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Faryan Amir-Ghassemi
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Novus Editorial

The hidden dangers of the traditional asset allocation model – Part 2

Without understanding a portfolio’s underlying tilts, an allocator will struggle to grasp how sub currents in the market affect performance.

Picking up from last week’s note, a criticism we often hear regarding exposure and risk decomposition is how it is unnecessary for the marketable portions of an allocator’s portfolio.  An allocator may have minimal investments in alternatives, balanced by a healthy allocation to long-only managers who have mandates within certain sectors, geographies or market capitalization bands.

While this makes things easier for aggregating risk and exposures across strategies and geographies, the hidden portfolio tilts often lie in the betas of the underlying positions, as well as the sub-sector and market-cap tilts in the portfolio. Long-only portfolio often have robust transparency, allowing one to accurately decompose these risks.

Imagine you have a domestic equity long-only portfolio that houses six external managers and four separately managed accounts.  Two are passive ETFs, while the remaining eight are active managers who may stay within certain investment mandates (e.g., healthcare, tech, small caps, and growth).  You may think you have a 100% plain-vanilla exposure to domestic equity, when in fact the beta – as calculated by regressing all of the individual positions against the market– of the portfolio is 1.25x.  That is significantly more risk than an asset-allocation model would assume.

Peeling the onion one step further, your balanced domestic equity portfolio may be overweight securities that are highly crowded, represent factor betas such as momentum, or even have a size tilt (e.g., overweight small caps).  We saw this trend hurt many allocators’ portfolios in March and April of this year, leaving many scratching their heads or scrambling to understand what they owned.

Momentum has been a bumpy ride.

Looking at factor risk derived by regressing holdings against underlying betas, we’ve seen intense swings during 2014 in the behavior of Fama-French Size (Small Cap vs Large), Value (as measured by Price to Book) and Momentum (highest returning securities net the lowest returning securities).  Momentum and Size were great trades in 2013, but both abruptly regressed from late February into May, and their behavior diverged further in September.  In particular, Social, Tech and Bio stocks were hurt disproportionately (sectors that managers coincidentally shifted into dramatically).  Portfolios that strayed from value into momentum had very turbulent months in 2014.

Sector allocation has been critical in 2014.

Specific sectors have been equally volatile, with Energy soaring into June before plummeting into October.  Without understanding a portfolio’s underlying tilts (over weights, underweights, and the interaction affect between performance and tilt), an allocator will find herself grasping to understand how sub currents in the market may dramatically affect their positioning and performance.  Having the tools and data horsepower to do so is a key weapon in the allocator’s arsenal.

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