VOL. XCIV, NO. 247

★ FINANCIAL TOOLS & SERVICES DIRECTORY ★

PRICE: 5 CENTS

Sunday, October 5, 2025

View okamaView QuantConnectBack to Home

Head-to-head

okama vs QuantConnect comparison

Compare pricing, supported platforms, categories, and standout capabilities to decide which tool fits your workflow.

Quick takeaways

okama adds Data Visualizations, Portfolio, Correlation, Risk Metrics (VaR/ES/Drawdown), Monte Carlo, Data APIs, ETF Performance, Inflation Rates, and Interest Rates coverage that QuantConnect skips.

QuantConnect includes Paper Trading, Auto-Trading & Bots, Options & Derivatives, 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..

QuantConnect is known for: Seamless environment that connects research, backtests, and live trading on institutional-grade co-located servers., Powered by the open-source LEAN engine (Python 3.11 and C#), with the flexibility to run locally or in the cloud., and Multi-asset coverage across equities, ETFs, options, futures, FX, and crypto, with a long list of broker and data integrations including Interactive Brokers, Schwab, TradeStation, Tastytrade, Alpaca, OANDA, Binance, Coinbase, Kraken, Bybit, and Bloomberg EMSX..

okama logo

okama

okama.io

Hands-on review

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.

Platforms

Web
API

Pricing

Free

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.

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QuantConnect logo

QuantConnect

quantconnect.com

QuantConnect runs on the open-source LEAN engine, giving quants and systematic traders a unified workflow from research to backtesting to live deployment. You can run everything locally or in the cloud. Historical data down to tick and second resolution is available on paid tiers, and live-trading notifications scale by plan (from a handful per hour to thousands). Some broker and data feeds—like Trading Technologies futures or premium vendors—are only unlocked at higher tiers.

Platforms

Web
Desktop
API

Pricing

Free
Subscription

Quick highlights

  • Seamless environment that connects research, backtests, and live trading on institutional-grade co-located servers.
  • Powered by the open-source LEAN engine (Python 3.11 and C#), with the flexibility to run locally or in the cloud.
  • Multi-asset coverage across equities, ETFs, options, futures, FX, and crypto, with a long list of broker and data integrations including Interactive Brokers, Schwab, TradeStation, Tastytrade, Alpaca, OANDA, Binance, Coinbase, Kraken, Bybit, and Bloomberg EMSX.
  • Robust options support with Greeks, implied volatility, and helpers for building multi-leg strategies such as iron condors.
  • Generates detailed backtest reports you can download as PDFs and raw results exportable as CSV or JSON.

Community votes (overall)

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Overlap

Shared focus areas

2 overlaps

Mutual strengths include Quant, and Backtesting.

Where they differ

okama

Distinct strengths include:

Data Visualizations
Portfolio
Correlation
Risk Metrics (VaR/ES/Drawdown)
Monte Carlo
Data APIs
ETF Performance
Inflation Rates
  • 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.

QuantConnect

Distinct strengths include:

Paper Trading
Auto-Trading & Bots
Options & Derivatives
APIs & SDKs
  • Seamless environment that connects research, backtests, and live trading on institutional-grade co-located servers.
  • Powered by the open-source LEAN engine (Python 3.11 and C#), with the flexibility to run locally or in the cloud.
  • Multi-asset coverage across equities, ETFs, options, futures, FX, and crypto, with a long list of broker and data integrations including Interactive Brokers, Schwab, TradeStation, Tastytrade, Alpaca, OANDA, Binance, Coinbase, Kraken, Bybit, and Bloomberg EMSX.
  • Robust options support with Greeks, implied volatility, and helpers for building multi-leg strategies such as iron condors.

Feature-by-feature breakdown

AttributeokamaQuantConnect
Categories

Which research workflows each platform targets

Shared: Quant, Backtesting

Unique: Data Visualizations, Portfolio, Correlation, Risk Metrics (VaR/ES/Drawdown), Monte Carlo, Data APIs, ETF Performance, Inflation Rates, Interest Rates

Shared: Quant, Backtesting

Unique: Paper Trading, Auto-Trading & Bots, Options & Derivatives, APIs & SDKs

Asset types

Supported asset classes and universes

Stocks, ETFs, Commodities, Currencies, Mutual Funds

Stocks, ETFs, Options, Futures, Currencies, 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, Desktop, API

Pricing

High-level pricing models

Free

Free, Subscription

Key features

Core capabilities called out by each vendor

Unique

  • 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.
  • Free end-of-day market and macroeconomic data via API, including equities, ETFs, mutual funds, commodities, currencies, indexes, inflation, policy rates, and CAPE10 ratios.

Unique

  • Seamless environment that connects research, backtests, and live trading on institutional-grade co-located servers.
  • Powered by the open-source LEAN engine (Python 3.11 and C#), with the flexibility to run locally or in the cloud.
  • Multi-asset coverage across equities, ETFs, options, futures, FX, and crypto, with a long list of broker and data integrations including Interactive Brokers, Schwab, TradeStation, Tastytrade, Alpaca, OANDA, Binance, Coinbase, Kraken, Bybit, and Bloomberg EMSX.
  • Robust options support with Greeks, implied volatility, and helpers for building multi-leg strategies such as iron condors.
  • Generates detailed backtest reports you can download as PDFs and raw results exportable as CSV or JSON.
  • Cloud API and Lean CLI for managing projects, running backtests, deploying live strategies, and pulling reports programmatically.
Tested

Verified by hands-on testing inside Find My Moat

Yes

Not yet

Editor pick

Featured inside curated shortlists

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Frequently Asked Questions

Which workflows do okama and QuantConnect both support?

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

Do okama and QuantConnect require subscriptions?

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

How can you access okama and QuantConnect?

Both okama and QuantConnect 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 QuantConnect stands out for Seamless environment that connects research, backtests, and live trading on institutional-grade co-located servers., Powered by the open-source LEAN engine (Python 3.11 and C#), with the flexibility to run locally or in the cloud., and Multi-asset coverage across equities, ETFs, options, futures, FX, and crypto, with a long list of broker and data integrations including Interactive Brokers, Schwab, TradeStation, Tastytrade, Alpaca, OANDA, Binance, Coinbase, Kraken, Bybit, and Bloomberg EMSX..

Keep exploring

Stay on top of related tools

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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.