10 ms·

Silicon Valley Hedge Fund Takes on Wall Street with AI Trader

191 points by bunburying 10y ago

JTon 10y ago
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
- alva 10y ago
  This is the most interesting bit for me : > It shares little about the data used for the AI's decision-making and isn't profitable
  - rayuela 10y ago
    Yup. This is a bullshit PR piece.
- rbinv 10y ago
  So, genetic algorithms? Good luck with that.
  - sixtypoundhound 10y ago
    I recall reading an early article about using genetic algorithms for stock trading in the early 90's. This isn't really that new....
    - draugadrotten 10y ago
      One of my school mates did it in mid-90s and he got his first yacht five years later. It worked for a while.
      - gaius 10y ago
        The second happiest day in your life is when you buy a yacht...
  - vijucat 10y ago
    Genetic Programming, rather. See the papers authored by their Co-founder and Chief Scientist: https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic&hl=en&as_sdt=0&as_vis=1&oi=scholart&sa=X&ved=0ahUKEwjR1JPfk_7RAhWCk5QKHVGsC8wQgQMIGDAA https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic...
- jcfrei 10y ago
  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.
  - uchish 10y ago
    It's not slow if you have enough compute
- scottlegrand2 10y ago
  So basically genetic programming? They didn't invent that, John Koza did...
growt 10y ago
I just started reading 0 to 1 and I think according to Peter Thiel this news sums up everything that is wrong with the world in one sentence :)
- fahadkhan 10y ago
  care to elaborate?
pdog 10y ago
> 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?
- problems 10y ago
  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.
- lutusp 10y ago
  > 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.
- BickNowstrom 10y ago
  > 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 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).
antr 10y ago
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.)
perlpimp 10y ago
fwiw http://www.forbes.com/sites/rickferri/2012/12/20/any-monkey-can-beat-the-market/#85db6466e8b6 http://www.forbes.com/sites/rickferri/2012/12/20/any-monkey-...
mjpuser 10y ago
I just checked out glassdoor, and it seems like they don't know what their product should be since top execs don't want to agree on anything. > 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.
- easytiger 10y ago
  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
- 65827 10y ago
  I mean sure, but take glassdoor with a huge grain of salt, people make up crap to post on there all the time.
  - drpgq 10y ago
    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.
    - simonebrunozzi 10y ago
      Curious to what your are referring to, related to Tolstoy (or Tolstoj as I like to write his name). Can you elaborate? Thanks!
      - 10y ago
robert_foss 10y ago
Taking on Wall Street by participating in Wall Street? I somehow doubt how 'disruptive' this will be.
sunrisetofu 10y ago
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.
samfisher83 10y ago
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.
SEJeff 10y ago
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.
- frankc 10y ago
  Longer than that. This article was passed around at my job to laugh at.
  - cr0sh 10y ago
    Definitely much longer - I'm pretty sure I read about things like this in Omni Magazine back in the 1980s...
- jredwards 10y ago
  HFT is a different kind of 'beating the market', though, don't you think?
  - SEJeff 10y ago
    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
    - raw23 10y ago
      Arguable whether or not HFT increases liquidity in the market.
      - SEJeff 10y ago
        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.
jliptzin 10y ago
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.
- solumos 10y ago
  They use "the field of artificial intelligence known as machine learning" duh. "Big Data" and "Data Science" weren't around 10 years ago /s
CuriouslyC 10y ago
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.
- imaginenore 10y ago
  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.
- BickNowstrom 10y ago
  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.
  - CuriouslyC 10y ago
    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).
logicallee 10y ago
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 http://rationalwiki.org/wiki/List_of_cognitive_biases https://en.wikipedia.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!
- user5994461 10y ago
  > 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.
bfrog 10y ago
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.
- alfalfasprout 10y ago
  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.
- edblarney 10y ago
  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.
  - brilliantcode 10y ago
    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.
    - edblarney 10y ago
      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.
kiernanmcgowan 10y ago
I'm having flash backs to xkcd: https://xkcd.com/1570/ https://xkcd.com/1570/
brilliantcode 10y ago
> 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."
raw23 10y ago
Frustrating that so many great minds are swooped into the finance industry. The lure of money is too strong.
- hendzen 10y ago
  Frustrating that so many great minds are swooped into the online advertising industry. The lure of money is too strong.
lutusp 10y ago
"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 http://arachnoid.com/equities_myths/#Miracle_Man
99_00 10y ago
Hedge funds need other people's money to make money. So I assume everything they make public is PR and marketing.

191 points by bunburying 10y ago

JTon 10y ago

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

alva 10y ago
This is the most interesting bit for me : > It shares little about the data used for the AI's decision-making and isn't profitable
- rayuela 10y ago
  Yup. This is a bullshit PR piece.
rbinv 10y ago
So, genetic algorithms? Good luck with that.
- sixtypoundhound 10y ago
  I recall reading an early article about using genetic algorithms for stock trading in the early 90's. This isn't really that new....
  - draugadrotten 10y ago
    One of my school mates did it in mid-90s and he got his first yacht five years later. It worked for a while.
    - gaius 10y ago
      The second happiest day in your life is when you buy a yacht...
- vijucat 10y ago
  Genetic Programming, rather. See the papers authored by their Co-founder and Chief Scientist: https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic&hl=en&as_sdt=0&as_vis=1&oi=scholart&sa=X&ved=0ahUKEwjR1JPfk_7RAhWCk5QKHVGsC8wQgQMIGDAA https://scholar.google.com.hk/scholar?q=Babak+Hodjat+genetic...
jcfrei 10y ago
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.
- uchish 10y ago
  It's not slow if you have enough compute
scottlegrand2 10y ago
So basically genetic programming? They didn't invent that, John Koza did...

growt 10y ago

I just started reading 0 to 1 and I think according to Peter Thiel this news sums up everything that is wrong with the world in one sentence :)

fahadkhan 10y ago
care to elaborate?

pdog 10y ago

> 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?

problems 10y ago
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.
lutusp 10y ago
> 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.
BickNowstrom 10y ago
> 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 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).

antr 10y ago

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.)

perlpimp 10y ago

fwiw http://www.forbes.com/sites/rickferri/2012/12/20/any-monkey-can-beat-the-market/#85db6466e8b6 http://www.forbes.com/sites/rickferri/2012/12/20/any-monkey-...

mjpuser 10y ago

I just checked out glassdoor, and it seems like they don't know what their product should be since top execs don't want to agree on anything. > 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.

easytiger 10y ago
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
65827 10y ago
I mean sure, but take glassdoor with a huge grain of salt, people make up crap to post on there all the time.
- drpgq 10y ago
  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.
  - simonebrunozzi 10y ago
    Curious to what your are referring to, related to Tolstoy (or Tolstoj as I like to write his name). Can you elaborate? Thanks!
    - 10y ago

robert_foss 10y ago

Taking on Wall Street by participating in Wall Street? I somehow doubt how 'disruptive' this will be.

sunrisetofu 10y ago

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.

samfisher83 10y ago

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.

SEJeff 10y ago

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.

frankc 10y ago
Longer than that. This article was passed around at my job to laugh at.
- cr0sh 10y ago
  Definitely much longer - I'm pretty sure I read about things like this in Omni Magazine back in the 1980s...
jredwards 10y ago
HFT is a different kind of 'beating the market', though, don't you think?
- SEJeff 10y ago
  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
  - raw23 10y ago
    Arguable whether or not HFT increases liquidity in the market.
    - SEJeff 10y ago
      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.

jliptzin 10y ago

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.

solumos 10y ago
They use "the field of artificial intelligence known as machine learning" duh. "Big Data" and "Data Science" weren't around 10 years ago /s

CuriouslyC 10y ago

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.

imaginenore 10y ago
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.
BickNowstrom 10y ago
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.
- CuriouslyC 10y ago
  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).

logicallee 10y ago

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 http://rationalwiki.org/wiki/List_of_cognitive_biases https://en.wikipedia.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!

user5994461 10y ago
> 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.

bfrog 10y ago

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.

alfalfasprout 10y ago
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.
edblarney 10y ago
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.
- brilliantcode 10y ago
  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.
  - edblarney 10y ago
    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.

kiernanmcgowan 10y ago

I'm having flash backs to xkcd: https://xkcd.com/1570/ https://xkcd.com/1570/

brilliantcode 10y ago

> 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."

raw23 10y ago

Frustrating that so many great minds are swooped into the finance industry. The lure of money is too strong.

hendzen 10y ago
Frustrating that so many great minds are swooped into the online advertising industry. The lure of money is too strong.

lutusp 10y ago

"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 http://arachnoid.com/equities_myths/#Miracle_Man

99_00 10y ago

Hedge funds need other people's money to make money. So I assume everything they make public is PR and marketing.