backtrader
backtesting.py
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backtrader | backtesting.py | |
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32 | 25 | |
12,922 | 4,797 | |
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2.7 | 0.0 | |
19 days ago | 22 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU Affero General Public License v3.0 |
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backtrader
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[HIRING] Develop template code for crypto backtesting using backtrader
You need to create a template code using https://github.com/mementum/backtrader. 1. Get the 1m candlestick data from binance for a period of 1 month for two symbols and store it in a data folder with data for each day and symbol in a different csv file. Read data for the symbols BTC & ETH. 2. Read the data for 1 month in python and put it in a dataframe for each symbol. 3. Import backtrader and feed data for these two symbols. 4. Create a basic strategy to check the ratio of prices and take trades accordingly. 5. Get the results using library. I am not much interested in the trading logic, just want to get the system to backtest up. It's a straightforward task for someone who has used backtrader before or 30-min job to read the documentation and do it. Project compensation : 5$ Can transfer directly to your binance account.
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What backtest data would you say is more accurate.
For this reason I think it's important to have a deep understanding of exactly how the backtesting engine that you are using works. Building your own backtesting engine is the absolute best way to gain this understanding. That is the path I personally chose and I don't regret it! However, that is also a very difficult and time consuming undertaking. So the next best thing is using something that is open source and has a good reputation like backtrader (https://www.backtrader.com/).
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Backtesting Engines for Testing Intraday Data on Thousands of Symbols Simultaneously
However, if you decide to go down the more well-trodden path of using open source backtesting frameworks then I personally would recommend backtrader (https://www.backtrader.com/). As far as I can tell, it has pretty much all the same features as my own system. The only difference is speed. My backtester is an order of magnitude faster and scales much better to testing thousands of symbols simultaneously. However, for 99% of retail algo traders this will be completely irrelevant.
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Algo Trading for SQQQ/TQQQ
You are welcome to go to discord or any other place. Your question wasn't very clear and thus I made that comment. Now, you still haven't made it clear so I am going to assume that you are looking for someone to "share a bot" that can trade your strategy. It doesn't work that way with algo trading. You code your "bot" to do things for you - The easiest way to start would be to look at backtrader but you will still have to code your own strategy in.
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Quantconnect Rant
I mean, some random dude managed to pull a platform with more basic functionalities than that. Sadly that repo is dead and the live trading implementation no longer works
- Do you use automated trading software or nah?
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Python library to retrieve data from TradingView
I've been working on a Python library which lets the user retrieve data from TradingView.com so it could be used in backtesting a strategy. The project is called TvDatafeedLive and is available on GitHub. To be fair, the project is actually an extension of a project called TvDatafeed, which is a really good project, but only supports retrieving historic data (so far). So, I've taken the liberty to fork it and implement retrieving data continously and "real-time". The data is retrieved in Pandas DataFrames and can easily be plugged into backtrader. There is instructions included in the GitHub page. If this sounds interesting then please check it out and leave feedback if there are any thoughts.
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Historical Trading to Prove/Disprove Plan
If you are a python programmer there is backtrader.
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Backtesting tools
For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer
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Algo Trading Environments
Backtrader can also do live trading afaik.
backtesting.py
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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?
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Bot development best practices for making backtesting easier?
I'm leaning towards using the backtesting.py library, but from the example on their main page, it looks like you need to program your strategy using their library?
What are some alternatives?
zipline - Zipline, a Pythonic Algorithmic Trading Library
vectorbt - Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
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ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
lumibot - Backtesting and Trading Bots Made Easy for Crypto, Stocks, Options, Futures, FOREX and more
pyfolio-reloaded - Portfolio and risk analytics in Python
gym-anytrading - The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
zipline-reloaded - Zipline, a Pythonic Algorithmic Trading Library
blankly - 🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.