Metadata-Version: 2.4
Name: timeseries_performance_calculator
Version: 0.3.11
Summary: A Python package for calculating and analyzing time series performance metrics
Author: June Young Park
Author-email: juneyoungpaak@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Office/Business :: Financial
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: universal_timeseries_transformer>=0.3.7
Requires-Dist: string_date_controller>=0.3.0
Requires-Dist: canonical_transformer>=1.0.5
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Time Series Performance Calculator

A Python package for calculating and analyzing time series performance metrics for financial data.

## Features

- Calculate annualized returns (CAGR method and days-based method)
- Generate monthly returns tables
- Create monthly cumulative returns tables
- Calculate relative performance against benchmarks
- Compute maximum drawdown metrics
- Calculate annualized volatility
- Generate performance tables with customizable formatting options

## Installation

```bash
pip install timeseries-performance-calculator
```

Or install from source:

```bash
git clone https://github.com/nailen1/timeseries-performance-calculator.git
cd timeseries-performance-calculator
pip install -e .
```

## Usage

```python
# Code examples will be updated in future releases.
# Detailed usage examples and documentation will be provided in upcoming versions.
```

> **Note**: This package is currently under development. More detailed usage examples and documentation will be provided in future updates.

## Dependencies

- fund_insight_engine
- universal_timeseries_transformer
- string_date_controller
- canonical_transformer

## License

MIT

## Author

June Young Park (juneyoungpaak@gmail.com)
