Thanks for the recent posts, I could share my thoughts but I don't think I've got much to add at this stage. My focus is definitely not get rich quick, what I'm attempting to do increase returns whilst reducing risk versus the 'market' by diversifying across asset classes and strategies - somewhat akin to building a mini hedge fund. I'm not shooting for astronomical returns, but if I can edge towards a 15% return a year, by taking an automated portfolio approach to investing that reduces risk and dreaded drawdowns then hip-hip-horrah! I don't plan to reinvent the wheel even, as 1invest pointed out QuantPedia is a great resource that's done most of the legwork for you in identifying tried and tested strategies. Along the way I hope to develop my python programming skills, better understand the whole algorithmic trading life cycle and finally get read and maybe put to good use a ton of trading and investing books I've picked up over the years.
Anyway, wanted to give a quick update, on progress in the last 3 weeks. So, it feels like it's been a bit all over the place, which probably reflects a) the fact that there's a ton of stuff to learn, b) there's no clear path to learn it, and c) we're all different, and we learn in different ways. Knowing myself I like to take a scattergun approach, which I need to be careful about, as I like to learn by touching multiple sources, but you can quickly become overwhelmed, so it's almost a psychological battle to feel like you're progressing at a rate, that keeps things interesting, makes you feel like you're progressing, whilst not quickly realising how much effort it's going to take.
I've come to the conclusion, that I only really need to know at this stage the basics of Python, and libraries like Numpy, Pandas, Matplotlib in order to feel comfortable reading algorithmic trading code. More important is choosing a path to the end goal which is live trading. Right now, I'm feeling good about using Zipline (open source Quantopian backtesting engine) running on QuantRocket on a cloud server, probably AWS. So my goal at the moment is to get my head around a few things 1) Quantopian/Zipline, meaning things like their Pipeline/Algorithm APIs primarily, as well as Pyfolio and Alphalens - these are all available on Zipline. To get off the ground I think it's helpful to start playing around with Quantopian, as you can immediately start coding and see the results, without worrying about configuring a local installation or getting the data you need. Then I plan to start playing around more Zipline to better understand the differences. 2) Trading Evolved book - my choice of Zipline has a lot to do with the fact that Clenow has chosen it for his book, so I plan to attempt to some of the strategies there up and running on Zipline myself, finally 3) QuantRocket - once I've got them running on my own local Zipline environment, I'll try moving these over to QuantRocket and attempt to live trade them with a paper trading account on IB (which I already have set up).
Before I got to this point, I was spending most of my time on Python learning, through a few sources:
- DataCamp
- SoloLearn
- Real Python ebook
- Various Printed Python Books I've accumulated over the years
I also started learning Flask (as a lightweight web framework) my thinking being to improve my Python I really need to get into a project that's going to interest me. Perhaps coding up a contest on T2W, as I know they're popular, but I quickly realised the time invested in that would right now be better served getting me nearer my immediate goals listed above, so give time is always a constraint, I'll put that on hold for now - but would live to come back to providing some tools or contests on T2W in due course.
