For those genuinely interested, for the most part trading firms employing quantitative and automated strategies look to keep the price of derivative or correlated assets in line with their underlying securities.

For example a stock ABC might either directly or indirectly represent two other underlying stocks FOO1 and FOO2 and a trading firm will create a model to determine the relationship between ABC, FOO1 and FOO2 so that ABC = f(FOO1, FOO2).

The role of trading firms then is to compete both on coming up with an accurate model (one firm might believe that the relationship is really ABC = f(FOO1, FOO2) while another firm models the relationship as ABC = g(FOO1, FOO2) and yet a third firm models the relationship as ABC = h(FOO2, FOO3) for some third asset FOO3) as well as premium (a firm will trade ABC = f(FOO1, FOO2) + small_fee and pocket that fee), as well as engineering aspects such as identifying cheaper costs to trade, providing fast execution etc etc...

In the absence of efficient trading strategies or market makers whose job is to maintain this price, what you get is ABC will trade at a huge spread and trades will cause the price of ABC to fluctuate significantly. Both of these properties are vaguely lumped together and called "liquidity" so that trading firms are said to provide liquidity to the market. They ensure that ABC is available to buy and sell at all times at a price that reflects its actual value at every moment in time.

If there's some kind of economic inequality created by keeping the price of assets tightly coupled to one another so that their price reflects their actual underlying value then you are welcome to take some time to present that argument.

From my point of view having done this now for close to 15 years, I find it to be a very interesting and challenging career that lets me consolidate knowledge from a variety of different fields. I get to study and put to use knowledge of many areas of computer science from machine learning, graphics/data visualization, compilers, databases, computer architecture, networking, as well as other fields such as physics, economics, law. I feel very privileged to be able to work in a multidisciplinary field and be able to see almost in real time the effect of my work. I worked as a software developer at Microsoft and Google prior to this and while those were both comfortable and pleasant places to work, it didn't compare in terms of feeling like you had an actual impact on anything. I felt at both of those companies like I was being paid a lot of money to do basically menial jobs.

There is nothing menial about working at a trading firm.

As for doing good in the world, there's an awful lot of businesses that really only contribute via tax. They do something where the entire benefit, sometimes more, is captured between the business and its customers.

But to say it specifically, you need market makers, because if they weren't there you'd have to wait a long time for someone with the opposite intention to you to show up, and that has a huge cost. And keep in mind MMs are only one part of the capital apparatus that we need in the world. This isn't just fluff, I literally had a friend phone me last week looking for money for his African startup that has had to turn down business for lack of capital.

The how of it is a long story as well, but quite an interesting one that spans a number of fields. Coding, economics, finance, and so on.

1. Market making (providing two sided liquidity in a market), and in general providing liquidity (even one sided) is a real benefit that (some) trading firms provide (e.g. Virtu, but also many proprietary shops).

The market making function solves the time-mismatch between client A who wants to buy now, and client B who would want to sell in 1 hour.

The liquidity provision is what allows, through pay-for-order-flow, retail investors to get the best current price for AAPL through their Schwab app. Not only that, they do not have to worry about the order execution (how long would it take to get filled), and their fees are low or 0 (because someone is paying Schwab for the order flow).

2. A similar, but slightly different trade is what ensures that ETF are priced "correctly". This is also a boon for retail investors.

In order to ensure the ETF price are in line with the price implied by their underlying assets, someone need to do the "index arbitrage" trade. Again, retail gets a nice useful product (e.g. SPY which tracks S&P500) instead of having to buy a lot of stocks (naively, 500).

3. And then there are directional trades, which are basically trying to "arbitrage away" moves in correlated prices. Is there a value in this? Maybe, but it is just accelerating existing trading realities. Someone would have done it anyway.

I am guessing the perception that the industry adds no value is because of stories about the ridiculously low latency number - trade in the blink of the eye, reacting in nanoseconds, etc.

And I tend to agree.

If the exchanges changed the way they matched orders (e.g. instead of First In First Out/time priority ["who came first"]) to a procedure that introduces randomness that eliminated the advantage from nanosecond/microsecond differences, it would make no difference to the world.

The prices would still be "good enough" (no retails participants care if the prices settled within 100 nanosecond, 1microsecond, or 1 millisecond).

So to sum up, does it bring value? Yes, but it does not mean there is no silliness involved.

From https://www.efinancialcareers.com/news/finance/jane-street-p...