrock's smart alpha ETF offerings like MTUM, QUAL, etc?
- grondilu 10y agoI've always been puzzled how it could be possible for a machine to predict stock markets, even on an purely hypothetical basis. To me the idea seems to generate the same kind of paradoxes as time travel or oracles. I mean, imagine there is a machine that is capable of predicting the markets with 100% reliability. Then soon enough, the machine will acquire a reputation and everyone will follow its advice. The machine says "the price of X will go up", everybody would buy X, so the price of X would indeed go up, but this price surge would have only been initiated by the machine statement and we'd have a self-realizing prophecy. Other situations would be more complicated I suppose, but in every case the machine would have to take into account its own prediction, which would be some kind of a mise en abyme. In the end just like antic oracles, the machine would have to make cryptic predictions that would make sense only with hindsight.
- fsloth 10y agoTo my understanding simple regression models worked pretty well the first time they were used. My laymans understanding is that the prediction of a simple model of the system like a stockmarket becomes unusable once there is a feedback loop from the model to the system. I.e. enough users using the same model that the model starts to affect prices.
- devilsavocado 10y agoTry out your thought experiment again with a machine that can predict markets with 55% reliability, or 50.1% reliability . This more likely reflects reality. If someone had a machine that could predict the stock markets with 100% reliability, or even 55% reliability, do you think they would make those predictions known to the public? Or would they start a hedge fund and become one of the wealthiest individuals of all time?
- runeks 10y agoAs far as I can see, making the information available to the public isn't even a choice. There is no market information you can make available to the public that will make everyone richer. The only people who get richer are the ones who act before it becomes public knowledge. When they are done, asset prices reflect the now public knowledge, and there is no longer a profit to take.
- NPMaxwell 10y agoStock prices screw up validation with back testing. I tried using stock prices to illustrate random walks and the superiority of naive forecasts with random walk data. Only problem: they aren't random walks. They are random sequences of predictable pattern. Frequently, a regression model, or Holt-Winters, or neural net will outperform the naive forecast on backtests, because it was a better model before now. The challenge, is that now it isn't.