algotrading
backtesting.py
algotrading | backtesting.py | |
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33 | 26 | |
1,089 | 5,413 | |
- | - | |
3.4 | 0.0 | |
3 months ago | 2 months ago | |
Python | Python | |
MIT License | GNU Affero General Public License v3.0 |
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algotrading
backtesting.py
- Show HN: High-Frequency Trading and Market-Making Backtesting Tool with Examples
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Python developers -- what broker and api do you use?
We chose backtesting.py for a backtesting framework. There are several to choose from but that one seems like the most well-supported and actively worked on at the moment.
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How do you backtest with IBKR Data?
The process might vary a bit based on what you want to trade, but I've had some success with back-testing by using the IBKR API to download historical data for the stocks I want, then plugging in that data to some other back-testing framework, like https://kernc.github.io/backtesting.py/
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Anyone here built backtest/alpha visualization/exploration dashboard(s)?
https://kernc.github.io/backtesting.py/ offers nice way to zoom backtesting. It has some bugs, but good for visualization.
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What platform do you use to backtest historical millisecond tick data?
Are there any free trading platform options to import and backtest millisecond historical tick data? Do you use something like https://github.com/kernc/backtesting.py and then translate algorithms into mql4/5 or pinescript?
- GitHub - kernc/backtesting.py: Backtest trading strategies in Python.
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Where/how do I “import backtesting” and other programs? TY!
But even if you don't know that, you can Google the library to find its documentation and installation instructions - in this case, here where it does indeed tell you to run pip install backtesting.
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What are your 2022 success stories? It's been a long year. You deserve to brag.
Sure. My strategy is actually very simple using common indicators like MACD and RSI. Most of the code is actually based on https://github.com/kernc/backtesting.py and I use it to check whether I should buy or sell on a particular day. Hope this helps!
- Backtesting.py - interpreting the generated chart
- How hard would this be?
What are some alternatives?
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