Q & A with Jeffrey Gundlach:
A closer look at Nordea’s US Total Return strategy
What is the main technical difference between the Nordea US Total Return strategy and its competitors?
Our Total Return strategy distinguishes itself along several lines. First, many so-called “active managers” are not actively managing their portfolios. They may differ from the benchmark index, but by adopting fixed overweights and underweights – over the past decade, many have stayed perennially overweight to corporate credit. We actively manage the risks which drive return: credit versus governments and overall portfolio duration. Second, we use no corporates; to achieve our credit exposures, we use private label mortgage-backed securities and other structured credit. Structured credit gives us a yield pick-up over corporates. Third, for our government exposure, we primarily use Agency Mortgage-Backed Securities (MBS), but also some Treasuries. Agency MBS always have lower interest-rate sensitivity and thus lower volatility than corporate bonds and U.S. Treasuries. Utilizing an active management approach to extract these advantages in Agency MBS and structured credit while mitigating the risks within these sectors, we try to construct a portfolio which delivers higher yield with less interest-rate and credit risks versus conventional core bond funds. In other words, the objective is to construct a portfolio which delivers superior risk-adjusted returns.
Why don’t other bond fund managers use this approach, favoring mortgage securities over corporates and Treasuries?
I don’t think they know how. DoubleLine has a large team with market cycles of experience managing across Agency MBS and securitized credit. Other asset managers have teams focused on the same sectors – Agencies, non-Agencies, CLOs, commercial MBS, etc. Buy they don’t know how to integrate the different risk and return profiles of these securities into an efficient portfolio.
Which are the top-3 positions in terms of percentage?
The pools underlying securitizations contain hundreds or even thousands of loans. This is very different from the holdings of a core bond fund with large exposures to the individual balance sheets of big corporations. It’s more helpful to focus on sector and subsector exposures than on a handful of securities. Agency MBS represent about 51% of the portfolio, structured credit 41%, cash and cash equivalents 8%. Within structured credit, the larger holdings by subsector are private label residential mortgage-backed securities at 24%, commercial MBS at 8% and asset-backed securities at 5%.
What is the most important part of managing a fund like yours?
I could fill a book answering that question, but let’s focus on the management of Agency Mortgage-Backed Securities, the largest allocation in the fund. Agency MBS historically have yielded more than Treasuries because investors demand a spread to compensate for prepayment risk: the possibility that refinancing will shorten the average life of securities, thus reducing interest income and returning principal early in a falling rate environment – precisely when an investor would want to stay invested. Agencies also have extension risk: a slowdown in mortgage prepayments, causing bond maturities to extend out. This usually happens when rates are rising – obviously a bad time to be exposed to rising duration.
Over three decades, we have successfully managed through these periods while other MBS portfolio managers have blown up. Their failures often resulted from dependence on probabilistic modeling of prepayment rates based on inputs such as interest rates, home prices and so forth. The models eventually fail, sometimes catastrophically, because no model can consistently forecast with accuracy the inputs. Even given correct forecasts of the inputs, prepayment speeds can depart from the forecast.
Our team does not rely on models; we rely on critical thinking. We start by working out what we think the returns will be for individual securities and ultimately for aggregated portfolios under various changes in interest rates over various timeframes – over a broader range of possibilities than we would considered under probabilistic boundaries of a model.
This process is labor-intensive. This is why we have a large team of portfolio managers, traders, analysts and information systems specialists devoted to the sector – some of us with three decades of experience managing through the cycles of the MBS market.