Archive | Research

The True Cost of Foreign Withholding Taxes

Back in the fall of 2012, I wrote a pair of blog posts about the impact of foreign withholding taxes in US and international equity funds. The first explained the general idea of this tax on foreign dividends, while the second showed which funds are best held in which types of account (RRSP, TFSA, non-registered). This is a complicated and confusing topic, so I was surprised at the enormous interest these articles generated from readers, the media, advisors and even the ETF providers themselves.

What was missing from those articles, however, was hard numbers: it’s one thing to say this fund is more tax-efficient than that one, but by how much? To my knowledge no one has ever quantified the costs of foreign withholding tax in a comprehensive way—until now. Justin Bender and I have done this in our new white paper, Foreign Withholding Taxes: How to estimate the hidden tax drag on US and international equity index funds and ETFs.

The factors that matter

The amount of foreign withholding tax payable depends on two important factors. The first is the structure of the ETF or mutual fund.

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Ask the Spud: Is There an Optimal Portfolio?

Q: I’m new to passive investing and am deciding how to allocate between the asset classes. The best split between Canadian equity, international equity, etc. should be determinable based on studies of their past returns, volatility and correlations. Obviously this would vary over time, but approximate weightings should be achievable. Based on this research, how would you weight the individual asset classes? – R.T.

It would look impressive if I designed my model portfolios based on an analysis of historical volatility, correlation matrices and expected returns based on Shiller CAPE or some other data. But instead I generally recommend a roughly equal allocation to Canadian, US and international stocks. Nice and simple, with no advanced math required. This is isn’t because building a “portfolio optimizer” is difficult: it’s because it’s a useless exercise.

Investors have a tendency to resist simple solutions, and this bias is exploited by fund managers and advisors who use algorithms and models designed to determine the “optimal” asset mix that will maximize returns and minimize volatility, sometimes down to two decimal places. That sounds more sophisticated than simply splitting your equity holdings in three, but there’s no evidence it produces better results.

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The Failed Promise of Market Timing

I’ve long believed the most difficult part of being a Couch Potato investor is resisting temptation. Index investors are asked to be content with market returns, but they are bombarded daily by fund companies, advisors and market gurus who promise more.

Back in May 2012, I wrote about one of these enticing strategies, described in The Ivy Portfolio by Mebane Faber and Eric Richardson. The so-called Global Tactical Asset Allocation (GTAA) strategy grew out of Faber’s widely read research paper, A Quantitative Approach to Tactical Asset Allocation, first published in 2007. It begins with a diversified portfolio inspired by the Yale and Harvard endowment funds, combining traditional and alternative asset classes. The “tactical” part involves using market timing to move in and out of these asset classes based on 10-month moving averages.

Faber updated the paper in early 2013 and it now includes four full decades of data. From 1973 through 2012, the GTAA strategy shows exactly one negative year: a modest loss of –0.59% in 2008. And over those 40 years, the GTAA delivered an annualized return of 10.48% with a standard deviation of 6.99%,

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Looking for Value in Canadian Equity ETFs

Monday’s post about factor analysis was, I admit, too technical for most readers’ tastes. At least that’s the conclusion I drew when the two most enthusiastic comments came from a professor of statistics and an astrophysicist. But the brave few who managed to read to the end saw my promise to put all this in context. What can factor analysis teach us about where an ETF’s returns are really coming from?

Two decades of research has shown that the returns of a diversified equity portfolio can largely be explained by its exposure to three factors: the market premium, the value premium, and the size premium. A broad-market index fund like the iShares S&P/TSX Capped Composite (XIC), by definition, should be neutral in its exposure to the value and size premiums. And as we saw in my previous post, it is: the value and size coefficients for XIC are negligible. So, on to the next step.

Let’s now take a look at the iShares Dow Jones Canadian Value (XCV) and the iShares S&P/TSX Small Cap (XCS).

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Going on a Factor-Finding Mission

Pick up almost any financial magazine or newspaper and you’ll find full-page ads touting the recent performance of mutual funds and ETFs. What’s the reason for their outperformance? The fund companies will give the credit to the genius of the manager, but there’s a way you can tease out a more complete explanation: it’s called factor analysis.

Don’t worry, I’m not going to get all mathy on you—well, maybe a little bit. Performing this kind of analysis is complicated, but understanding the basic ideas doesn’t require a a Ph.D. in statistics. We know  investment returns come from exposure to known risk factors (or premiums), and every equity portfolio is exposed to these in varying degrees. What we want to learn is how much each factor contributed to the fund’s returns. If the fund outperformed or underperformed its benchmark, factor analysis can tell you why.

Just the factors, ma’am

What are the risk factors? The first is the market premium (or equity premium), which is simply the expected excess return from stocks compared with risk-free investments like T-bills. The second is the value premium: stocks with high book-to-market ratios have historically delivered higher returns than growth stocks.

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More Power in Passive Portfolios

Rick Ferri and Alex Benke recently collaborated on an interesting white paper called A Case for Index Fund Portfolios, which I introduced in my previous post. They compared index portfolios to thousands of randomly generated active portfolios to estimate the probability of outperformance. Passive came out ahead in about 80% to 90% of the trials, which is compelling enough. But there were some surprises, too. Let’s look at a few of them.

Indexing gets better with age

Ferri and Benke’s paper was novel in that it looked at portfolios rather than individual funds. They found that combining index funds led to greater outperformance than you would expect from examining the funds in isolation. In other words, the portfolios were greater than the sum of their parts. The authors called these factors Passive Portfolio Multipliers, or PPMs

One of these PPMs highlights the importance of taking a long-term view. Ferri and Benke looked at the five-year periods ending in 2002, 2007 and 2012. The first of those periods includes the dot-com bubble, while the last includes the worst market crash since the Great Depression. Not surprisingly,

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Putting the Portfolio Odds in Your Favour

It’s well known that the majority of actively managed mutual funds underperform comparable index funds over any period longer than a few years. In fact, that statement has become so uncontroversial that even mutual fund salespeople freely acknowledge it. But a recent white paper co-authored by Rick Ferri, A Case for Index Fund Portfolios, takes this idea a step further.

Academic studies of mutual funds go back to the 1960s, and the well-known SPIVA scorecards are updated twice a year. So there’s no shortage of data on individual funds. But investors don’t use mutual funds in isolation: they build portfolios of funds in several asset classes. And there has been surprisingly little research on the performance of actively managed portfolios compared with passive alternatives.

Ferri introduced this idea in The Power of Passive Investing in 2011, and I wrote about his findings when that book came out. Now Ferri and his co-author Alex C. Benke have improved the analysis using more robust data. “The probability of outperformance using the simplest index fund portfolio started in the 80th percentile and increased over time,” the authors write in their summary.

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Seeing Diversification in Action

Why should you add multiple asset classes to your portfolio? That seems like a simple question, but it’s one many investors would answer with only a vague comment about “more diversification.” It’s more precise to say you do so to increase expected returns or to decrease volatility. Sometimes these are mutually exclusive, but Harry Markowitz won a Nobel Prize for explaining that you can sometimes accomplish both at the same time. That insight is the basis for Modern Portfolio Theory.

One of the clearest illustrations of this idea can be found in Larry Swedroe’s book Think, Act, and Invest Like Warren Buffett, which I reviewed late last year. Swedroe shows how the return and risk characteristics of a 60/40 portfolio change as you slice and dice the equity allocations.

A portfolio made up of just the S&P 500 and five-year Treasuries returned 10.6% annually from 1975 through 2011, with a standard deviation of 10.8%. By gradually splitting that equity allocation into multiple asset classes (international stocks, value stocks, small caps, and commodities) the portfolio’s annual return increased 150 basis points to 12.1%,

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Why Your Problem Is Not Your Funds

In Monday’s post I looked at “smart beta,” which promises to outperform cap-weighted indexing strategies. I’m frequently asked if I think Couch Potato investors should dump their traditional index funds in favour of these tempting alternatives. Here’s why my answer is no.

I could rhyme off technical reasons for being skeptical about the outperformance of alternative indexes: the research ignores costs and taxes, the strategies may not work in the future, and so on. But I won’t go down that road, because the most important reason is not technical, but behavioral.

Everything beats the market—except investors

To recap, two recent papers from Cass Business School in London looked at US stocks from 1968 through 2011, a period when a cap-weighted portfolio would have returned 9.4% annually. (Canadian stocks had an almost identical return over those 43 years.) The researchers examined 13 alternative strategies—which favoured value stocks, small-cap stocks or low-volatility stocks—and found all of them outperformed, with returns between 9.8% and 11.5%.

For many people, the takeaway from these findings is, “I should use alternative indexes, because I can beat the market by a point or two.” My reaction is different: I want to know how many investors earned even 9.4%.

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