BST Awards 2020: Best buy-side AI platform or tool—MarketAxess
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This year has been chaotic for the markets, bringing to the fore the importance of having access to real-time actionable data and liquidity. MarketAxess has spent the past three-and-a-half years developing its AI-powered pricing engine, Composite+, in a bid to tackle these challenges in the fixed-income markets, and this year it has secured the prize for the best AI platform category at the Buy-Side Technology Awards. In response to the volatility in March and April, David Krein, global head of research at MarketAxess, says the firm has taken steps to improve the AI engine’s resilience for coping with higher demand for real-time pricing data. “Traders need more information faster [in times of crisis] than they do under normal conditions, because they have less sense of where the market stands,” Krein adds.
The Composite+ machine-learning algorithm includes executable levels and transaction data for compiling accurate pricing information. Julien Alexandre, head of data science at MarketAxess, says the engine is built on a gradient-boosting machine-learning model, an ML technique that is effective in processing large volumes of complex and disparate datasets, like that of the corporate bond market.
Over the past 12 months, MarketAxess built out the platform to support emerging capabilities such as streaming prices, predictive pricing, and automated trading workflow support. Composite+ uses data from millions of transactions and covers more than 25,000 fixed-income instruments. The AI engine’s pricing data is updated every 15 seconds, pulling transaction data from MarketAxess’ trading platform, Trax traded prices in Europe and Asia, and Finra’s Trade Reporting and Compliance Engine in the US.
Alexandre says the firm has used the lessons of the last several months to make changes to its pricing algorithm. Over the next several months, MarketAxess aims to offer more context around the pricing information it provides, such as metadata, in addition to extending its pricing coverage of corporate bonds.
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