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News - Better Data for Best Execution

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27.04.2020 Issuers

Better Data for Best Execution

An article by the Swiss Stock Exchange shows how quality market data increases transparency, reduces fragmentation and improves price discovery.

At the Swiss Stock Exchange, quality comes as standard. This applies to the performance and stability of its trading infrastructure, the liquidity, prices and spreads in its order books, its services in the listing, trading and post-trading space – and also to the quality of the market data it delivers.

In the thought-leadership article The long way towards data excellence[pdf], Marc Berthoud, Head Exchange Data Strategy in the Business Unit Securities & Exchanges at SIX, addresses the relevant aspects such as data accuracy, improving data standards and the challenges to be resolved, all in the context of MiFID II.

End-to-end insight

The article emphasizes the importance of generating reliable market data by trading venues such as the Swiss Stock Exchange. Only their end-to-end insight over the order-transaction lifecycle gives them an informed view on how to deliver a fully compliant, immediate and meaningful data output.

Marc Berthoud points out: "Price discovery through efficient liquidity pooling is the core function of a securities exchange, and data standardization initiatives have played a crucial role in ensuring reported data is of excellent quality."

Continuous improvement

The article also lists which measures the Swiss Stock Exchange has implemented to ensure compliance with MiFID/MiFIR regulations, for example by launching the MDDX feed, by introducing more granular timestamping up to the microsecond and by implementing MMT (Market Model Typology) trade flags.

The article was first published in The Trade magazine (issue 63) and is also available online. The Swiss Stock Exchange has a solid track record of delivering consistent high-quality market data, both in terms of content and latency. SIX is actively involved in industry initiatives aimed at promoting better data standards.

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