Bond Fund Attribution with NAV Factors and Alpha-Based Selection

Summary

The report summary presents a Campisi-style performance attribution model for bond funds using net asset value returns, an approach intended for cases where timely holdings data are scarce, especially for private funds. It describes five explanatory factors: interest-rate level exposure, yield-curve slope, credit spreads, default risk, and convertible bonds. The model is tested by regression on public bond funds, with the summary reporting overall fit above 0.6. Rate level, curve structure, and credit spread factors are described as significant; default and convertible-bond factors matter more for mixed bond funds.

The proposed selection method ranks private bond funds by alpha remaining after regression removes exposure to the modeled risk factors, then forms a portfolio from selected funds. The authors say this supports the feasibility of NAV-based alpha selection for private bond funds. However, the supplied text is only an abstract and does not give factor construction details, sample dates, portfolio rules, or full out-of-sample performance evidence. The results should therefore be read as a reported finding, not as independently verifiable proof of manager skill.

Key ideas

• The model attributes bond-fund NAV returns to five rate, credit, default, and convertible-bond factors.
• Public bond fund regressions are reported to have overall fit above 0.6.
• Rate level, yield-curve structure, and credit spreads are described as significant factors.
• The proposed private-fund screen selects on alpha after modeled risk exposures are removed.
• The supplied abstract omits factor definitions and detailed validation of the selection portfolio.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.