Quantdom is a simple but powerful backtesting framework written in python, that strives to let you focus on modeling financial strategies, portfolio management, and analyzing backtests. It has been created as a useful and flexible tool to save the systematic trading community from re-inventing the wheel and let them evaluate their trading ideas easier with minimal effort. It's designed for people who are already comfortable with Python and who want to create, test and explore their own trading strategies.
Quantdom is in an early alpha state at the moment. So please be patient with possible errors and report them.
- Free, open-source and cross-platform backtesting framework
- Multiple data feeds: csv files and online sources such as Google Finance, Yahoo Finance, Quandl and more
- Investment Analysis (performance and risk analysis of financial portfolio)
- Charting and reporting that help visualize backtest results
- Python 3.6 or higher
- PyQt5
- PyQtGraph
- NumPy
- See pyproject.toml for full details.
You can download binary packages for your system (see the Github Releases page for available downloads):
You can install last stable release from pypi:
$ pip install quantdomAnd latest development version can be installed directly from GitHub:
$ pip install -U git+https://github.com/constverum/Quantdom.gitAfter that, to run the application just execute one command:
$ quantdom- Run Quantdom.
- Choose a market instrument (symbol) for backtesting on the
Datatab. - Specify a file with your strategies on the
Quotestab, and select one of them. - Run a backtest. Once this is done, you can analyze the results and optimize parameters of the strategy.
A simple trading strategy based on the assumption that after three consecutive bullish bars (bar closing occurred higher than its opening) bulls predominate in the market and therefore the price will continue to grow; after 3 consecutive bearish bars (the bar closes lower than its opening), the price will continue to down, since bears predominate in the market.
from quantdom import AbstractStrategy, Order, Portfolio
class ThreeBarStrategy(AbstractStrategy):
def init(self, high_bars=3, low_bars=3):
Portfolio.initial_balance = 100000 # default value
self.seq_low_bars = 0
self.seq_high_bars = 0
self.signal = None
self.last_position = None
self.volume = 100 # shares
self.high_bars = high_bars
self.low_bars = low_bars
def handle(self, quote):
if self.signal:
props = {
'symbol': self.symbol, # current selected symbol
'otype': self.signal,
'price': quote.open,
'volume': self.volume,
'time': quote.time,
}
if not self.last_position:
self.last_position = Order.open(**props)
elif self.last_position.type != self.signal:
Order.close(self.last_position, price=quote.open, time=quote.time)
self.last_position = Order.open(**props)
self.signal = False
self.seq_high_bars = self.seq_low_bars = 0
if quote.close > quote.open:
self.seq_high_bars += 1
self.seq_low_bars = 0
else:
self.seq_high_bars = 0
self.seq_low_bars += 1
if self.seq_high_bars == self.high_bars:
self.signal = Order.BUY
elif self.seq_low_bars == self.low_bars:
self.signal = Order.SELLIn progress ;)
- Add integration with TA-Lib
- Add the ability to use TensorFlow/CatBoost/Scikit-Learn and other ML tools to create incredible algorithms and strategies. Just as one of the first tasks is Elliott Wave Theory(Principle) - to recognize of current wave and on the basis of this predict price movement at confidence intervals
- Add the ability to make a sentiment analysis from different sources (news, tweets, etc)
- Add ability to create custom screens, ranking functions, reports
- Fork it: https://github.com/constverum/Quantdom/fork
- Create your feature branch: git checkout -b my-new-feature
- Commit your changes: git commit -am 'Add some feature'
- Push to the branch: git push origin my-new-feature
- Submit a pull request!
This software should not be used as a financial advisor, it is for educational use only. Absolutely no warranty is implied with this product. By using this software you release the author(s) from any liability regarding the use of this software. You can lose money because this program probably has some errors in it, so use it at your own risk. And please don't take risks with money you can't afford to lose.
I'm very interested in your experience with Quantdom. Please feel free to send me any feedback, ideas, enhancement requests or anything else.
Licensed under the Apache License, Version 2.0
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