FWDB: 4th Quarter 2020 Portfolio Review
Performance data quoted represents past performance and is no guarantee of future results. Current performance may be lower or higher than the performance data quoted. Investment return and principal value will fluctuate so that an investor’s shares, when redeemed, may be worth more or less than original cost. Returns less than one year are not annualized. For the fund’s most recent standardized and month-end performance, please click www.advisorshares.com/etfs/fwdb.
FolioBeyond’s algorithm underlying the AdvisorShares FolioBeyond Smart Core Bond ETF (FWDB) returned 2.92% in during the 4th quarter versus 0.67% for the Bloomberg Barclays U.S. Aggregate Bond Index (“AGG”). As a possible harbinger of future rate moves, the Treasury yield curve steepened by 12 basis points in December, with the 10-year yield rising by nine basis points while the 2-year yield declined by three basis points. Short duration credit exposures were the main drivers of our strategy returns as High Yield Corporate Credit and Bank Loan exposures were the main contributors to positive returns.
Performance Summary as of December 31, 2020
|Total Return||1-Month||YTD 2020||1-Year||3-Year||5-Year|
U.S. Aggregate Bond Index (“AGG”)
|Morningstar Multisector Bond Category||1.27%||4.84%||4.84%||4.28%||5.14%|
|FWDB’s Morningstar Category Percentile Rank||—||—||80||68||65|
|# of Funds in Morningstar Multisector Bond Category||373||336||336||295||259|
|Morningstar Multisector Bond Avg.
|Morningstar Multisector Bond Avg.
Source: BNY Mellon, Morningstar.
Standard Deviation measures the dispersion of a set of data from its mean and is calculated as the square root of variance. Sharpe Ratio measures the average return minus the risk-free return divided by the standard deviation of return on an investment.
Performance data quoted represents past performance and is no guarantee of future results. All Fund data and performance data quoted is believed to be accurate, and unless otherwise stated, is sourced from the Fund administrator, the Advisor’s or Sub-Advisor’s proprietary data, and Morningstar. Current performance may be lower or higher than the performance data quoted. Investment return and principal value will fluctuate so that an investor’s shares, when redeemed, may be worth more or less than original cost. Returns less than one year are not annualized.
Morningstar rankings are based on a fund’s average annual total return relative to all funds in the same Morningstar category. Fund performance used within the rankings, reflects certain fee waivers, without which, returns and Morningstar rankings would have been lower. The highest (or most favorable) percentile rank is 1 and the lowest (or least favorable) percentile rank is 100. Standard Deviation measures the dispersion of a set of data from its mean and is calculated as the square root of variance. Sharpe Ratio measures the average return minus the risk-free return divided by the standard deviation of return on an investment.
Although 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.
Highlight: Review of Fixed Income Markets and FolioBeyond’s Model
As we enter the new year, it is important to put current market conditions in perspective and discern potential risks and opportunities as investors plan out portfolio positioning for both shorter- and longer-term horizons.
Given the transition to a Democratic administration and other macro effects related to the Covid vaccine, both rate and spread products may respond quickly to changing economic conditions. The relative value relationships will likely continue to be in flux as shifts in fundamental factors, whether it be changes in prepayment expectations in MBS, modifications in default projections on corporate credit, or rising CPI projections. There will be direct implications for Fixed Income sector valuations and risks. The re-shaping of the yield curve will also determine potential benefits from extending duration to pick up additional income. These dynamic changes need to be captured in a disciplined and objective manner, with regular updates to relevant analytical measures. FolioBeyond’s algorithm is set up to capture these effects systematically and on a daily basis.
In terms of diversity, the Fixed Income market offers a variety of risk/return tradeoffs that are well represented in liquid, sub-sector ETFs. May Fixed Income investors have tended to simplify their exposure to be in a few broad sectors, missing the opportunity for excess returns with some allocation to a multisector and tactical approach. FolioBeyond explores a wider range of sub-sector opportunities than most other multi-sector strategies, with a process that is implemented in an algorithmic and systematic manner. Currently, we have 23 liquid, sub-sector ETFs in our Fixed Income universe, each with fairly discrete exposures along the dimensions of duration, credit and product type. There is minimal overlap in the underlying bond holdings across these sub-sector ETFs. In a low interest-rate environment, it is even more imperative that an investment strategy constantly explores opportunities in a wide range of sub-sectors. Based on a full analysis of the various sector opportunities, FolioBeyond’s algorithm typically produces an optimized portfolio consisting of 5-7 sub-sectors.
Momentum effects can be enduring and significant in the Fixed Income market. Due to the vagaries of the market and certain structural impediments facing different types of institutional investors, price relationships can often be driven by momentum effects that can overshoot. Many investment management firms have implemented momentum models to capture positive short-term and long-term momentum trends. FolioBeyond’s proprietary 2-factor momentum model is embedded into our portfolio optimization model to adjust portfolio allocations based on both positive and negative trends. But in addition to simply modeling this phenomenon, what differentiates our optimization process versus most other momentum approaches in the marketplace is that our momentum factor is one of multiple factors that drive the model’s overall optimization process. De-risking when there is downward momentum can be expected but this effect has to be evaluated in the context of resulting changes in relative value relationships. Our model attempts to capture all these variables in an effective manner to generate properly optimized solutions.
Another dimension of risk is future expectation of volatility as priced into the options market. Relying solely on historical data puts all the focus on the rear-view mirror. Forward expectations of volatility levels are efficiently captured in the options market. This provides another automated input to our models which can potentially trigger adjustments in portfolio allocations. The result is consistent risk management oversight that ensures the portfolio remains within the range of desired risk targets, with a goal to capture upside while avoiding extreme downside scenarios. This approach leaves less room for qualitative bias as the markets effectively price risk emanating from macro events.
|Ticker||Security Description||Portfolio Weight %|
|AGZ||ISHARES AGENCY BOND ETF||30.23%|
|SJNK||SPDR BBG BARC ST HIGH YIELD||20.98%|
|BKLN||INVESCO SENIOR LOAN ETF||20.59%|
|TLH||ISHARES 10-20 YEAR TREASURY||9.92%|
|SHYG||ISHARES 0-5 YR HY CORP BOND||8.72%|
|IEI||ISHARES 3-7 YEAR TREASURY BO||3.42%|
|TLT||ISHARES 20+ YEAR TREASURY BO||2.81%|
|HYMB||SPDR NUVEEN BLOOMBERG H/Y M||1.78%|
|CMBS||ISHARES CMBS ETF||1.31%|
As of 12.31.2020. Cash is not included.