Hi Andrew,
Welcome! Based on your first couple of sentences you've come to the first place :)
There are many places to learn Python (most of these resources are free!), and the speed depends on your technical background and available time. If you need a place to start, take a look at these threads:
https://www.quantopian.com/posts/portfolio-evaluation-pm
https://www.quantopian.com/posts/baby-steps-a-novice-quants-adventure-begins
https://www.quantopian.com/posts/21-and-hungry-want-to-learn-as-much-as-possible
https://www.quantopian.com/posts/where-do-i-start-1
https://www.quantopian.com/posts/beginner-where-to-start-learning-more
You can use algorithms to code any kind of strategy, from an aggressive intra-day strategy to a long term buy-and hold. Our data is minutely frequency, so this rules out high frequency trading. From what I've seen, majority of the algorithms tend to be longer-term trading strategies.
And how long does it take to build? Well, this all depends on the strategy you're trying to create. You can search the forums to find publicly-shared algorithms for inspiration. Then clone the strategy and begin experimenting with your custom tweaks. If you don't want to code your own strategy we have 2 options for you:
- AlgoBuilder - Choose a pre-selected basket of securities or create your own custom basket from our database of over 8,000 stocks and ETFs. You can backtest to see the results and begin paper trading and live trading.
- US Diversified Portfolio - Deploy a 9 sector ETF rebalancing strategy that we shared and are running against on our real money account. You can read more about the code here.
As far as limits on the algorithms, you can trade up to 200 securities at a time and here are the current technical limitations in live trading: https://www.quantopian.com/help#overview-livetrading
To get familiarized with the platform, take a look at the help documentation and then begin playing with the sample strategies. Feel free to post your progress and questions in the forums. And you can email us anytime at [email protected].
Best of luck!
Alisa
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