Jane Street Joins Pyth Network

We are thrilled to welcome Jane Street, a premier and dynamic market-making firm, to Pyth Network in order to rewire the current financial infrastructure in a way that is not only faster and more cost-efficient but also fully transparent and making it available to the masses!

Who is Jane Street?

  • Jane Street is a quantitative trading firm and liquidity provider widely regarded for its proprietary trading models and quantitative computing power that places them at the forefront of market structure in equities, bonds, options, and ETFs globally
  • Starting in late 2017, the firm has started to actively trade crypto assets and continues to do so until the present day.

Proven Track Record:

  • The company is active in over 5,000 ETFs worldwide and we continuously refine our quantitative models and cutting-edge technology to provide order-book liquidity in over 45 countries.
  • As one of the world’s finest market-makers, Jane Street owns more than $15 billion in trading capital and is believed to hold about $50 billion in securities on any given day, much more than many of its rivals (source: FT).

Jane Street will initially contribute its real-time crypto market data to Pyth Network with plans to later expand into equities and other products as the network continues to scale.

Ian McGuinn, Head of Crypto Business Development at Jane Street, commented: “Jane Street has been an active participant in the crypto markets, and we are continuously exploring ways to advance the ecosystem. We see the promise of the Pyth Network, with its innovative use of the blockchain to increase transparency, efficiency, and security in financial data. By providing our unique market data on-chain in real-time, we look forward to playing a role in the Pyth Network’s growth.”


We look forward to further coordinating with amazing partners to establish a digital marketplace of institutional grade, high-fidelity financial data to power any financial dApps regardless of their blockchain base and offer the best data to the world.

Source: Pyth

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