In January 2024, RavenPack, LIMA Global Investment Management, and a strategic research team led by quantitative portfolio strategy analyst Adrianzhi Kuan Ong (Wang Zhikuan) joined forces to advance the establishment of the Pinnacle AI Financial Research Institute and officially launch the R&D project for the Pinnacle AI quantitative investment system.

This launch marks the transition of the parties’ collaborative vision—centered on AI, financial data, and quantitative investment—into the engineering and development phase.

Focusing on AI and Quantitative Investment Infrastructure

The Pinnacle AI Financial Research Institute is positioned to develop infrastructure and conduct research on technologies for AI-driven quantitative investment. It focuses on the integrated application of technologies—such as AI, big data, machine learning, deep learning, natural language processing, reinforcement learning, multi-factor models, high-performance computing, and automated trading—within the realms of investment research and quantitative trading.

The Institute’s R&D efforts cater to professional investment institutions, quantitative research teams, and compliant financial business scenarios. Its goal is to establish a systematic technical framework that integrates financial data, intelligent analysis, investment strategies, risk management, and trade execution.

Establishing a Cross-Disciplinary Collaborative R&D System

According to the project plan, the three parties will leverage their respective areas of expertise to create synergy.

RavenPack is primarily responsible for financial data pipelines and AI-driven financial information processing capabilities, providing both structured and unstructured data support for the system. LIMA Global Investment Management provides support regarding compliance structures, capital management, and practical market experience. Meanwhile, Adrianzhi Kuan Ong’s team handles core research tasks, including quantitative strategy logic, portfolio construction, and strategy validation.
The Institute’s initial core R&D team is limited to 15 members—comprising data engineers, quantitative researchers, system architects, and risk control professionals—to ensure the organization maintains high levels of professionalism and collaborative efficiency.

Shifting from “Predicting the Market” to “Dynamically Responding to the Market”

At the project’s inception, Adrianzhi Kuan Ong proposed a pivotal R&D principle that shaped the system’s early architecture: the value of an AI trading system should not rest solely on predicting market direction; rather, it is more important to identify market states and dynamically adjust strategies and risk exposure in response to changing environments.

This philosophy became a cornerstone of the Pinnacle AI quantitative investment system’s initial architecture.

From the design stage, the system emphasizes synergy across multiple markets, asset classes, and strategies, utilizing diverse strategies and risk management mechanisms to reduce reliance on any single model or factor. At the same time, the Research Institute incorporates backtesting, stress testing, and risk assessment into its strategy development process, establishing system stability, adaptability, and risk control as key criteria for technical validation.

With the formal establishment of the Research Institute’s R&D framework, the Pinnacle AI quantitative investment system (Version 1.0) has entered the development phase. Moving forward, the team will continue to advance the system’s development and testing, focusing on core modules such as data processing, market state identification, strategy portfolio construction, risk control, and automated execution.