Reddit reviews Algorithmic Trading: Winning Strategies and Their Rationale
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Anything written by Ernest Chan is excellent, and he also has a blog. Here's one of his books:
https://www.amazon.com/Algorithmic-Trading-Winning-Strategies-Rationale/dp/1118460146
Algorithmic Trading: Winning Strategies and Their Rationale by Ernie Chan
Trading and Exchanges: Market Microstructure for Practitioners by Larry Harris
Algorithmic Trading and DMA: An introduction to direct access trading strategies by Barry Johnson
Probably just start with a book on the subject to introduce you to concepts / terminology. Find a provider for data, preferably one that has backtesting support as well. Find a strategy, test, paper trade it, launch it live.
This will take a considerable amount of time.
https://www.amazon.com/Algorithmic-Trading-Winning-Strategies-Rationale/dp/1118460146
They're not really "backtesting resources" but Ernie Chan's books all use matlab code examples, and he has all of the full example code on his website (viewable with a password obtained from the book)
It actually does use indicators, and those indicators predict trends.
Mathematical models: I have only studied indicators. In the beginning of my project, I tried to create my own indicators using parametric equations, but it wasn't working. I couldn't get the algorithms to produce results better than random backtests. So I moved from that into real indicators.
Books:
The Ultimate Day Trader
It was the most helpful when I was getting started and learning about indicators. It taught me how trading was done, and it introduced the typical algorithmic trading like MACD crossovers, bullish convergence/divergence. It may be too much for beginners. As a warning, reviewers on Amazon don't think highly of the book.
I had to learn a lot on my own through trial and error and the occasional google search, so I The Ultimate Day Trader is the only book that I fully read.
Building Winning Algorithmic Trading Systems
Gives a lot of good information in getting good backtest results, and the steps an algorithm should have to pass in order to be traded with.
Algorithmic trading: Winning strategies and their rationale.
Currently reading this, and it starts off basic, like most books. It talks about look-ahead biases and that sort of stuff. It also talks about the different backtesting software and programming languages. I'm only on page 40/200, and it looks like it gets more complex.
I also have a few books on options, but those don't have to do with algorithmic trading.
That's fine, then. My main concern was that you might be putting your money on the line!
I am not sure that an automated momentum system can't work. In fact, many CTAs (commodity trading advisors... a kind of hedge fund) made consistent returns in 2000-2009 by following pretty simple momentum strategies - generally moving averages or moving average crossovers on a 100-300 day window. Note that the timescale is much longer than yours, and also note that most of those CTAs have been in drawdown since about 2010 (ie they've lost money or just about broken even for the last four years).
But I am pretty certain that an intraday trading system based on trashy, discredited technical analysis isn't going to yield consistent profits, especially when applied by someone who is trading for the first time.
One way to tell if a trader knows what they are doing is to listen to their language - if they talk about technical indicators, fibonacci retracement, elliott waves, entry and exit points, MACD etc then they are a quack. If they talk about regression, signal processing, traing and test sets, regularization, bias/variance etc then there's a chance that they know what they're talking about.
There is fifty years of history building mathematical tools for analysing random processes, making time series forecasts, building regression models, and analysing models out of sample, all of which is generally ignored by the quacks who rely on spurious "indicators" and "entry/exit points". A good place to start is this book -
http://www-bcf.usc.edu/~gareth/ISL/
and this is a good book for when you've progressed beyond the intermediate level
http://statweb.stanford.edu/~tibs/ElemStatLearn/
There are two books by Ernest Chan about quantitative trading that frankly don't tell you anything that will be immediately applicable to creating a strategy (there's no secret sauce) but they do give you a good high level overview of what building a quantitative trading system is all about
http://www.amazon.co.uk/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889/ref=sr_1_2?ie=UTF8&qid=1406963471&sr=8-2&keywords=ernest+chan
http://www.amazon.co.uk/Algorithmic-Trading-Winning-Strategies-Rationale/dp/1118460146/ref=sr_1_1?ie=UTF8&qid=1406963471&sr=8-1&keywords=ernest+chan
Hope that's helpful.
My school had a book from Ernest Chan in the library. I recommend something like it https://www.amazon.com/Algorithmic-Trading-Winning-Strategies-Rationale/dp/1118460146
For trading & quant background reading try:
Algorithmic Trading: Winning Strategies and T... http://www.amazon.com/dp/1118460146/ref=cm_sw_r_tw_dp_w795tb18DWJYM via @amazon
Volatility Trading, + CD-ROM by Euan Sinclair http://www.amazon.com/dp/0470181990/ref=cm_sw_r_tw_dp_z895tb04AE5BJ via @amazon
Nuclear phynance http://www.nuclearphynance.com
Stocktwits www.stocktwits.com