alphatools
fastquant
alphatools | fastquant | |
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7 | 2 | |
385 | 1,431 | |
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10.0 | 4.3 | |
over 1 year ago | 8 months ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | MIT License |
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alphatools
fastquant
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Launch HN: Coinrule (YC S21) – Automated Trading Made Easy
I would never trust a service like this, but at the same time, I'm curious on how to setup the opposite of their motto: "compete with professional algorithmic traders and hedge funds. coding required!".
Does Fidelity offer an API of some sort so that I can login with my normal credentials and buy/sell? I'm assuming the strategies being used here, like "Ride the Trend", are basically the same ones available here: https://github.com/enzoampil/fastquant
So, given that the previous statements are true, do I just need some Yahoo! Finance API + FastQuant and then MyBank API to autotrade for myself? What else would be involved?
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Backtesting in Python, recommendations please.
https://github.com/enzoampil/fastquant -sort of a wrapper for backtrader that makes it very easy to run backtests and design trade strategies.
What are some alternatives?
FinanceExamplesPy - Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir). [Moved to: https://github.com/mrtkp9993/QuantitaveFinanceExamplesPy]
backtrader - Python Backtesting library for trading strategies
gs-quant - Python toolkit for quantitative finance
market-making-backtest - algo trading backtesting on BitMEX
StockSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
FinanceOps - Research in investment finance with Python Notebooks
ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
coda - Mina is a new cryptocurrency with a constant size blockchain, improving scaling while maintaining decentralization and security. [Moved to: https://github.com/MinaProtocol/mina]
Mad-Money-Backtesting - Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"
backtesting_and_algotrading_options_with_Interactive_Brokers_API - backtesting and algotrading options using Interactive Brokers API (native python api)