Exploring Smart Leverage: DAA on Steroids

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Exploring Smart Leverage: DAA on Steroids

  • 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.

With a modified DAA framework to support the required signal-trade separation, we explore smart leverage based on the diversified G12 ETF portfolio as featured in our DAA-paper: SPY, QQQ, IWM, VGK, EWJ, VWO, GSG, GLD, VNQ, HYG, TLT, and LQD. The demonstration is introduced with the DAA setup as benchmark for the subsequent smart leverage setups.

For readers unfamiliar with the concepts of breadth momentum and protective momentum, the VAA and DAA posts (see here and here) are required reading as these concepts along with the used abbreviations are considered prior knowledge.

Warning: Caution is warranted as leverage involves higher risks to costs and loss.

Volatility regimes

The below daily chart for SPY paints a clear picture with respect to the volatility regimes over the last nearly 20 years. The two sub panes show the annualized volatilities measured over the rolling 21-days (1-month) and 252-days (1-year) respectively. Notice the rise in volatility during bear markets and the drop to lower volatility typical for periods when bull markets are picking up steam. Smart leverage targets those lower volatility regimes because of their higher streak potential.
The accompanying table with SPY’s key performance indicators offers insight into the regime characteristics for the 2000-2018 time frame. Notice the changes in CAR’s and volatilities. To match the above daily chart, the table metrics are obtained with daily endpoints for higher granularity too.
NB! Tables in the remainder of this article are based on monthly endpoints for comparison with previous posts, i.e. on EAA, PAA, VAA, and DAA.

Smart Leverage

The smart leverage approach is demonstrated using the DAA framework. To recall, DAA’s key elements are its fast 13612W momentum filter combined with a dedicated protection universe with only two “canary” assets (VWO and BND) whose absolute momentum readings are decisive for capital allocation between “risky”and “safety” assets.

Smart leverage incorporates a clever separation of signals and trades. Absolute and relative momentum based position sizing is derived from non-leveraged ETF universes, while the actual trading universes may hold matching leveraged ETFs (in bold below).

To crystalize the concept for the DAA smart leverage framework:
Protection: VWO, BND


For the portfolio ETFs the daily (leveraged) histories are synthetically extended going back to December 31, 1998. For our favorite setup a long-term backtest is shown too, covering smart leverage over 1971-2018. The long-term backtests are based on monthly data going back to December 31, 1969. Both series use October 31, 2018 as end dates. For both the daily and monthly data based series results are reported by using monthly endpoints for comparison reasons.

Backtests Summary

For both the G4 as well as the G12 universe a comprehensive series of backtests gave the following results. The [updated] Appendix holds the used universe compositions along with detailed performance results. The Appendix also shows the benefit of using separate universes for signals and trades.

For the remainder of this post DAA-G12 combined with a limited number of double leveraged assets will be in the spotlights. This is the setup with the highest [long-term] risk adjusted performance as measured by Sharpe, MAR, and K(20%) from the full series (see last table row). Noteworthy, long-term results for the DAA-G4 limited leverage setup are very close to DAA-G12's, while the limited leverage setup of DAA-G4 shows the best results over 2000-2018.

DAA-G12: The Non-Leveraged Benchmark

The setups for analyzing the global diversified 12 asset portfolio, adhere to DAA’s novel protective momentum approach as introduced in our DAA paper with (always and only) VWO and BND as canary assets. All non-leveraged and leveraged variations use a T6B1 scenario. With a T6 top size rotation, maximum diversification is reached within the top half of the risky R12 universe during lower volatility regimes with higher streak potential. Additionally, with a binary B1 setting DAA reallocates all capital to the best performing safety (treasury) asset in case one or both canary assets register negative 13612W momentum. Only when both VWO and BND register positive 13612W momentum (and only then), risky assets are under consideration for capital allocation. So the used B1 setting keeps defenses high which is key when leveraged assets are involved.

Actually the benchmark setup is quite similar to the setup used in the DAA paper, with the exception of a smaller, treasury only, bond universe: SHY and IEF. Furthermore, since no leverage is involved for the benchmark setup, signal-trade discrimination is superfluous at this point, hence the benchmark signals are derived from the trade universe.

DAA-G12 T6B1 R12 C2 P2 (VWO,BND)

NB! All presented results are derived from simulated total return data. Furthermore, trading costs, slippage, and taxes are disregarded. Results are therefore purely hypothetical and no investor could have attained these results. The presented results are no guarantee of future returns.
For maximum insight the table shows key performance indicators for 8 distinctive periods with changing market regimes. Our DAA-G12 benchmark achieves both volatility and maximum drawdown readings well below a conservative level of 15%, hence the use of the Keller ratio with a (low) 20% threshold (for more on the Keller ratio see here).

DAA-G12: Limited Double Leverage 

Next the proposed signal-trade separation is deployed for analyzing smart leverage with mixed leveraged and non-leveraged trade universes. Adding double leverage assets, for the R12 portfolio SPY, QQQ, IWM, VNQ, and TLT are replaced by SSO, QLD, UWM, URE, and UBT respectively, while IEF is exchanged for UST on the bonds side. Furthermore signal-trade separation is deployed to ascertain the discrimination effect of the permanent P2 protection universe. All other settings are kept equal to those of the benchmark setup.

DAA-G12 T6B1 R12 C3 P2 (VWO,BND)
Referencing the benchmark, the smart leverage setup achieves considerable higher CAR metrics but at the cost of higher volatilities and worse maximum drawdowns. The better K(20%) readings for all but one sub period combined with mostly somewhat lower but still impressive UPI readings demonstrate the robustness of the smart leverage approach on a risk adjusted basis.

A comparison of the following table with the previous one displays the benefit of using separate signal and trade universes for the DAA-G12 setup with its dedicated P2 protection universe. Omitting the separation between signals and trades results in deteriorated performance on both a raw return and a risk adjusted basis for a multitude of metrics on most sub periods.

Long-term Impression: DAA-G12 with Limited Double Leverage

A long-term monthly look from December 31, 1970 (excluding 13612W’s initialization period of 1-year) until October 31, 2018 at the global diversified portfolio concludes the demonstration of the smart leverage approach. The used setup has again a T6B1 rotation scenario for maximum diversification within the G12 portfolio’s top half. The protective B1 setting makes sure that the portfolio rotates 100% into safe treasury assets at the first sign of weakness within the canary assets as measured by their 13612W momentum.

For the above series of comparisons ETFs were used with synthetically extended daily (leveraged) histories going back to December 31, 1998. Since daily index data going back as far as December 31, 1969 is hard to find, if even available, the below used long-term approximations of leveraged assets are derived from monthly total return data (so with monthly instead of daily resets). Therefore the results of the following backtests are merely an impression how the smart leverage approach might have performed over the last nearly 50 years.

In familiar fashion first the equity chart of the non-leveraged benchmark portfolio is shown, followed again by the chart of the limited double leveraged portfolio.

DAA-G12 T6B1 R12 C2 P2 (VWO,BND)
For the benchmark setup the impact of the 1970s “Oil Shock” is visible in the chart, but due to the highly diversified T6 top size the shock effect is mitigated to a great extent. Furthermore the benchmark using only non-leveraged assets shows impressive performance metrics with an overall CAR of 16.50% combined with very low volatility (8.36%) and maximum drawdown (-8.00%) readings. As a result the overall risk adjusted metrics are nothing less than outstanding.

Next up is the smart leverage setup with its typical signal-trade separation combined with limited double leveraged universes.

DAA-G12 T6B1 R12 C2 P2 (VWO,BND)
Referencing the benchmark, over the backtested period of nearly half a century the smart leverage setup achieves a nearly 50% higher CAR reading of 23.78% against 16.50% for the non-leveraged setup. Volatility and maximum drawdown increase by roughly the same ratio. Noteworthy, the maximum drawdown level of 12.54% is still well contained below our 15% mark. The risk adjusted K(20%) metric of the smart leverage setup even beats the one of the benchmark and MAR and UPI readings are only slightly lower. Again, this demonstrates the robustness of the smart leverage approach both on a raw return basis as well as on a risk adjusted basis.

Long-term Charts

To conclude our exploration of smart leverage with the the DAA-G12 approach with its protective momentum through dedicated canary assets and signal-trade separation, a couple of extra charts are shown to allow for a detailed impression of its long-term performance.

Annual returns:
Monthly maximum drawdowns:
Profit contribution:
Monthly returns and win-rates:
Rolling 1-year returns:


Smart leverage with the demonstrated DAA-G12 setup using signal-trade separation manages to steer clear from the constant leverage trap. Combining smart leverage's clever separation of signals and trades together with DAA's novel canary protection proves successful in detecting lower volatility regimes and banks on its higher streak potential resulting in considerable outperformance for both raw and risk adjusted returns as measured with the conservative K(20%) ratio.

Strategy Signals

A (nearly) “live” signals table for the DAA-G12 T6B1 strategy with the above mentioned setup will be added to the Strategy Signals page in due time. Until then, the table is fully functional below. Please take note of the limitations as mentioned on the Strategy Signals page.

NB! No guarantee whatsoever is given for the soundness of the strategy nor the proper functioning of the table nor for the accuracy of the (time delayed) signals. Please do your own due diligence and use at your peril. The Important Notice in the footer applies as well as the Disclaimer.

Update: By popular demand signals are also maintained for the DAA-SL-G4 T3B1 limited double leverage strategy from the Appendix. Again, please take note of the limitations as mentioned on the Strategy Signals page.

NB! No guarantee whatsoever is given for the soundness of the strategy nor the proper functioning of the table nor for the accuracy of the (time delayed) signals. Please do your own due diligence and use at your peril. The Important Notice in the footer applies as well as the Disclaimer.

Endnotes and cautions

  • All reported results are derived from simulated total return ETF data. Furthermore, trading costs, slippage, and taxes are disregarded. Results are therefore purely hypothetical and no investor could have attained these results. The presented results are no guarantee of future returns. Especially for synthesizing extended data series of leveraged ETFs expense ratios along with the the impact of historically higher borrowing costs are difficult to estimate.
  • Liquidity, low trading volumes, and assets-under-management requirements limit the practical application of leveraged assets to avoid high slippage costs. These limitations may cause to be problematic in times of market stress when spreads typically widen. Caveat emptor!
  • Contrary to the mainly decreasing interest rates environment during the analyzed period, the regime for foreseeable future may be characterized by rising rates. Most likely this will have a negative impact on the reported results.
  • Recommended further reading: “Trend Following on Steroids” by Wouter Keller. Furthermore we have included a leverage example in the latest update of our DAA-paper on SSRN (see section 9, page 22).
The full AmiBroker code for DAA's Smart Leverage framework is available upon request. Interested parties are encouraged to support this blog with a donation:

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