Excess liquidity, net interest margin compression and a low-rate environmenthave made the search for investment yield top of mind for many financial institutions and their investment managers. However, it is critical to remember that simple measures of “yield” can have the unintended effect of keeping investors misinformedas to a portfolio’s true risk/return profile.
As you can see in the chart below, topline yield may be misleading as assets with similar – or even the exact same – yield on the surface may have very different risks, which can impact their actual returns over time. Risk-adjusted spread analysis levels the playing field in the investment universe and allows institutional investors to examine investment selections on a relative value basis.
Expected Performance vs. Realized Performance
Even after you deconstruct a yield into risk/return components and establish a foundation for relative value analysis, it is important to note that much of spread analysis is a model-driven, forward-looking exercise. Therefore, an informed investor should always remember that expected performance may not result in realized performance, or as we used to say “your mileage may vary,” particularly when observed events differ from original inputs and assumptions.
A recent example of this can be seen in very new production mortgage-backed security (MBS) pools trading at high dollar prices as investors struggle to evaluate pre-payments. As uncertainty increases with more complex assets, short-term yields can be drastically different than what models project as the yield to maturity (YTM). While more modeling and better analytics are necessary for more complex assets, diversifying the risk profile of the assets that comprise your investment portfolio is often the best solution as individual securities may vary month-to-month. A diversified portfolio is often able to produce a more consistent rate of return in various environments.
Modeling Option-Adjusted Spread (OAS)
The ability to assess a complex asset’s OAS requires the use of an interest-rate model tovalue the embedded option and a prepayment model to project future asset cashflows. The appropriate models vary depending on the type of security.
- For mortgages and residential mortgage-related securities, models employ a Monte Carlo
simulation of prepayment behavior across potential future interest rate and value the optionality
- For callable bonds, models employ a binominal interest rate tree function to price the option
- Numerous variants of these models exist in the industry, each with its own parameters andassumptions
- Multi-factor models based on coupon, size, seasoning, seasonality, burnout, geography, creditaspects of the borrower, etc.
- ZMFS, Bloomberg Prepay Agency Model (BAM), Andrew Davidson, etc.
Projecting yield/OAS for mortgages and mortgage-related assets can be complicated given thesignificant impact of prepayments on performance, particularly for securities priced well below or
above par. That’s why some financial institutions choose to work with an unbiased, strategic partner to assist them with this level of analysis.
Limitations to Expected Return Metrics
As discussed, both yield and OAS metrics are model-dependent and realized returns canvary greatly from expected returns. Yields often don’t translate into actual returns because of changes in market risk factors,most notably prepayments. For example, a high-premium MBS pool’s yield-to-maturity can varysignificantly from itsshort-term dollar return (period coupon – premium amortization) as actual short-termprepayment speeds may differ from expected model speeds. With interest rates falling significantly overthe past 6 months, many MBS pools are experiencingfaster-than-expected prepayments and corresponding erosion of premiums on those pools.
You Can’t Eat OAS – Dollar Returns will Differ from Model Returns
• A 15yr 3.0% new-production MBS pool can have a model OAS of 50bps and top-line YTM of 1.15%.
• However, yield is not linear – aside from the actual return most likely differing from projected, the realization of that return will also be uneven over the life of the pool.
• As the pool moves up the WALA ramp, the accelerated amortization of premium can turn realized dollar return negative until the pool’s prepayments slow down and the pool seasons.
Variance in Prepayments Significantly Impacts MBS Returns
For a high-premium MBS pool experiencing elevated prepayments speeds, premiumamortization can negate much of the coupon collected in the period, resulting in lower-thanexpectedand possibly even negative dollar returns. The model expectation is that prepayment speeds will slow down at some point in thefuture and that over the life of the investment, the investor is more likely to realize the YTM. However, premium erosion can really hurt an institution’s earnings over the short-term andthere is no guarantee that realized prepayment speeds will follow model speeds.
Want to learn more about how to effectively evaluate investment offerings? ALM First’s recent webinar on this topic is now available on-demand. Contact ALM First to request access to the recording.
Gleb Barkovskiy joined ALM First Financial Advisors in 2017. As an Associate in the Investment Management Group, Gleb is primarily responsible for serving ALM First clients in an investment advisory capacity, focusing on fixed income research, analytics, and portfolio management. In this role, he assists in investment strategy development, policy review, and portfolio reinvestment and rebalancing needs. Gleb works closely with the firm’s traders and maintains a keen awareness of fixed income capital markets.
Prior to ALM First, Gleb interned at Goldman Sachs in their Fixed Income Asset Management department across Securitized, Alternative Investments, and Product Development desks.
Gleb holds a bachelor’s degree in Economics from BucknellUniversity in Lewisburg, PA.
Robert Perry is a Principal at ALM First, joining the firm in 2010. Mr. Perry leads ALM First’s ALM and Investment Strategy Groups and is responsible for the development of asset liability and investment portfolio themes for the firm. He also provides strategic focus for financial institution client portfolios that are primarily invested in the high credit quality sectors, and is instrumental in balance sheet hedging strategy development.
Mr. Perry has more than 30 years of experience in the banking and bank-consulting businesses. Mr. Perry has shared his in-depth knowledge and financial management background at many conferences, training and educational events in the areas of ALM and investment strategy, profitability and portfolio strategies, as well as hedging and derivatives use. Mr. Perry has been quoted and published in various publications including WIB CFO Digest, WIB Directors Digest, Credit Union Business, Bloomberg News, and many more.
Before joining ALM First, Mr. Perry previously served as Managing Director of the ALM and Investment Strategy division of DataTech Management in Los Angeles, California, and Chief Investment Officer for First Coastal Bank in Manhattan Beach. Previously, Mr. Perry was a Principal and Product Portfolio Manager at Smith Breeden Associates, Inc., where he managed Smith Breeden’s Enhanced Cash and Enhanced Equity Strategies. He also managed Smith Breeden’s bank consulting group, which included the non-discretionary asset management and risk-reporting businesses. Prior to joining Smith Breeden in 1991, he worked as an analyst in the risk management area of Centura Bank in North Carolina.
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