Model Portfolio Quarterly Update

n April 2022, I introduced on this blog The Italian Leather Sofa Model Portfolio. As a reminder, here is the portfolio composition:

• 60% stocks (via NTSX)
• 40% bonds (via NTSX)
• 20% trend (via DBMF)
• 10% commodities trend (via COM)
• 4% Tail risk (via TAIL)
• -34% cash

The idea behind the portfolio is stolen from here. The link offers the best explanation of what I think is the most common question related to it, i.e. why the portfolio uses leverage (and why, in this context, leverage decreases risk).

It represents a simplified version of the portfolio I have been building since I moved to Switzerland: here you can find details about the “enhancements” to this model.

Please note that the returns you find in the Model Portfolio series will always reflect the point of view of a USD-based investor. The ETFs are priced in USD and Testfol.io, the app I use to track the portfolio, does not allow me to change the reference currency.

Besides these ‘technicalities’, the focus of this series is on how to build a great and simple permanent portfolio. There are various solutions an investor can employ if they do not have the USD as their base currency and want to eliminate the FX volatility. As I wrote here about the All Weather Portfolio, I am not bothered by the FX risk, given my investment horizon and the fact that I do not consider myself a CHF-based investor even if I live in Zurich. Plus, I do not have any currency-specific audience that would make this series more helpful if run in EUR, CHF or GBP (if you want a deeper dive into FX risk, I wrote this).

After increasing 7.10% in Q3-25, the portfolio increased by 2.96% in Q4-25:

Since Inception, including a backtest period

The blue line represents the Model Portfolio, while the other two are functional references (I cannot really call them benchmarks): the 60/40 portfolio (yellow line) and the S&P500 (red line).

Q4

Since inception plus backtest (May, 2019). VBAIX is the 60/40.

Below you can find details of each ETF performance, including dividends, in the quarter:

Here is the Q4 price graph for each component of the portfolio:

How to read the portfolio performance

I have to admit I fell for the single-line item performance fallacy. NTSX is the ETF with embedded leverage that allows the addition of “free diversifiers” to the portfolio. I, wrongly!, judged the merits (or otherwise) of leverage within NTSX, thinking, for example, about the implications of an inverted yield curve (NTSX borrows at the short-term rate and invests in bonds that pay the long-term rate…not great when the curve is inverted).

Leverage belongs to the portfolio.

Not only that. COM and DBMF use futures; a small fraction of the sum invested in those ETFs is posted as margin while all the balance erns the T-Bills returns. In other words, if the Bills rate is 5% and DBMF returns 3%, it means DBMF alpha, the real yield of the strategy, was -2% for that year.

Bridgewater and State Street recently introduced ALLW, an ETF that is based on the famous Bridgewater All Weather risk-parity strategy. Here is a breakdown of the ETF’s current holdings:

Despite differences in asset allocation, the ETF and the model portfolio have maintained similar risk/return profiles to date:

Obviously, this observation doesn’t provide any deep insights; it’s merely an oddity. I’m curious to see how both will perform in a 2022-style environment. We likely won’t have to wait long to find out.

I was listening to the guys over at Click Beta, and they dropped a fascinating point: Emerging Markets didn’t even truly exist as a formalized “asset class” in the minds of most investors until after 2009. Think about that. We spent the “Lost Decade” of the 2000s watching the S&P 500 do a whole lot of nothing, literally flat, while EM was out there putting up legendary numbers. It was (almost) the only game in town.

Enter Jim O’Neill. In 2001, sitting at his desk at Goldman Sachs, he dreams up the “BRIC” acronym. It was a marketing masterstroke. But let’s keep it real: if you had tried to put on a “BRIC trade” in 1995, you would’ve been carried out on a stretcher. You would’ve watched your capital vanish in the 1998 Russian default, stagnated in China, and been whipped around by the volatility in Brazil. O’Neill didn’t discover these countries; he just perfectly timed the moment they finally stopped catching on fire long enough to look like a secular growth story. (Survivorship Bias, as well, enters the chat: in fact, we do not know how much Jim ‘s intuition was correct and how much it was pure luck)

Everyone knows the BRICS today, even after they tacked on South Africa to keep the party going, but hardly anyone talks about Jim anymore. Why? Because the trade stopped working. BRIC was the king of the 2000s, but it’s been a total disaster for the last 15 years. It begs the question: Was that decade of outperformance a normal cycle, or just a massive, one-time aberration fueled by a commodity super-cycle?

Look at the tape since 2010. If you stayed in Developed Markets (VEA), you didn’t just win, you crushed the EM index (VWO) by more than 250 basis points per year. And you did it with way less heartburn and half the volatility.

Over on Top Traders Unplugged, Cem Karsan is asking the same tough questions about the legendary 60/40 model. If you look at the decade-by-decade returns, the data tells a fascinating story:

Decade	Annualized Real Return (approx.)	Market Context
1900–1909	+6.3%	Pre-WWI industrial growth despite the Panic of 1907.
1910–1919	-4.7%	Lost Decade: High inflation from WWI and the 1918 pandemic.
1920–1929	+12.7%	The “Roaring Twenties” boom; massive equity gains.
1930–1939	-2.3%	Lost Decade: The Great Depression; bonds helped but couldn’t offset stock crashes.
1940–1949	+1.1%	WWII volatility and post-war inflation dampened growth.
1950–1959	+9.1%	Post-war economic boom; one of the best eras for 60/40.
1960–1969	+4.5%	Steady growth until the late 60s when inflation began to rise.
1970–1979	-0.3%	Lost Decade: “Stagflation” era; high inflation crushed bond prices.
1980–1989	+11.7%	Volcker’s interest rate hikes followed by a long bull market.
1990–1999	+11.7%	The Dot-com boom; stocks carried the portfolio.
2000–2009	+0.5%	Lost Decade: Two major crashes (Dot-com and 2008 GFC).
2010–2019	+8.2%	Post-GFC recovery and low-inflation environment.
2020–2024*	+3.6%	High 2021 returns offset by the “perfect storm” of 2022.

And here is the performance in two specific 20-year periods:

Period	Annualized Real Return	Cumulative Real Growth
1900 – 1919	~ +0.6%	~12.4%
1960 – 1979	~ +2.1%	~51.5%

All the above data are from Gemini.

Cem Karsan is hitting on a truth that most of the “indexing-is-religion” crowd ignore: Passive investing and the 60/40 portfolio didn’t just appear out of thin air in the ’80s. They became “things” because they started working. Before that? The performace was not so impressive.

If you pull the data from Testfol.io, the 60/40 has put up a 7.11% annualized real CAGR from 1980 through today. That is a great run. But look at the “Dark Ages”, the periods from 1900–1919 or 1960–1979. When you zoom out and look at the full 80-year picture (1900-1980), that return gets chopped in half to about 3.5%.

Here’s the reality: the entire financial industry is drunk on that 7.11% number. Your retirement calculator, your advisor’s ‘Monte Carlo’ projections, your own mental math—they’re all anchored to a period of outperformance that looks more like a lucky streak than a guarantee. If that number drops, your whole plan goes up in smoke.

Imagine a world where the next 40 years deliver 3.5% instead of 7%. Your “(early) retirement” plan just became a “good luck with those spreadsheets“. According to Bengen’s seminal research on Safe Withdrawal Rates (SWR), the worst 30-year cohort to retire in was 1966. Yep, not 2000 or 2007.

I bring this up because every time I talk about one of the pillars of my model portfolio, specifically Trend Following, the skeptics start screaming “data mining!” They want to treat Trend Following like it’s some failed Emerging Markets experiment: a strategy that had one good run and is now back to being “return-free risk” (even if it seems it worked for 221 years…).

I built this model the way I did to give people an easy “apples-to-apples” comparison with the 60/40, the undisputed heavyweight champion of the last half-century. I’ve been writing about this for three years, and even I’m surprised to see a 200bps raw outperformance with less risk.

But here is the kicker, and it’s classic human nature: Instead of seeing this outperformance and realizing they need more diversification (trend following or not), most investors are doing the exact opposite. They’ve decided bonds are trash, diversification is for losers, and the only way to play is “all-in” on stocks. Or delude themselves by calling diversification a mix of domestic stocks, international stocks, factors, sectors, Private Equity and…maybe Corporate Bonds.

Less protection, more concentration, right at the moment the 40-year tailwind is dying. What a wonderful world.

What I am readind now:

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