PLUTUS Open Source -- Breaking Barriers in Algorithmic Trading

TL;DR

PLUTUS Open Source aims to transform algorithmic trading by promoting openness, standardization, and collaboration through a modular framework, reproducibility standards, and community-driven strategies.

Contribution

It introduces a comprehensive open-source platform for algorithmic trading that emphasizes transparency, reproducibility, and community engagement, which is a novel approach in this domain.

Findings

Development of a reproducibility standard for trading algorithms

Creation of a modular framework for algorithm design and testing

Successful implementation of community-built reference strategies

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.