PLUTUS Open Source -- Breaking Barriers in Algorithmic Trading
An-Dan Nguyen, Quang-Khoi Ta, Duy-Anh Vo
TL;DR
PLUTUS Open Source presents a structured, community-driven framework to address reproducibility, standardization, and openness in algorithmic trading. It introduces a reproducibility standard, a modular framework, and PROTO reference strategies (Smart Beta and Market Maker) that demonstrate end-to-end replication across data, backtesting, optimization, and paper trading. The initiative emphasizes lowering entry barriers, enabling transparent evaluation, and fostering global collaboration to raise the floor of the field rather than replace proprietary edges. The work lays a practical blueprint for building credible, open trading research through standardized documentation, versioned code, and community-driven growth with a roadmap toward hosted platforms and broader market coverage.
Abstract
Algorithmic trading has long been an opaque, fragmented domain, guarded by secrecy and built around proprietary systems. In contrast to the open, collaborative evolution in fields like machine learning or software engineering, the algorithmic trading ecosystem has been slow to adopt reproducibility, standardization, and shared infrastructure. This paper introduces PLUTUS Open Source, an initiative sponsored by ALGOTRADE to reshape this landscape through openness, structure, and collaboration. PLUTUS combines a reproducibility standard, a modular development framework, and a growing suite of community-built reference strategies. The project provides a systematic approach to designing, testing, and documenting trading algorithms, regardless of the user's technical or financial background. We outline the motivation behind the initiative, present its foundational structure, and showcase working examples that adhere to the PLUTUS standard. We also invite the broader research and trading communities to contribute, iterate, and help build a transparent and inclusive future for algorithmic trading.