The constant leverage myth is busted: there is no spoon natural decay.
DAA’s fast protective momentum approach successfully detects lower volatility regimes with higher streak potential.
Smart leverage through a clever separation of signals and trades can achieve considerable outperformance even on a risk adjusted basis.
Popular belief that constant leveraging results in decay over time is a myth. Michael Gayed and Charles Bilello busted the myth in their 2016 Dow Award winning paper “Leverage for the Long Run”. Their research shows that daily re-leveraging is not without risk. At times the act of re-leveraging can even be mathematically destructive. Yet the source of that risk does not come from some inherent form of natural decay. The authors single out high volatility and seesawing action as the (real) enemies of leverage, while low volatility and streaks in performance are its friends.
As stated in the paper daily re-leveraging combined with high volatility creates compounding issues, often referred to as the “constant leverage trap”. A systematic way of identifying lower volatility regimes with higher streak potential is key for achieving outperformance through smart leverage. Expanding on the authors application of moving averages for identifying those conditions, in the following article smart leverage is explored using the DAA framework with its fast 13612W protective momentum approach with a dedicated two-asset canary universe.
When the stock market is in an uptrend - positive 13612W momentum for all canary assets - favorable conditions for leveraged stock positions are assumed targeting positive streaks in performance. When the stock market is in a downtrend - negative 13612W momentum for one or more of the canary assets - a rise in volatility is expected and a (relatively) safe Treasury bond position is acquired to avoid the constant leverage trap for stocks.
On top of DAA’s dedicated 13612W protective momentum deployment for detecting favorable conditions for leverage, the smart leverage approach incorporates a clever separation of signals and trades. As proposed by Matthias Koch, a quant from Germany, non-leveraged asset universes are used for signaling momentum based position sizing while universes that hold a limited number of matching leveraged funds are used for actual trading.
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”.
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.