Now that inflation is raging at highs not seen in the last 40 years, it’s no wonder that investments which guard against inflation have been experiencing a massive influx of money. With billions of dollars of new inflows every month, Treasury Inflation-Protected Securities (commonly referred to as TIPS) have quickly become some of the hottest portfolio options for nervous investors. And since questions about TIPS on message boards and in my inbox are apparently directly proportional to those cash flows, this feels like a good time to dig into the topic and separate the measurable truth from what passes as common knowledge.
How do TIPS work? How often have they succeeded in generating a real return above inflation? And are they really better than normal bonds without the inflation protection? Stick with me, and I wager you’ll learn a few things that may surprise you.
One of the core assumptions baked into all of the Portfolio Charts calculations is the idea that the portfolios are rebalanced once a year back to their target percentages. While that simple process seems rather mundane on the surface, there’s actually a bit of mathematical magic going on that often gets lost in broader portfolio discussions. Yes, maintaining your target asset allocation is an important part of risk management, but it goes so much deeper than that. What if I told you that, like a lonely plant in a barren desert, in the right conditions rebalancing can cause profits to seemingly appear out of nowhere?
That peculiar phenomenon can clearly have a major impact on the way people think about diversification in their investments. So let’s unpack the mystery and talk about the elusive rebalancing bonus.
December is often the time of retrospection and yearly wrap-ups, with stories recapping events of the last year and looking forward to new opportunities. In the finance space, you’ll find endless collections of the top performers of the year and forecasts for the one to come. While that’s all interesting and comforting in its own ritualistic way, this holiday season I decided to revisit a bold question that’s much bigger than short-term market news cycles:
What do the most efficient portfolios in history have in common?
Truly understand that answer, and much of the market noise that worries you from day-to-day and year-to-year loses its power over not only your emotions but also your account balances. So if you’ve ever wanted to think beyond your investing assumptions and explore the data for proven ways to approach timeless portfolio problems, grab a cup of coffee and pull up a chair. This article is for you.
Buried in an otherwise mind-numbingly boring regulatory filing released recently was a seemingly innocuous line item that most people would not give a second thought. Sometime in the second quarter, Berkshire Hathaway invested a comparatively tiny 0.3% of their total portfolio into just a single new company. No big deal, right?
But it wasn’t just any company. After spending decades as perhaps the most respected and widely-cited critic of gold as an investment, Warren Buffett bought 21 million shares of Barrick Gold — one of the largest gold mining companies in the world. It was so out of character that the financial world immediately did a huge double-take. The headline from Bloomberg pretty much speaks for itself:
Berkshire Makes a Bet on Gold Market That Buffett Once Mocked
As one might expect, investors on both extremes of the gold-appreciating spectrum are furiously debating what this all means. Buffett’s closest gold-averse followers are circling the wagons and dealing with a lot of cognitive dissonance, while gold bugs are enjoying dishing out some playful jabs after years of being on the receiving end. Lost in the middle is a vast sea of normal investors watching the news and searching for actionable information.
This article is for that last group just wanting to know the truth about gold and what it can (and can’t) do for their own portfolios.
Sometimes the simplest investing concepts we take for granted are actually a lot more complicated than we think. For example, reasonable people might rationally assume that two small cap value index funds should have identical returns since they theoretically follow the same asset. But it doesn’t really work that way because definitions matter. What does “small cap” mean? Who defines “value”? Read the fine print and two similar funds may be a lot more unique than you realize.
I’ve been thinking about that subtle complexity recently, as in the process of finalizing the most recent annual Portfolio Charts data update I refined the definition of “small cap” to better match common index fund methodologies. The tweak was simple enough, but succinctly explaining what it means and why it matters got more and more difficult the longer I thought about it. The entire process made me realize it might be a good time to have a longer discussion on how stock index fund definitions work.
So if you’ve ever looked at an assortment of large, mid, small, blend, value, and growth stocks and wondered what all of that actually means, this article is for you. It’s going to get a little technical, but if you stick with it you’ll learn something not only about how indices are constructed but also how to use that info to interpret the data you find both here and elsewhere.
An interesting recent trend I’ve noticed in portfolio discussions is a renewed debate about the resilience of factor premiums versus the good old cap-weighted stock market. It’s entirely predictable that a tough stretch for any investment has a way of bringing out both the nervous supporters on one side and the proud haters on the other. But I really can’t fault the pros for keeping an eye on performance of some of the trendier factors or the investing laypeople for wondering what everyone is even talking about.
What do I think? It’s complicated. So let’s talk about factor investing.
I’ve flown a lot over the years, and I understand first-hand how all of the little details like packing, efficiently getting through security, and getting settled on the plane become so routine for frequent travelers that they can do them without even thinking. But occasionally life throws you a curveball, just as it did on a recent flight where I was without my normal headphones. Stuck for several hours with nothing but the drone of the engines to keep me company, I can’t say I was thrilled but it turns out it was just the inspiration I needed to explain a complicated concept:
How do consistent portfolios full of volatile assets actually work?
Sure, I could go into a detailed discussion of covariance, standard deviations, and the complicated math behind efficient portfolio construction, but frankly I know I would quickly lose most people and even bore myself in the process. So inspired by the the desire for silence I normally take for granted, let’s step back and think of the problem a little differently in terms we can all relate to — noise.
When discussing historical investing data one of the more interesting points that inevitably arises is the question of just how applicable past results are to current events and future investing decisions. Some people reject all historical data as completely irrelevant because the future will never look exactly like the past, while others hold up mathematical evidence-based investing as some sort of scientific principle that one would be foolish to question. I imagine one might expect me to fall into the latter camp, but frankly I think it’s more complicated than that. Good data speaks for itself but unless you’re speaking the same language you can easily get the message completely wrong.
In the world of investing, it seems most people’s energy is focused squarely on stocks. Massive amounts of research goes into stock investing every day and even casual investors have an incredible amount of information at their fingertips. Combine that wealth of data with a long term growth pattern in the stock market since 2009 that means anyone who has been in the market less than ten years has no recollection of a single meaningful bear market, and stocks are so ingrained on our collective investing consciousness that many people don’t give other assets a second thought.
As a result, while bonds were once staples of any self-respecting asset allocation lots of investors just aren’t into them like they used to be. Some of it is definitely recency bias, and I think another factor is that many people don’t truly understand how bonds work. But I’ll concede that the bond market is also different than it was more than a decade ago, and I can understand why people might think twice about relying too much on historical data. After all, bonds sound like awesome choices when they paid 10% interest, but consistent declining rates over time surely boosted any backtested numbers while depressing yields today to something a lot less desirable. So it’s no surprise that I see questions along this line all the time:
With record low interest rates today that are even negative in some situations, what’s the point of having bonds in a portfolio at all?
That’s a very good question. And the full answer is kinda complicated and includes some advanced finance mechanics that fly under the radar even for very experienced investors. But explaining complicated concepts is kinda my thing, so let’s talk about a little thing called bond convexity.
If you’re one of the millions of people launching into the gift-buying spree this holiday season, then there’s a good chance you’re inundated with numbers right now. From performance statistics and customer ratings to price points and discount percentages, smart shoppers are in a constant search for the best bang for the buck. Even if you’re not the type of impulse shopper that particularly enjoys the experience of browsing the aisles for just the right gift, experienced marketing professionals have learned that maximization of value is a powerful motivator that can pull even the strongest introverts into crowded stores against their better judgement. Why do you think they spend so much money on Black Friday ads touting record-breaking deals?
After a lifetime of this type of shopping conditioning, it’s no wonder that this same maximization mindset might bleed into other decisions as well. Like, for example, what asset allocation you might choose for your life savings. So the same highly intelligent shoppers often create very similar lists of investing options sorted by the most common performance metric available — average return. Just like how you might seek the best resolution for a new computer monitor or the highest customer rating for a new toy, you surely want the highest average return for your hard-earned savings. Right?
Unfortunately it’s not that simple. Contrary to your data-driven instincts, averages lie. So take a break from your holiday shopping, find a comfortable chair with your favorite drink, and let’s talk about how averages distort our thinking.