Axyon IRIS Forecast Feeds

AI-powered asset performance forecasts feeds for quantitative teams and portfolio managers

Product overview

Axyon IRIS® Forecast Feeds are an off-the-shelf solution designed to help quantitative teams and portfolio managers by delivering AI-powered forecasts on the performance of target asset pools.

  • Forecasts identify the probability of individual assets to out-perform others over each prediction horizon. E.g. “Unicredit stock price has a 56% probability of outperforming ING in the next week”.
  • Aggregate forecasts over selected screenings within an asset pool allow to obtain recap insights such as “Unicredit has a 59% probability of outperforming the EUROSTOXX 50 Financials in the next month.”.
  • Predictive models are based on deep learning - trained over hundreds of thousands of samples from the past - and provide visibility on the strongest factors driving each prediction (momentum, risk, value and sector).
  • Solid predictive performance is ensured by a proprietary no-overfit, leak-free technology and process.
  • Forecasts are delivered on a daily basis, via FTP, APIs or IRIS Web.

CMTYFUTURE feed

AI-powered insights on commodity futures performance. The feed includes the 8 most-liquid commodity continuous futures, and provides forecasts on relative performance over 1-week, 1-month and 3-months horizons.

EUROSTOXX50 feed

AI-powered insights on the EUROSTOXX 50 constituents, in the form of relative performance forecasts over 1-week, 1-month and 3-months horizons.

Customised feeds

Axyon IRIS® Web can become a fully integrated component of the client's quantitative portfolio construction process.

The following elements can be customised for the client:

  • Coverage of asset pools and forecast horizons.
  • Prediction targets beyond ranking by expected return (e.g. ranking by expected sharpe or volatility).
  • Integration with bespoke prediction models trained over the client's proprietary data feeds.

Talk to one of our specialists today for a free Axyon IRIS® Forecast Feeds demonstration.