| Are you interested in a genuine discussion on this topic or have you already made up your mind? 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. |
All of those firefighters, police officers, and teachers can't get their monthly check unless the pension funds converts part of their investment into cash, and the amount traded gets so large you need well-funded financial participants who will pay the pension fund a large lump of cash and assume the risk of unwinding the position.
The same thing goes for portfolio rebalances. Some smart and prudent retirement fund has run their risk model and decided that their sector exposures are off by like a few percent. They've got 2% too much financials, 2% too little tech, they want to move 1% from consumer staples to consumer discretionary, etc. We're talking about billions of dollars being moved right here! They want to use the money from the assets they sold to purchase the assets they bought, but they want the transaction to happen all at once... not in two parts. Again, this is where the quant funds and market makers of the world come in.
It's easy to think that finance is all fat cats, hedge funds and multibillionaires, but anybody with a retirement plan, a pension, ETF holdings, or mutual fund holdings, benefits from the work these quant funds do.