Announcing Defensive Asset Allocation (DAA)

  • Defensive Asset Allocation (DAA) builds on the framework designed for Vigilant Asset Allocation (VAA)
  • For DAA the need for crash protection is quantified using a separate “canary” universe instead of the full investment universe as with VAA
  • DAA leads to lower out-of-market allocations and hence improves the tracking error due to higher in-the-market-rates

In our brand new SSRN-paper “Breadth Momentum and the Canary Universe: Defensive Asset Allocation (DAA)” we improve on our Vigilant Asset Allocation (VAA, see post) by the introduction of a separate “canary” universe for signaling the need for crash protection, using the concept of breadth momentum (see VAA). This protective universe functions as an early warning system similar to the canary in the coal mine back in the day. For DAA the amount of cash is governed by the number of canary assets with negative momentum. The risky part is still based on relative momentum, just like VAA. The resulting investment strategy is called Defensive Assets Allocation (DAA). The aim of DAA is to lower the average cash (or bond) fraction while keeping nearly the same degree of crash protection as with VAA.

Using a very simple model from 1925 to 1970 with only the S&P 500 total return index as investment asset, we arrive at a two-asset canary universe (VWO and BND) combined with a protective B2 breadth momentum setting, which defines DAA’s core elements.

The DAA concept turns out to be quite effective for nearly all four universes examined in our VAA-paper from 1971 to 2018. The average cash fraction of DAA is often less than half that of VAA’s (below 30% instead of nearly 60%), while return and risk are similar and for recent years even better. Deploying a separate “canary” universe for signaling the need for crash protection also improves the tracking error with respect to the passive (buy-and-hold) benchmark due to higher in-the-market-rates than with VAA. The separate “canary” universe also limits turnover. This makes DAA less sensitive for rising cash (or bond) yields, which is key in view of recent low rates.

To crystallize the DAA concept:
  1. When both canary assets VWO and BND register negative 13612W momentum, invest 100% in the single best bond of the cash universe;
  2. When only one of the canary assets VWO or BND registers negative momentum, allocate 50% in the top half of the best risky assets, while applying equal weights, and invest the remaining 50% in the best bond of the cash universe;
  3. When none of canary assets VWO and BND register negative momentum, indicating the risk of a crash is deemed low, invest 100% in the full top risky assets, again applying equal weights. 

Presenting the Keller Ratio

  • Many traditional return to risk measures are not apt for intuitive interpretation
  • The Keller ratio is expressed as an adjusted return and therefore easy to interpret
  • The Keller ratio allows for strategy selection optimally aligned with an investor’s risk appetite

In our VAA-paper we introduced a new metric for assessing a portfolio’s equity line in terms of the reward to risk relationship: return adjusted for drawdown (RAD). We did choose RAD above the usual risk measures like the Sharpe and the MAR ratios (Sharpe: return divided by volatility, MAR: return divided by maximum drawdown), because most retail investors commonly identify true risk with maximum drawdown over volatility. Since RAD is an adjusted return, its interpretation is similar to any return (a simple percentage). For this reason we prefer RAD over MAR, which as such is just a numeric value with little context.

Frankly, albeit return adjusted for drawdown states exactly what RAD is all about, it is quite a mouthful. Therefore, and not only because RAD is his brainchild, but also to commemorate Wouter Keller’s contributions to the TAA literature (FAA, MAA, CAA, EAA, PAA, and VAA; see SSRN) it only seems fitting to accredit the return adjusted for drawdown indicator with his name. So henceforward RAD is to be named the “Keller ratio”.

Celebrating Wouter Keller's 70th birth year

Every investor with skin in the game acknowledges a large portfolio drawdown as the ultimate investing risk. Large drawdowns are devastating to long term returns. For example, during the 2008 subprime crisis the S&P 500 Total Return index crashed over 50% in approximately 1.5 years from its late 2007 peak, needing 3 years for recovery to breakeven. This left Buy & Hold investors without any positive returns for over nearly five years, not to speak of the excruciating anxiety along the way.

The following table illustrates how severe drawdowns wreak havoc to portfolio performance. Total loss of principal is the biggest risk of all.