On November 7, 1940, the nearly 6,000-foot span of the Tacoma Narrows Bridge collapsed in spectacular fashion. According to David Billington’s account in The Tower And The Bridge (which I highly recommend), at the time, the zeitgeist of suspension bridge design was to reduce the span’s thickness-to-length ratio under a new mathematical concept coined ‘deflection theory.’ This theory promised that bridge decks could be laid lighter, longer, and cheaper. The Tacoma Narrows pushed the boundaries of deflection theory with an unprecedented 1/180 ratio for its massive span. But an over-belief in the theory’s elegance proved disastrous less than six months after the bridge’s opening. Caught on camera, the thin bridge span swayed, flapped, and then crashed into the water below during a moderate windstorm. The previously undetected dynamic of “aero-flutter” had been discovered the hard way.
In an abstract sense, fixed income management shares a variety of best practices with civil engineering — the margin of safety, minimum coverage ratio, and error of estimation, to name a few. Long before Newton revealed calculus to the world, medieval builders innately grasped advanced loadings and weight distributions in their use of flying buttresses, vaulted arches, and ribbed ceilings. By repeatedly combining these elements, they were able to construct massive, timeless cathedrals out of stone. Fixed income managers anchor on similar intuition, honed from years of experience in over-the-counter markets. Liquidity profiles, price sensitivities, and margins of safety are pivotal to every trade decision we make. Sophisticated risk metrics enter our processes only as complements to our core practices. We construct portfolios by adhering to a consistent investment philosophy that does not waiver over time.
But quantitative acumen is still required. The fixed income universe is constantly evolving, with new collateral types and structures coming to market, often without pre-packed analytics in place. For example, asset-backed (ABS) issuers have increasingly employed master trust structures in recent years. These revolving collateral warehouses typically issue tranches with open call windows. However, issuer friendly optionality is not always modeled correctly in ubiquitous analytic platforms, such as Bloomberg. At best, the yield, spread, and duration on the callable tranche may be overstated. At worst, the tranche is coded with a fixed maturity that may expose the investor to premium loss if “unexpectedly” redeemed prior to maturity.
So how do bottom-up bond pickers get comfortable with the nuances of structure? Conventional Option Adjusted Spread (OAS) models estimate the open window’s theoretical spread cost with the help of option-pricing engines. The key inputs include the level of yield volatility, length of the call window, and the price premium/discount to the call’s strike (typically par). For continuously and partially callable Mortgage Backed Securities (MBS), off-the-shelf analytic packages provide essential computational horsepower, but their assumptions must be carefully calibrated. Even then, a single OAS metric can tell us only so much. Understanding the possible range of outcomes behind otherwise attractive OAS is critical in managing security level outcomes. This is especially true for certain structures found in Collateralized Mortgage Obligations (CMOs). These CMO’s may advertise high OAS, but mask whippy cashflows. The option adjusted duration (OAD) on such securities must be stress tested to understand the true extent of the risks.
Other areas of the fixed income markets suffer a dearth of pre-packaged analytics, as well. In our opinion, SBA Debentures, Agency ARMs, Specified Pools, Callable Fixed-To-Float Preferreds, hundred-year bonds, and putable corporate bonds all necessitate bespoke modeling efforts. Leaving the evaluation of these security types to third-party black-boxes would be risking “aero-flutter” in the form of mismatched durations, overstated yields, and/or hidden pockets of negative convexity.
At IR+M, our portfolios are constructed more like skyscrapers than cathedrals built to revere “the gods of macro-economics.” In other words, we forgo ornateness in favor of flexibility and transparency. Fortunately, gaffs in modern skyscraper design have been limited (for fun, look up the history of NYC’s Citigroup Center or San Francisco’s Millennium Tower). In portfolio management, our “no surprise” approach emphasizes diversification, liquidity, and parsimony in transaction costs. In my eyes, the fixed income equivalent to the modern skyscraper is a broad, efficient, and transparent core portfolio. It doesn’t hold thousands of line-items, or rely on large sector concentrations or complex derivative instruments to chase returns. It protects the principal, produces yield, and provides liquidity during times of stress. Margins of safety are embedded at the security level, and stress testing is conducted on the broad portfolio over time. Over-quantifying this endeavor is unnecessary, provided that the toolkit is selected with care, and the portfolio is constructed by adroit hands.
The academic study of civil engineering came to the forefront during the railroad boom of the mid-19th century. Quantitative fixed income analysis took off with the 1972 publishing of Leibowitz and Homer’s seminal work, Inside The Yield Book. Since then, bond market participants have pushed the boundaries of quantitative rigor much further. But, the heart of fixed income still beats inside the Monroe Bond Trader Calculator. Cash trades remain beholden to matching individual buyers with sellers, often by phone via a broker. Settlements require the reconciliation of notionals, factors, and dirty and clean prices between back offices. New issues require building books, hand-allocating deal portions, and striking prices with issuers and end-accounts upon verbal command. Understanding how these fixed income anachronisms affect pricing, liquidity, and transaction costs through a market cycle remains a manager’s piece de resistance, and the keystone to how we conduct our day-to-day business.
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