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python   PyPI Latest Release   Coverage Status MIT license   MIT license  

Okama Documentation

okama is a Python library for investment portfolio analysis and optimization. It applies concepts commonly used in quantitative finance.

okama provides access to free end-of-day historical market data and macroeconomic indicators through an API.

…entities should not be multiplied without necessity

– William of Ockham (c. 1287–1347)

Okama main features

  • Constrained Markowitz Mean-Variance Analysis (MVA) and portfolio optimization

  • Multi-period Efficient Frontier optimization with rebalancing constraints

  • Investment portfolios with contribution and withdrawal cash flows (DCF)

  • Monte Carlo simulations for financial assets and investment portfolios

  • Popular risk metrics: VaR, CVaR, semideviation, variance, and drawdowns

  • Forecasting models based on normal, lognormal, and Student’s t distributions

  • Distribution fitting and goodness-of-fit testing on historical data

  • Dividend yield and other dividend indicators for stocks

  • Backtesting and comparing the historical performance of a broad range of assets and indexes in multiple currencies

  • Methods for tracking the performance of index funds (ETFs) and comparing them with benchmarks

  • Main macroeconomic indicators: inflation, central bank rates, and financial ratios

  • Matplotlib visualizations for the Efficient Frontier, Transition Map, and asset risk/return performance

Financial data and macroeconomic indicators

okama can work with free financial data available through its API.

End of day historical data

  • Stocks and ETFs for major world markets

  • Mutual funds

  • Commodities

  • Currencies

  • Stock indexes

Macroeconomic indicators

For several countries, including the USA, the United Kingdom, the European Union, Russia, and Israel:

  • Inflation

  • Central bank rates

  • CAPE10 (Shiller P/E), or cyclically adjusted price-to-earnings ratios

Other historical data

  • Real estate prices

  • Top bank rates

Installation

Okama can be installed from PyPI:

pip install okama

The latest development version can be installed directly from GitHub:

git clone https://github.com/mbk-dev/okama@dev
poetry install

Warning

The development version of okama may have technical and financial issues. Use it carefully and at your own risk.

Quick Start

Index Funds Performance

Investment Portfolios

Main

Assets & Portfolio

okama.Asset([symbol, first_date, last_date])

A financial asset, that could be used in a list of assets or in portfolio.

okama.AssetList([assets, first_date, ...])

List of financial assets.

okama.Portfolio([assets, first_date, ...])

Investment portfolio.

okama.Rebalance([period, abs_deviation, ...])

Rebalancing strategy for an investment portfolio.

Cash Flows & DCF

okama.PortfolioDCF(parent[, discount_rate])

Discounted cash flow (DCF) methods for a Portfolio.

okama.MonteCarlo(parent[, distribution, ...])

Monte Carlo simulation parameters for an investment portfolio.

okama.IndexationStrategy(parent[, ...])

Cash flow strategy with regular indexed withdrawals or contributions.

okama.PercentageStrategy(parent[, ...])

Cash flow strategy with regular fixed percentage withdrawals or contributions.

okama.TimeSeriesStrategy(parent[, ...])

Cash flow strategy with user-defined withdrawals and contributions.

okama.VanguardDynamicSpending(parent[, ...])

Vanguard Dynamic Spending strategy.

okama.CutWithdrawalsIfDrawdown(parent[, ...])

Withdrawal strategy that reduces the withdrawal amount if the portfolio drawdown exceeds a certain threshold.

Efficient Frontier

okama.EfficientFrontier([assets, ...])

Efficient Frontier with multi-period optimization.

Macroeconomics

okama.Inflation([symbol, first_date, last_date])

Inflation related data and methods.

okama.Rate([symbol, first_date, last_date])

Rates of central banks and banks.

okama.Indicator([symbol, first_date, last_date])

Macroeconomic indicators and ratios.

Indices and tables