VOL. XCIV, NO. 247
★ FINANCIAL TOOLS & SERVICES DIRECTORY ★
PRICE: 5 CENTS
Saturday, September 27, 2025
Investors comparing Portfolio Visualizer and PortfoliosLab will find that Both Portfolio Visualizer and PortfoliosLab concentrate on Quant, Factor Exposure, and Risk Metrics (VaR/ES/Drawdown) workflows, making them natural alternatives for similar investment research jobs. Portfolio Visualizer leans into Data Visualizations, and Monte Carlo, which can be decisive for teams that need depth over breadth. PortfoliosLab stands out with Screeners, ETF Screeners, and Portfolio 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
Portfolio Visualizer vs PortfoliosLab
Compare pricing, supported platforms, categories, and standout capabilities to decide which tool fits your workflow.
Quick takeaways
- Portfolio Visualizer adds Data Visualizations, and Monte Carlo coverage that PortfoliosLab skips.
- PortfoliosLab includes Screeners, ETF Screeners, Portfolio, Watchlist, Stock Comparison, ETF Comparison, Financials, and APIs & SDKs categories that Portfolio Visualizer omits.
- Portfolio Visualizer highlights: Portfolio backtesting for mutual funds, ETFs, and stocks with configurable rebalancing rules; separate modules for asset-class backtesting., Monte Carlo simulations for portfolio growth, survival probabilities, and goal-based financial planning., and Optimization tools including efficient frontier modeling, mean–variance optimization, and the Black–Litterman model..
- 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..
Portfolio Visualizer
portfoliovisualizer.com
Web-based analytics suite for portfolio backtesting, optimization, and factor analysis. The free tier supports up to ~15 assets and limited history, while Basic and Pro tiers extend to ~150 assets with YTD results, model saving, and data export. Paid plans include a 14-day free trial.
Categories
Platforms
Pricing
Quick highlights
- Portfolio backtesting for mutual funds, ETFs, and stocks with configurable rebalancing rules; separate modules for asset-class backtesting.
- Monte Carlo simulations for portfolio growth, survival probabilities, and goal-based financial planning.
- Optimization tools including efficient frontier modeling, mean–variance optimization, and the Black–Litterman model.
- Factor analytics with multi-factor regressions and a risk-factor allocation optimizer.
- Correlation analysis at the asset or asset-class level via heatmaps and matrices.
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
Portfolio Visualizer
Distinct strengths include:
- Portfolio backtesting for mutual funds, ETFs, and stocks with configurable rebalancing rules; separate modules for asset-class backtesting.
- Monte Carlo simulations for portfolio growth, survival probabilities, and goal-based financial planning.
- Optimization tools including efficient frontier modeling, mean–variance optimization, and the Black–Litterman model.
- Factor analytics with multi-factor regressions and a risk-factor allocation optimizer.
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 | Portfolio Visualizer | PortfoliosLab |
|---|---|---|
Categories Which research workflows each platform targets | Shared: Quant, Factor Exposure, Risk Metrics (VaR/ES/Drawdown), Backtesting, Correlation Unique: Data Visualizations, Monte Carlo | Shared: Quant, Factor Exposure, Risk Metrics (VaR/ES/Drawdown), Backtesting, Correlation Unique: Screeners, ETF Screeners, Portfolio, Watchlist, Stock Comparison, ETF Comparison, Financials, APIs & SDKs |
Asset types Supported asset classes and universes | Stocks, ETFs, Mutual Funds, Bonds, Commodities | 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 | Web |
Pricing High-level pricing models | Free, Subscription | 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 Portfolio Visualizer and PortfoliosLab both support?
Both platforms cover Quant, Factor Exposure, Risk Metrics (VaR/ES/Drawdown), Backtesting, and Correlation workflows, so you can research those use cases in either tool before digging into the feature differences below.
Do Portfolio Visualizer and PortfoliosLab require subscriptions?
Both Portfolio Visualizer and PortfoliosLab keep freemium access with optional paid upgrades, so you can trial each platform before committing.
How can you access Portfolio Visualizer and PortfoliosLab?
Both Portfolio Visualizer 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?
Portfolio Visualizer differentiates itself with Portfolio backtesting for mutual funds, ETFs, and stocks with configurable rebalancing rules; separate modules for asset-class backtesting., Monte Carlo simulations for portfolio growth, survival probabilities, and goal-based financial planning., and Optimization tools including efficient frontier modeling, mean–variance optimization, and the Black–Litterman model., 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.