VOL. XCIV, NO. 247

★ FINANCIAL TOOLS & SERVICES DIRECTORY ★

PRICE: 5 CENTS

Monday, October 13, 2025

View AmiBrokerView QuantRocketBack to Home

Head-to-head

AmiBroker vs QuantRocket comparison

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

Quick takeaways

AmiBroker adds Data Visualizations, Monte Carlo, Risk Metrics (VaR/ES/Drawdown), Correlation, and APIs & SDKs coverage that QuantRocket skips.

QuantRocket includes Advanced Order Types, Paper Trading, Data APIs, and Broker Connectors categories that AmiBroker omits.

AmiBroker highlights: Portfolio‑level backtesting with dynamic position sizing and bar‑by‑bar ranking/PositionScore., Walk‑forward testing integrated with optimization; in/out‑of‑sample stats., and Monte Carlo simulation (custom metrics can drive optimization/WF objective)..

QuantRocket is known 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..

QuantRocket keeps a free entry point that AmiBroker lacks.

AmiBroker logo

AmiBroker

amibroker.com

Windows desktop platform for technical/system research with a fast AFL scripting language, portfolio‑level backtester, walk‑forward testing, Monte Carlo, and extensive optimization. Real‑time capability and instrument coverage depend on the data plug‑ins you use (e.g., IQFeed, eSignal, Interactive Brokers, Norgate Data). Auto‑trading to IB is available via the official interface. Licenses are perpetual with 24 months of updates.

Platforms

Desktop

Pricing

One-time

Quick highlights

  • Portfolio‑level backtesting with dynamic position sizing and bar‑by‑bar ranking/PositionScore.
  • Walk‑forward testing integrated with optimization; in/out‑of‑sample stats.
  • Monte Carlo simulation (custom metrics can drive optimization/WF objective).
  • Very fast multi‑threaded optimization with 3D optimization surface visualization.
  • Exploration/Scanner to build custom screeners and reports via AFL.

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QuantRocket logo

QuantRocket

quantrocket.com

A Docker-based research, backtesting, and live-trading platform built around Jupyter. The free tier is limited to research, while paid plans unlock live and paper trading along with bundled US minute-bar data. Broader global datasets are available via third-party providers. Its tight IBKR integration brings advanced order types, while real-time market data can be streamed from IBKR, Polygon, or Alpaca.

Platforms

Web
API

Pricing

Free
Subscription

Quick highlights

  • 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.
  • 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.
  • Deep IBKR integration enabling advanced order types such as algorithmic, parent-child, and bracket orders, as well as combos/spreads, margin 'what-if' checks, option greeks, and auction imbalance data.
  • Streams tick-level data into TimescaleDB with WebSocket access, and allows flexible bar aggregation.

Community votes (overall)

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Overlap

Shared focus areas

4 overlaps

Mutual strengths include Quant, Backtesting, and Screeners plus 1 more area.

Where they differ

AmiBroker

Distinct strengths include:

Data Visualizations
Monte Carlo
Risk Metrics (VaR/ES/Drawdown)
Correlation
APIs & SDKs
  • Portfolio‑level backtesting with dynamic position sizing and bar‑by‑bar ranking/PositionScore.
  • Walk‑forward testing integrated with optimization; in/out‑of‑sample stats.
  • Monte Carlo simulation (custom metrics can drive optimization/WF objective).
  • Very fast multi‑threaded optimization with 3D optimization surface visualization.

QuantRocket

Distinct strengths include:

Advanced Order Types
Paper Trading
Data APIs
Broker Connectors
  • 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.
  • 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.
  • Deep IBKR integration enabling advanced order types such as algorithmic, parent-child, and bracket orders, as well as combos/spreads, margin 'what-if' checks, option greeks, and auction imbalance data.

Feature-by-feature breakdown

AttributeAmiBrokerQuantRocket
Categories

Which research workflows each platform targets

Shared: Quant, Backtesting, Screeners, Auto-Trading & Bots

Unique: Data Visualizations, Monte Carlo, Risk Metrics (VaR/ES/Drawdown), Correlation, APIs & SDKs

Shared: Quant, Backtesting, Screeners, Auto-Trading & Bots

Unique: Advanced Order Types, Paper Trading, Data APIs, Broker Connectors

Asset types

Supported asset classes and universes

Stocks, ETFs, Mutual Funds, Futures, Currencies

Stocks, ETFs, Futures, Currencies, Options

Experience levels

Who each product is built for

Intermediate, Advanced

Beginner, Intermediate, Advanced

Platforms

Where you can access the product

Desktop

Web, API

Pricing

High-level pricing models

One-time

Free, Subscription

Key features

Core capabilities called out by each vendor

Unique

  • Portfolio‑level backtesting with dynamic position sizing and bar‑by‑bar ranking/PositionScore.
  • Walk‑forward testing integrated with optimization; in/out‑of‑sample stats.
  • Monte Carlo simulation (custom metrics can drive optimization/WF objective).
  • Very fast multi‑threaded optimization with 3D optimization surface visualization.
  • Exploration/Scanner to build custom screeners and reports via AFL.
  • Rich AFL scripting language for indicators, scans, backtests, and custom metrics; visual debugger.

Unique

  • 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.
  • 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.
  • Deep IBKR integration enabling advanced order types such as algorithmic, parent-child, and bracket orders, as well as combos/spreads, margin 'what-if' checks, option greeks, and auction imbalance data.
  • Streams tick-level data into TimescaleDB with WebSocket access, and allows flexible bar aggregation.
  • REST API ('Houston') with Python client and CLI tools; endpoints return CSV or JSON for easy downstream use.
Tested

Verified by hands-on testing inside Find My Moat

Not yet

Not yet

Editor pick

Featured inside curated shortlists

Standard listing

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Frequently Asked Questions

Which workflows do AmiBroker and QuantRocket both support?

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

Which tool offers a free plan?

QuantRocket offers a free entry point, while AmiBroker requires a paid subscription. Review the pricing table to see how the paid tiers compare.

How can you access AmiBroker and QuantRocket?

Both AmiBroker and QuantRocket 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?

AmiBroker differentiates itself with Portfolio‑level backtesting with dynamic position sizing and bar‑by‑bar ranking/PositionScore., Walk‑forward testing integrated with optimization; in/out‑of‑sample stats., and Monte Carlo simulation (custom metrics can drive optimization/WF objective)., 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..

Keep exploring

Stay on top of related tools

Browse the categories and profiles that overlap most with this comparison to round out your shortlist.

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.