PortfoliosLab vs QuantRocket comparison

Both platforms cover Backtesting, Screeners, Quant, and Data APIs workflows, so you can research those use cases in either tool before digging into the feature differences below.

Both PortfoliosLab and QuantRocket keep freemium access with optional paid upgrades, so you can trial each platform before committing.

Both PortfoliosLab and QuantRocket prioritize web or desktop access. Investors wanting a mobile-first workflow may need to rely on responsive web views.

PortfoliosLab differentiates itself with Portfolio and instrument analytics suite with 20+ tools for performance, risk and optimization (portfolio analysis, portfolio performance, stock comparison, Sharpe, Sortino, Omega, Martin, VaR, CVaR, volatility models)., Portfolio tracking for both static and transactional portfolios, including lazy model portfolios and public user portfolios, with benchmarking against indices and other portfolios., and Backtesting of portfolios and single instruments with configurable rebalancing and long lookback windows (Free limited to ~10 years, paid plans use 40+ years of data)., whereas QuantRocket stands out for Includes survivorship-bias-free US minute-bar data (from 2007 onward) for Zipline backtests and live trading, with optional real-time feeds from brokers like IBKR and Alpaca., Supports point-in-time screening and ranking pipelines, and integrates with Alphalens and Pyfolio for in-notebook analysis inside Jupyter., and Global coverage through Interactive Brokers’ historical and real-time data across 60+ exchanges, plus optional feeds like EDI global EOD, Sharadar fundamentals, and Brain sentiment datasets..