# jamesmawm/high-frequency-trading-model-with-ib **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/jamesmawm-high-frequency-trading-model-with-ib).** 2,891 stars · 683 forks · Python · mit ## Links - GitHub: https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB - awesome-repositories: https://awesome-repositories.com/repository/jamesmawm-high-frequency-trading-model-with-ib.md ## Description This is a containerized algorithmic trading system that connects to Interactive Brokers to execute high-frequency pairs trading strategies on forex instruments. The project implements a mean-reversion model that maintains long-short position pairs, continuously recalculating a beta hedge ratio to profit from temporary divergences in correlated price spreads. The system processes each incoming market tick through a signal pipeline that immediately evaluates indicators and triggers market orders without batching or aggregation. It includes an irregular tick resampling engine that converts inhomogeneous tick data into uniform time series for consistent quantitative analysis. The architecture runs in a Docker-isolated headless environment, enabling remote deployment and automated execution on server infrastructure without a graphical interface. The trading model supports historical backtesting to derive initial strategy parameters such as beta and volatility thresholds before switching to live data feeds. Order execution happens synchronously within the main event loop, relying on the Interactive Brokers API's callback mechanism for confirmation and error handling. The system also periodically re-evaluates the hedge ratio between paired securities at set time intervals to maintain neutrality. ## Tags ### Part of an Awesome List - [Trading Broker APIs](https://awesome-repositories.com/f/awesome-lists/devtools/trading-broker-apis.md) — Connects to Interactive Brokers API to execute automated trades based on model signals in real time. - [Arbitrage Trading](https://awesome-repositories.com/f/awesome-lists/data/arbitrage-trading.md) — Trades a pair of highly-correlated stocks by taking opposing long and short positions based on volatility and beta signals. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/tree/v2.0)) - [Broker Connectivity](https://awesome-repositories.com/f/awesome-lists/devops/broker-connectivity.md) — Connects to Interactive Brokers API for live market data and automated order execution. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/tree/master/models)) - [Interactive Brokers TWS Connections](https://awesome-repositories.com/f/awesome-lists/devops/broker-connectivity/interactive-brokers-tws-connections.md) — Configures host and port settings for connecting to Interactive Brokers TWS or Gateway. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/blob/master/main.py)) - [Interactive Brokers Connectors](https://awesome-repositories.com/f/awesome-lists/devtools/trading-broker-apis/interactive-brokers-connectors.md) — Ships a dedicated connector for the Interactive Brokers API to stream live market data and execute orders. - [Historical Parameter Bootstraps](https://awesome-repositories.com/f/awesome-lists/devtools/trading-and-derivatives/historical-parameter-bootstraps.md) — Bootstraps strategy parameters like beta and volatility thresholds from historical market data. - [High Frequency Trading](https://awesome-repositories.com/f/awesome-lists/data/high-frequency-trading.md) — HFT model using Interactive Brokers API. ### Business & Productivity Software - [Automated Trading Execution](https://awesome-repositories.com/f/business-productivity-software/automated-trading-execution.md) — Places buy and sell orders programmatically based on model signals without manual intervention. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/tree/master/models)) - [Pairs Trading Strategies](https://awesome-repositories.com/f/business-productivity-software/pairs-trading-strategies.md) — Executes pairs trading strategies that open long and short positions on correlated securities for mean reversion. - [Tick-Driven Trading](https://awesome-repositories.com/f/business-productivity-software/trading-simulations/real-time-simulated-trading/tick-driven-trading.md) — Generates trade signals and places buy or sell market orders on every incoming tick from the data feed. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/blob/master/README.md)) - [Tick-Triggered Order Placements](https://awesome-repositories.com/f/business-productivity-software/trading-simulations/real-time-simulated-trading/tick-driven-trading/tick-triggered-order-placements.md) — Generates trade signals and executes buy/sell market orders on each incoming tick, re-evaluating beta at set intervals. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB#readme)) - [Beta Re-evaluation Schedulers](https://awesome-repositories.com/f/business-productivity-software/pairs-trading-strategies/beta-re-evaluation-schedulers.md) — Periodically recalculates the hedge ratio between paired securities at set time intervals to maintain neutrality. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/tree/v3.0)) - [Trading Strategy Backtesters](https://awesome-repositories.com/f/business-productivity-software/trading-strategy-backtesters.md) — Simulates historical market conditions to evaluate and validate trading model performance before live deployment. ### Data & Databases - [Tick-Driven Signal Generators](https://awesome-repositories.com/f/data-databases/data-processing-pipelines/document-llm-preparation/multi-stage-pipeline-processing/signal-pipelines/tick-driven-signal-generators.md) — Processes each tick through a signal generator that immediately evaluates indicators and triggers orders. - [Tick Data Retrieval](https://awesome-repositories.com/f/data-databases/data-retrieval-pipelines/tick-data-retrieval.md) — Streams and processes tick-level market data to generate trade signals and place orders on every tick. - [Real-Time Data Streaming](https://awesome-repositories.com/f/data-databases/real-time-data-streaming.md) — Streams tick-level price and volume data in real time from the exchange for live trading. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/tree/master/models)) - [Tick Data Resamplers](https://awesome-repositories.com/f/data-databases/data-retrieval-pipelines/tick-data-retrieval/tick-data-resamplers.md) — Provides an irregular tick resampling engine that converts inhomogeneous tick data into uniform time series for backtesting. - [Time Series Resampling](https://awesome-repositories.com/f/data-databases/time-series-resampling.md) — Resamples irregular tick data into uniform time series for consistent quantitative analysis. ### Scientific & Mathematical Computing - [Pairs Trading Strategies](https://awesome-repositories.com/f/scientific-mathematical-computing/pairs-trading-strategies.md) — Implements a mean-reversion pairs trading model with continuously recalculated beta hedge ratios. ### DevOps & Infrastructure - [Docker Container Deployments](https://awesome-repositories.com/f/devops-infrastructure/container-orchestration/container-runtimes/runtime-configuration-interfaces/docker-socket-orchestrators/docker-target-configurators/docker-container-deployments.md) — Packages the trading model into a Docker container for isolated, headless deployment. ([source](https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB/blob/master/README.md)) - [Headless Container Execution](https://awesome-repositories.com/f/devops-infrastructure/headless-container-execution.md) — Runs the trading application in a headless Docker container for remote server deployment. ### Software Engineering & Architecture - [Synchronous Order Executions](https://awesome-repositories.com/f/software-engineering-architecture/synchronous-event-dispatch-loops/synchronous-order-executions.md) — Executes orders synchronously within the event loop, relying on API callbacks for confirmation.