A Python package to find and measure negative price shocks in financial time-series data
Sigmet (Signal Metrics Toolkit) is an end-to-end solution for the detection and measurement of negative shocks in time series data.
Sigmet requires the following packages:
- Pandas: primary data format for easy data manipulation and datetime functionality
- Numpy: for computation
- Statsmodels: AU3 uses statsmodel’s ARIMA and SARIMAX models for prediction
- Matplotlib: plotting for .graph() method
To install, run the following on the command line
pip install sigmet
First we instantiate an AU3 object
from sigmet import Sigmet data = pd.read_csv('time-series.csv') ex = Sigmet(start, end, data) ex.fit(window_start, window_end) # graph the result as follows import matplotlib.pyplot as plt fig, ax = plt.subplots() ax = ex.graph() plt.show()
- Issue Tracker: https://github.com/agupta01/sigmet/issues
- Source Code: https://github.com/agupta01/sigmet
The project is licensed under the GNU General Public License.
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