Yale University recently released their 2017 annual report for the Yale Endowment, and while normally this would pass without much notice they appear to have made a few waves by continuing an ongoing feud with Warren Buffett. In his 2016 investor letter, Buffett criticized how university endowments pursue market-beating returns through active management and suggested they might be better off investing in index funds instead. Of course the CEO of Berkshire Hathaway follows none of that advice himself, but he has consistently said that most investors including his own wife would be better off with a low-fee S&P500 index fund rather than paying expensive active managers so it’s certainly not out of character. In any case, Yale appears to have taken that a little personally and they dedicated an entire section in their annual report to dispute his claim and promote their own success.
To support their belief in active management, Yale provides data that proves their managers have exceeded stock market returns for the past two decades. For example, over the past 20 years they posted an average return of 12.1% versus 7.5% for the total US stock market which gives them confidence to say they “crush the returns produced by US stocks”. Ending with a flourish, they conclude that “not only has the model worked for the past two decades, it will work for decades to come.”
That’s bold. And it caused a bit of a tizzy in the financial blogosphere with several stories on the topic. So are they right?
Asset allocation is a obviously passion of mine, and I’m always excited when I find a new metric to tinker with. These new ideas are not only interesting in their own right, but they also allow me to go back and refine some older tools to make them even better. And it’s hard to think of a more appropriate place to start than one of my personal favorites — the Portfolio Finder.
I went shoe shopping today for the first time in a while, and I forgot just how frustrating it can be. Finding a nice pair of shoes seems like it should be a pretty simple task these days, but the number of options makes it much more difficult than you’d think! It’s kinda surreal to walk through aisles and aisles of shoes and immediately dislike about 90% of them for one reason or another, and even the ones you like may not be that comfortable once you try them on. Buying shoes can be a real pain.
Well if you think about it, finding a good portfolio is a similar experience — there are lots of good options but very few easy answers. I do my best to curate some of the best options to avoid the cheap knockoffs likely to wear a hole in the sole on the first walk, but just like there’s no one pair of shoes for every person there’a also no single best portfolio for every investor. So you’ve gotta try them on for yourself.
I once knew a guy who was really into woodworking. One of the more fascinating things about him was that he not only made his own furniture but also was quite proud of his collection of hand-made woodworking tools. I once asked him why he preferred those tools to mass-produced alternatives. Among several reasons, “They do what I want”.
Some casual investors may wonder why I spend so much time investigating things like modeling mid caps and figuring out how to measure the error of older international bond data in backtesting calculations. While I certainly find this kind of information intellectually interesting, I admit that it sometimes becomes a chore and I can see why most people steer clear. The upside to all the groundwork, however, is that it expands my collection of tools and allows me to do what I want — explore interesting portfolios previously off limits simply due to lack of data.
Like, for example, the 7Twelve Portfolio.
In the late first century, a Latin poet named Juvenal described something thought to be unlikely as “a rare bird in the lands and very much like a black swan”. At the time, black swans were thought to not exist at all and the idea was preposterous. The clever turn of phrase was both memorable and descriptive, and by the 16th century “black swan” was a common expression in London to describe the idea of impossibility. Of course there was a looming problem with this saying, and in 1697 Dutch explorers discovered that black swans really do exist in western Australia. What once was used to describe something impossible quickly changed meaning to connote ideas thought to be impossible that are later discovered to be real.
Interviewing contractors to work on your home is an interesting exercise in managing expectations. Purchasing a product where you know exactly what you’re getting ahead of time is a lot different than purchasing a service where the end result can never be fully appreciated until the work is complete. Who you choose to do the work thus becomes the most important step, but it’s also the trickiest to navigate.
The salesmen dress in their finest clothes and are on their absolute best behavior, and they all claim to have a glowing track record and seem to be very capable. You know intuitively that not all companies can be above average and that some crews are measurably better than others, but looking at their finely curated portfolios of their absolute best work it’s sometimes hard to tell the truly talented craftsmen from the ones who only talk about their few successes.
Without the benefit of a crystal ball to see all the surprise issues they’ll have to navigate on your project and how they will react, the best one can generally do is study the history of the company and check their references. By gauging how consistently they delivered what they promised and exceeded customer expectations over time, one can learn something about their character and gain enough confidence to hand over your hard-earned money to a company with a trustworthy reputation.
There’s a similar issue in investing, although the stakes are even higher.
Perhaps because of how prominently it features in the Portfolio Finder, I’ve noticed a great deal of questions and conversations about the Golden Butterfly portfolio of late. Rather than scatter my thoughts around the internet, I realized it might be best to provide a centralized synopsis of how and why it works so that everyone can benefit.
My single favorite toy as a child really wasn’t a single toy. It was my giant bucket of LEGO accumulated over many years. The beauty of LEGO is that the combinations are absolutely limitless and the things you can build with them are constrained only by your imagination. Well… and access to all the right pieces.
You see, when building a spaceship, race car, or castle it’s sometimes not good enough to have a big bucket of parts. You need to have the right parts. The right color for the walls, the right size to fit in a tight space, or the right shape to make a respectable wheel or wing. Many hours were spent browsing the toy aisle not for the final product pictured on the box, but for just the right part in the kit to add to my collection. Without the right building blocks, the best designs just aren’t the same.
For a while now Portfolio Charts has been focused on the LEGO kits — the portfolios that you can build for yourself and the calculators to help you do it. But I’ve known for a while that it’s been missing an important ingredient. Today I’m happy to unveil brand new section to the site dedicated to the portfolio building blocks themselves — Assets.
I love perusing message boards, and a recent conversation on the All Seasons portfolio mentioned in Tony Robbins’ recent book naturally piqued my interest. It’s based on the highly respected work of Ray Dalio (of Bridgewater All Weather Fund fame), but pared down to a form that a normal non-institutional investor can easily implement themselves.
With a focus on wide diversification and risk parity for a variety of economic climates, the fundamental theory behind the All Weather Fund has always appealed to me. So it was refreshing to find a simplified version endorsed by Dalio to compare against other lazy portfolio options.
After publishing a few tools and articles based on safe withdrawal rates, one of the most common questions I’ve seen so far is some iteration if this:
Obviously higher returns support higher withdrawal rates. That’s why I invest in 100% stocks! How can a lower-return portfolio possibly support higher withdrawal rates than a higher-return portfolio?
I admit the answer is fairly unintuitive, and explaining this without getting too deep into the weeds is a bit of a challenge. I’ve touched on it here and there around the site, but this is an important concept that deserves a thorough explanation.