HFTENGINE

Vibe-Trading is an open-source AI personal trading agent and quantitative-finance research workspace developed by HKUDS. It turns natural-language finance questions into runnable analysis and backtesting workflows by connecting an agent to market-data loaders, portfolio and backtesting engines, report generation, persistent memory, and multi-agent research teams across asset classes. Its quantitative and risk-analysis capabilities include strategy backtesting, Heston stochastic-volatility pricing, hierarchical risk parity, copulas, and market-microstructure estimators. The project provides API and MCP interfaces, broker and market-data connectors, portfolio-management and broker-authorized trading workflows, examples, documentation, a demo, and a Shadow Account for testing. It supports read-only account sources such as official IBKR MCP and opt-in Binance USD-M snapshots, while scheduling actions require explicit confirmation and live-order safeguards fail closed on contradictory or invalid data. Implemented as a Python project, it uses a connector onboarding system that stores connection secrets in the operating-system keyring and is distributed under an open-source license.

Binance Futures is Binance’s futures-trading platform. In the cited context, recorded futures-market data from it is used for market-making backtests.

NautilusTrader is an open-source, Rust-native engine and platform for multi-asset, multi-venue algorithmic trading. Its deterministic, event-driven architecture spans research, simulation, backtesting, and live execution, using Python as the control plane for strategy logic, configuration, and orchestration while also supporting systems written entirely in Rust. The same execution semantics and deterministic time model are used in research and live systems, allowing strategies to move from research to production without code changes. Modular adapters connect venues through REST APIs or WebSocket feeds; the engine supports historical quote, trade, bar, order-book, and custom data, multi-venue strategies, advanced order types, optional Redis-backed state persistence, and training AI trading agents with reinforcement-learning or evolutionary-strategy methods. It runs on Linux, macOS, and Windows and can be deployed with Docker.

Higgsfield is an open-source GPU workload manager and machine-learning framework for training models ranging from billions to trillions of parameters, including large language models. It allocates exclusive or non-exclusive access to nodes, queues experiments to manage resource contention, and provides interfaces for distributed training with DeepSpeed ZeRO-3 and PyTorch fully sharded data parallelism. Its framework supports initiating, running, monitoring, and checkpointing experiments on allocated nodes, while its LLM training API includes model, data-loader, and experiment components. Higgsfield integrates with GitHub and GitHub Actions to generate deployment and run workflows: required tools and project deployment keys are installed on servers, code is deployed to configured nodes, and experiments are launched and monitored through GitHub. The repository describes compatibility with Ubuntu nodes offering SSH access and passwordless sudo, and reports testing with Azure, LambdaLabs, and FluidStack.

FLYON is a read-only EVM wallet tracker and command-line tool that extracts swap logs from a chain, reconstructs closed trades using first-in-first-out accounting, and ranks realised profit in each pool’s quote asset rather than in dollars. It sets aside proceeds from tokens whose purchases the chain cannot show, leaving those amounts off the leaderboard. When a watched wallet buys, FLYON records a call with its confidence before the outcome is known. Calls are stored in an append-only, hash-chained JSONL ledger and later settled using the first trade in the same pool at or after the configured window; calls without a qualifying trade remain open. It scores settled calls with the Brier score and builds a static site containing the trades, board, feed, calls, settlements, and scores. The tool uses six read-only JSON-RPC methods and has no API account, signing, wallet, or transaction-submission capability. It supports demo markets and replayable recorded indexer runs, requires Python 3.10 or later, has zero dependencies, and is released under the MIT license.