Silicon Valley Hedge Fund Takes on Wall Street with AI Trader(bloomberg.com)
bloomberg.com
Silicon Valley Hedge Fund Takes on Wall Street with AI Trader
https://www.bloomberg.com/news/articles/2017-02-06/silicon-valley-hedge-fund-takes-on-wall-street-with-ai-trader
110 comments
Which is really odd, since if they had any idea of what they were doing, they wouldn't need to sell. Trading is among one of the few industries out there where you don't need to have anything like a customer.
What you do is make money, and if you're making money, well, you don't need to ask anybody else for money. This tells me that its a bunch of executives who either don't know anything about trading and/or don't have any coherent strategy, and are really just trying to throw enough buzzwords out there to get investor capitol.
What you do is make money, and if you're making money, well, you don't need to ask anybody else for money. This tells me that its a bunch of executives who either don't know anything about trading and/or don't have any coherent strategy, and are really just trying to throw enough buzzwords out there to get investor capitol.
Peter Muller has the most succinct summary of this that I've seen in his (very worthwhile) opinion piece on proprietary trading [1]:
Sharpe Ratio, Marketing department
≤ 0: Runs the firm
0.25: Very important; involved in all investment decisions; major focus on asset gathering
0.5–1.0: Secondary
1.0–2.0: Almost superfluous
≥ 2.0: What marketing department?
[1] https://faculty.fuqua.duke.edu/~charvey/Teaching/BA453_2004/...
Sharpe Ratio, Marketing department
≤ 0: Runs the firm
0.25: Very important; involved in all investment decisions; major focus on asset gathering
0.5–1.0: Secondary
1.0–2.0: Almost superfluous
≥ 2.0: What marketing department?
[1] https://faculty.fuqua.duke.edu/~charvey/Teaching/BA453_2004/...
For others: https://en.wikipedia.org/wiki/Sharpe_ratio
> if they had any idea of what they were doing, they wouldn't need to sell
Having spent some time in the industry, I disagree, you're always trying to maintain or increase AUM. Funds constantly sell to existing and future limited partners (investors). Internal prop trading desks sell to management in order to keep their allocated VaR and to risk for similar reasons. Traders themselves sell to their boss and peers. VCs sell their top quartile-ness. All of the above sell to their junior staff to keep them around.
The thing is you don't know if you are good or lucky until many years into your career and someone has to put up the capital until then. Even the top funds with great track records can one day stop producing results, at which point people abandon ship.
Having spent some time in the industry, I disagree, you're always trying to maintain or increase AUM. Funds constantly sell to existing and future limited partners (investors). Internal prop trading desks sell to management in order to keep their allocated VaR and to risk for similar reasons. Traders themselves sell to their boss and peers. VCs sell their top quartile-ness. All of the above sell to their junior staff to keep them around.
The thing is you don't know if you are good or lucky until many years into your career and someone has to put up the capital until then. Even the top funds with great track records can one day stop producing results, at which point people abandon ship.
> Trading is among one of the few industries out there where you don't need to have anything like a customer.
You can usually make a lot more money with Other People's Money than with in-house money.
You can usually make a lot more money with Other People's Money than with in-house money.
>" Trading is among one of the few industries out there where you don't need to have anything like a customer."
Trading yes but a hedge fund or any fund really implies customers no?
Trading yes but a hedge fund or any fund really implies customers no?
Hedge funds have customers because the majority of them don't beat the market in the long run.
If a hedge fund is consistently highly profitable, they stop taking customers. For example, see RenTec's Medallion Fund, which is only open to its own employees.
If a hedge fund is consistently highly profitable, they stop taking customers. For example, see RenTec's Medallion Fund, which is only open to its own employees.
Depends on their Sharpe and capacity. Really, only prop shops have no customers, and even those were often backed by someone in the early days.
RenTech's Medallion fund doesn't have customers, but it did for much of its history, and they have lower Sharpe programs with more market depth (and many customers).
That said, the track record for Bay Area hedge funds trying to do things "the Silicon Valley way" without experienced founders (experienced in trading) is pretty grim. The ones who succeeded had a track record of doing it before.
That said, the track record for Bay Area hedge funds trying to do things "the Silicon Valley way" without experienced founders (experienced in trading) is pretty grim. The ones who succeeded had a track record of doing it before.
Exactly, if they can't extract their wealth from the market, they extract it from their customers.
>"Hedge funds have customers because the majority of them don't beat the market in the long run"
Interesting do you have any data to look at regarding that? How do they justify their 2 and 20 then?
Interesting do you have any data to look at regarding that? How do they justify their 2 and 20 then?
Well, originally the purpose was to 'hedge' your other investments. Typically, hedge funds invested in ways that would do well when the rest of the market struggled. Even if they don't best the market over the long run, they could be worthwhile investments to protect your wealth during ,Arlen downturns.
Right, they don't hedge at all now do they? Its mostly just high speed trading?
In short, having someone do HFT with your money can be a hedge because HFT strategies often do better when markets are volatile and other funds lose money.
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"Trading is among one of the few industries out there where you don't need to have anything like a customer."
Yes, but knowing how to trade is obviously very important, it's not just picking stocks, it's risk management, regulatory issues, and tons of industry specific knowledge.
That said - if they have 'tech that works' they should be able to partner with a few financial people and wrap a fund around it without too much trouble.
That so much negativity is on Glassdoor is really a bad sign.
Yes, but knowing how to trade is obviously very important, it's not just picking stocks, it's risk management, regulatory issues, and tons of industry specific knowledge.
That said - if they have 'tech that works' they should be able to partner with a few financial people and wrap a fund around it without too much trouble.
That so much negativity is on Glassdoor is really a bad sign.
I mean sure, but take glassdoor with a huge grain of salt, people make up crap to post on there all the time.
After a certain number of reviews, Glassdoor becomes a more honest reflection of a company's actual state than anything else.
It's certainly more truthful that marketing fluff pieces like this.
It's certainly more truthful that marketing fluff pieces like this.
Absolutely. It's a great resource, I have used it regularly since it launched.
People still make up fiction and post it on there all. the. time. Keep that in mind.
People still make up fiction and post it on there all. the. time. Keep that in mind.
Its like a Cohen Brothers Film: Lots of stuff happens that is really entertaining, but at the end of the movie you have learned nothing.
I agree as well. I've noticed many problems in my current organization but it is really telling when people are complaining about the same things I'm seeing. The problems really exist, people have fought to fix them and failed, management either doesn't care or want to fix them.
Yes there will always be people that were fired writing things up as well as others just lying (competitors). Like you said, at some point when there is enough smoke you should expect a fire.
Yes there will always be people that were fired writing things up as well as others just lying (competitors). Like you said, at some point when there is enough smoke you should expect a fire.
The company I work for is around 100 people, but the few postings I have seen that are negative and descriptive are on the mark. Maybe Tolstoy was right about unhappy companies as well.
Curious to what your are referring to, related to Tolstoy (or Tolstoj as I like to write his name). Can you elaborate? Thanks!
It's called The Anna Karenina principle. Tolstoy posited an analogy in his novel Anna Karenina that "happy families are all alike; every unhappy family is unhappy in its own way."
Interestingly, Peter Thiel starts his book Zero To One with a reference to the Anna Karenina principle by showing a corollary in business: "All happy companies are different, all unhappy companies are alike."
Interestingly, Peter Thiel starts his book Zero To One with a reference to the Anna Karenina principle by showing a corollary in business: "All happy companies are different, all unhappy companies are alike."
“All happy families are alike; each unhappy family is unhappy in its own way.”
Not OP, but this might be the reference: https://en.m.wikipedia.org/wiki/Anna_Karenina_principle
I've also worked places that were pretty effective at getting glassdoor to take down the negative reviews. They could always find some sort of explanation for how the negative ones didn't meet the terms and conditions and glassdoor seemed relatively ok with taking them down.
Sounds to me like a shopfront to build up an emotionally weighted patent Portfolio to then beat others around the head with.
Hope it fails
Hope it fails
The clickbait headline is amusing, but "Wall Street" has been doing this > 10 years. I'm genuinely not sure if they're trying to "beat wall street" or simply be yet another quantitative hedge fund that happens to use machine learning and neural networks to power their strategies.
Most real electronic trading firms are putting those algorithms in hardware.
Source: Have worked in HFT the past 10 years.
Most real electronic trading firms are putting those algorithms in hardware.
Source: Have worked in HFT the past 10 years.
I used to have a stock broker co-worker who had one rule for investing if day trading or even trying to employ a strategy: "You can't fight the Street."
His point was trying to bet against a momentum trade or some other scenario was foolish. He watched time and again. There were opportunities to get with the crowd, or be on the wrong side.
His point was trying to bet against a momentum trade or some other scenario was foolish. He watched time and again. There were opportunities to get with the crowd, or be on the wrong side.
Great point. And even if you are "with the crowd" more often than you are not, your timing/sizing on each trade you make as a day trader or mom-and-pop investor is very likely to be worse than an institutional trading firm. So you can be right on a "buy" vs "sell" decision 51% of the time, but an algo trading firm has probably executed with better timing/trade size and beaten you to a percentage of the profit.
A friend who works in quant finance said something along the lines of "if a trader can identify a mom-and-pop investor, it's like taking candy from a baby" in terms of making an easy profit.
A friend who works in quant finance said something along the lines of "if a trader can identify a mom-and-pop investor, it's like taking candy from a baby" in terms of making an easy profit.
I'd rather just try really hard to get people to understand that active trading is negative sum, and that unless (As a mom and pop investor) you are properly bench-marking against a relevant index - you're just lying to yourself.
Sure HFT guys are faster than you to get short term signals and make money on the micro scale - but even ignoring that way too many people are thinking they're beating the market and they really really aren't.
Sure HFT guys are faster than you to get short term signals and make money on the micro scale - but even ignoring that way too many people are thinking they're beating the market and they really really aren't.
You just nailed it! I work for a very large HFT and my portfolio for my 401k and extra retirement (in the market) is primarily low cost / fee vanguard index funds. You really can't beat a FPGA with tick to trade times in the milliseconds. Your optical nerve likely hasn't even processed a number changing yet.
I'm looking at low cost/fee index funds as well (I strongly agree with you that I don't want an active trading strategy for my retirement account). Have you looked at things like Motif Investing? I'm torn on whether I want to create a sector-balanced Vanguard-style index, or just invest in an existing index.
silly question, but why do your LinkedIn and Github say you work at a generic "Financial Industry Company" rather than Jump? especially since Jump is quite prominent.
I'm assuming you mean nanoseconds?
Yes, but people roll their eyes when you say that even if it is true.
Fair enough. If you're not in the nanos what is the point of even bothering with FPGAs and all the pain involved? CPUs can handle single digit micros just fine.
Yes! Completely agreed. The fact that it's a negative sum game is really hard to explain to people who've had some moderate success trading (and there are plenty of those anecdotal examples out there).
But that's a great point that any kind of active trading strategy needs to be compared against the right index. I think this holds true for pension/sovereign funds which invest in multiple hedge funds as well - comparing to the overall market performance may be less relevant than comparing to sector-weighted market performance, for example.
But that's a great point that any kind of active trading strategy needs to be compared against the right index. I think this holds true for pension/sovereign funds which invest in multiple hedge funds as well - comparing to the overall market performance may be less relevant than comparing to sector-weighted market performance, for example.
> Source: Have worked in HFT the past 10 years.
OT question: how would I get into acquiring market data to try my own backtesting strategies ? Is there anyway to "get in" without putting up $5k + for the data ? I'm not green to this, I worked at a prop shop for a year writing market feed handlers. I know the dangers of overfitting data and how hard it is to make money (so I'm not deluded by a fantasy). I want to start out just for fun doing backtesting and see if I can scrape out a (paper) profit, but accessing historical data seems to be the hard part. I dont think online services that offer this would work for me because I want to use intraday data and replay many times with different parameters. I want access to "the whole firehose" if you will.
OT question: how would I get into acquiring market data to try my own backtesting strategies ? Is there anyway to "get in" without putting up $5k + for the data ? I'm not green to this, I worked at a prop shop for a year writing market feed handlers. I know the dangers of overfitting data and how hard it is to make money (so I'm not deluded by a fantasy). I want to start out just for fun doing backtesting and see if I can scrape out a (paper) profit, but accessing historical data seems to be the hard part. I dont think online services that offer this would work for me because I want to use intraday data and replay many times with different parameters. I want access to "the whole firehose" if you will.
Not a personal recommendation as I haven't used it, but you might find quantopian.com fun if you've got any python.
You are not going to get usable intraday data for free. Best bet is to pony up for NYSE TAQ.
http://www.nyxdata.com/Data-Products/Daily-TAQ
http://www.nyxdata.com/Data-Products/Daily-TAQ
TickData[1] are cheap and good for US data, I have had bad experience with them for EU data. They have a minimum of (IIRC) $1K but you can get a ton for that.
Some exchanges offer free historical data, for instance BM&F BOVESPA[2], trading in some markets (such as Brasil and China) is often difficult if you are a foreigner.
[1] https://www.tickdata.com/
[2] http://www.bmfbovespa.com.br/en_us/services/market-data/hist...
Some exchanges offer free historical data, for instance BM&F BOVESPA[2], trading in some markets (such as Brasil and China) is often difficult if you are a foreigner.
[1] https://www.tickdata.com/
[2] http://www.bmfbovespa.com.br/en_us/services/market-data/hist...
IQFeed has many many years of historical data at the minute level, and tick data for 6 months (for equities), at ~$80/month... they many not have the highest quality data from what I've heard, or the most tick data, but are so much cheaper than any of the more professional solutions a large fund would use that it's a pretty decent start for a hobbyist.
Not sure how usable it would be for your use-case, but I heard a talk explaining Quandl – they want to do to Bloomberg what Wikipedia did to Encyclopedia Britannica.
https://www.quandl.com
https://www.quandl.com
HFT is a different kind of 'beating the market', though, don't you think?
It isn't beating the market, it is literally "making the market":
https://en.wikipedia.org/wiki/Market_maker
https://en.wikipedia.org/wiki/Market_maker
Arguable whether or not HFT increases liquidity in the market.
It is arguable if more liquidity is a good or a bad thing from some sides, but I'm not sure how HFT increasing liquidity was ever a question? It is a matter of volume and there is more automated than non-automated volume in most equities and futures exchanges.
However, given that you want to make a trade, it's not arguable whether you want more market participants or fewer.
It is "beating the market" if your strategy results in higher net fee-adjusted returns than the overall market (typically ~7-11%). But yes it's different because you're not deploying a trading strategy, you're being a market maker for other traders.
Machine learning and neural networks?
SHUT UP AND TAKE MY MONEY!
SHUT UP AND TAKE MY MONEY!
> Source: Have worked in HFT the past 10 years.
This is not about High Frequency Trading, but about machine learning applied to the stock market.
This is not about High Frequency Trading, but about machine learning applied to the stock market.
Which every single HFT firm that isn't a pure market maker (such as Virtu Financial, my previous employer) does already and has done for years. That is my point. Here's a great example of Citadel talking about how they use Hashicorp nomad to spin up 100,000 cpu research jobs on AWS.
What do you think their 100k cpu jobs are doing? Machine learning and quantative analysis, what else?
https://www.youtube.com/watch?v=MRtRwhL5lwM
What do you think their 100k cpu jobs are doing? Machine learning and quantative analysis, what else?
https://www.youtube.com/watch?v=MRtRwhL5lwM
I think you are willingly failing to understand what is being said by me and more people on the comments.
This is not about exploiting a privileged access to market conditions (as in the sub millisecond access HFT firms have) in order to gain an advantage.
This is about using machine learning to predict future (as in hours/days) moves on the market and take advantage of them.
This is not about exploiting a privileged access to market conditions (as in the sub millisecond access HFT firms have) in order to gain an advantage.
This is about using machine learning to predict future (as in hours/days) moves on the market and take advantage of them.
Yes and I think you are willingly failing to understand reality from someone who has worked in technology in finance for a long time. HFT or perhaps more accurately, Electronic Trading, is more than simply passive trading and "doing something faster than everyone else". That is a part of it absolutely, but the industry also hires people with PHDs in quantum physics, or builds supercomputers at national labs to build private ones, or teach mathematics at ivy league universities. For much of this math, speed is beneficial, but it isn't universally and always required.
Speed is nice, but smarts are better. "Machine Learning" is the new buzzword for a way to mathematically deducing future outcomes based on data science and quantitative analysis. That is a grotesque simplifications and there are specific ways of approaching this (Tensorflow/Keras from Google, Torch from Facebook, etc). This could be nanoseconds in the futures, it could be hours, or even weeks / months. And this is the part you're failing to understand by trying to assume (incorrectly) that all HFT is made up of is bid sniping and latency arbitrage (often referred to as front running). It isn't really that privileged access if you yourself can pay any exchange, such as NYSE, for a feed to your house.
TL;DNR: Your understanding of electronic / HFT trading is wrong. If you try to understand it first, you'll realize your statements bear absolutely no basis whatsoever in facts. Facts are that Electronic Trading firms have been using machine learning literally since the invention of machine learning and quantitative analysis to make money. A new firm trying to do this can simply join the club.
Speed is nice, but smarts are better. "Machine Learning" is the new buzzword for a way to mathematically deducing future outcomes based on data science and quantitative analysis. That is a grotesque simplifications and there are specific ways of approaching this (Tensorflow/Keras from Google, Torch from Facebook, etc). This could be nanoseconds in the futures, it could be hours, or even weeks / months. And this is the part you're failing to understand by trying to assume (incorrectly) that all HFT is made up of is bid sniping and latency arbitrage (often referred to as front running). It isn't really that privileged access if you yourself can pay any exchange, such as NYSE, for a feed to your house.
TL;DNR: Your understanding of electronic / HFT trading is wrong. If you try to understand it first, you'll realize your statements bear absolutely no basis whatsoever in facts. Facts are that Electronic Trading firms have been using machine learning literally since the invention of machine learning and quantitative analysis to make money. A new firm trying to do this can simply join the club.
> HFT or perhaps more accurately, Electronic Trading
Electronic trading as opposed to what?
Electronic trading as opposed to what?
Click trading? Calling your broker and having them trade for you? Old school open outcry trading. Algorithmic Trading might be better?
Before you seemed to apply the term essentially to HFT only ("Most real electronic trading firms are putting those algorithms in hardware"), now it seems to include all the "systematic" trading. Or maybe only when fully automated? (I imagine low-frequency startegies might still require some human clicks).
And even if I call my broker, and he clicks somewhere to enter the order, it's still executed by some HFT agent somewhere. And the same applies to low frequency strategies, I guess (why bother with the execution details, just use a broker).
And even if I call my broker, and he clicks somewhere to enter the order, it's still executed by some HFT agent somewhere. And the same applies to low frequency strategies, I guess (why bother with the execution details, just use a broker).
Can you do HFT without a privileged connection to the trading system that beats most of the market players in access time? No.
TL;DNR: You keep ignoring both the point of the comments and the point of the TFA. This is about market prediction, not technical exploitation of a privileged access to market.
TL;DNR: You keep ignoring both the point of the comments and the point of the TFA. This is about market prediction, not technical exploitation of a privileged access to market.
> a privileged connection t
anyone can buy co-located rack space.
anyone can buy co-located rack space.
I'm not sure if you have some kind of cognitive impairment, that you still didn't get the point after I explained it 5 times already, so I'll explain it yet again as simply as possible:
If you buy a co-located rack space you are using a PRIVILEGED CONNECTION to the market that and taking advantage of that using some algorithm: That's High Frequency Trading.
The all point of TFA and the comments was the OPPOSITE: To be in a NON PRIVILEGED position (as in, the same access time to market transactions as the median of the access time to market of EVERYONE ELSE) and to use machine learning to predict market moves in a long enough term so that the market access time was irrelevant.
Do you understand the complete difference between the two scenarios now?
If you buy a co-located rack space you are using a PRIVILEGED CONNECTION to the market that and taking advantage of that using some algorithm: That's High Frequency Trading.
The all point of TFA and the comments was the OPPOSITE: To be in a NON PRIVILEGED position (as in, the same access time to market transactions as the median of the access time to market of EVERYONE ELSE) and to use machine learning to predict market moves in a long enough term so that the market access time was irrelevant.
Do you understand the complete difference between the two scenarios now?
calm down. anyone privileged enough to buy stocks is also privileged enough to buy colocated rack space. so yes, it's "privileged", just like everyone else.
Huh, hasn't wallstreet being doing this, and even putting these things into FPGA's for nearly a decade now? Hell I wouldn't be surprised if they're printing ASICs with their algos.
Other than trading on news, you really don't need that kind of speed for using ML powered algos. Generally these rely on a ton of data so GPUs still reign king.
But yes, hedge funds and prop shops have been doing this for over a decade.
But yes, hedge funds and prop shops have been doing this for over a decade.
Not all algorithmic trading is high-frequency where you need to shave microseconds to beat someone else's order. If you're predicting actual price movements instead of order book fluctuations there's no reason to use hardware.
Surely - but 'AI' is new. Surely 'Deep Learning' is something at least they are not doing widely, because it's difficult to pull off.
That said, anyone actually doing it would be smart enough to shut the hell up about it.
Finally - one might argue that the big money is all made in 'soft insider' information anyhow, and that with so much tech, analysts already there ... there's just no way to win without clear leverage i.e. relationships, servers on premises of the trading facility, or some other non-market advantage.
That said, anyone actually doing it would be smart enough to shut the hell up about it.
Finally - one might argue that the big money is all made in 'soft insider' information anyhow, and that with so much tech, analysts already there ... there's just no way to win without clear leverage i.e. relationships, servers on premises of the trading facility, or some other non-market advantage.
This is just an anecdotal experience but according to a former hedge fund manager, insider trading is an open secret in the industry. You really can't expect to gamble away billions of investor's money without an edge. Information is the only possible edge that is closely guarded in the markets.
I don't know how true that is, he's a washed up piece of shit that wall street chewed out but has the eyes and ears of gordon gekko wanna be finance grads.
but I'm writing this because this is like the 3rd time I've heard this. Just throwing it up there if "soft insider" information is what they were referring to.
I don't know how true that is, he's a washed up piece of shit that wall street chewed out but has the eyes and ears of gordon gekko wanna be finance grads.
but I'm writing this because this is like the 3rd time I've heard this. Just throwing it up there if "soft insider" information is what they were referring to.
Big funds will have direct access to CEO's and execs.
They'll sit down for an interview. Technically speaking, everything that the CEO will say has to be public information. It has to be above bar.
But sitting in the room, being right there, one might easily be able to glean more information than is actually public. Ergo - and edge. And it's not quite illegal.
So that is a form of fairly above board 'soft inside' information that nobody will ever go to jail for.
As far as more obvious 'insider' - maybe so, maybe not - I don't know - but I do know that you don't even need to do that.
But generally I believe there is basically no reasonable way to beat the market: all of the quant stuff is done by very smart people, fast computers, the value investing done by massive players like Buffet, and the regular investing done by people with 'extra info'.
I really do think that small retail investors are the losers in the casino.
Oh - and also 'big dumb money', i.e. low-performing people at big banks, sitting on huge sums that the hedges get little bites out of.
They'll sit down for an interview. Technically speaking, everything that the CEO will say has to be public information. It has to be above bar.
But sitting in the room, being right there, one might easily be able to glean more information than is actually public. Ergo - and edge. And it's not quite illegal.
So that is a form of fairly above board 'soft inside' information that nobody will ever go to jail for.
As far as more obvious 'insider' - maybe so, maybe not - I don't know - but I do know that you don't even need to do that.
But generally I believe there is basically no reasonable way to beat the market: all of the quant stuff is done by very smart people, fast computers, the value investing done by massive players like Buffet, and the regular investing done by people with 'extra info'.
I really do think that small retail investors are the losers in the casino.
Oh - and also 'big dumb money', i.e. low-performing people at big banks, sitting on huge sums that the hedges get little bites out of.
How many retail investors get face time with CEO of Kraft? It's a pretty rigged zero sum game for the rest with much of the edge in the hands of the few.
I actually started to treat trading very much like the casino. I just do it to make news reading interesting. Of course the mental pictures I form in my head are influenced by what I read. I use my gut....
Therefore retail trading is a social acceptable gambling.
brb shorting TSLA.
I actually started to treat trading very much like the casino. I just do it to make news reading interesting. Of course the mental pictures I form in my head are influenced by what I read. I use my gut....
Therefore retail trading is a social acceptable gambling.
brb shorting TSLA.
> Sentient Technologies won't disclose its performance
"We are doing some shit but we have nothing great to show but you should probably read the rest of our PR article."
> The CEO lives in HongKong and remotely manages this crew of distrusting, non-supportive and close-minded execs.
"We are a highly disruptive people working on disruptive technology in a disruptive way."
"We are doing some shit but we have nothing great to show but you should probably read the rest of our PR article."
> The CEO lives in HongKong and remotely manages this crew of distrusting, non-supportive and close-minded execs.
"We are a highly disruptive people working on disruptive technology in a disruptive way."
PR bluff.
I find the Renaissance Technologies story more compelling and worthy than a press release drafted by the VCs funding/cheering Sentient (Kleiner Perkins, Tata, Horizon, etc.)
I find the Renaissance Technologies story more compelling and worthy than a press release drafted by the VCs funding/cheering Sentient (Kleiner Perkins, Tata, Horizon, etc.)
This is the most interesting bit for me:
>Sentient's system is inspired by evolution. According to patents, Sentient has thousands of machines running simultaneously around the world, algorithmically creating what are essentially trillions of virtual traders that it calls "genes." These genes are tested by giving them hypothetical sums of money to trade in simulated situations created from historical data. The genes that are unsuccessful die off, while those that make money are spliced together with others to create the next generation. Thanks to increases in computing power, Sentient can squeeze 1,800 simulated trading days into a few minutes
>Sentient's system is inspired by evolution. According to patents, Sentient has thousands of machines running simultaneously around the world, algorithmically creating what are essentially trillions of virtual traders that it calls "genes." These genes are tested by giving them hypothetical sums of money to trade in simulated situations created from historical data. The genes that are unsuccessful die off, while those that make money are spliced together with others to create the next generation. Thanks to increases in computing power, Sentient can squeeze 1,800 simulated trading days into a few minutes
I believe anyone who has considered applying machine learning tools for identifying trading signals came across the idea of using some kind of optimization algorithm to find the best parameters. Evolutionary algorithms seem like a fair approach because the parameter space is (for lack of a better word) very sparse and anything but continuous (lots of parameter combinations don't make sense / don't work). Using a genetic algorithm - like for example the differential evolution algorithm by Price, Storn and Lampinen - is really the most naive approach. I assume they must have some pretty clever, human made models in the back - because in a very general model the parameter space would be so vast, they would probably never find good parameters. And even if they did, they would have to run thousands of tests to make sure they are not overfitting the data - making this a very slow optimization. Not saying this will or will not work - I'm just thinking out loud here.
It's not slow if you have enough compute
So, genetic algorithms? Good luck with that.
Genetic Programming, rather. See the papers authored by their Co-founder and Chief Scientist:
https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic...
https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic...
I recall reading an early article about using genetic algorithms for stock trading in the early 90's. This isn't really that new....
One of my school mates did it in mid-90s and he got his first yacht five years later. It worked for a while.
The second happiest day in your life is when you buy a yacht...
So basically genetic programming? They didn't invent that, John Koza did...
Taking on Wall Street by participating in Wall Street?
I somehow doubt how 'disruptive' this will be.
I somehow doubt how 'disruptive' this will be.
Haven't wall street firms been doing this for decades now? I remember 10 years ago I created a trading algorithm that ran by itself without my intervention. I fail to see what is different about this company than some generic quant hedge fund.
They use "the field of artificial intelligence known as machine learning" duh. "Big Data" and "Data Science" weren't around 10 years ago /s
Can you imagine an investment AI that did not have human biases. Here are some my favorite investor biases:
SALIENCY bias. People remember memorable things. The guy who made $100 million by investing in a Romanian immigrant will invest in you if you're a Romanian immigrant, but not if you're one country over even if their education and politics are the same. Computers don't care.
AVAILABILITY bias. People analyze data that is available. If you have worldwide sales figures your market seems huge. If you no data investors will be strongly prejudiced against it.
CONFIRMATION bias. Investors who have a bubble mentality will see the positive and reinforce their theory, however non-rooted in facts (for example the theory that silicon valley teams will succeed and, for example, foreign teams will fail)
There are a bunch more, too.
http://rationalwiki.org/wiki/List_of_cognitive_biases
https://en.wikipedia.org/wiki/List_of_cognitive_biases
An AI would not suffer from any of these. However, due to the skills required to evaluate a pitch, the AI would have to be much, much smarter than any expert system today. Today you can't even tell a robot how to boil a pot of water (no matter how explicit your verbal description is) or anything else, and have it even come close to succeeding.
We're far away from robots (AI) evaluating pitches and business plans. But how cool would that be!
SALIENCY bias. People remember memorable things. The guy who made $100 million by investing in a Romanian immigrant will invest in you if you're a Romanian immigrant, but not if you're one country over even if their education and politics are the same. Computers don't care.
AVAILABILITY bias. People analyze data that is available. If you have worldwide sales figures your market seems huge. If you no data investors will be strongly prejudiced against it.
CONFIRMATION bias. Investors who have a bubble mentality will see the positive and reinforce their theory, however non-rooted in facts (for example the theory that silicon valley teams will succeed and, for example, foreign teams will fail)
There are a bunch more, too.
http://rationalwiki.org/wiki/List_of_cognitive_biases
https://en.wikipedia.org/wiki/List_of_cognitive_biases
An AI would not suffer from any of these. However, due to the skills required to evaluate a pitch, the AI would have to be much, much smarter than any expert system today. Today you can't even tell a robot how to boil a pot of water (no matter how explicit your verbal description is) or anything else, and have it even come close to succeeding.
We're far away from robots (AI) evaluating pitches and business plans. But how cool would that be!
> Can you imagine an investment AI that did not have human biases. Here are some my favorite investor biases:
It's actually a trivial problem. Just need to ask a few questions to determine the investor risk profile and goals, then pick the appropriate Vanguard fund.
It's actually a trivial problem. Just need to ask a few questions to determine the investor risk profile and goals, then pick the appropriate Vanguard fund.
"Silicon Valley Hedge Fund Takes on Wall Street with AI Trader"
Another generic, contentless article using the standard outline: (name) takes on Wall Street with (scheme).
Percentage of traders who beat the market average: 50%.
Traders to the left of the average who assign the outcome of bad luck: 100%.
Traders to the right of the average who assign the outcome to a secret method and/or genius: 100%.
An unscupulous broker can "prove" to you that he is a stock picking genius, by mailing you correct predictions of the market in advance of the outcomes for, say, six months, then ask you to assign your assets over to him -- but it's a scam, a trick. The explanation: http://arachnoid.com/equities_myths/#Miracle_Man
Another generic, contentless article using the standard outline: (name) takes on Wall Street with (scheme).
Percentage of traders who beat the market average: 50%.
Traders to the left of the average who assign the outcome of bad luck: 100%.
Traders to the right of the average who assign the outcome to a secret method and/or genius: 100%.
An unscupulous broker can "prove" to you that he is a stock picking genius, by mailing you correct predictions of the market in advance of the outcomes for, say, six months, then ask you to assign your assets over to him -- but it's a scam, a trick. The explanation: http://arachnoid.com/equities_myths/#Miracle_Man
> Thanks to increases in computing power, Sentient can squeeze 1,800 simulated trading days into a few minutes.
How is it possible to generate seven years of convincing sample data from historical trading data without overfitting your models?
How is it possible to generate seven years of convincing sample data from historical trading data without overfitting your models?
Probably by testing against other data to make sure you're not overfit. Though it looks like they're not profitable currently, so... maybe they just don't.
> How is it possible to generate seven years of convincing sample data
From the article:
> These genes are tested by giving them hypothetical sums of money to trade in simulated situations created from historical data.
So they simply use historical data (going 7 years back). This is fed into a simulator (a trading day where you have access to the data of all days leading up to the simulated trading day).
> without overfitting your models?
Traditionally backtesting is used: http://www.investopedia.com/terms/b/backtesting.asp
Care should be taken to run the tests over significant periods of time (to reflect changing market conditions) and to have a final out-of-time holdout set to lessen the effects of picking "winners" that were winning purely due to chance (introduced by cherry-picking winners from thousands of models).
From the article:
> These genes are tested by giving them hypothetical sums of money to trade in simulated situations created from historical data.
So they simply use historical data (going 7 years back). This is fed into a simulator (a trading day where you have access to the data of all days leading up to the simulated trading day).
> without overfitting your models?
Traditionally backtesting is used: http://www.investopedia.com/terms/b/backtesting.asp
Care should be taken to run the tests over significant periods of time (to reflect changing market conditions) and to have a final out-of-time holdout set to lessen the effects of picking "winners" that were winning purely due to chance (introduced by cherry-picking winners from thousands of models).
> How is it possible to generate seven years of convincing sample data from historical trading data without overfitting your models?
Simple -- create a large set of models, each using different selected parameters, run them against the market, and pick the outcomes that make the scheme look good. It's called "data mining."
A famous "psychic," who shall go nameless, made a career of appearing with a sealed, dated, registered letter, opening it, and proving that she had correctly predicted the outcome of an election / horse race / other event in advance. She was always right, and the registered letters were real and were mailed before the event to be predicted. How did she do it? She mailed herself more than one registered letter for each event. People are sooo ... credulous.
Simple -- create a large set of models, each using different selected parameters, run them against the market, and pick the outcomes that make the scheme look good. It's called "data mining."
A famous "psychic," who shall go nameless, made a career of appearing with a sealed, dated, registered letter, opening it, and proving that she had correctly predicted the outcome of an election / horse race / other event in advance. She was always right, and the registered letters were real and were mailed before the event to be predicted. How did she do it? She mailed herself more than one registered letter for each event. People are sooo ... credulous.
I'm having flash backs to xkcd:
https://xkcd.com/1570/
https://xkcd.com/1570/
Renaissance Technologies, DE Shaw, etc. wall street. Wall street is usually on the forefront on using math, technology, etc. to make trades. Sometimes the models end up causing calamity as well.
The problem with algorithmic trading is that markets are complex systems. As an algorithm is adopted, it changes the dynamics of the market, and the result the assumptions it was based on tend to no longer hold. Note that humans trade via implicit algorithms, which is part of the reason why consistently outperforming the market is highly unlikely.
In my opinion, the whole idea of investing to try and maximize profits is myopic. The real reason to invest should be to gain a measure of control over the corporation being invested in. This suggests that the board should play a more active role in the governance of corporations.
People who just want to make a buck off a corporation should be limited to providing debt financing.
In my opinion, the whole idea of investing to try and maximize profits is myopic. The real reason to invest should be to gain a measure of control over the corporation being invested in. This suggests that the board should play a more active role in the governance of corporations.
People who just want to make a buck off a corporation should be limited to providing debt financing.
Let's assume your algorithm moves the market: 1) This is not a big problem: Lots of machine learning and control theory involves dealing with feedback loops. 2) If it moves the market in a predictable way, you can use this to make money.
The Western world is capitalist, not a Platonic ideal. Even if you strongly feel that people should have different reasons to invest, you will not be able to sway them (unless you can show that your alternative makes them even more money).
If you claim that long-term outperforming of the market is highly unlikely, you contribute outperforming to short-time flukes: The stock market is essentially unpredictable or in perfect equilibrium.
Unpredictability implies all these hedge funds would do better consulting random number generators, instead of well-paid quants.
Equilibrium implies the current market is operating at maximum efficiency, yet one currently makes money by exploiting non-equilibrium and erroneous evaluations.
The Western world is capitalist, not a Platonic ideal. Even if you strongly feel that people should have different reasons to invest, you will not be able to sway them (unless you can show that your alternative makes them even more money).
If you claim that long-term outperforming of the market is highly unlikely, you contribute outperforming to short-time flukes: The stock market is essentially unpredictable or in perfect equilibrium.
Unpredictability implies all these hedge funds would do better consulting random number generators, instead of well-paid quants.
Equilibrium implies the current market is operating at maximum efficiency, yet one currently makes money by exploiting non-equilibrium and erroneous evaluations.
Point #2 is what I'm talking about. Any algorithm that is going to make money long term on a large scale has to be inherently unpredictable, which is difficult if it is an algorithm that predicts the future state of the market from past data.
Sure, the world is less than perfect in a lot of ways. In most cases we try and fix it. Why is capitalism the one way where we say "oh well, that's just how things are" ??
Research has demonstrated that barring insider information, random stock picking often outperforms "experts".
I believe the market is fairly efficient, and people who make money are either lucky or are leveraging short term information differentials, which in today's hyper-connected society are going to become increasingly rare (barring insider information, again).
Sure, the world is less than perfect in a lot of ways. In most cases we try and fix it. Why is capitalism the one way where we say "oh well, that's just how things are" ??
Research has demonstrated that barring insider information, random stock picking often outperforms "experts".
I believe the market is fairly efficient, and people who make money are either lucky or are leveraging short term information differentials, which in today's hyper-connected society are going to become increasingly rare (barring insider information, again).
Unless you're trading low volume penny stocks, or have hundreds of millions of dollars under your control, your trades will likely not affect anything. Considering that you need lots of data and high frequency, you will not be trading penny stocks with your [hypothetical] clever algorithm.
There's this thing called data snooping bias, I hope these GA folks recognize that.
As trading goes, past performance does not equate future performance.
As trading goes, past performance does not equate future performance.
Hedge funds need other people's money to make money. So I assume everything they make public is PR and marketing.
> We have too many executives for a company this size - most don't add much value except for fighting with each other and politicizing issues. The CEO lives in HongKong and remotely manages this crew of distrusting, non-supportive and close-minded execs. The HR function is practically a joke. You don't ask questions, challenge their decisions or speak up - they'll threaten to fire you if you did. They have not been able to productize their technology, their trading business has not picked up and their sales pipeline is pretty dry for the other businesses. They have laid off a large number of people recently and financial trouble seems to be brewing - lot of marketing smoke in here!
> Focus on one product and give it more time.
> Productize, productize, productize.