FolioBeyond Fixed Income Commentary For September 2020
Performance Summary
FolioBeyond’s algorithm underlying the S-Network FolioBeyond Optimized Fixed Income Index (“SNFBFI”) returned -0.04% (net of a 30bp annual fee assumption) in September versus -0.05% for the Bloomberg Barclays U.S. Aggregate Bond Index (“AGG”). Treasury rates were range bound during the month with the 10-year Treasury yield declining by 3 basis points (from 0.72% to 0.69%) while the 2-year Treasury dropped by only 1 basis point to 0.13%. SNFBFI’s returns in September had marginal positive contributions from CMBS offset by small losses on short High Yield Corporate and Agency exposures.
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: Risk/Return Frontier
Highlight: High Yield Corporate Sector Rotation Strategy
The framework of FolioBeyond’s multi-factor model can be customized for various Fixed Income market applications. Given the availability of proper analytical measures, the simulation can be set up to optimize portfolio allocations across a user defined universe of investment choices along with desired risk/return targets.
We illustrate this using an example with the High Yield Corporate Bond (“High Yield”) market. The High Yield market is characterized by a diversity of industries comprising 17 major sectors as defined by Bloomberg. While correlations across the industry sectors may be high in certain scenarios, the relative performance across multiple industries will vary depending on a variety of factors including defaults, recovery rates, relative value and other industry specific factors. In the aftermath of the Covid-induced dislocation, there continues to be several dynamic factors influencing the value and risk of individual industries. Consequently, sector rotation strategies have the potential to add value and relative performance. A consistent and objective rules-based process can help manage a rigorous methodology for implementing a disciplined sector rotation strategy.
To this end, we demonstrate the customization of the FolioBeyond multi-factor model to optimize across 17 industry sectors in the High Yield market. The major components of the simulation included the following:
Daily update of yields and probability of default assumptions for each industry sector
Application of industry-specific long-term recovery rates
Maximum return volatility set to the 1-year rolling historical volatility of the High Yield market (represented by the iShares iBoxx $ High Yield Corp Bd ETF (“HYG”)
Maximum exposure of 20% per industry sector
The historical return simulation shows that this type of sector rotation strategy outperformed the overall High Yield Index (Markit iBoxx Liquid High Yield TR USD) by 75 basis points annually during the past 9.9 years (this time period was limited by the availability of historical analytical measures). Relative to the HYG ETF, the outperformance was greater at 124 basis points annually. Additionally, the volatility of FolioBeyond’s sector rotation strategy was lower than both the overall index and ETF, leading to a significantly better Sharpe Ratio.
This illustration demonstrates the merits of an advanced multi-factor model that captures the major components of value and risk including forward looking relative value, historical and future implied volatility levels, momentum effects and correlations. Please contact us to explore how our advanced, low-cost portfolio optimization solutions can be customized to meet your specific investment goals.
