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For around eight years my primary job function was to put investment bank traders out of a job, by automating what they did. There were still humans in charge

For around eight years my primary job function was to put investment bank traders out of a job, by automating what they did. There were still humans in charge of the algorithms, but they moved more towards Python programmers than market traders. Many of the "old-style" traders bitched about what we did, and most moved jobs to banks that were less advanced. (I was in the interest rates line; typical trade size is $10M)

adwhit 10y ago
This was my first thought. Of course their jobs can be automated. Automation increases the productivity of the average employee to the point where fewer employees are needed. Investment bankers are extremely vulnerable to this given how much fat there tends to be in their organizations.
2sk21 10y ago
I am curious about how the old-style traders actually did their jobs. Did they base their trading decisions on data or instinct?
- cm2187 10y ago
  Trading illiquid products is all about knowing your market, and having a good idea of who you will be able to sell something when you accept to buy it (you are not in the business of taking a position you cannot get out of). Having a good understanding of the flows, who is buying, who is selling, who still has room for this exposure, etc. This is achieved by discussing with sales people, who themselves discuss with investors, as well as traders at other banks (through brokers). Now the definition of illiquid varies. Many products that used to be illiquid are now pretty liquid (interest rate derivatives) while many other are liquid only for small trade size (certain bonds). FX is an interesting example. It is very liquid but it is also a market where many clients need to make jumbo transactions on the spot, and these would be market moving if not carefully managed. That's something that could be probably automated. I find the article very poorly written. "Investment bankers" is extremely vague and the breadth of very different product in different markets traded by investment banks makes this sort of generalization a bit absurd. The other reason why I think the article doesn't make sense is that investment banks cater for certain giant markets (equity, FX, treasuries, etc) but also for a huge variety of niche markets, in which only a handful of banks and traders are active. If you add the salaries of the couple of traders in each of the active banks on one particular market, the savings you would do automating the market wouldn't justify the years of IT development to train and fine tune an algo, which would still need to be maintained as the market evolves (and then you end up overpaying an AI expert instead of overpaying a couple of traders...). I think AI will shine at solving wide problems that affect a large number of people. Self driving cars. Butler robots. Building a house. Manufacturing something common. These markets have the scale to justify large investments. I very much doubt that AI will replace every single complex task done by a man today, for the very same reason that software hasn't replaced every single manual task done by a man today: the cost of developing and maintaining software can easily exceed the salary of the few guys you are trying to replace. To overcome that with software, we need to dramatically reduce the cost of developing software, enabling ordinary employees to develop their own software. But even today we are very far from that. What's the % of a generation who can actually code out of college today? How easy and useful are the main programming languages? I'd argue we are now going into the opposite direction. Microsoft is poised to take VBA out of office. All major OS are evolving toward the iOS-style locked down platform where you can only run Apple/Microsoft approved software. Corporate IT is ever more locking down platforms with software whitelisting, etc. I wonder if the golden age of productivity improvement through software has not peaked.
  - kpil 10y ago
    >To overcome that with software, we need to dramatically reduce the cost of developing software, enabling ordinary employees to develop their own software. I think this is the key to running an effective organisation. It requires that most people know how to program, or at least know enough to understand what is possible to program. I also don't see this coming, partly because the education systems are not really up to par, but also because it's really hard to develop complex systems. I'd argue that the languages are not really the issue here even if the trends seems to go towards even crappier languages (like js, php) to really mess up the heads of beginners. But even with a hypothetical "perfect language" the main problems is the huge amount of time and effort it takes to learn any programming language at all, plus the even more enormous amount of time it takes to write something useful even for a really experienced developer. But sure. It's perhaps time for a new cycle of tearing down the "mainframes" (in someone else's basement this time) and reinvent personal computing for the 2nd or 3rd time...
- bboreham 10y ago
  Knowledge and experience of how the market reacts to other movements. I guess you could call some of that "instinct". Of course, they did know more than the machine did in certain situations, but not enough to make up the cost.

adwhit 10y ago

This was my first thought. Of course their jobs can be automated. Automation increases the productivity of the average employee to the point where fewer employees are needed. Investment bankers are extremely vulnerable to this given how much fat there tends to be in their organizations.

2sk21 10y ago

I am curious about how the old-style traders actually did their jobs. Did they base their trading decisions on data or instinct?

cm2187 10y ago
Trading illiquid products is all about knowing your market, and having a good idea of who you will be able to sell something when you accept to buy it (you are not in the business of taking a position you cannot get out of). Having a good understanding of the flows, who is buying, who is selling, who still has room for this exposure, etc. This is achieved by discussing with sales people, who themselves discuss with investors, as well as traders at other banks (through brokers). Now the definition of illiquid varies. Many products that used to be illiquid are now pretty liquid (interest rate derivatives) while many other are liquid only for small trade size (certain bonds). FX is an interesting example. It is very liquid but it is also a market where many clients need to make jumbo transactions on the spot, and these would be market moving if not carefully managed. That's something that could be probably automated. I find the article very poorly written. "Investment bankers" is extremely vague and the breadth of very different product in different markets traded by investment banks makes this sort of generalization a bit absurd. The other reason why I think the article doesn't make sense is that investment banks cater for certain giant markets (equity, FX, treasuries, etc) but also for a huge variety of niche markets, in which only a handful of banks and traders are active. If you add the salaries of the couple of traders in each of the active banks on one particular market, the savings you would do automating the market wouldn't justify the years of IT development to train and fine tune an algo, which would still need to be maintained as the market evolves (and then you end up overpaying an AI expert instead of overpaying a couple of traders...). I think AI will shine at solving wide problems that affect a large number of people. Self driving cars. Butler robots. Building a house. Manufacturing something common. These markets have the scale to justify large investments. I very much doubt that AI will replace every single complex task done by a man today, for the very same reason that software hasn't replaced every single manual task done by a man today: the cost of developing and maintaining software can easily exceed the salary of the few guys you are trying to replace. To overcome that with software, we need to dramatically reduce the cost of developing software, enabling ordinary employees to develop their own software. But even today we are very far from that. What's the % of a generation who can actually code out of college today? How easy and useful are the main programming languages? I'd argue we are now going into the opposite direction. Microsoft is poised to take VBA out of office. All major OS are evolving toward the iOS-style locked down platform where you can only run Apple/Microsoft approved software. Corporate IT is ever more locking down platforms with software whitelisting, etc. I wonder if the golden age of productivity improvement through software has not peaked.
- kpil 10y ago
  >To overcome that with software, we need to dramatically reduce the cost of developing software, enabling ordinary employees to develop their own software. I think this is the key to running an effective organisation. It requires that most people know how to program, or at least know enough to understand what is possible to program. I also don't see this coming, partly because the education systems are not really up to par, but also because it's really hard to develop complex systems. I'd argue that the languages are not really the issue here even if the trends seems to go towards even crappier languages (like js, php) to really mess up the heads of beginners. But even with a hypothetical "perfect language" the main problems is the huge amount of time and effort it takes to learn any programming language at all, plus the even more enormous amount of time it takes to write something useful even for a really experienced developer. But sure. It's perhaps time for a new cycle of tearing down the "mainframes" (in someone else's basement this time) and reinvent personal computing for the 2nd or 3rd time...
bboreham 10y ago
Knowledge and experience of how the market reacts to other movements. I guess you could call some of that "instinct". Of course, they did know more than the machine did in certain situations, but not enough to make up the cost.