bond-benchmarking

Bond spreads measure yield differences between a bond and its benchmark. G-spread, I-spread, and Z-spread are calculated by comparing bond yields against Treasury curves or corporate indices, identifying relative value and credit compensation across fixed-income portfolios using numpy and pandas calculations.

Select a Treasury curve or corporate index as your benchmark, then compare the bond's yield, duration, and credit quality metrics against that benchmark. The Skill computes spread analytics and tracking error to identify relative value opportunities and attribution within peer groups.

Tracking error measures portfolio performance deviation from a benchmark using duration and yield spread analysis. Information ratio normalizes excess return by tracking error, enabling performance attribution analysis and identification of manager skill across fixed-income portfolios and peer comparisons.

Yes. Duration and convexity metrics quantify interest rate sensitivity and bond price curvature. The Skill calculates these measures alongside yield spreads and tracking error to support benchmarking dashboards and attribution reports for relative value assessment.

Bond benchmarking requires structured yield, duration, credit quality, and benchmark index data. The Skill handles Treasury curves and corporate indices using pandas DataFrames and numpy arrays, supporting comparative analysis across multiple benchmarks and peer groups simultaneously.

Spread analysis reflects current market conditions and credit risk but may not capture liquidity premiums, market regime shifts, or tail risks. Duration matching assumes parallel yield curve movements; convexity adjustments are required for large rate changes in non-linear scenarios.