Former investment banker here. This is a question I had when I hit the desk, and it's an important question.<p>The short answer to your question is: because most of the volume traded on exchanges is large blocks of stock being bought and sold by institutional investors, and you need humans to make these deals happen.<p>Longer explanation as follows:<p>On the trading floor [0], you have two groups of people: the sales team and the traders.<p>The sales team gets paid when they make markets, i.e., connect buyers and sellers. Specifically, the financial institution takes a fee that's a very small % of the overall transaction volume, and some of that goes into the sales team's bonus pool. The more stock trades flow through the firm (specifically, their business unit), the more they get paid.<p>The traders, on the other hand, gets paid to do two things, which are really the same thing: a) not put too much of the firm's capital at risk and b) set the firm up to make money by buying securities low and selling them high. Every trader has a "P&L" (profit & loss) number, which is the total amount of money they've made or lost for the firm since the start of the fiscal year. They get paid a bonus based on this number. They tend to know exactly what their number is at any given time.<p>So, there is actually a lot of tension on the trading floor between the sales team and the traders, because the sales team wants a lot of volume to go through their business unit, and any given trader wants to maximize her P&L.<p>Real world example might be: the sales dude gets a call from a hedge fund saying, "we want to sell $100mm of our shares in Alphabet at $720". He then shouts over to the trader (who sits close to him) to tell her about the call and she thinks for a couple seconds [1] and then says, "you need to make a market for 80mm of those shares at that price, I'm only taking 20mm."<p>In other words, the trader is saying that she'll only tie up $20mm of the firm's capital on this particular trade [2]. The sales person might come back and say, "c'mon, they took that $50mm of Microsoft stock you were trying to get rid of last quarter, we as a firm owe them a favor" to which the trader might respond, "OK, we'll take $30mm tops". So then the sales person will get on the phone and start calling everyone (other mutual / hedge funds, pension funds, etc) who might be interested in buying Alphabet at $720. Maybe the sales person makes it happen; maybe they don't. In any case, they need to figure out whether they can get 70 million dollars worth Alphabet stock pre-sold to other people in the market at $720 before they get back to the hedge fund trying to sell it with a response as to whether they can make the trade.<p>All of this involves MASSIVE HUMAN FACTORS. I'm sure we will one day be able to train AI to work through various constructs of "we owe them a favor" but right now you still need humans to get big trades like this done. And again, big trades like this constitute the majority of the overall volume in the market. So, that's why trades don't run entirely on algorithms...yet.<p>[0] I was in banking, not S&T, but have a decent understanding of how this works.<p>[1] Being able to make decisions of this magnitude in a couple of seconds (and have them be good ones) is one of the two skills you need to have as a trader; the other one is not letting the outcome of the last trade (good or bad) affect your thinking on the next trade.<p>[2] There is potential for both upside and downside in a decision like this; if the stock appreciates, the firm can profit by selling the stock at a higher price than it paid, but the reverse is also true. This is also an example of why "proprietary trading" is such a blurry line. In order to make markets for big trades, firms usually have to put their own capital at risk, even for a few minutes. At what point are they trading for their own profit vs. temporarily assuming risk in order to broker a deal between two counterparties? Go read Matt Levine's archived columns at Bloomberg if you find stuff like this interesting.