About alphabench

Why alphabench Exists

The problem: Quantitative trading has a massive execution gap. You have an idea at 2 AM. By the time you've set up data pipelines, written backtesting infrastructure, debugged edge cases, and validated results—the opportunity is gone. Or worse, you never start.

The insight: 90% of strategy research is undifferentiated heavy lifting. Data fetching, portfolio management, order execution simulation, performance metrics—this should be infrastructure, not your job.

The vision: What if testing a trading hypothesis was as fast as having the idea? What if you could iterate on 50 strategy variations in an afternoon instead of spending 50 days building the framework to test one?

alphabench makes quantitative trading immediate. The barrier between insight and validation collapses. This is where quant is moving—and the future is now.

Philosophy

alphabench is built on three principles:

1. Ideas Should Be Cheap to Test The cost of validating a hypothesis should approach zero. When testing is instant, you can iterate faster, explore more, and find alpha others miss.

2. Infrastructure Should Be Invisible You shouldn't need to be a software engineer to be a quantitative trader. The plumbing should just work.

3. Speed Compounds The faster you can go from idea → validation → refinement, the more strategies you can explore. More exploration = more edge. This is the only sustainable moat in quant.

What's Next

Q1 2025

• ✅ Natural language strategy generation
• ✅ Complete backtesting engine
• ✅ Indian equities support (NSE/BSE)
• 🚧 Real-time paper trading
• 🚧 Strategy optimization engine

Q2 2025

• Portfolio-level backtesting (multi-strategy)
• Options and derivatives support
• Custom data source integration
• Webhooks for live signals

Q3 2025

• Global markets (US, EU, Asia)
• Live trading integration (broker APIs)
• Strategy marketplace (share & monetize strategies)
• Collaborative research workspaces

Vision: 2026 and Beyond

• Multi-asset portfolio optimization
• Alternative data integration (satellite, sentiment, crypto)
• Institutional-grade risk management
• Decentralized strategy execution

The goal: Make quantitative trading accessible to anyone with curiosity and edge, regardless of their engineering background. Democratize alpha generation.

Contributing

alphabench is built for quants, by quants. We're open to:

• Strategy templates: Share your best frameworks
• Feature requests: What's blocking your research?
• Bug reports: Help us make this bulletproof
• Documentation: Make it easier for the next person

Open an issue or submit a PR at github.com/alphabench/alphabench-python (opens in a new tab)

Resources

• Documentation: docs.alphabench.in (opens in a new tab)
• Web Platform: alphabench.in (opens in a new tab)
• Examples: github.com/alphabench/examples (opens in a new tab)

Support

• Email: [email protected]
• Twitter: @alphabench (opens in a new tab)

Built with conviction. Ship with speed. Trade with edge.