From Quant to CEO: Suki Yang on Building a Trading Machine for Institutional Crypto

Suki Yang has spent her career at the intersection of quantitative research, product design and institutional crypto investing. With prior roles at Electric Capital, Pantera Capital and CertiK, Yang has seen first-hand how professional investors evaluate risk, returns and repeatability in liquid markets.

Today, as the CEO of Icon Trading, she is attempting to close what she sees as one of crypto’s most persistent gaps: the absence of truly institutional, system-driven trading operations that scale beyond individual intuition.

Why Build Icon Trading?

Yang spoke to CryptoNews explaining the motivation to launch Icon Trading came from repeatedly encountering the same structural weakness across crypto trading desks. “Crypto does not lack trading ideas. It lacks trading systems that institutions can actually trust”, Yang says.

Many firms excel either at generating trading ideas or at managing risk, but very few succeed at doing both in a way that is scalable and auditable.

“Too many desks still rely on individual judgement,” she explains. “That makes them hard to scale, inconsistent in how risk is budgeted and difficult to audit.”

In a market defined by fragmented venues, perpetual funding dynamics and complex on-chain and off-chain interactions instinct alone is not enough. For Yang, trading had to be treated as a system — not a collection of clever signals but an operating machine spanning data ingestion, execution, risk control, review and iteration.

Why Now?

Timing matters. Yang entered crypto in 2018, when asymmetric opportunities such as ICOs and early venture bets dominated returns. Those inefficiencies, she explains have largely disappeared. “Many of the signals that worked in the past no longer do. They get arbitraged away very quickly.”

At the same time, market maturation has created new opportunities. Exchanges are more reliable, data quality has improved and institutional investors are increasingly comfortable allocating to quantitative strategies. Returns, however, must now be explainable, controlled and repeatable. “The market is moving away from purely narrative-driven volatility towards execution-based advantage,” she says.

What Makes Icon Trading Different?

Yang explains Icon Trading’s core distinction is architectural. Rather than building a loose collection of strategies, the firm has developed a unified trading operating system. Risk budgets, exposure limits and drawdown controls form the foundation, with strategies layered on top as modular components.

Execution is treated as a primary asset, encompassing cross-venue routing, slippage and impact modelling, and both on-chain and off-chain execution. Research itself is productised, with live monitoring, attribution and clear performance metrics. “Most firms search for alpha,” Yang says. “We build a machine designed to keep producing it.”

From Quant to CEO

Transitioning from quantitative research to CEO required a fundamental mindset shift. “The world is non-linear,” Yang reflects. “As a CEO, your job is not to make everything perfect but to get things done.”

She reduces the role to three core responsibilities: ensuring sufficient capital, setting clear direction, and attracting exceptional people. Everything else is secondary. “As a quant, you operate in algorithms and numbers. As a CEO, you’re responsible for everything — including decisions that can’t be optimised with a formula.”

Rules, Discretion and Discipline

At Icon Trading, core execution and risk management are fully rules-based. Limited discretion is allowed for regime identification and extreme events, but even that is gradually encoded into systematic processes. “We allow judgement,” Yang says, “but not opacity or speculation.”

One early assumption she had to unlearn was that transparency naturally leads to efficiency. In crypto, transparency often amplifies reflexivity and strategic behaviour. Public data alone is not an edge; the advantage lies in modelling latency, noise and execution costs. “Transparency didn’t eliminate alpha,” she notes. “It relocated it.”

Lessons from Institutional Investing

Having worked inside one of crypto’s most influential funds, Yang says founders often misunderstand how professional investors evaluate liquid strategies. Returns matter, but risk comes first.

LPs want to know how you make money, how you lose money, and whether you survive losing. Explainability, repeatability and fluency in risk language — drawdowns, correlations, tail risk and liquidity — are non-negotiable.

When markets turn reflexive or narrative-driven, Yang focuses less on opinions and more on capital behaviour. Funding rates, open interest, liquidation density and liquidity conditions reveal real risk appetite. “Narratives may create waves,” she says, “but positions determine the tide.”

Drawdowns and Hard Lessons

Drawdowns, for Yang, are both mathematical outcomes and psychological stress tests. Icon Trading defines acceptable drawdowns first, then derives position sizing and strategy allocation from those limits. During drawdowns, leadership enforces discipline — de-risking, audits and structured reviews — while avoiding revenge trading or ad-hoc changes.

One early mistake reshaped her approach: underestimating the importance of generosity toward top talent. “The strongest trading firms are built by people,” she says. “Being overly cautious on compensation is one of the biggest errors a CEO can make.”

No single individual can build a world-class trading desk alone — and Icon Trading, Yang believes, is proof that systems and people must scale together.