VOL. XCIV, NO. 247
★ FINANCIAL TOOLS & SERVICES DIRECTORY ★
PRICE: 5 CENTS
Saturday, September 27, 2025
Investors comparing okama and PortfoliosLab will find that Both okama and PortfoliosLab concentrate on Quant, Portfolio, and Correlation workflows, making them natural alternatives for similar investment research jobs. okama leans into Data Visualizations, Monte Carlo, and Data APIs, which can be decisive for teams that need depth over breadth. PortfoliosLab stands out with Screeners, ETF Screeners, and Watchlist that the competition lacks. Use the feature-by-feature table to inspect unique capabilities and confirm which roadmap best maps to your process.
Head-to-head
okama vs PortfoliosLab
Compare pricing, supported platforms, categories, and standout capabilities to decide which tool fits your workflow.
Quick takeaways
- okama adds Data Visualizations, Monte Carlo, Data APIs, ETF Performance, Inflation Rates, and Interest Rates coverage that PortfoliosLab skips.
- PortfoliosLab includes Screeners, ETF Screeners, Watchlist, Stock Comparison, ETF Comparison, Factor Exposure, Financials, and APIs & SDKs categories that okama omits.
- okama highlights: Interactive Efficient Frontier (mean–variance) widget for quick visualization., Compare-assets widget covering returns, drawdowns, CVaR, and correlations., and Portfolio widget built on adjusted monthly data for risk/return analysis..
- PortfoliosLab is known for: Portfolio analytics and backtesting with benchmarking, monthly returns, and risk-adjusted ratios such as Sharpe, Sortino, Omega, Calmar, and Martin., Optimization models include Mean–Variance (MVO), Risk Parity, and Hierarchical Risk Parity (HRP), with the ability to backtest from a chosen optimization date., and Risk analytics cover drawdowns, Value at Risk (VaR), Expected Shortfall (CVaR), and multiple volatility estimators..
okama
okama.io
Free open-source toolkit for portfolio analysis and market data. Okama offers web widgets, an API, and a Python library with efficient frontiers, risk metrics, and Monte Carlo simulations. Market and macro data is available end-of-day, with live prices delayed by ~15–20 minutes.
Categories
Platforms
Pricing
Quick highlights
- Interactive Efficient Frontier (mean–variance) widget for quick visualization.
- Compare-assets widget covering returns, drawdowns, CVaR, and correlations.
- Portfolio widget built on adjusted monthly data for risk/return analysis.
- Python library supports mean–variance optimization, rebalancing scenarios, backtesting, and advanced risk metrics such as VaR, CVaR, semideviation, and drawdowns.
- Monte Carlo simulations and wealth-index forecasts with percentile bands.
PortfoliosLab
portfolioslab.com
Portfolio analytics platform with screeners, optimizers, and backtesting. The free tier includes 10 years of data and basic calculations. Plus extends coverage to 40+ years and 200 calculations per month, while Pro unlocks unlimited calculations, 500 holdings per portfolio, CSV import/export, and screener exports. Enterprise offers an API, data-feed integration, and white-labeling. Broker sync is not supported; CSV imports are recommended.
Categories
Platforms
Pricing
Quick highlights
- Portfolio analytics and backtesting with benchmarking, monthly returns, and risk-adjusted ratios such as Sharpe, Sortino, Omega, Calmar, and Martin.
- Optimization models include Mean–Variance (MVO), Risk Parity, and Hierarchical Risk Parity (HRP), with the ability to backtest from a chosen optimization date.
- Risk analytics cover drawdowns, Value at Risk (VaR), Expected Shortfall (CVaR), and multiple volatility estimators.
- Comprehensive stock, ETF, and mutual fund screeners with sortable columns, filters, and risk-versus-return scatterplots. Screener results export is available on Pro.
- Factor analysis tools for Alpha and Beta measurement.
Shared focus areas
Both platforms align on these research themes, so you can stay within one workflow when your use case involves them.
Where they differ
okama
Distinct strengths include:
- Interactive Efficient Frontier (mean–variance) widget for quick visualization.
- Compare-assets widget covering returns, drawdowns, CVaR, and correlations.
- Portfolio widget built on adjusted monthly data for risk/return analysis.
- Python library supports mean–variance optimization, rebalancing scenarios, backtesting, and advanced risk metrics such as VaR, CVaR, semideviation, and drawdowns.
PortfoliosLab
Distinct strengths include:
- Portfolio analytics and backtesting with benchmarking, monthly returns, and risk-adjusted ratios such as Sharpe, Sortino, Omega, Calmar, and Martin.
- Optimization models include Mean–Variance (MVO), Risk Parity, and Hierarchical Risk Parity (HRP), with the ability to backtest from a chosen optimization date.
- Risk analytics cover drawdowns, Value at Risk (VaR), Expected Shortfall (CVaR), and multiple volatility estimators.
- Comprehensive stock, ETF, and mutual fund screeners with sortable columns, filters, and risk-versus-return scatterplots. Screener results export is available on Pro.
Feature-by-feature breakdown
| Attribute | okama | PortfoliosLab |
|---|---|---|
Categories Which research workflows each platform targets | Shared: Quant, Portfolio, Correlation, Backtesting, Risk Metrics (VaR/ES/Drawdown) Unique: Data Visualizations, Monte Carlo, Data APIs, ETF Performance, Inflation Rates, Interest Rates | Shared: Quant, Portfolio, Correlation, Backtesting, Risk Metrics (VaR/ES/Drawdown) Unique: Screeners, ETF Screeners, Watchlist, Stock Comparison, ETF Comparison, Factor Exposure, Financials, APIs & SDKs |
Asset types Supported asset classes and universes | Stocks, ETFs, Commodities, Currencies, Mutual Funds | Stocks, ETFs, Mutual Funds, Cryptos |
Experience levels Who each product is built for | Beginner, Intermediate, Advanced | Beginner, Intermediate, Advanced |
Platforms Where you can access the product | Web, API | Web |
Pricing High-level pricing models | Free | Free, Subscription |
Key features Core capabilities called out by each vendor | Unique
| Unique
|
Tested Verified by hands-on testing inside Find My Moat | Yes | Not yet |
Editor pick Featured inside curated shortlists | Standard listing | Standard listing |
Frequently Asked Questions
Which workflows do okama and PortfoliosLab both support?
Both platforms cover Quant, Portfolio, Correlation, Backtesting, and Risk Metrics (VaR/ES/Drawdown) workflows, so you can research those use cases in either tool before digging into the feature differences below.
Do okama and PortfoliosLab require subscriptions?
Both okama and PortfoliosLab keep freemium access with optional paid upgrades, so you can trial each platform before committing.
How can you access okama and PortfoliosLab?
Both okama and PortfoliosLab prioritize web or desktop access. Investors wanting a mobile-first workflow may need to rely on responsive web views.
What unique strengths set the two platforms apart?
okama differentiates itself with Interactive Efficient Frontier (mean–variance) widget for quick visualization., Compare-assets widget covering returns, drawdowns, CVaR, and correlations., and Portfolio widget built on adjusted monthly data for risk/return analysis., whereas PortfoliosLab stands out for Portfolio analytics and backtesting with benchmarking, monthly returns, and risk-adjusted ratios such as Sharpe, Sortino, Omega, Calmar, and Martin., Optimization models include Mean–Variance (MVO), Risk Parity, and Hierarchical Risk Parity (HRP), with the ability to backtest from a chosen optimization date., and Risk analytics cover drawdowns, Value at Risk (VaR), Expected Shortfall (CVaR), and multiple volatility estimators..
Curation & Accuracy
This directory blends AI‑assisted discovery with human curation. Entries are reviewed, edited, and organized with the goal of expanding coverage and sharpening quality over time. Your feedback helps steer improvements (because no single human can capture everything all at once).
Details change. Pricing, features, and availability may be incomplete or out of date. Treat listings as a starting point and verify on the provider’s site before making decisions. If you spot an error or a gap, send a quick note and I’ll adjust.