Who to Sue When a Robot Loses Your Fortune
bloomberg.com
bloomberg.com
In this case, the investor was foolish to believe that a magic AI system could generate reliable positive returns. At the same time, it sounds like the performance of the system was misrepresented. Either way, if you're responsible for 1bn of assets, you better do really good homework.
Investing is not a guaranteed return system. You might win, or you might lose all your money. At the end of the day, the only person who is responsible for it is you.
Don't want to lose your money? Don't invest.
There are rules about fraud and fiduciary duty and disclosure which make blanket statements like this incorrect.
A retail investor can't be expected to properly research claims, but a professional should be.
Sigh. Unless you're too big to fail in 2008.
Trump has not declared bankruptcy. He has been owner or part-owner of hundreds of companies and a handful have declared bankruptcy.
As terrible (or not) as that is, there's a stark difference between availing yourself of long-standing bankruptcy law and the just-for-you shenanigans pulled by the federal government in 2008.
In the end, people will use whatever software has a good reputation. If something bad happens, well it's on them. The sky didn't fall using this model.
Therefore his criticism made sense at the time.
While open-source code and open-source maintainers are critical parts of the ecosystem, I think open source users are underrated. If nobody shared their experience about how a piece of open-source software is actually behaving once you put it to use in production, open-source software would have much less value than it currently has.
I told him that most of the software using this model is simply more reliable than proprietary software, but he just didn't get it. There was already plenty of "reputation" even back then, he just wasn't a hacker and couldn't understand any other perspective other than his own.
The evolution of open source software in the twenty years hence suggests that this particular question is not as silly as you frame it.
You're right that open source had been a thing for quite some time in 1998. GNU was started in 1983 after all.
But I respectfully disagree that open source was "obvious" in 1998. Hell, at that time, one could argue it was not obvious for a lot of people how much the Internet and computers would alter our lives. Open source was the least obvious part of quite a few a mind-bending paradigm shifts.
One of PG’s essays has a line like, ‘any competitor using Oracle was easy to ignore.’ Successful OS software needs to be good enough not to need marketing and happens to be free. It might not be the best, but cheap and good enough generally has a lot going for it.
My CEO could do my job. He would need an additional degree in programming, and even more time in a day. He hires me because telling my bosses bosses (skip several levels) boss to get something done will go down the chain into figuring it out how to go from we need to grow market share in the area I'm working to actual code that will grow that market share. This across thousands of employees - the CEO could learn to do any one but he can't do all of them.
On the contrary every big org is using OSS.
OSS is in everything.
That there is 'nobody to sue' is besides the point, it's like suing the inventor of the fork because something happened with a fork.
If you bought something complicated from someone with a contract and you depend on it doing ABC and it doesn't, then there's a case of liability.
But tons of software is OSS and there's nobody to sue.
'Liability' in software is maybe important in some areas, but mostly it's not.
Most of our problems as a society are due to that gap.
For example, if not being able to explain a model leaves an organization open to litigation, they may instead rely on statistical based learning methods even if they performed less well.
Is cheesing an algorithm illegal?
Saying the algorithm makes 95% winning trades may not mean much if those remaining 5% of trades cause you to lose most of your value.
So much money slushing around can make things a little grayer because in either case the investor didn't actually perform any work themselves. But I'm confident they can use some of that money to discern who ultimately owned what, who employed who, and what type of relationship was created.
I feel like newswriters just love to generate hot air with this "sue a robot" trope. Who to sue for that?
Although obviously such warnings can't reach some people... My favourite example of this was the collapse of OptionSellers.com following the huge move in Natural Gas futures. I mean, they were selling options - it's right there in the name...
https://www.bloomberg.com/news/articles/2018-11-19/hedge-fun...
For the time being, they often go back and give posts and accounts a manual second review, and often reverse the decision. For now, that keeps the general conversation around this issue from going too far. But it can't last.
If anyone should be sued, its Costa (Captain Magic/con-artist/salesperson/whatever) who, if what the investor claims is true, greatly oversold the capabilities of the software.
And even then there might not be a strong case against him.
1.You develop an alpha factor that you believe is associated with out performance.
2. You control risk factors such as beta, volatility, Fama French 3 factor, etc.
3. Now you create a neutral L/S portfolio that only has exposure to your alpha factor while also negating the risk factors like beta and volatility.
4. Backtest it, run a paper portfolio for awhile, etc.
5. Combine your new alpha factor with a bunch of other factors that you have already developed. The idea being that layering these alpha factors on top of each other will negate some of the noise inherent to each factor.
6. Make money and cycle out and in alpha factors for as long as they work/don't work.
It seems like this "hedge fund" was solely trading based on sentiment without creating a L/S market neutral portfolio or layering on any other factors. This is a very bad idea. The quote from the guy who made the software is pretty damning:
"The signals we have been provided have a strong scientific foundation. I think we did a pretty decent job. I know I can detect sentiment. I’m not a trader."
This is a big red flag. A lot of AI/ML people have this arrogance that trading is easy and that you don't need any financial knowledge to make money. Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies.
But all of this is off-topic, to get to the point: the Bloomberg article is garbage click-bait. You sue the General Partners, and I don't think anyone is confused about this.
Are you saying there is no luck in the market any more? Doesn't that mean it's deterministic; and doesn't that mean that market trading is unnecessary as we can allocate needs perfectly?
Active traders are trying to find mis-priced securities (market inefficiencies). That used to be relatively easy for smart people who could think up a few key insights. But now there are so many quant funds deploying fast computers and legions of mathematicians that most new strategies stop working quickly. The act of making those trades drives out inefficiencies.
Market trading is still necessary for liquidity to minimize the cost of capital.
> This is a big red flag. A lot of AI/ML people have this arrogance that trading is easy and that you don't need any financial knowledge to make money. Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies.
If they were making the trading bot via training it on past data and what they call 'sentiment signals' generated from social media reaction, etc, do they need experience with trading?
Is there something else that a human trader knows that the bot (which has been trained on past data and accounts for live reactions) doesn't?
Since the bot wasn't implementing a day-trading strategy it's pretty clear the programmers didn't know much about how the markets work. I would guess the training data reflected that knowledge gap. As the saying goes, you don't know what you don't know.
> do they need experience with trading?
That's a yes. You don't get to put a lot of money onto an investment without some experience on how it's done. This is true for all forms of investment, not only trading.
How do you even evaluate to robot if you don't know the market? What do you do if the robot breaks? What do you do if the market breaks (happens once in a while)? How much money you leave under its supervision?
I worked as a quant, and the finance knowledge you need is very deep.
The thing is that we generally have absolutely no clue what is the quality of the piece of the code that is controlling our destiny right now. What if the airplane we are flying right now decides to dive? What if bank looses all our record? What if Nest thermostat goes crazy and burns thousands of dollars on heating during your vacation? What if your 401k disappears because of the obvious bug in the bot's script? I can go on and on.
To be able to live in this world without going nuts we have to trust that those systems are correct and if something goes wrong we do need a legal way to punish responsible party (if there is a fault on their side).
The weird thing is that we still treat software and real engineering differently. If you enter the bridge that collapses under you feet because it is a bad design - you will sue. But if you trust a company that sells a superhuman trading bot which makes silly decisions and loses your money -> it is your problem. Following this logic - don't step on the bridge without reviewing the design and making sure it is safe.
How could you trust him to trade $2.5B?
"Li eventually let K1 manage $2.5 billion—$250 million of his own cash and the rest leverage from Citigroup Inc."
Leverage = Loan
r/wallstreetbets is that-a-way.
> Over the following months, Costa shared simulations with Li showing K1 making double-digit returns, although the two now dispute the thoroughness of the back-testing.
And I wished the article linked to the fillings or at the least discussed this more thoroughly.
Is it just me or is that quote kind of disingenuous? "People tend to assume" and "That may OFTEN be true" make it sound like it isn't as clear cut or there's still doubt over whether such algorithms outperform humans. Is that truly the case? I don't know much about trading but aren't algorithms doing most of the trading now?
They are prone to some occasional "dumb" errors however - like humans but different those which attempt to predict trends using feeds like Twitter have caused losses as they fail to get the context.
And it depends on the area and how you define algorithm and trading. Your bank has lists of requirements for mortgages beyond legal minimums - essentially already following an algorithm but due dilligence involves humans in the loop.
If you don't know who the idiot is, it's you.
The dudes who put this thing together were using a theory from, get this, 2015, to do sentiment analysis. Cool 4 character domain, but they couldn't even be assed to get a let's encrypt cert for it -- why would you trust them to manage billions?
http://42.cx/ The number of buzzwords is both overwhelming and inherently fishy.
At least not where I'm from - is this not the case in the USA?
Years ago, I noticed that my kids’ inner tube had multiple disclaimers, including multiple English disclaimers. The disclaimers next to the Union Flag, Australian Flag, and Canadian Flag were “use under competent supervision.” The disclaimer next to the US Flag was much longer and more detailed (“use under adult supervision” [note that is different from “competent supervision”], “do not tow from boat,” “do not use when drunk,” “do not dive into”, etc.). It did not make me proud to be American.
Additionally, many states have the concept of “joint and several liability,” so that if multiple parties share responsibility for an accident, the victim can collect the full amount from any of them and the perpetrators are expected to pay each other appropriately. The end result is that, generally, the company with the deepest pockets pays the full amount and then hopes to collect from the other parties later.
So, the answer is that you sue the chainsaw manufacturer, the chain manufacturer, the landowner, etc. and hope that they settle or that you get a final judgement that you can collect from the richest one, even if that particular party is held to be, say, 1% responsible.
Nitpick, but you can sue for anything, just not necessarily be successful at it.
This, along with [AIUI] not default providing an award of costs to a successful plaintiff in USA, makes it possible to sue and get a substantial out of court settlement because the risk profile is such that this is cheaper than paying your defence lawyers considering the [mathematical] expectation that you might lose a case that seemingly has no merits.
This is why you get warnings like "chainsaws are dangerous and may cause bodily injury or death, only for use by certified personnel". Then you can't [it is hoped by all reasonable people!] successfully claim that your naivety should have been accounted for, as it was by the warning.
If a robot doesn’t function properly, you fix it or take it out of service. Taking retribution against a robot (or abstractly, the civilization that created it) is of questionable value. The right question is how do we build robots that don’t lose fortunes?
The fact that human beings get angry at robots and want retribution or recompense for malfunctions is an evolutionary adaptation for dealing with other humans. It is useless when it comes to dealing with non sentient deterministic agents. Sure, if the robot was being controlled by a human, go after the human. If not, what’s the point?
Again, the legal theory works because when dealing with human beings you have to assign responsibility to human beings. Hurricanes and earthquakes kill tons of human beings and there’s no legal theory of responsibility. We simply work as a society to minimize those deaths without blaming anyone.
If that's not your intent, I suggest you rephrase.
When a bridge (another system which is complex but tractable in principle) fails, we work hard to find the feature of the design that led to the failure, and if we decide it was negligence, we exact consequences.
From current news: Should Boeing get a pass on their MCAS failures because "Gosh, it's really hard" ? The MCAS is a robot.
Take Boeing for example. Assigning blame to individuals, while rewarding, may not be as effective as changing the system that allows Boeing to continue to act the way it does. Boeing scapegoats, fires some people (which may include the CEO) but the organization, and the nation and legal system that sustains it continues largely unchanged.
You’re trying to patch by punishing humans individually, while ignoring faults in the system we have collectively created. Our instinct is to assign blame because historically and evolutionarily harm is usually done by individual humans, and punishing humans is a good heuristic. But it does not seem to me that punishment does a good job of creating good large scale organizations or systems.
In my nanny state, the government will appoint a team of therapist to mange the trauma, we get mandatory employer 4 weeks paid pain and suffering leave. The government refunds your loss plus potentially lost opportunity cost
In the country next to us, they are savages. Can you believe each adult is responsible for the consequences of their decision They have some meager protection for fraud and general exploitive behavior. But if it’s a legitimate investment firm and you go in knowing what you are doing and they loose your money THAT IT your money is lost. savagery
Edit: post is tongue in cheek, assuming there is no fraud some of the comment suggest there could be subtle fraud involved
The factory owner.
Software has been around for a long time.
(Pedantic tl;dr: I refuse to put the punctuation inside the quotes. I consider that an outright bug in English and it needs to be stamped out by rebellion.)
What a stupid idea to make "it's" stand for "it is"
"It's" is just the standard use of apostrophe to indicate a contraction.
[0] https://www.merriam-webster.com/words-at-play/history-and-us...
The S&P 500? The FTSE 250? The Nikkei? The Russell 2000? The Russel 3000? The risk-free rate? LIBOR?
When you make statements like this, they mean nothing at all.
Let's say you're talking about the S&P 500. Many hedge funds have been beating it for 20 years or more.
But let's say you had 2 Billion dollars. What would you do with it? Are you telling me you would put it all in one index fund? Maybe you would put it in a couple, maybe you would put it in some bonds? Well guess what, you just made an active management decision! You decided what index, or what bonds, or whatever.
There is no such thing as passive management.
2bil is so easy. Highly rated tax-free munibonds...a very safe 3% coupon will net you completely tax-free 60mil/yr...I would say plenty to live off of and even reinvest.
Relatively few, I would say, if you measure it by realised Sharpe. Rentech, Brevan Howard, D.E. Shaw, and maybe AHL and Winton excluding the past few years. I'm struggling to name others that have done well over a sustained period.
There are a lot of funds out there, and IMO much of the supposed 'outperformance' is a combination of leverage and survivor bias (I say this as a former hedge fund quant).
Given that sample size of funds, possible returns, and any distribution you want to fit into it, your odds may be better at a roulette table.
Also if we're talking about market makers, Jane Street, Susquehanna, Fortress, and Citadel very well for themselves.
Market making is a different kettle of fish in the sense that it's more of a financial service than a directional bet on markets. It's also much less capital intensive so there's less pressure to raise money from clients. As a market-maker, you can certainly find yourself on the wrong side of a trade, but generally the goal is to be as market-neutral as possible.
I’ve worked as a quant at both hedge funds and market makers, and both have a similar philosophy of a only getting exposure to “alpha”, though the means and capital required (as you mentioned) are quite different.
I think a concept of Sharpe ratio still applies to both though, with market making having an clearly higher one.
Personally, I’ve found working for a hedge fund a lot better, market making is kind of a drab business when you get down to the nuts and bolts.
I recommend “Common Sense on Mutual Funds” by John C. Bogle on this topic.
Uh... don't get me wrong, but when you go to the casino and lose all your money, it's no one's fault but yours. Same way for stock markets.
Whoever is dumb enough to put money into essentially a gambling algorithm should be able to pay for the losses himself.
But it is a very real possibility as the recent financial crisis shows. Everyone who is unable to stomach a total loss of his investment in one basket should not do so, and it is double dumb to invest in unproven automation like this.
We often hear about the crazy lawsuit culture in US anyway and how insane it is. Whether that is true or not I don't know.