Click here to see the full blog post. It has many of the same features Zipline does, and provides live trading. I can confirm that backtrader is by far the best option compared to zipline, and quantconnect. It's from some of same developers that brought us the excellent Pandas data analysis library. My main focus would be custom indicators for experimentation and given the lack of answers I went on looking for examples and I found one implementing the ATR with an SMA in Quantopian: From: https://www.quantopian.com/posts/custom-factor-kaufmans-efficiency-ratio. All my of my algotrading code is written by me. The biggest challenge for us, in my mind, is making it easy for people to get their data into Zipline. It is better to understand your system inside and out and it also allows for much more customization. Custom minutely data from pandas is currently broken, but it's being actively worked on, and there's a documented on-disk format that Zipline can read efficiently without having to pull everything into memory (this is the point where I'd agree that things are more cumbersome than they probably could be). if you need to go even further, I would suggest that you apply your strategy in python and backtest it using any backtesting framework such as backtrader or zipline (i would go with backtrader) as it is easier to learn and to apply. I guess it's a matter of taste. (5) BackTrader: Feel free to submit papers/links of things you find interesting. Quantopian/Zipline. Press J to jump to the feed. I'm curious to hear what makes it feel cumbersome to your taste. After doing the same research, I ended up building my own. This is actually the same scheme which one of the Quant firms (which I personally visited) used: prototyping in backtrader and production in Java. Let’s explain some of the magic: Upon init being called the strategy already has a list of datas that are present in the platform. A popular choice when it comes to interactive IDE’s is Jupyter Notebook. Backtrader is good but a bit too simple for me (generally geared towards indicator-based strategies), though one can circumvent this. Python serves as an excellent choice for automated trading when the trading frequency is low/medium, i.e. (5) BackTrader: (zipline added this a month ago) i have been looking at zipline, pyalgotrader, backtrader for python based environments. It has multiple APIs/Libraries that can be linked to make it optimal, cheaper and allow greater exploratory dev… once you are there, basket your strategies and optimize them in backtrader for the best variables (weight). backtrader vs zipline. Backtrader Plotting & Visualization. Quantopian provides a free, online backtesting engine where participants can be paid for their work through license agreements. Canonical vs Non Canonical Buy and Hold Momentum Strategy 2018 2018 Improving Code Dynamic Indicators Stop-Loss Trading Recursive Indicators 2017 2017 Down Jones 10 Day Streak Order History Renko Bricks Fund Tracking Release 1.9.51.121 Strategy Selection - Revisited Timers It has many of the same features Zipline does, and provides live trading. backtrader‘s closest Python “competitor”, zipline, advertises its strong pandas support (though Mr. Kipnis believes it is inferior to quantstrat and looking though the documentation it has not bedazzled me to the extent backtrader has). Looking at the closed issues it will not integrate ta-lib (this may not be a real issue given the ease of developing indicators). The other challenge is live execution if/when you decide you want to actually trade your strategy. Summary of Zipline vs PyAlgoTrade Python Backtesting Libraries. 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