Metadata-Version: 2.4
Name: simplifi
Version: 1.0.1
Summary: Class for Black-Scholes option pricing and Greeks calculation with real-time data integration.
Author-email: Steven McWilliams <skmcwilliams@protonmail.com>
License-Expression: GPL-3.0-or-later
Project-URL: Homepage, https://github.com/skmcwilliams/simplifi
Project-URL: Issues, https://github.com/skmcwilliams/simplifi/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.23
Requires-Dist: pandas>=1.5
Requires-Dist: scipy>=1.10
Requires-Dist: plotly>=5.0
Requires-Dist: yahooquery>=2.2
Requires-Dist: requests>=2.28
Requires-Dist: beautifulsoup4>=4.11
Dynamic: license-file

# Simplifi

A comprehensive Python library for financial analysis and stock market data visualization. This library combines data from multiple sources including Yahoo Finance and Finviz to provide a rich set of financial analysis tools.

## Features

- **Historical Data Analysis**
  - Fetch and process 30-day historical data
  - Calculate average prices and logarithmic returns
  - Generate OHLC (Open-High-Low-Close) candlestick charts with volume

- **Options Analysis**
  - Black-Scholes option pricing model implementation
  - Options chain analysis

- **Dividend Discount Model**
  - Fetch stock valuation based on DDM calculations
  - Cost of Equity calculations
  - Risk-free rate analysis based on 10yr Treasury

## Installation

```bash
pip install simplifi
```

## Usage

### Basic Usage

```python
from simplifi import Simplifi

# Create an instance for a specific stock
stock = Simplifi('AAPL')

# Get historical data
historical_data_df = stock.get_historical_data()

# Get Black-Scholes option valuations
options_analysis_df = stock.blackscholes()

```

### Advanced Features

#### OHLC Chart Generation
```python
# Get historical data with OHLC chart
historical_data_df = stock.get_historical_data(make_ohlc=True)
```

Example OHLC chart output:

![OHLC Chart Example](chart.png)

#### Dividend Discount Model Valuation
```python
# Calculate stock valuation using DDM
ddm_valuation = stock.ddm_valuation()
```

## Dependencies

- numpy
- pandas
- plotly
- yahooquery
- beautifulsoup4
- requests
- scipy

## Data Sources
- Yahoo Finance (via yahooquery)

## Notes
- Features require internet connection for real-time data
- OHLC charts include 50-day and 200-day moving averages
- Black-Scholes calculations use the current 10-year Treasury rate as the risk-free rate

## License

See the LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
