ETF growth tests market makers’ pricing and hedging tech

Market makers in Europe are under pressure to upgrade technology and processes after ETFs expanded into multi-asset, active, thematic and crypto exposures. Firms are adjusting basket construction, pricing models and dynamic hedging to maintain secondary-market liquidity.

“The price visible on-screen is just the ‘tip of the iceberg’,” said Sylvain Thieullent, chief executive of Horizon Trading Solutions. He outlined four linked stages firms must manage: building baskets, pricing, quoting and hedging.

Those stages must run continuously and at scale. Errors in basket construction or valuation can reduce quote quality. Slow or manual hedging raises the risk for liquidity providers and can lead them to quote wider prices.

Market makers are combining live market data, pricing logic and basket models to produce continuous theoretical values. Those values feed automated quoting and dynamic hedging across equities, bonds, currencies and crypto derivatives that trade on different venues and at different hours.

Regulators have introduced an EU equities consolidated tape and the UK plans a similar scheme to increase market data access. Thieullent warned better visibility alone will not improve ETF pricing unless firms can integrate that data into valuation and hedging workflows in real time.

Execution speed remains important, but competitive advantage is shifting toward the accuracy and intelligence of pricing and risk-management systems rather than latency alone. Larger firms have invested in automation and model development, yet scale does not always guarantee an advantage.

Active strategies, thematic funds and crypto exposure add layers of correlation, liquidity and settlement risk. Firms that can calculate fair value accurately, automate hedging decisions and scale those capabilities can compete with bigger market makers and expand the pool of liquidity providers.

The ability of market makers to price and manage ETF risk affects how readily liquidity appears on screens and how trading holds up during market stress. Thieullent noted asset managers will need ongoing investment in models, data feeds and automation to support the growing and more complex ETF market.