Wizardry
vectorbt
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Wizardry | vectorbt | |
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2 | 5 | |
39 | 3,734 | |
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2.6 | 6.2 | |
almost 3 years ago | 10 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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Wizardry
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 itās 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
Itās 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. āGreat, it seems like I can get up and running and Iāll have an awesome money making trading algorithm in no timeā.... unfortunately, wrong. Why is this wrong? Well, simulation is NOT the real world. The real world is not a CSV fileāthe 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 āI have all of this data, let me run this all through time and figure it outā. 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, youāre 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.
- Vectorbt ā Find your trading edge
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Repost with explanation - OOS Testing cluster
I second the idea of looking through software optimization, but there is no need to jump right to C. I would look at something like vectorbt. You get the speed of C running under the hood while staying in Python for your back testing code
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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.
What are some alternatives?
Python-NSE-Option-Chain-Analyzer - The NSE has a website which displays the option chain in near real-time. This program retrieves this data from the NSE site and then generates useful analysis of the Option Chain for the specified Index or Stock. It also continuously refreshes the Option Chain and visually displays the trend in various indicators useful for Technical Analysis.
backtrader - Python Backtesting library for trading strategies
ta4j - A Java library for technical analysis.
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
gym-anytrading - The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
fast-trade - low code backtesting library utilizing pandas and technical analysis indicators
quantstats - Portfolio analytics for quants, written in Python
jesse - An advanced crypto trading bot written in Python
PyTrader-python-mt4-mt5-trading-api-connector-drag-n-drop - Open Source Trading Strategies & End-to-End solution connecting Metatrader4 & Metatrader5 š¹ with Python with a simple drag and drop EA. Fully tested bug free & efficient solution for live & paper tradingā Full Documentation ready. Lightweight, efficient and stable implementation š„ [UnavailableForLegalReasons - Repository access blocked]
zipline - Zipline, a Pythonic Algorithmic Trading Library
oanda - Implementation of OANDA's REST API in R. This project is an attepmt to bring research, backtest, trading, and monitoring using R wrapper around OANDA broker's HTTP API. Follow @oanda for their python bindings. [Moved to: https://github.com/ltekengineering/oanda]
OctoBot - Open source crypto trading bot