
VectorBT
A Python package for quantitative analysis and vectorized backtesting.

Professional-grade, low-latency programmatic trading infrastructure for quantitative developers.

Lime Trading is a premier technology-first brokerage platform designed for high-frequency and quantitative trading entities. Historically known as Lime Brokerage, the platform has evolved into a robust 2026 execution suite providing direct market access (DMA) for equities, options, and futures. The architecture is built on ultra-low-latency gateways that cater to systematic traders who require sub-millisecond execution speeds. Lime's infrastructure is particularly significant for the 2026 market as it bridges the gap between AI-driven autonomous trading agents and institutional-grade liquidity. The platform offers a multi-layered API approach, including REST for account management, WebSockets for real-time data streaming, and binary protocols for high-performance order execution. By integrating pre-trade risk management directly into the hardware/software boundary, Lime ensures regulatory compliance without sacrificing the speed required for arbitrage and market-making strategies. Its position in the market is defined by its ability to provide retail-accessible professional infrastructure, allowing independent quant developers to compete with institutional desks through co-located servers and optimized routing logic.
Lime Trading is a premier technology-first brokerage platform designed for high-frequency and quantitative trading entities.
Explore all tools that specialize in optimize trading strategies. This domain focus ensures Lime Trading delivers optimized results for this specific requirement.
Explore all tools that specialize in quantitative strategy backtesting. This domain focus ensures Lime Trading delivers optimized results for this specific requirement.
Proprietary binary gateways designed to minimize the tick-to-trade time for automated strategies.
Real-time verification of buying power and regulatory compliance at the gateway level.
Server placement within Equinix NY4 and CH2 data centers for proximity to exchange matching engines.
Unified API interface for trading Equities, Options, and Futures simultaneously.
Access to granular tick-by-tick historical data for strategy validation.
Native Python wrappers for asynchronous order handling and data ingestion.
Algorithmic routing across 25+ venues to capture the best bid/offer (NBBO).
Create a Lime Trading account and complete the institutional or individual KYC/AML process.
Fund the account via wire transfer or ACH to meet the minimum equity requirement for API access.
Generate API credentials (Client ID and Secret) through the Lime Dashboard.
Configure IP whitelisting for your trading server to ensure secure connectivity.
Install the Lime SDKs for your preferred language (Python, Java, or C++).
Connect to the Simulation (Paper Trading) environment using the provided sandbox endpoint.
Implement pre-trade risk controls within your logic to comply with Lime's safety parameters.
Execute a series of test orders in the sandbox to verify connectivity and latency.
Request production API access once testing logs are validated by the Lime support team.
Deploy your strategy to a co-located server for optimal execution speed in the live market.
All Set
Ready to go
Verified feedback from other users.
"Highly regarded by quant developers for its speed and developer-first approach, though perceived as expensive for low-volume traders."
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A Python package for quantitative analysis and vectorized backtesting.

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