backtrader
awesome-quant
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backtrader | awesome-quant | |
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32 | 18 | |
12,985 | 15,910 | |
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0.0 | 8.2 | |
9 days ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 only | - |
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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.
awesome-quant
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RustQuant: A Library for Quantitative Finance
No, it looks more like a Rust equivalent of libraries like ffn (financial functions for python) or many of the other ones listed here https://github.com/wilsonfreitas/awesome-quant
Using rust to do exploratory analysis in python seems like a misguided idea. But using rust to productize models that have performance and accuracy sensitivities, the things that C/C++ is still used for, indeed sounds like a good idea.
Most of the python libraries used in finance, like numpy/pandas, call out to C for performance reasons; the libraries are essentially python bindings + syntax to C functions. It would be interesting to think about replacing that backend with rust.
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Open Source Projects
This is a good list https://github.com/wilsonfreitas/awesome-quant
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I’m not a Quant, but a Headhunter - ask me anything
also, what are the best quanty python packages that you like to see an applicant use? there are so many. https://github.com/wilsonfreitas/awesome-quant
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Why building profitable trading bot is hard?
If the financial analyst does not have a (possibly piecewise) software function to at least test with backtesting and paper trading, do they even have an objective relative performance statistic? Your notebook or better should also model fees and have a parametrizable initial balance.
Here's the awesome-quant link directory: https://github.com/wilsonfreitas/awesome-quant
- For Traders Who Want To Be Quants
- A curated list of libraries, packages and resources for Quants
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Hacker News top posts: Feb 22, 2022
A curated list of libraries, packages and resources for Quants\ (0 comments)
What are some alternatives?
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
zipline - Zipline, a Pythonic Algorithmic Trading Library
uniswap-sushiswap-arbitrage-bot - Two bots written in JS that uses flashswaps and normal swaps to arbitrage Uniswap. Includes an automated demostration.
vectorbt - Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
CUDA.jl - CUDA programming in Julia.
ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
awesome-discord-communities - A curated list of awesome Discord communities for programmers
fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Gekko-Strategies - Strategies to Gekko trading bot with backtests results and some useful tools.
pyfolio-reloaded - Portfolio and risk analytics in Python
WorldQuant_alpha101_code - Code implementation of the Quantigic 101 Formulaic Alphas