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Vectorbt Alternatives
Similar projects and alternatives to vectorbt
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backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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fast-trade
low code backtesting library utilizing pandas and technical analysis indicators
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Alpaca-API
The Alpaca API is a developer interface for trading operations and market data reception through the Alpaca platform.
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Onboard AI
Learn any GitHub repo in 59 seconds. Onboard AI learns any GitHub repo in minutes and lets you chat with it to locate functionality, understand different parts, and generate new code. Use it for free at www.getonboard.dev.
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ccxt
A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
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Wizardry
💫 Wizardry is an open-source CLI for building powerful algorithmic trading strategies 交易框架 (by ssantoshp)
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finance
This project facilitates trying different buy and sell strategies for stock and crypto currencies. There are also scripts that provide different types of security analysis. Both technical analysis and fundamental analysis are considered. (by eContriver)
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aat
Asynchronous, event-driven algorithmic trading in Python and C++ (by AsyncAlgoTrading)
vectorbt reviews and mentions
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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.
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Stats
polakowo/vectorbt is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of vectorbt is Python.