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Quool is a Python framework designed specifically for quantitative investment research. It aims to provide a flexible and efficient set of tools to help researchers and developers quickly implement data management, factor analysis, trading recording, and strategy evaluation functionalities. With Quool, users can focus on strategy and factor research without spending excessive time on data management and infrastructure setup.
Currently, the Quool framework is not available on PyPI. You can install it from the source code as follows:
git clone https://github.com/your-username/quool.git
cd quool
pip install .
Here are the basic steps to conduct factor research and strategy evaluation using Quool:
First, inherit the BaseFactor
class to define your own factor. For example, define a factor that calculates the Volume Weighted Average Price (VWAP):
from quool import BaseFactor
class VWAPFactor(BaseFactor):
def get_vwap(self, date: pd.Timestamp):
# Implement the calculation logic for VWAP
pass
Instantiate your factor class and use the get
method to calculate factor values for a specific date range:
vwap_factor = VWAPFactor(uri="./path/to/factor/data")
vwap_values = vwap_factor.get("vwap", start="2021-01-01", stop="2021-12-31")
Use the TradeRecorder
or other recorder classes to record your trading activities and use the evaluate
method to assess strategy performance:
from quool import TradeRecorder
# Record trading activities
trade_recorder = TradeRecorder(uri="./path/to/trade/data")
trade_recorder.record(date="2021-01-01", ...)
# Evaluate strategy performance
performance = trade_recorder.evaluate(...)
Contributions in the form of issue reports and pull requests are welcome on GitHub.
Quool is released under the MIT license.
FAQs
Quantitative Toolkit - a helper in quant developing
We found that quool demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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