Waton and Panda AI Launch Global AI Trading Agent Competition

Waton Financial Limited has entered a strategic partnership with Panda AI to launch the Global Competition for AI Agents in Securities Trading, an initiative designed to push the boundaries of AI adoption across traditional financial institutions. The competition represents a significant leap forward for the securities industry: rather than relying on simulated environments, participants will deploy live AI trading agents directly in real markets using Waton’s institutional-grade execution and infrastructure.

This framework provides a rare opportunity for developers, quants, and AI researchers to test multi-model, fully autonomous trading strategies under real-world conditions. Waton will supply secure and regulated market access, while Panda AI contributes its multi-model agent development toolkit and applied AI support, creating a comprehensive environment for validating advanced automated strategies. The inaugural competition begins in Greater China, with as adoption scales.

Kai Zhou, Chairman of Waton Financial Limited, emphasized that this partnership is part of a wider vision: strengthening DePearl’s ecosystem and transitioning Waton into a financial infrastructure layer built for AI-native trading. Through this competition, Waton aims not only to identify high-performing autonomous systems but also to integrate winning strategies into its broader suite of services, potentially defining AI agents as a new markets.

Takeaway

A New Model for AI Strategy Development, Validation, and Commercialization

The competition introduces a new blueprint for how financial institutions can identify, test, and commercialize . Instead of isolated research labs or static backtests, Waton and Panda AI’s model creates a pipeline where AI agents are tested under real conditions, validated through measurable performance, and elevated into production environments for institutional clients.

This live-market approach offers participants the ability to run multiple AI agents simultaneously, stress-testing decision frameworks, risk architectures, and model adaptability. Panda AI’s technical stack provides reinforced learning environments, multi-model orchestration, and agent deployment infrastructure, enabling developers to focus on strategy design while relying on industrial-grade tools to manage execution considerations.

Waton expects the competition to serve as both a discovery channel and a proof-of-concept system, enabling the firm to identify standout strategies that can strengthen its competitive position in the rapidly evolving AI finance sector. This model also unlocks new monetization pathways, including AI-powered funds, licensing agreements, and institutional partnerships centered around autonomous agent deployment.

Takeaway

Strengthening AI Capabilities While Attracting Global Talent and Institutional Demand

The strategic initiative also aims to attract a global community of developers, data scientists, quants, and fintech innovators viewking to test sophisticated autonomous trading systems. This positions Waton to become a central hub for AI trading talent, similar to how traditional quant competitions assisted launch major hedge fund strategies in past decades.

At the identical time, institutional clients increasingly viewk validated, explainable, and for portfolio automation, execution optimization, and real-time risk intelligence. The competition provides Waton with access to promising strategies that could evolve into deployable products for its brokerage, asset management, and software licensing divisions.

Supported by Panda AI’s multi-model framework and reinforced learning systems, Waton intends to develop an ecosystem where AI agents can be stress-tested, regulated, and ultimately offered as a new class of financial tools. The company expects this collaboration to contribute meaningfully to its long-term AI roadmap—accelerating the convergence of traditional finance and autonomous machine-driven trading.

Takeaway