> Backtesting tools.

Analyzes historical patterns by matching current market conditions against 30+ years of data across 2,000+ stocks, ETFs, and crypto to calculate base rates for specific moves.

Provides AI-powered stock screening, backtesting, and market analysis integrated with real-time data feeds covering US equities, events, and sector rotation

Provides institutional investors with factor risk models, crowding data, and portfolio decomposition tools to isolate idiosyncratic returns and optimize construction.

Teaches quantitative finance models by building them step-by-step in Python then deliberately breaking one assumption to expose failure modes

Builds, backtests, and deploys trading algorithms without coding using AI-powered strategy transformation.

Provides charting, screening, alerts, backtesting, and social trading features across stocks, crypto, forex, futures, and commodities with 100+ community indicators and broker integrations.

Runs Monte Carlo simulations across 10,000 paths to estimate the probability a stock reaches a target return within a given time horizon

Builds and backtests rule-based stock strategies against historical data, then executes them via paper trading or connected brokerages

Deploys autonomous AI trading agents on Hyperliquid with non-custodial execution and open-source skill library

Provides free authenticated API access to prediction market data, basket analytics, and hosted backtesting infrastructure for researchers and academics.

Multi-agent platform for stock research, strategy backtesting, and prediction market analysis using MCP servers and autonomous agents

Provides AI deep-research agents, institutional fundamentals, factor models, and predictive ML signals for US stocks via a unified equity terminal.

Runs autonomous AI research agents that monitor portfolios, analyze earnings transcripts, track SEC filings, and deliver scheduled briefings with citations to source data.

Executes trades on Hyperliquid via an AI agent that follows user-written or forked strategies, running continuously with visible decision-making.

Tracks and analyzes trades across stocks, futures, options, forex, and crypto with 600+ statistics, AI-powered insights, and auto-sync from 200+ brokers.

Provides a no-code platform for retail investors to build machine learning stock prediction models, run walk-forward backtests, and receive daily ranked stock picks.

Combines 15 smart money signals into a single live directional bias indicator for TradingView and generates PineScript strategies from natural language descriptions.

Builds, backtests, and deploys algorithmic trading strategies using an AI agent that researches markets, generates strategies from natural language prompts, and executes trades via broker integrations

Provides multi-asset analysis tools including scanners, market replay, fundamental heatmaps, and a news feed powered by Benzinga for stocks, futures, crypto, forex, and bonds.

Provides gap analysis, stock scanning with real-time alerts, no-code backtesting, and 20+ years of historical US equity data with premarket and intraday statistics.

Converts investment theses and market narratives into live playbooks with backtesting, automation, data APIs, and 24/7 agent execution

Provides institutional-grade historical and real-time options data via API, including implied volatility, Greeks, full chains, and volatility surfaces across 20+ years of equity and futures options markets.

Tracks institutional investor 13F filings, insider transactions, 13D/13G disclosures, and mutual fund holdings with backtesting and portfolio replication tools

Calculates the minimum number of trades required to validate a trading strategy's statistical significance based on win rate and risk-reward ratio

Provides a self-hosted Python library for downloading Polygon flat-file data, building point-in-time ticker universes with adjustments, and running backtests against 1m/5m/daily bars using a declarative DSL for entry/exit conditions.