openseries Documentation

openseries is a Python library for analyzing financial time series data. It provides tools to work with single assets or groups of assets, designed specifically for daily or less frequent data.

The library is built around two main classes:

OpenTimeSeries: For managing and analyzing individual time series
OpenFrame: For managing groups of time series and portfolio analysis

Key Features

Financial Analysis: Comprehensive set of financial metrics and ratios
Risk Management: VaR, CVaR, drawdown analysis, and risk-adjusted returns
Portfolio Tools: Portfolio optimization, rebalancing, and performance attribution
Visualization: Interactive plots using Plotly
Data Handling: Robust date handling and business day calendars
Type Safety: Built with Pydantic for data validation and type safety

Quick Start

Install openseries using pip:

pip install openseries

Or using conda:

conda install -c conda-forge openseries

Here’s a simple example to get you started:

from openseries import OpenTimeSeries
import yfinance as yf

# Download data
ticker = yf.Ticker("^GSPC")
history = ticker.history(period="5y")

# Create OpenTimeSeries
series = OpenTimeSeries.from_df(dframe=history.loc[:, "Close"])
series.set_new_label(lvl_zero="S&P 500")

# Calculate key metrics
print(f"Annual Return: {series.geo_ret:.2%}")
print(f"Volatility: {series.vol:.2%}")
print(f"Sharpe Ratio: {series.ret_vol_ratio:.2f}")
print(f"Max Drawdown: {series.max_drawdown:.2%}")

# Create interactive plot
series.plot_series()

Documentation Contents

User Guide

Tutorials

Examples

Important Notes

API Consistency Notes

openseries Documentation

Key Features

Quick Start

Documentation Contents

Python Version Support

Indices and tables