The best book that I've read on order execution was "Algorithmic Trading and DMA". [0]

The book is kind of old now, but it was written by Barry Johnson, who worked at Morgan Stanley on their algo trading team.

The book is kind of dry, but very thorough and clear on its concepts. It reads more like a university text book than anything else. It just goes through concepts one by one, chapter by chapter.

[0]: https://www.amazon.co.uk/Algorithmic-Trading-DMA-introductio...

Thank you kindly for what looks like a great resource!

I've been trying to put myself through YouTube night school on some of this stuff, and MIT OCW has great resources as well at significantly less cost than going to MIT ;)

This is a pretty reasonable jumping off point for their corpus of financial engineering stuff: https://www.youtube.com/watch?v=HdHlfiOAJyE.

I'm fortunate enough to work with a person who actually understands derivatives trades with some sophistication, but that's a happy accident and the more people have access to good online resources the better!

Edit: I forgot to mention this book (https://www.amazon.com/Algorithmic-Trading-DMA-introduction-...) in the spirit of something more technical than the general-audience one I linked above. I have some nitpicks with it as well, but I've gotten value out of it.

Generally low level C++ will do it. I have been out of the game for about 5 years now, but when I left the game was all about speed speed speed. We weren't trading smarter anymore, it was just about trading fast. If you are faster, you don't just put an order out there with an opinion that the market will move in your favor, you get an immediate risk free return (risk free assuming operationally everything works as expected). I also worked on the "benchmark strategy" side- VWAP/TWAP type algos, when they were very new, and there was some statistics involved but the math was fairly simple. I haven't kept up with that side of the space, I am sure they have added complexity, but fundamentally you are looking at how a particular security has traded in the past- IE how much volume does it tend to trade at 10am vs 10:30 vs 11am, compare that with market statistics for the current day- is it high or low volume, is volatility higher- and apply some heuristics about what % of a parent order to put in the market at any given time.

This is a bit separate from the actual execution in the market, which is called smart order routing, and that just focuses on speed.

The best book on this still seems to be the now almost 10 year old "Algorithmic Trading and DMA" by Barry Johnson. If you want to get a feel for the strategies involved, this is your best bet: https://www.amazon.com/Algorithmic-Trading-DMA-introduction-...

As for job titles, they tend to be generic like "infrastructure developer, strategist" but look for key words like "Smart Order Router, Algorithmic Trading, Index Arb (itrage), statistical arbitrage, market making, dark pool. I put two of those in Morgan Stanley's site and got a bunch of relevant hits. Posting numbers 3119617 3120636 are actual jobs in this space.

A better bet is to just look at job openings for the companies who specialize in this stuff- Virtu, Jump, Hudson River Trading, Citadel Securities, etc...

IMHO This is the book to read: http://www.amazon.com/Algorithmic-Trading-DMA-introduction-s...

Are you really interested in learning quant finance (learning how to mathematically model various parts of financial markets, pricing/measuring risk of specific instruments, etc.) or are you interested in programming systems for the financial industry (trading/risk/compliance/banking/etc)?

This book, "Algorithmic Trading and DMA: An introduction to direct access trading strategies" (http://www.amazon.com/Algorithmic-Trading-DMA-introduction-s...) is pretty darn good if you are a programmer. However, if you really meant "quant finance," then others can give you better suggestions :)

edit: I just remembered, Paul Wilmott and Hull have several introductory books if you are interested in what is usually called "quantitative finance." This means how to price options, futures, etc. From what I recall, this does NOT mean using statistical correlations to trade two similar stocks, making market-making models, etc.

Don't try to teach the machine things you don't know yourself. Study the rules and actors in the systems you're studying, and come up with theories to test against the data. You'll need to do this work anyway, so it's at least a good way to start before you complicate things further with AI/machine-learning.

Understand this first though: The vast majority of money made in trading is made without anything more than a trivial prediction of the future. Investing is different, but very very few have enough money to make active investing worthwhile.

Start out with "Algorithmic Trading & DMA" by Johnson: http://www.amazon.com/dp/0956399207 If you choose not to, you're better off not reading anything about the actual trading than trying to pick another.. The vast majority of published material is so bad that it'll set you back.