Metadata-Version: 2.4
Name: quantmod
Version: 0.1.5
Summary: Quantitative finance toolkit for Python — markets, options, risk, and time series
Project-URL: Homepage, https://docs.kannansingaravelu.com
Project-URL: Repository, https://github.com/kannansingaravelu/quantmod
Project-URL: Documentation, https://docs.kannansingaravelu.com
Author-email: Kannan Singaravelu <inquant@outlook.com>
License: Apache-2.0
License-File: LICENSE.txt
Keywords: finance,options,quant,quantmod,risk,timeseries
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.10
Requires-Dist: joblib
Requires-Dist: matplotlib
Requires-Dist: nbformat>=5.10.4
Requires-Dist: numpy>=2.0.2
Requires-Dist: pandas>=2.2.2
Requires-Dist: plotly>=6.1.2
Requires-Dist: pydantic>=2.8.2
Requires-Dist: scipy>=1.13.1
Requires-Dist: sqlalchemy>=2.0.38
Requires-Dist: supabase>=2.27.2
Requires-Dist: tabulate>=0.9.0
Requires-Dist: urllib3==1.26.15
Requires-Dist: yfinance>=1.0
Description-Content-Type: text/markdown

quantmod is a Python library for market data access, quantitative analysis, and financial modeling. It provides a unified framework to move seamlessly from data ingestion to derivatives analytics, pricing, risk analysis, and visualization.

## Installation

Install quantmod using pip:

```bash
pip install quantmod
```

Or, using uv:

```bash
uv add quantmod
```

## Modules

### Data & Markets

- [datasets](https://docs.kannansingaravelu.com/datasets/)
- [database](https://docs.kannansingaravelu.com/db/)
- [markets](https://docs.kannansingaravelu.com/markets/)
- [derivatives](https://docs.kannansingaravelu.com/derivatives/)

### Quant & Analytics

- [charts](https://docs.kannansingaravelu.com/charts/)
- [models](https://docs.kannansingaravelu.com/models/)
- [risk](https://docs.kannansingaravelu.com/risk/)
- [indicators](https://docs.kannansingaravelu.com/indicators/)
- [timeseries](https://docs.kannansingaravelu.com/timeseries/)

## Quickstart

```py
# Market data
from quantmod.markets import getData, getTicker

# Visualization
import quantmod.charts

# Option pricing models
from quantmod.models import (
    OptionInputs,
    Black76,
    BlackScholes,
    MonteCarloOptionPricing
)

# Risk measures
from quantmod.risk import (
    RiskInputs,
    ValueAtRisk,
    ConditionalVaR,
    VarBacktester
)

# Time series utilities
from quantmod.timeseries import *

# Technical indicators
from quantmod.indicators import ATR

# Derivatives (option chain analytics)
from quantmod.derivatives import maxpain

# Datasets
from quantmod.datasets import fetch_historical_data
```

<br>
Note: quantmod is currently under active development, and anticipate ongoing enhancements and additions. The aim is to continually improve the package and expand its capabilities to meet the evolving needs of the community.

## Examples

Refer to the [examples](https://docs.kannansingaravelu.com/examples/) section for detailed use cases and workflows.

## Changelog

See the full list of changes [here](https://docs.kannansingaravelu.com/changelog/)

## Legal

`quantmod` is distributed under the **Apache Software License**.  
See the [LICENSE](https://www.apache.org/licenses/LICENSE-2.0.txt) for details.
