FolioBeyond Fixed Income Commentary For October 2020
Performance Summary
FolioBeyond’s algorithm underlying the S-Network FolioBeyond Optimized Fixed Income Index (“SNFBFI”) returned -0.13% (net of a 30bp annual fee assumption) in September versus -0.45% for the Bloomberg Barclays U.S. Aggregate Bond Index (“AGG”). The Treasury yield curve steepened 18 basis points between the 2-year and 10-year maturities, with the 10-year yield rising by 19 basis points during the month. Short dated High Yield Corporate exposure was the main positive contributor to returns while long Treasuries and intermediate Agencies detracted from returns.
Source: Morningstar
* SNFBFI’s returns are net of underlying ETF fees and 30 bp assumed management fee. Although the information herein is believed to be reliable, FolioBeyond makes no representation or warranty as to its accuracy, and information and opinions reflected herein are subject to change at any time without notice. The past performance information presented herein is not a guarantee of future results.
** The Rank is calculated using the total return of the S-Network FolioBeyond Optimized Fixed Income Index ("SNFBFI") ranked against the closing total returns of the open-end mutual funds in Morningstar's US Fund Multisector Bond Category. Percentile Rank is the total-return percentile rank of SBFBFI relative to all funds in the defined Morningstar Category. The highest (or most favorable) percentile rank is 1 and the lowest (or least favorable) percentile rank is 100.
Highlight: Duration Barbell, Credit Positioning, and Model Implications
The diversity of risk/return profiles in the fixed income universe in conjunction with correlation, momentum, and volatility effects provide a rich opportunity set for optimizing portfolio exposure. FolioBeyond’s multi-factor model captures the multi-dimensional aspects of the varied Fixed Income subsectors and produces optimal portfolio solutions within a specified risk framework. In addition to fundamental analytical measures, the algorithm also captures empirical return behavior in various ways. With this overall quantitative framework in mind, it is helpful to review and summarize the model results in the context of the current market environment.
The model results as of October month-end exhibit the following themes. The portfolio duration exposure is a modest barbell profile where shorter duration exposures to Treasuries, Agencies, and High Yield Corporate Credit are partly offset by long duration Treasuries. This type of positioning reflects the risks associated with the current low interest rate environment. The model does not see significant benefits from reaching for yield by extending duration, especially in the Credit space. However, some exposure to long Treasuries can provide ballast to the portfolio in the event of a flight-to-quality bond market rally.
With respect to Credit positioning, the portfolio has heavier exposure to the short-term High Yield sector that includes Corporate Bonds and some Bank Loans. These allocations provide good risk-adjusted returns in the context of current default probabilities without taking material duration risk. Additionally, these sectors offer additional income alpha versus Investment Grade credit products that have remained at narrow spreads in recent months. While there are other higher yielding opportunities in the marketplace, those opportunities are more appropriate for customized portfolios with higher risk targets.
Another important dynamic is the impact of macro factors and how the model potentially captures those along with the effects of government intervention. While there are no specific macro inputs to the model, the algorithm provides a solid foundation for reacting to these macro factors quickly on a daily basis. For example, the Fed’s Mortgage Backed Security (“MBS”) purchase activity has translated directly to narrowing MBS spread levels that the model measures daily. Potential election related uncertainty gets reflected in forward looking implied volatility levels in the options market, which is an input to the algorithm. If the yield curve changes shape due to the potential impact of a divided government, the resulting changes in yield levels get incorporated into the forward-looking valuations of all the subsectors in the Fixed Income market. If the impact of COVID is likely to be extended and corporate default expectations rise, the model will capture the rising probability of defaults.
In summary, the framework of FolioBeyond’s algorithm is designed to incorporate appropriate risk/return measures that are tied to both fundamental factors and the immediate impact of macro events. We have summarized the themes around the positioning of the model portfolio as of month-end. Looking ahead, we face a historically low interest rate environment buffeted by polarizing elections and the uncertainty of the pandemic. Consequently, it has become even more crucial to manage fixed income portfolios dynamically and tactically. We believe our disciplined investment process puts investors in the best position to maximize expected return versus market risk.
Please contact us to explore how our advanced, low-cost portfolio optimization solutions can be utilized to meet your investment targets.
