vectorbt
fast-trade
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vectorbt | fast-trade | |
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5 | 12 | |
3,660 | 334 | |
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6.0 | 3.7 | |
about 1 month ago | 1 day ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
vectorbt
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Is there any python libraries to backtest buy and sell signals with dates?
For exactly this I use this https://github.com/polakowo/vectorbt it’s really a powerful tool and you can tons of things with it. Recently the developer decided to maintain it but not adding new features, which from now on will be released on the pro version. However, the free version is still very valuable, incredibly fast and suitable for basic to intermediate tasks.
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Why Building a Trading Algorithm is More Than Just the Algorithm - 3 Things
It’s super easy to get up and running with code. With the rise of data science as a field, datasets are far and wide. Accessible from just about any venue. Take a look at Kaggle, QuiverQuant, Yahoo Finance, or even directly from the brokerages and exchanges. Developers can easily download data directly as a .csv or .json and quickly get up and running by utilizing frameworks like backtesting.py or vectorbt. “Great, it seems like I can get up and running and I’ll have an awesome money making trading algorithm in no time”.... unfortunately, wrong. Why is this wrong? Well, simulation is NOT the real world. The real world is not a CSV file—the real world is a stream of events. Cause and effect. The real world works in a fashion where new data comes in, you make a decision, and then you figure it out, not “I have all of this data, let me run this all through time and figure it out”. Indeed, the data sources that you get in real-time are almost completely different from the data sources you use in simulation. Rather than .csv you use WebSockets; rather than QuiverQuant you use APIs; rather than backtesting frameworks you use more robust, event driven packages. Without it, you’re stuck duplicating code, rewriting it into an event-based system, and ultimately using that to go into production, and who knows if your code is going to change along the way.
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Looking for active python backtesting framework
However, it's not the fastest framework. If you need speed, and are good with the data science tool chain in python and the concept of flattening loops into vectorized operations, check out vector-bt. I haven't gotten a chance to play with it yet, but I'm definitely going to as soon as I find some spare time. It seems like a great option with a nicely modernized approach.
fast-trade
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Important python libraries?
I'm also going to shamelessly plug fast-trade, which is a backtesting library where you write strategies as objects instead of actual code. It's also built on a couple of pretty wonderful libraries including pandas and FinTa, which has a lot of indicators and it's really simple to use.
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Custom forex backtester
I wrote fast-trade to answer exactly questions like this
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What do they use to manage the tick data?
For ohlcv data,I wrote fast-trade with a data downloader. Basically it pulls 1 minute Kline data from Binance. It’s pretty easy to keep up to date. It works well for managing a local cache for backtesting.
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Best Python libraries for backtesting and algo trading
Hey! Yup, here you go: https://fasttrade.dev. Here's the script I use to do it: https://github.com/jrmeier/fast-trade/blob/master/fast_trade/update_symbol_data.py. I also have a discord with some people that are also doing trading stuff (I’m also building a platform around this stuff). Let me know if you would like an invite!
I’m working on fast-trade. It’s small, simple library you can set up technical analysis with for live trading and backtesting.
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How to start developing your own backtester
You can start with fast-trade if you’d like. It’s a pretty simple backtesting engine but you can modify it however you’d like. Full disclosure I made it but I was trying to figure out how to get started as well and this is what I ended up with. Good luck!
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Backtesting tool for python binance
I wrote fast-trade to do exactly that. Funny enough I wrote it for Binance but it works with any Kline data.
- An awesome list about crypto trading bots : find open source crypto trading bots, technical analysis and market data libraries, data providers, APIs, ...
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Looking for active python backtesting framework
I wrote fast-trade, you can use it from the command line or a script. Strategies are in JSON, so it’s easy to iterate.
What are some alternatives?
backtrader - Python Backtesting library for trading strategies
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
jesse - An advanced crypto trading bot written in Python
zipline - Zipline, a Pythonic Algorithmic Trading Library
quantstats - Portfolio analytics for quants, written in Python
OctoBot - Open source crypto trading bot
python-binance - Binance Exchange API python implementation for automated trading
Alpaca-API - The Alpaca API is a developer interface for trading operations and market data reception through the Alpaca platform.
Wizardry - 💫 Wizardry is an open-source CLI for building powerful algorithmic trading strategies 交易框架
ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
finta - Common financial technical indicators implemented in Pandas.