SGX FX Joins The Pyth Network: Institutional FX Composite Benchmarks on a Modern Distribution Layer

SGX FX joins Pyth Network, bringing institutional FX composite benchmarks covering 74 currency pairs and 40+ tenors to a modern distribution layer.

Announcements

Apr 16, 2026

SGX FX Joins Pyth Network: Institutional FX Composite Benchmarks on a Modern Distribution Layer
SGX FX Joins Pyth Network: Institutional FX Composite Benchmarks on a Modern Distribution Layer

SGX FX, a wholly-owned subsidiary of Singapore Exchange Group (SGX Group), is joining the Pyth Network as a data publisher. This collaboration makes SGX FX's real-time institutional FX composite benchmarks available through Pyth.

SGX FX contributes composite benchmarks providing a market-neutral mid-rate for 74 currency pairs and over 40 tenors, aggregated from institutional liquidity across major financial centers including Singapore, Tokyo, London, and New York.

SGX FX is one of six institutions that recently joined Pyth Network alongside the launch of the Pyth Data Marketplace, a new platform enabling institutions to distribute and monetize proprietary datasets through Pyth's global infrastructure.

What SGX FX Brings

SGX Group operates one of the world's most trusted multi-asset marketplaces, spanning equities, fixed income, commodities, and FX. Through SGX FX, the exchange connects institutional participants worldwide via an integrated trading and clearing ecosystem that supports price discovery and settlement across both onshore and offshore markets.

The global FX market processes over $9 trillion in daily transaction volume yet remains among the most fragmented asset classes in global finance. Pricing varies across regions and intermediaries, limiting transparency and access to accurate benchmarks.

SGX FX's composite benchmarks address this directly. By aggregating liquidity across multiple venues and time zones, they deliver a transparent, market-neutral reference rate that reflects real institutional activity rather than indicative quotes. Publishing this data through Pyth makes it accessible across 100+ blockchains and 700+ applications through a single integration, providing developers and financial institutions with continuous, verified FX benchmarks that can be integrated into risk systems, DeFi protocols, and analytics platforms.

"We are committed to upholding the highest standards of transparency and integrity through our SGX FX benchmarks. Contributing this critical pricing data to the Pyth Network is a deliberate step towards accelerating real-time, decentralized finance, ensuring the ecosystem is built on a foundation of trusted, institutional-grade data." — Jean-Philippe Male, CEO of SGX FX

Why It Matters

For decades, institutional FX benchmark data has been locked behind proprietary terminals and fragmented vendor relationships. SGX FX's decision to publish through Pyth marks the first time these composite benchmarks have been made available through onchain infrastructure.

SGX FX joins over 120 institutions already publishing through Pyth with each addition strengthening the network's coverage across asset classes and geographies, and SGX FX brings one of Asia's most trusted FX benchmark platforms into the network.

"SGX FX's contribution exemplifies the shift toward a transparent, programmable market data economy. The world's leading market operators are now connecting directly to the next generation of financial infrastructure, and together we're building a seamless global price layer for every asset class and geography." — Mike Cahill, CEO of Douro Labs and Contributor to Pyth Network

About the Pyth Network

The Pyth Network sources market data directly from the institutions that set prices. More than 120 trading firms, exchanges, banks, and market makers contribute proprietary data to the network, which delivers 3,000+ price feeds across every major asset class. Pyth Pro is an institutional market data subscription. The Pyth Data Marketplace enables institutions to distribute and monetize proprietary datasets through Pyth's global infrastructure.

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