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Goldman Sachs automated trading replaces 600 traders with 200 engineers

technologyreview.com

21–30 of 155 posts

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#21
post #10

A lot of dope smoking in this article. There are a handful of markets that are large and liquid enough to fully move to electronic trading, like spot FX, vanilla interest rate swaps, perhaps treasuries trading. But most other markets are very much relationship driven. For instance a trader will make a market on illiquid bonds based on what he thinks is the appetite from the short list of potential buyers, and that's…

As Big Data encroaches more and more into reality these decisions are going to be less relationship based and more AI based. The reason before it had to be relationship based was because computers didn't have visibility into the real world to make these decisions. However, with the advent of big data, their visibility is increasing.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#22

Earlier quoted context omitted.

Isn't this type of trading sort of unique in how easy it is to consume the data? Even in other investing areas, people who just "look at data and make decisions" cannot be easily replaced until computers can read and understand natural language and understand the state of the world. I can't immediately think of anything else this type of automation could apply to.

Not really. The world is data. Anything you need to know about the world is in a table somewhere, and the web has done a great job of making the planets data accessible to machines. Other areas may be more complex, but complexity isn't as big a barrier as it may seem. Also, those areas are probably not as complex as people think they are. I'm reminded of the AI that started making breakthroughs in oncology by looking…

Spoken like a true data scientist. Hope there's room for culture in there somewhere.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#23
post #22

Earlier quoted context omitted.

Not really. The world is data. Anything you need to know about the world is in a table somewhere, and the web has done a great job of making the planets data accessible to machines. Other areas may be more complex, but complexity isn't as big a barrier as it may seem. Also, those areas are probably not as complex as people think they are. I'm reminded of the AI that started making breakthroughs in oncology by looking…

Spoken like a true data scientist. Hope there's room for culture in there somewhere.

Sorry to burst your bubble, but culture is data too.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#24
post #12

Earlier quoted context omitted.

Isn't this type of trading sort of unique in how easy it is to consume the data? Even in other investing areas, people who just "look at data and make decisions" cannot be easily replaced until computers can read and understand natural language and understand the state of the world. I can't immediately think of anything else this type of automation could apply to.

Computers are already making trades based on natural language articles. EX of some research from 2008: http://www.seas.upenn.edu/~cse400/CSE400_2007_2008/DavdaMitt... You see real world movement within seconds of the release of some public data. Which is far to soon for humans to read much of anything.

Absolutely, but isn't this type of software generally used to augment existing jobs, rather than replace them? The program can make basic inferences like "10 negative GE articles -> Sell GE stock", but you still need a human to make more general decisions about an industry as a whole, related companies, how long-term an issue is, etc. Basically, nobody's job is as simple as reading the news and deciding whether articles are positive or negative. In the case of this Goldman Sachs story, some people's jobs really were as simple as looking at the performance of equities and making decisions based on that alone.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#25
post #12

Earlier quoted context omitted.

Computers are already making trades based on natural language articles. EX of some research from 2008: http://www.seas.upenn.edu/~cse400/CSE400_2007_2008/DavdaMitt... You see real world movement within seconds of the release of some public data. Which is far to soon for humans to read much of anything.

I'd have to wonder what type of safeguards vet against intentional false data released to poison the well of other HFT bots? Maybe it's not too important yet because HFT bots only need to game the slower mass of "dumb (reactionary) money"

Not a whole lot. [1]

[1] http://www.theatlantic.com/sponsored/etrade-social-stocks/th...

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#26

Earlier quoted context omitted.

Isn't this type of trading sort of unique in how easy it is to consume the data? Even in other investing areas, people who just "look at data and make decisions" cannot be easily replaced until computers can read and understand natural language and understand the state of the world. I can't immediately think of anything else this type of automation could apply to.

Not really. The world is data. Anything you need to know about the world is in a table somewhere, and the web has done a great job of making the planets data accessible to machines. Other areas may be more complex, but complexity isn't as big a barrier as it may seem. Also, those areas are probably not as complex as people think they are. I'm reminded of the AI that started making breakthroughs in oncology by looking…

The problem is understanding data. A human can learn a new word's meaning by reading its definition in a dictionary; a computer can't.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#27

Earlier quoted context omitted.

Isn't this type of trading sort of unique in how easy it is to consume the data? Even in other investing areas, people who just "look at data and make decisions" cannot be easily replaced until computers can read and understand natural language and understand the state of the world. I can't immediately think of anything else this type of automation could apply to.

Not really. The world is data. Anything you need to know about the world is in a table somewhere, and the web has done a great job of making the planets data accessible to machines. Other areas may be more complex, but complexity isn't as big a barrier as it may seem. Also, those areas are probably not as complex as people think they are. I'm reminded of the AI that started making breakthroughs in oncology by looking…

> Anything you need to know about the world is in a table somewhere

Not yet.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#28

I'm super skeptical of these type of automated trading outfits. There's no edge in them. All you've done is take a shoddy system done by hand into code. At the end of the day, they still crap out when the market conditions it was designed for shifts or naive view of the markets as something as a math formula. Exceptions are HFT, arbitrages where you don't need to speculate and take the corresponding risks.

From the article > employed 600 traders, buying and selling stock on the orders of the investment bank’s large clients.

The traders sound fancy but werent much more than call center staff, receiving orders by telephone and writing paper tickets. They weren't prop traders.

Re: Goldman Sachs automated trading replaces 600 traders with 200 engineers

#30
post #10

A lot of dope smoking in this article. There are a handful of markets that are large and liquid enough to fully move to electronic trading, like spot FX, vanilla interest rate swaps, perhaps treasuries trading. But most other markets are very much relationship driven. For instance a trader will make a market on illiquid bonds based on what he thinks is the appetite from the short list of potential buyers, and that's…

As Big Data encroaches more and more into reality these decisions are going to be less relationship based and more AI based. The reason before it had to be relationship based was because computers didn't have visibility into the real world to make these decisions. However, with the advent of big data, their visibility is increasing.

What big data?

How many acquisitions of an irish insurance company by a german bank are you going to use to train your algorithm to understand the legal and regulatory issues? How are you going to teach your algorithm to anticipate how IFRS9 or the upcoming Banking regulations being discussed with the regulator going to affect that? How are you going to train your algorithm to draft the disclosures in the offering circular, or to challenge the management's view during the due diligence?

Are you going to mine gmail traffic? Are you going to mine websites? There are like one or two companies in the world that would face this particular combination of problems. You won't find a nice article on wikipedia to tell you how to handle it.

What big data?

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