The Best Static Leveraged Portfolio for the Long Term

Fair criticism. I agree the exact weights are overfit-prone, and I probably should have emphasized “robust region” more than “best portfolio”.

The full-period argmax is not what I would trust. In my 5%-step scan, the argmax moves a lot by start date, but 35/40/25 stays inside the 95%-of-max-Sharpe plateau in all 8 start-date tests. That is the real point.

Gold definitely has recent-performance bias. ZROZ definitely benefited from the long bond bull market. MF is the most fragile proxy and carries implementation/survivorship/model risk. I agree with all of that.

The reason I still like the structure is not because each sleeve is guaranteed to repeat, but because they fail in different regimes. ZROZ failed hard in 2022, but managed futures helped. Gold helped in inflation/stagflation-style regimes. Removing ZROZ improved CAGR but worsened drawdown materially, from about -31% to -45%.

So I would frame it as: not an optimized “best” allocation, but a diversified static range where the goal is avoiding dependence on a single hedge.

What are you invested in?

Not exactly true at all at least for dbmfsim or KMLMsim. Dbmfsim is a live index since 2000 (socgen) of private funds that charged high ass fees 2/20. Amazing the backtested after returns are as high as they are. Think of it more like the DOW as it only is 10 funds and generally qualify with decent AUM. There is no “delisting” of funds like you are claiming, in fact majority are still around and the ones that aren’t are niche cases or retirements. KMLM is just data mainly from the KFA strategy they have run with real money since the 90s. Btop50 and other hedge fund data that’s all inclusive would have some of that bias tho.

Done. Updated the first backtest image and the backtest link. Thanks for the suggestion.

Interesting. I actually like the logic: equal-weight, multiple issuers/managers, global equity through RSIT, trend exposure through several wrappers, RSSX for gold/BTC convexity, and ZROZ as explicit duration convexity.

My only caution is that I would classify that as more experimental than the simple GDE/RSST/ZROZ core, mostly because several of those funds have very short live histories.

Rough look-through, if I understand the products correctly, is something like:

• US equity from RSSX/CTAP/MATE;
• International equity from RSIT;
• A very large managed-futures/trend sleeve from RSIT + CTAP + MATE.
• Gold/BTC from RSSX;
• Long duration from ZROZ;

So it is probably more “MF-heavy global return-stacked core” than the version I tested. That may be great if trend continues to be the diversifier that matters, but it also concentrates a lot of the portfolio’s success in the implementation quality of those managed-futures overlays.

My personal caveats would be:

• RSSX is partly a BTC expression, so I would not extrapolate its backtest too strongly;
• MATE is interesting, but still very new;
• CTAP is a useful manager/process diversifier, but not obviously cheap once you include the embedded CTA/swap economics;
• 20% ZROZ may be enough, but my tests usually wanted 25-35% duration when adding more global equity.

Still, conceptually I get it. It is a clean, diversified, low-maintenance implementation. I would just want to monitor live tracking, fees/financing drag, and whether the MF wrappers actually diversify each other rather than all loading on the same trend premia.

Thanks, I really appreciate this.

I agree with your framing. If there is overfitting here, I do not think it is the usual “12-rule tactical model optimized to dodge every historical drawdown” type of overfit. This is basically a static allocation with 2 free weight parameters, since the weights sum to 100%, and the sleeves were chosen for economic reasons: equity growth, gold/inflation hedge, managed futures/trend, and long duration/deflationary crash hedge.

That said, I still want to be conservative. I see three different risks:

1. Exact-weight overfit: probably low, because the triangle plot shows a broad plateau rather than one magic point. That is why I would not promote the full-period argmax.

1. Regime risk: real. Gold, bonds, and trend may not behave the same way in the future.

1. Proxy/model risk: definitely real, especially for managed futures and pre-inception fund sims.

Good point on the correlation matrix. I have one and should probably add it. Monthly correlations vs SPY in the 2000-2026 window were roughly: gold +0.06, managed futures -0.22, ZROZ -0.15. Diversifier-to-diversifier correlations were also low, all around +0.15 to +0.19. The caveat is that rolling correlations are unstable; ZROZ, for example, flipped positive with equities in 2022. So the case is not “these are always negatively correlated”, but rather “they tend to respond to different crisis regimes.”

It is not the live RSST history except for the recent period. I use a proxy simulation.

For the long backtest I approximate RSST as:

RSST ≈ 100% SPY + 70% DBMF + 30% KMLM - cash/financing drag

So it is basically a return-stacked proxy: equity beta plus a managed-futures sleeve, with the MF sleeve modeled as 70/30 DBMF/KMLM.

Important caveat: this is only a simulation, not an official RSST backtest. The real fund can differ because of fees, collateral management, futures selection, roll costs, tracking error, and the manager’s actual implementation. So I treat the RSST numbers as directional evidence for the equity + managed-futures stack, not as a precise live-fund history.

I’m no LETF expert but if you take a monthly chart of gold/WM2NS you will see gold declined big time in the period of 1980-1999 and stated a bull run 2000-2008 and 2024-2026. OP’s backtest starts at the bull run of 2000 so choosing just one fund overfits to the result of the backtest period.

Backtests just prove your portfolio got trough the last decades of market conditions and correlations in a good way but don’t use it to overconcentrate your portfolio because something yielded like 0,1% better CAGR. Nobody knows what the next decades will look like.

100% GDE is actually a very strong portfolio if the objective is CAGR.

In my 2000-2026 test:

• 100% GDE: 16.3% CAGR, -52.7% MDD, Sharpe 0.75
• 35/40/25 core: 12.5% CAGR, -30.8% MDD, Sharpe 0.85
• SPY: 8.5% CAGR, -55.1% MDD, Sharpe 0.52

So the reason is not that GDE is bad. It is that 100% GDE gives you almost SPY-like drawdown with a lot of gold concentration. It is basically 90% US equity + 90% gold, so only two return streams.

The core gives up CAGR to add managed futures and long-duration Treasuries. That helped most in regimes where stocks/gold alone were not enough. For example, in the GFC, GDE was about -41% while the core was about -23%. In 2022, GDE was about -29% while the core was about -21%, because managed futures offset some of the equity/bond/gold pain.

So I would frame it as:

• 100% GDE = excellent aggressive growth stack.
• GDE/RSST/ZROZ = lower-CAGR, more diversified crisis stack.

If someone can tolerate -50% drawdowns and wants more gold exposure, 100% GDE is a totally defensible choice. It just solves a different problem than the portfolio I was testing.