I've heard some crazy shit about how much money comes from adtech to fund blackhat data brokers. Adtech buys hacked databases on underground markets, but more than that they fund supply chain attacks to get highly intrusive adware into popular apps. They frequently buy up applications that have a wide install base on phones and browser extensions, and then on the next update, request maximum privileges and use it to loot as much as they can from user systems.
It's a symbiotic relationship. Shady ad networks are often used by criminals for narrowly targeted attacks (advertise this crafted phishing site to women aged 25-35 in the greater Dallas Fort Worth area who are recently married). Those criminals use that access to obtain more private data which they sell to adtech companies. It's a pretty gross business.
In other news, HFT isn't bad because it's HFT, it's bad because order matching services have a bunch of shady, undocumented order types that are designed to allow HFT firms to specifically extract winnings from retail investors. They are absolutely economic parasites, and no one has any incentive to stop them.
You can see the old homepage here http://josh.com/oldindex.htm
Some of his code (through acquisitions) lives on at the Nasdaq exchange. He's a fascinating person in the history of electronic markets.
If we accept financial services as a whole to be OK, then HFT certainly is. I'd suggest the book "Dark Pools":
It describes how automatic trading started. If you're a programmer, you'll probably have your mouth hanging open realising how up-for-grabs so much money was. At least that's how it sounded on reading it.
Some of this maybe a repeat to people as I often get asked for recommendations on how to get into algorithmic trading.
http://www.amazon.ca/Fortunes-Formula-Scientific-Betting-Cas... The history of hte first real quant
http://www.amazon.ca/Dark-Pools-Machine-Traders-Rigging-eboo... The history of the rise of algorithmic trading
The phyisics of wall street was mentioned by someone else, great book
http://www.amazon.ca/Quants-Whizzes-Conquered-Street-Destroy... This profiles 4 famous traders including Simons, alos a great book
http://www.amazon.ca/Heard-Street-Quantitative-Questions-Int... A must read if you want to get into quantitative finance.
As always, email if you'd like to chat.
Good riddance, the markets are better off in almost every way but removing pit traders.
- end of day's reconcile,
-machines aren't tempted to "lose" trade tickets for trades that would have been loses.
- machines don't hold clients trades while they jump infront of them.
- liquidity is much, much better off now. Every flash crash has an almost instantaneous rebound of prices back to their "true" values.
To the city of Chicago's credit. Even thought they lost pit trading for futures and almost all options, they've still managed to keep the bulk of those trades via the electronic CBOE and being the center of HFT.
I would guess that when an industry gets as disrupted as pit trading was, then the center of gravity would tend to move. In this case, Chicago did well to hang onto it.
However, there wasn't really too much actionable advice in it. I don't think I actually saw any advice as to how to become an algorithmic trader in the post.
I think I actually wrote a better answer in a previous post here:
The sad fact is that if you want to get into algorithmic trading you really have 3 choices.
1) got to MIT, get an undergrad in math/engineering, apply to TradeBot, Virtu, Getco, Jane Street.
This provably works as this is how these firms hire, sadly its not very applicable for most people.
2) Get into a small and successful fund that was previously a prop shop( traders without any algorithmic tooling and then start to build it out yourself.
This can work, but its a very hard and long slog. You'll be creating everything from scratch and wont' have alot of people to bounce technical ideas off of. This might be the hardest way to break into the industry, as you'll essentially be creating a new company inside of an existing one, but it is possible, as this is how I did it.
3) Get hired in a technical capacity with a major algorithmic trading firm and move up.
The key here is to not be in a strictly technical capacity for more than a few years. The industry has a tendency to box people into their current roles.
You have to make people aware of what your goals are. Shadow the best traders you can find. Be mentored by the technical talent who writes the strategies. Get as close to the money as possible!
I lied there is actually a secret option 4)
You can go it alone and trade your own money. I really don't recommend this to people as you need a minimum of $50,000 to $100,000 to do this well. Its hard as you won't have anyone to bounce ideas off of or to lean on when times are tough.
The biggest problem I've seen with going it on your own is that since 2009 we've been in a huge bull market. Everyone is making money. We haven't had a challenging market for 5 years so if you've been trading for less its hard to know if its you who is making money(alpha) or if its the market(beta).
I really don't try to time the market but I have a feeling that late next year people who have been trading their own strategies will start to find out what its like to trade in a bear market.
Someone privately messaged me about math. For each of these options, I find math, specifically stats, to be very important. The hard part is getting programmers to learn stats. There is an old Simpsons episode where Homer is trying to learn about marketing. He starts with a huge book on marketing reads it for a few minutes and then goes to a beginners guid to marketing before finally looking the definition of marketing up on the internet.
Don't be afraid to learn math this way.
I usually recommend people read chapters 2-5 of
Introduction to Statistically learning
If you are flying through it then graduate to Elements of statistical learning http://statweb.stanford.edu/~tibs/ElemStatLearn/
If you are working hard to understand Intro to statistical learning then go to Kahn Academy and spend 2 weeks doing all their stats lessons.
I feel like I'm repeating my self but there are no free lunches. You need to work to learn the material. Don't be afraid to go back to basics.
On his book recommendations, Trading and Exchanges is awesome. Michael Lewis' Flash boys is not, read Scott Patterson's DarkPools instead http://www.amazon.com/Dark-Pools-Machine-Traders-Rigging/dp/...
If you are determined to read Flash Boys then atleast read the counter argument by a HFT https://news.ycombinator.com/item?id=8577237
Its a much more enlightening read and is only a few dollars:)
Good book. HFT gives the illusion of liquidity - can dry up real quick and if things go wrong, well, as suggested below, you get the Flesh Crushes ;)
There is (perhaps) no way a human can compete in the stock market any more. This is the age of AI, where computers are pushing around billions of dollars in an automated fashion. Taking every arbitrage advantage in milliseconds, and are even able to find under- and over-valued stocks in the blink of an eye.
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