Cboe Global Markets

Samuel Zou

Market Intelligence Authority

Samuel leads Cboe Global Markets’ Data Vantage businesses in Asia Pacific, consisting of Market Data, Risk & Market Analytics, and Index Solutions. Cboe is a leading global markets operator with a long history of innovation in equity and index derivatives, and provides investors with market data, access, and analytical tools to navigate global markets confidently. Prior to Cboe, Samuel spent 12 years in leadership roles across global data & technology providers, including FactSet, Refinitiv, and IHS Markit. Samuel holds a Master’s in Financial Engineering from University of Michigan, Ann Arbor.

A Decade of Transformation in Market Data

With a math and financial engineering background, financial data & analytics was a natural fit to my career interests. Over the past decade, we have observed tremendous evolvements in the market data landscape, in particular:

- AI & cloud technologies have fundamentally reshaped how market data is generated, processed, disseminated, and consumed. With a decline in the usage of financial terminals, investors are increasingly leveraging flexible APIs, MCP (Model Context Protocol) & Agentic AI-powered tools & solutions.

- Global financial markets are more interconnected than ever. US equities & derivatives markets, for example, have been experiencing record-high trading volumes for several consecutive years, and investors from Asia have been one of the largest growth segments.

The upcoming introduction of 23x5 U.S. equities trading, tokenization, and the exuberance of prediction markets, may bring changes to Asian investors, as well as the market data landscape in APAC. Cboe, being front & centre of the developments, is working closely with our partners in the ecosystem, such as market makers, brokers, data & technology providers, in shaping those initiatives via our regional hub in Singapore, and other APAC offices including Hong Kong and Tokyo.

From Team Building to Market Intelligence Leadership

Building high-performing teams in APAC requires both a clear leadership philosophy and a genuine tolerance for complexity. High-performing teams often have common characteristics such as ownership and accountability, cross-functional collaboration and a learning and growth mindset that cascades from the leader to everyone on the team. With APAC being a collection of many fragmented markets in nature (geography, time zone, language, culture, jurisdiction, etc.), there are more nuances to consider when building a diversified, robust, and strong team.

“Always anchor to the client's workflow first, not the other way around.”

The teams navigating that complexity are doing so against a market data landscape that is itself changing rapidly. Market data is now almost everywhere, and in real-time. Mobile apps, social media, AI tools, for example, all need it and no longer just consult with a bank, financial advisor, or data terminal to fetch the latest pricing. This greatly enhanced accessibility, but also resulted in noise, complexity and an overload of information for investors to comprehend.

Real-time analytics, on the other hand, have also been made easier thanks to technology advancements. Investors need more than just pricing feeds to make trading decisions, they also need reference data, volatilities, theoretical value, etc. The demand for more real-time, actionable analytics with minimal latency will be a focus; firms either self-develop, or opt for an "as-a-service" model from providers. At Cboe, we started investing in ticker plants, GPUs and real-time calculation engines many years ago, providing high-quality, real-time analytics to investors and risk managers around the world.

Navigating this environment effectively comes down to a principle I have carried throughout my career. There is a saying ‘Lead with the business question, not the data’. That resonates when clients get excited and hope to receive high-stakes feeds from Cboe, including many of the world’s most complex and sophisticated datasets - real-time OPRA feeds, options analytics, VIX Index and Futures, etc.

Always anchor to the client's workflow first, not the other way around. You should understand if it is for trading, research, risk, or compliance, whether it translates to requirements on latency and delivery, or whether it ultimately shapes the data architecture and lifecycle.

For professionals looking to build a career in this space, I would suggest keeping their eyes open, adapting to new technologies, and always pivoting to the fundamentals of financial workflow & data lifecycle. There will always be new types of data and new analytical tools and the key to navigate this is gaining a deep understanding of the workflow itself. Ask what the pain points are, how that translates to the data lifecycle, what sort of analytics are needed and other important questions. As such, with a solutions mindset, it helps keep up with the latest and succeed in financial market data & analytics.