Metadata-Version: 2.1
Name: stock-pairs-trading
Version: 0.1.0
Summary: stock-pairs-trading is a python library         for backtest with stock pairs trading using kalman filter on Python 3.8 and above.
Home-page: https://github.com/10mohi6/stock-pairs-trading-python
Author: 10mohi6
Author-email: 10.mohi.6.y@gmail.com
License: MIT
Keywords: pairs trading python backtest stock kalman filter
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Operating System :: OS Independent
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8.0
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: yfinance
Requires-Dist: matplotlib
Requires-Dist: statsmodels
Requires-Dist: pykalman
Requires-Dist: seaborn

# stock-pairs-trading

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stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.

## Installation

    $ pip install stock-pairs-trading

## Usage

### find pairs
```python
from stock_pairs_trading import StockPairsTrading

spt = StockPairsTrading(
    start="2007-12-01",
    end="2017-12-01",
)
r = spt.find_pairs(["AAPL", "ADBE", "MSFT", "IBM"])
print(r)
```
```python
[('ADBE', 'MSFT')]
```
![pairs.png](https://raw.githubusercontent.com/10mohi6/stock-pairs-trading-python/main/tests/pairs.png)

### backtest
```python
from pprint import pprint
from stock_pairs_trading import StockPairsTrading

spt = StockPairsTrading(
    start="2007-12-01",
    end="2017-12-01",
)
r = spt.backtest(('ADBE', 'MSFT'))
pprint(r)
```
```python
{'cointegration': 0.0018311528816901195,
 'correlation': 0.9858057442729853,
 'maximum_drawdown': 34.801876068115234,
 'profit_factor': 1.1214715644744209,
 'riskreward_ratio': 0.8095390763424627,
 'sharpe_ratio': 0.03606830691295276,
 'total_profit': 35.97085762023926,
 'total_trades': 520,
 'win_rate': 0.5807692307692308}
```
![performance.png](https://raw.githubusercontent.com/10mohi6/stock-pairs-trading-python/main/tests/performance.png)

### latest signal
```python
from pprint import pprint
from stock_pairs_trading import StockPairsTrading

spt = StockPairsTrading(
    start="2007-12-01",
    end="2017-12-01",
)
r = spt.latest_signal(("ADBE", "MSFT"))
pprint(r)
```
```python
{'ADBE Adj Close': 299.5,
 'ADBE Buy': True, # entry buy
 'ADBE Cover': False, # exit buy
 'ADBE Sell': False, # entry sell
 'ADBE Short': False, # exit sell
 'MSFT Adj Close': 244.74000549316406,
 'MSFT Buy': False, # entry buy
 'MSFT Cover': False, # exit buy
 'MSFT Sell': True, # entry sell
 'MSFT Short': False, # exit sell
 'date': '2022-09-16',
 'zscore': -36.830427514962274}
```
## Advanced Usage
```python
from stock_pairs_trading import StockPairsTrading

spt = StockPairsTrading(
    start="2007-12-01",
    end="2017-12-01",
    outputs_dir_path = "outputs",
    data_dir_path = "data",
    column = "Adj Close",
    window = 1,
    transition_covariance = 0.01,
)
r = spt.backtest(('ADBE', 'MSFT'))
pprint(r)
```
