u/Comfortable_Bad9963

Question for the people here who run tactical asset allocation from a European broker.

I've been trying to set up HAA on IBKR Ireland. The strategy wants nine US-listed ETFs (SPY, QQQ, IWM, IEF, TLT, GLD, VWO, VEA, DBC). Eight of those have a clean UCITS substitute on XETRA or LSE. The ninth (DBC, diversified commodity strategy) doesn't, because the active K-1-free wrapper isn't doable under UCITS rules.

That's fine for HAA, where DBC is a small sleeve. But the same pattern repeats across half the popular TAA strategies. Some sleeves substitute cleanly, some don't, and people on these subs tend to either say "just buy VWCE" or hand-wave that UCITS is fine without actually checking which sleeves degrade.

I came across a writeup on bestfolio.app that ranks ~10 well-known TAA strategies by how cleanly their universes translate to UCITS. Tier 1 are the ones that just work (HAA-minus-DBC, GEM, Permanent Portfolio, Dalio All-Weather, 60/40). Tier 2 are the ones where a sleeve loses methodology character (small-cap value: ZPRV is the closest UCITS, but the Avantis profitability tilt is missing; AVWS launched late 2024 if you want the Avantis methodology on a global rather than US-only universe). Tier 3 is where there's no real substitute (active commodity DBC/PDBC, USD-denominated TIPS).

Link: https://bestfolio.app/blog/taa-strategies-europe-ucits-substitution

Two things I'd actually like input on:

What's the cleanest UCITS substitute people here have found for the US TIPS sleeve, ideally EUR-hedged without the 30-50bp hedging drag?

And has anyone backtested the AVUV-vs-AVWS divergence over a real strategy window? I expect global-developed-SCV to bleed maybe 50-100bp annually vs the US-only original on a 15% sleeve, but I haven't seen the actual numbers.

Been running monthly walk-forward weight optimization on a basket of 5 systematic TAA strategies (Keller's HAA/BAA/PAA/VAA family plus a couple of others) over 26 to 30 year out-of-sample windows. Standard knobs: 36-month rolling lookback, max-Sharpe for the conservative basket, max-CAGR for the aggressive one, 40% per-strategy weight cap, monthly rebalance.

The empirical thing that surprised me is how persistent the optimizer's weight allocations turn out to be. "Eliminated" (assigned <5% weight) streaks I observed in a single OOS run:

• One strategy: <5% weight for 88 consecutive months (Jan 2011 to Apr 2018)
• Another: <5% weight for 87 consecutive months (2003 to 2010)
• A third in a different basket: <5% for 49 months (late 2015 to late 2019), then snapped back to the 40% cap by COVID

So for ~25% of the OOS history, several sleeves are effectively absent from the portfolio.

Mechanically this makes sense: a 36-month lookback means 35 of the 36 months overlap with the previous month's lookback, so the input data is highly serially correlated and so are the output weights. But the magnitude (years of zero allocation followed by a snap-back) is more extreme than I would have predicted.

A few framings I'm considering:

1. Feature. The persistence is what stops you from emotionally firing a strategy at the bottom of its drawdown. The optimizer benches a sleeve when its trailing risk-adjusted profile is bad and reinstates it when conditions change. Behavioral discipline by accident.

2. Bug. Long elimination streaks suggest the optimizer is overconfident on noisy estimates of forward Sharpe. Equal-weight or shrinkage toward a prior would be more honest (DeMiguel/Garlappi/Uppal 2009 territory).

3. Lookback artifact. 36 months is forcing this. Shorter window would react faster but be noisier; longer would over-anchor. Multi-horizon ensemble might be more robust.

4. Basket-selection symptom. If candidate strategies are too correlated, you get aggressive weight switching driven by tiny estimation noise. With genuinely diverse mechanisms, the optimizer's preferences carry more signal.

Curious what people who do this for a living think:

• Do you shrink toward a prior (equal-weight, risk-parity)?
• Do you use multiple lookback horizons and combine?
• Do you switch criteria based on a regime indicator?
• Or do you just accept long persistence as the price of having any signal at all?