After one of our regular springtime walks through the neighborhood enjoying the flowering trees, neighborly hellos, and the smell of freshly mowed grass, my wife and I arrived back at our front porch. As I fumbled for the keys, she was clearly still thinking of the many beautiful homes we saw and had a moment of inspiration. “You know, we should really update our porch light. It’s completely rusted and the glass is cracked!” She had a point — it had definitely seen better days. So we hopped in the car and made a trip to the local hardware store. And that’s when things started to go downhill.
After browsing the insane number of light fixtures, we zeroed in on one we liked. But it seemed to generate more questions than answers.
“This one is nice, but the color is completely different from the other door hardware.”
“Maybe we should change that, too. And the door threshold while we’re at it.”
“Well if we’re doing that, we might as well also paint the door.”
“You know, the house could really use a fresh coat of paint, too.”
In the eternal words of Ron Burgundy, that escalated quickly. To the point where we left the store without purchasing anything and ended up selling the entire home and moving to an apartment downtown!
OK, maybe I exaggerated that last part and left out a few years of intermediate steps. But that first experience talking about a simple light fixture did become a running gag for us. It’s funny how small ideas can quickly snowball into big changes once you get past the first action and start the process rolling.
History has a way of repeating itself, and I had a similar experience more recently. It started innocently enough when I finally sat down to research ETFs that I would recommend to match each of the assets. No big deal, right? Well that simple task on my to-do list eventually expanded to a bunch of other related things. Fast forward several months, including countless hours of data research and 151(!) iterations of interface ideas, and the end result may not be a new home but the remodel is indeed pretty significant.
Long story short, a lot has changed here at Portfolio Charts. And it’s not only in what you see but also in how the utilities work behind the nicely painted drywall. So let’s dive in and talk about all of the home improvements.
New Portfolio Interface
The first thing you’ll probably notice is that the interface for each of the charting tools has changed quite a bit.
The biggest difference is that there are now fewer options than before. I’m not normally one to eliminate data, but one of the first things I learned when researching associated ETFs was that a bunch of the asset options I carried had no available index funds that track them. While that sort of purely academic data is interesting in an intellectual sense, one of my driving goals is to make Portfolio Charts not only educational but also actionable. So with that mission in mind, I think paring back on things you can’t easily invest in makes a lot of sense. Not only does it make the wall of options a bit less intimidating, but it also helps people focus on the choices that matter.
Beyond the simple asset count, there are two other changes worth mentioning. First, the World section and the associated countries have been reorganized to make the regional definitions a bit more intuitive. That includes making the Developed and Developed ex-US toggle a lot more prominent and adding a visual indicator under USA that helps describe what’s going on. And second, I did my best to add a few more descriptive labels to help explain the acronyms for new users. I understand it can be a lot of information to take in all at once, but hopefully this will help make things a little more clear.
Improved Data Quality
One of the nice side effects of weeding out the assets without real-world index funds is that it allows me to stop leaning so heavily on purely academic sources. As a result, I was able to give the underlying data a major overhaul with the goal of improving the overall historical accuracy of every asset. Without getting too deep into the weeds, the changes come down to definitions and sources.
It may not be obvious from the fund summary that lists your favorite stock fund in the “large cap” category, but if you read the fine print you may notice that most large cap funds include both large and mid caps. So where I used to separate them as two different assets, large cap now tracks the top 85% of the market and includes both large and mid caps consistent with how the majority of index funds work. Small cap covers the remainder of the market excluding the very smallest micro caps.
The bond data is similar to before and tracks long, intermediate, and short government bond ladders matching the methodologies of bond index funds. The one new wrinkle is that intermediate bonds now have slightly different maturity ranges that match the common local definitions of that particular type of bond. For example, the intermediate US bond data has a maturity range of 3-10 years, but intermediate European bonds have a range of 3-7 years matching the more popular local definition. The goal with any variation in model definition is simply to accurately describe the performance of the real-world funds.
For a detailed explanation of the index definitions, be sure to read the Index Funds page.
While my previous sources were largely academic in nature, I’ve taken advantage of the new emphasis on known fund performance to refocus on layering multiple sources to maximize accuracy. Fans of the Simba Spreadsheet should find this process very familiar as it follows a similar strategy, but here’s the short story of how it works.
I start by identifying popular index funds with preferred cap-weighted methodologies that match the definitions I described above. The measurable fund data takes precedence, and I simply rebate the expense ratio to match any other sources that do not include fees. For years before the fund inception date, I turn to data for the underlying index that the fund tracks. When that’s not available, I use academic sources and my own calculations. And in the event that there’s simply no data out there, I take it one step further and use similar-but-different assets along with my home-grown error measurement system that clearly shows on each chart when the results are only estimated.
Maybe that sounds simple on the surface, but picture individually collecting, verifying, and assembling all of those different sources for 75 different assets one-by-one. It was a TON of work! But I’m really proud of the end result, and I’m more confident than ever that it’s the most accurate and thorough set of free portfolio data that you’ll find anywhere.
For much more information about sources, including recommendations on where to find data to build your own personal collection, check out the dedicated Data Sources page.
Updated Portfolio Translations
Discussing portfolio theory for a global audience is sometimes trickier than you might think. So much investing advice is written from a US perspective, and it doesn’t always translate well. For example, let’s say a wise investing expert wrote a well-researched book recommending that you invest 40% your money in domestic US stocks, 30% in small cap value, and 30% in international stocks. Easy enough.
Well, what if you live in Italy?
Does “domestic” mean Italian stocks or European stocks? What if there are no good Italian small cap value funds available? And if you go the European path, what does “international” mean when world ex-Europe isn’t really a thing? Even with the best asset allocation on paper, things get confusing pretty quickly.
When offering non-US interpretations of US-centric portfolio concepts, I’ve always taken the simplest path of describing them primarily through the “domestic” and “international” lens where domestic means your own home country and international is a broad developed world fund. But the process of updating my data sources to include investable ETFs outside of the US was an educational experience, and it caused me to reevaluate how I interpret concepts for non-US investors. So when you visit the Portfolio pages or browse tools like the Portfolio Matrix, here’s how it now works when you change the home country.
US portfolios are always modeled to the best of my ability as described by the original author. Australian, Canadian, and Japanese portfolios use the classic domestic & international splits with local and world funds. Where it starts to get a little more interesting is in Europe.
The default translation for portfolios using simple assets like a total stock and intermediate bond fund is to use the classic domestic & international paradigm just like Australia, Canada, and Japan. Not only does it keep things nice and consistent, but it also generally follows the fundamental local diversification philosophy of strategies like the Classic 60-40 and Permanent Portfolio.
But once an asset allocation starts tilting towards things like small and value, many smaller markets don’t offer those types of funds and the idea begins to get watered down. So for those portfolios, I adopted a new mindset that considers Europe to be the larger domestic market. It’s not about politics — it’s just a simple investing reality. There are LOTS of different types of European ETFs spanning the small and value spectrum, so why not put them to good use?
As one example, here’s how I now model the famously diversified Merriman Ultimate portfolio for an Italian investor. The domestic portion is allocated to European funds while the international portion is allocated to US funds. And while it’s true that it excludes the Canadian and Pacific exposure that a US-based investor using an ex-US international fund would get, it’s also true that from a theoretical ex-Europe perspective the United States is the hulking elephant in the room that dwarfs everyone else. Combine that with a healthy availability of US index funds, and for most people that’s the best option without going overboard.
To really understand the details, I recommend not only playing with the individual portfolio tools but also reading the work of the original authors. It’s entirely possible you may disagree with my own interpretation for your country, and that’s perfectly ok! My goal is simply to help open your mind to new ideas and point you in the right direction, but I certainly don’t pretend to speak for the authors or know what works best for you personally. In fact, I’m all about self-empowerment. So fire up the fully customizable Charts and take charge.
Helpful Tools for Real People
I’ve been working on this stuff so long that I could probably go on for hours, but at some point it’s probably best to just let you start exploring. Here’s the 30,000 foot summary:
I did a whole bunch of work to make Portfolio Charts more accurate, intuitive, and actionable. And I hope you enjoy the results.
Some of the numbers and portfolio interpretations definitely changed, so be sure to check out the new data and explore how it affected your favorite asset allocation. Definitely let me know if you spot something that looks like a bug, as a change this big probably does include a few mistakes. And if you like what you see, please spread the word!
In the meantime, maybe now I can finally get back to that original task of listing the recommended ETFs for each asset. The work may have spiraled way beyond that original light fixture, but with that out of the way the foundation has finally been laid for lots of future development.
Until then, enjoy!
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