Permanent Portfolio Strategy | Low Risk And Easy To Maintain | Does It Really Work?

by Andrea Unger

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How do you invest the profits made with trading so you can manage risk in the best possible way? 

One possible solution is represented by the asset allocation models proposed by investment experts over the years. 

In this video, we test the effectiveness of one of these models, the “Permanent Portfolio” by analyst Harry Browne in the 1980s. It's a portfolio made up of 4 different assets that is rebalanced annually and aspires to perform well in all market conditions.

Watch the video to find out how the Permanent Portfolio works and what results it would have produced over the last few decades!



Hello everybody, and welcome to this new video.

I am one of the coaches of Unger Academy, and today I'd like to talk about “Permanent Portfolio”, a portfolio model that was created by analyst Harry Browne in the 1980s.

So, why am I talking about investment models? I mean, you know that we generally talk about things that are more closely related to systematic trading, right?

The reason is that it can be extremely useful to know how to diversify the allocation of the profits you make with your trading systems. 

 The asset allocation models I'm presenting in these videos allow for an easy allocation of the capital and so, they can turn out to be very useful.

So, today we are talking about the Permanent Portfolio allocation model devised by analyst Harry Browne in the 1980s. The purpose of this allocation model is quite similar to that of the model we've seen last week, which is Ray Dalio's All Weather, because also in this case the main goal is being able to gain in virtually every market condition.

To achieve this purpose, the author suggests building a portfolio made up of 4 different assets and investing 25% of the capital in each of these components. In particular, he suggests investing 25% in US stocks (for example, you can invest in the SPY ETF, which is the ETF on the S&P 500). Then he suggests investing 25% of the capital in long-term US government bonds (in this case, you can use the TLT ETF, for example). Another 25% should be invested in cash because, in Browne's opinion, liquidity could be useful in periods of recession. Instead of cash, however, you can decide to invest in short-term bonds such as the US Treasury Bills for example. In this case, I’ll use the SHY ETF, which is composed of bonds with remaining maturities between 1 and 3 years. Finally, the remaining 25% should be invested in precious metals, Gold in particular. The purpose of including precious metals in the portfolio is that they should be able to protect you in periods of high inflation.

I haven't mentioned it yet, but investing 25% of the capital in stocks should be helpful in periods of prosperity, and investing 25% in long-term bonds, such as the TLT EFT for example, should be helpful both in periods of prosperity and in periods of deflation, which is the opposite of inflation, so when Gold and the other precious metals may not perform at their best.

Once again, I've used our asset allocation software - the one we created internally at Unger Academy - to test this portfolio. The portfolio is rebalanced annually, which means that the weights of the four assets that compose it are rebalanced once per year.

Let's start by testing a portfolio made up of the ETFs I have already mentioned. On the left, you can see a logarithmic scale because, as you know, on a medium-long time horizon it's generally convenient to evaluate things on a logarithmic scale since profits are reinvested.

As you can see, this model has actually managed to produce consistent results over the years. For example, it performed quite well in 2008 and 2009. Ok, it didn't produce any profits in that period and, actually, it even made some slight losses and suffered a little bit, but, all in all, we can say that it behaved quite well, considering what happened in the markets in those years. Let's compare the drawdown of the strategy with that of the benchmark, which is S&P 500. The maximum drawdown of the strategy is 14.07% while that of the benchmark is 57%. This proves that the logic behind this asset allocation model would have protected the investor from particularly harmful markets phases.

If we go and see the annual performance report of the portfolio, we can see that the strategy worked pretty well. In 2008, for example, it would have made a 2% profit. If we held the SPY, so the ETF on S&P 500, we would have made a -38%, which means that we would have lost a lot of money. So, all in all, the strategy seems to work.

Now let's see what happens by replacing the ETFs with indexes. Of course, I know that you can't buy indexes, but by running this simulation, we can evaluate how the strategy would have performed over a longer period of time. In fact, the ETFs we used in the previous test were issued quite recently, which means that the historical data to test our strategy is not long enough to evaluate its performance in the more distant past. So, by replacing ETFs with indexes we have longer historical data available. 

So, here's the test starting from 1995. Obviously, since then the strategy would have gone through different market conditions and more periods of crisis. For example, here we can see the dot-com bubble that hit Nasdaq in the early 2000s. As you can see, even in this case, the curve of the strategy seems to be quite constant or, at least, it certainly is more linear than that of S&P 500. In fact, we can see that the strategy would have even gained also in periods of significant falls when holding the benchmark – so the S&P 500 alone - would have produced rather large losses.

In this case, too, the drawdown of the strategy is significantly lower than that of the benchmark.

Speaking of returns, the average annual return of the strategy, so it's C.A.G.R., is equal to 6.57%. That of S&P 500, instead, is 8.87%. However, risk is considerably higher, as we can see from the red curve, which is clearly more indented.

Let's take a look at what would have happened more recently. The downward spike here occurred in March 2020, so in the most acute and critical stage of the Covid pandemic from the markets perspective. We can see that all in all, the drawdown of the strategy wouldn't exceed 12%, while if we had held S&P 500 or one of its ETFs, the drawdown would have been considerably higher, about 30-35%.

So, this rather simple strategy, which is very easy to follow and also requires little effort, can be very useful. And it’s also quite inexpensive, as the rebalancing happens once per year and involves only four assets.

Well, guys, this short analysis of the Permanent Portfolio asset allocation model ends here. We have seen how it works, its composition, and the results it would have made in the past. However, we have also seen some differences between this model and the one I showed you last week, which is Ray Dalio's All Weather portfolio.

It's up to you now to further explore this interesting and very well-known topic. 

If you liked this video, I invite you to please leave us a "Like" and of course, please share it. And if you haven't done it yet, also subscribe to our channel to stay updated on all our new content!

Also I remind you that if you click on the link in the description of this video, you'll find a completely free webinar. It's an introduction to the creation of trading systems and well-diverse portfolios of automated strategies following the method of the 4-time world trading champion Andrea Unger.

See you in our next video, discovering together other aspects related to the world of trading systems and online trading! Goodbye everyone!


Need More Help? Book Your FREE Strategy Session With Our Team Today!

We’ll help you map out a plan to fix the problems in your trading and get you to the next level. Answer a few questions on our application and then choose a time that works for you.


Andrea Unger

Andrea Unger here and I help retail traders to improve their trading, scientifically. I went from being a cog in the machine in a multinational company to the only 4-Time World Trading Champion in a little more than 10 years.

I've been a professional trader since 2001 and in 2008 I became World Champion using just 4 automated trading systems. 

In 2015 I founded Unger Academy, where I teach my method of developing effecting trading strategies: a scientific, replicable and universal method, based on numbers and statistics, not hunches, which led me and my students to become Champions again and again.

Now I'm here to help you learn how to develop your own strategies, autonomously. This channel will help you improve your trading, know the markets better, and apply the scientific method to financial markets.

Becoming a trader is harder than you think, but if you have passion, will, and sufficient capital, you'll learn how to code and develop effective strategies, manage risk, and diversify a portfolio of trading systems to greatly improve your chances of becoming successful.