Tradefeedr has continued the development of its secure unified data API product, enabling the analysis and sharing of trading data at scale with the aim of improving transparency in the FX markets.
It unveiled a number of new strategic partnerships, including a far-reaching tie-up with LSEG for FX data and analytics.
During the review period, Tradefeedr’s pre-trade analytics product transformed its FX algo performance forecasting techniques by allowing clients to accurately compare expected algo costs and durations from various providers using a standardized methodology.
In addition, and responding to its client’s demands, Tradefeedr has since enhanced its product in three key areas. Firstly, this included client-specific data forecasts that now offer algo forecasts based on a client's own data, providing more accurate estimates by using advanced machine learning to handle smaller data sets.
Secondly, Tradefeedr introduced a model that predicts whether request-for-quote (RFQ) or algo execution is optimal for a client, helping avoid information leakage by comparing likely RFQ bid-offer costs with algo costs.
Finally,