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USE CASE

Bond Pricing and Performance

Objective

● Train and score 2-way bond pricing models in real-time

● Predict errors between price and rule based predictions

● Optimize rules engine with greater accuracy

● Improve accuracy of reference price predictions on days with high variability in the market

● Predict OAS (Option Adjusted Spread) for Corporate Bonds

Outcome

● Improved performance, scoring 24,000 corporate bonds globally for a single customer

● Predicted pricing accuracy every 15 seconds, removing features that were not predictive to price

● Reduced errors by $0.66 per bond

● The AI model will predict the 90 days forward OAS for the corporate bonds.

● Feature includes issuer fundamentals, current credit ratings, bond features and other fixed income analytics variables.

● The solution can be delivered through APIs to the research team.

Business Value

● Fulfill client liquidity needs with more accurate and timely bond pricing data

● Predicting OAS (Option Adjusted Spread) is a good indicator that can be used to assess the credit quality of the bond and an important input to determine the bond  ratings (high yield to investment grade or vice a versa)

H2O's AI and Data Approaches

● Classification Models

H2O-3 gradient boosting machine to improve performance

● Automatically create interactions between features

● Perform feature selection to remove features that are not predictive to price

Linear model predictions

Resources

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