okama is a Python package developed for asset allocation and investment portfolio optimization tasks according to Modern Portfolio Theory (MPT).
The package is supplied with free «end of day» historical stock markets data and macroeconomic indicators through API.
...entities should not be multiplied without necessity
-- William of Ockham (c. 1287–1347)
- Investment portfolio constrained Markowitz Mean-Variance Analysis (MVA) and optimization
- Rebalanced portfolio optimization
- Monte Carlo Simulations for financial assets and investment portfolios
- Popular risk metrics: VAR, CVaR, semi-deviation, variance and drawdowns
- Forecasting models according to normal and lognormal distribution
- Testing distribution on historical data
- Dividend yield and other dividend indicators for stocks
- Backtesting and comparing historical performance of broad range of assets and indexes in multiple currencies
- Methods to track the performance of index funds (ETF) and compare them with benchmarks
- Main macroeconomic indicators: inflation, central banks rates
- Matplotlib visualization scripts for the Efficient Frontier, Transition map and assets risk / return performance
- Stocks and ETF for main world markets
- Mutual funds
- Commodities
- Currencies
- Stock indexes
- Inflation
- Central bank rates
- Real estate prices
- Top bank rates
pip install okama
import okama as ok
x = ok.AssetList(['SPY.US', 'BND.US', 'DBXD.XETR'], ccy='USD')
print(x)
Get the main parameters for the set:
x.describe(tickers=False)
Get the assets accumulated return, plot it and compare with the USD inflation:
x.wealth_indexes.plot()
weights = [0.3, 0.2, 0.2, 0.2, 0.1]
assets = ['T.US', 'XOM.US', 'FRE.XETR', 'SNW.XETR', 'LKOH.MOEX']
pf = ok.Portfolio(assets, weights=weights, ccy='EUR')
print(pf)
Plot the dividend yield for each group of assets (based on stock currency).
pf.dividend_yield.plot()
ls = ['SPY.US', 'GLD.US']
curr = 'USD'
frontier = ok.EfficientFrontierReb(ls, last_date='2020-10', ccy=curr, reb_period='year') # Rebalancing periods is one year (dafault value)
frontier.names
Get the Efficient Frontier points for rebalanced portfolios and plot the chart with the assets risk/CAGR points:
points = frontier.ef_points
fig = plt.figure(figsize=(12,6))
fig.subplots_adjust(bottom=0.2, top=1.5)
ok.Plots(ls, ccy=curr).plot_assets(kind='cagr') # plots the assets points on the chart
ax = plt.gca()
ax.plot(points.Risk, points.CAGR) 
* - rebalancing period is one year.
ls = ['SPY.US', 'GLD.US', 'BND.US']
map = ok.Plots(ls, ccy='USD').plot_transition_map(cagr=False)
More examples are available in Jupyter Notebooks.
For basic usage questions (e.g., "Is XXX currency supported by okama?") and for sharing ideas please use GitHub Discussions. Russian language community is available at okama.io forums.
We encourage you to report issues using the Github tracker. We welcome all kinds of issues, especially those related to correctness, documentation, performance, and feature requests.
All contributions, bug reports, bug fixes, documentation improvements, enhancements, frontend implementation and ideas are welcome.
MIT