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timercrack avatar

timercrack/trader

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Trader

This project is a futures algorithmic trading system designed to execute high-performance trading strategies through direct API integrations and low-latency message routing. It features a strategy execution engine that automates order placement and manages trade flows based on predefined logic and API triggers.

The system utilizes a native trading API bridge and a low-latency message bus to interface internal logic with external exchange APIs while minimizing execution delays. Monitoring is handled through a web-based trading dashboard for real-time activity tracking and remote management.

Broad capabilities include algorithmic order management, asynchronous notification delivery via background queues for corporate messaging, and system administration through a command-line interface. Runtime parameters are managed via configuration merging of YAML and INI files.

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Features

  • Trading Strategy Execution Engines - Provides a high-performance backend system that automates order placement and manages trade flows based on predefined futures trading logic.
  • Futures Trading Engines - Provides a high-performance engine for executing automated futures trades based on predefined algorithmic strategies.
  • Trading APIs - Provides a native extension that bridges internal trading logic with external exchange APIs for high-speed execution.
  • Market Trading Integrations - Connects internal trading logic to external financial markets using native extensions for high-speed execution.
  • Multi-Exchange Trading Connectors - Provides a high-performance native extension for executing futures trading operations via direct external API connectivity.
  • Native API Bridges - Interfaces with external trading APIs through a native layer to achieve high-performance execution of futures trades.
  • Algorithmic Platforms - Provides a complete automated platform for executing high-performance futures trading strategies via direct API integrations.
  • Algorithmic Order Executions - Automates the placement and querying of trade orders by bridging strategy logic to the market.
  • Trading Dashboards - Features a trading dashboard for real-time activity tracking and system alerts via a web interface.
  • Low Latency Messaging - Uses a native message bus for low-latency messaging of trade reports and requests between components.
  • Message Bus Routing - Implements native message bus routing to distribute trade reports and requests across internal components with low latency.
  • Message Bus Systems - Employs a native message bus system to ensure decoupled, low-latency communication between trading system modules.
  • Web-Based Remote Control Interfaces - Ships a web-based remote control interface for monitoring and managing automated trading operations.
8,281 stars·1,903 forks·C·Apache-2.0·38 views

Star history

Star history chart for timercrack/traderStar history chart for timercrack/trader

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does timercrack/trader do?

This project is a futures algorithmic trading system designed to execute high-performance trading strategies through direct API integrations and low-latency message routing. It features a strategy execution engine that automates order placement and manages trade flows based on predefined logic and API triggers.

What are the main features of timercrack/trader?

The main features of timercrack/trader are: Trading Strategy Execution Engines, Futures Trading Engines, Trading APIs, Market Trading Integrations, Multi-Exchange Trading Connectors, Native API Bridges, Algorithmic Platforms, Algorithmic Order Executions.

Which projects share features with timercrack/trader?

Projects with overlapping indexed features include: shinnytech/tqsdk-python — tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures,… drakkar-software/octobot — OctoBot is an open-source automated trading platform that connects to over 15 cryptocurrency exchanges, enabling users… kungfu-origin/kungfu — Kungfu is a high-performance quantitative trading framework and algorithmic execution engine. It provides a… ricequant/rqalpha — RQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides… michaelgrosner/tribeca — Tribeca is a Node.js cryptocurrency trading platform designed for high-frequency trading and automated market making.… fasiondog/hikyuu — Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading…

Projects sharing features with Trader

These projects share indexed features with Trader. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • shinnytech/tqsdk-pythonshinnytech avatar

    shinnytech/tqsdk-python

    4,789View on GitHub↗

    tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures, options, and stocks using Python. It functions as an algorithmic trading engine and financial market data API, providing the tools necessary to backtest strategies, analyze historical data, and execute live trades across multiple brokerage accounts. The project distinguishes itself through a specialized option analytics library that calculates Greeks, implied volatility, and volatility surfaces using the Black-Scholes model. It further supports complex order execution patterns, s

    Python
    View on GitHub↗4,789
  • drakkar-software/octobotDrakkar-Software avatar

    Drakkar-Software/OctoBot

    6,079View on GitHub↗

    OctoBot is an open-source automated trading platform that connects to over 15 cryptocurrency exchanges, enabling users to deploy grid, dollar-cost averaging, market-making, and AI-driven trading strategies. It functions as a unified multi-exchange trading platform, a TradingView alert executor, and a crypto trading bot, all within a single system. The platform is built on an event-driven trading loop with a plugin-based strategy engine, an exchange-agnostic connector layer, and a cloud-synced profile store for multi-device consistency. What distinguishes OctoBot is its integration of large la

    Python
    View on GitHub↗6,079
  • kungfu-origin/kungfukungfu-origin avatar

    kungfu-origin/kungfu

    3,876View on GitHub↗

    Kungfu is a high-performance quantitative trading framework and algorithmic execution engine. It provides a development kit for writing trading logic and a dedicated in-memory financial time-series database for recording and analyzing tick-by-tick market data with high temporal accuracy. The system integrates a market gateway layer to interface with stock and futures exchange protocols, enabling the routing of orders and receipt of price updates. It features a trading operations interface that allows for the management of strategies in both manual and automated headless modes. The framework

    C++ctphftkungfu
    View on GitHub↗3,876
  • ricequant/rqalpharicequant avatar

    ricequant/rqalpha

    6,166View on GitHub↗

    RQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides an event-driven engine for simulating trading strategies against historical market data, with realistic transaction costs, slippage models, and corporate action handling. The platform supports multi-asset class trading including stocks, futures, options, and REITs, with separate sub-accounts for different asset types and configurable margin requirements. The framework distinguishes itself through a plugin-based extensible architecture that allows users to swap out core componen

    Pythonbacktestfinancefutures
    View on GitHub↗6,166
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