Skip to main content

A Python package for calculating and analyzing time series performance metrics

Project description

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

pip install timeseries-performance-calculator

Or install from source:

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

Usage

# 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)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

timeseries_performance_calculator-0.2.2.tar.gz (11.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file timeseries_performance_calculator-0.2.2.tar.gz.

File metadata

File hashes

Hashes for timeseries_performance_calculator-0.2.2.tar.gz
Algorithm Hash digest
SHA256 b8e8d7a56a5bfb5b20195ba73d97eb99dcfbbfbb140980886f17eece22731760
MD5 39a518f3ec4c7346f3f3f65968b2ff21
BLAKE2b-256 dfc349c7d7935c1a90c73e1c46bcea9b3f21b5d1f73f0725f81c27e9149dac8f

See more details on using hashes here.

File details

Details for the file timeseries_performance_calculator-0.2.2-py3-none-any.whl.

File metadata

File hashes

Hashes for timeseries_performance_calculator-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 b8afef6b7c2f2c8680ed9e60f2a9aba0cf8dc43b82de668a66e104f5789f3cc7
MD5 5cd94d53311d1220bbf7c43f3194a10b
BLAKE2b-256 4e748625722a283fe67d08394f2fb6ce0149db4d64ebceb6933c44b04edb5030

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page