January 29, 2026

Episode 394: Equal Weight vs. Market Cap Weight Index Funds

January 29, 2026

Equal-weighted index funds sound like an elegant solution to some of today’s biggest investor anxieties: high market concentration, elevated valuations, and outsized influence from a handful of mega-cap stocks. In this episode of the Rational Reminder Podcast, Ben Felix, Dan Bortolotti, and Ben Wilson take a deep, evidence-based look at whether equal weighting actually improves portfolios—or simply introduces new risks under a different name. The discussion breaks down how equal-weighted indices differ fundamentally from traditional market-cap-weighted indexes, why equal weighting has historically outperformed in certain periods, and what’s really driving those results beneath the surface. The team explains how equal weighting tilts portfolios toward smaller, cheaper, and more volatile stocks, while also systematically trading against momentum due to frequent rebalancing.

Key Points From This Episode:

(0:01:10) Introduction to Episode 394 and discussion about declining enthusiasm over long podcast runs.

(0:02:00) PWL Capital’s growing work with institutional clients and why index-based approaches are rare in that space.

(0:05:12) Episode topic introduced: equal-weighted index funds and why listeners keep asking about them.

(0:06:00) Definition of market-cap-weighted vs. equal-weighted indexes using the S&P 500 as the main example.

(0:07:14) Historical outperformance of equal-weighted S&P 500 indexes and why start dates matter.

(0:09:00) Equal weight vs. cap weight performance over the last decade: meaningful recent underperformance.

(0:10:21) Market concentration concerns and why equal weighting appears attractive during periods of high valuations.

(0:12:00) Why market-cap-weighted indexes do not mechanically buy more overvalued stocks as prices rise.

(0:16:14) Trading costs explained: explicit vs. implicit costs and why turnover matters more than TER.

(0:19:16) Capital gains, tax efficiency, and reporting differences between Canadian and U.S. funds.

(0:21:07) Market concentration historically shows little relationship with future returns.

(0:24:58) Volatility comparison: equal-weighted indexes are meaningfully more volatile due to small-cap exposure.

(0:25:12) Equal weighting increases exposure to small-cap, value, and high-volatility stocks.

(0:28:58) Sector distortions created by equal weighting and why this represents uncompensated risk.

(0:31:21) Unintended consequences: sector bets, security-level overweights, and forced rebalancing.

(0:32:30) Turnover is roughly 10× higher in equal-weighted funds than cap-weighted equivalents.

(0:33:15) Equal weighting behaves as a systematic anti-momentum strategy.

(0:34:02) Multi-factor regression results: positive size and value exposure, negative momentum loading.

(0:36:33) Rebalancing frequency trade-offs and how quarterly rebalancing amplifies momentum drag.

(0:42:21) Comparison with alternative approaches that target similar factor exposures more efficiently.

(0:44:47) Why backtests are seductive—and why live fund results matter more.

(0:47:40) Investor behavior, uncertainty, and the constant search for strategies that “fix” the market.

(0:48:41) Factor investing in disguise: most deviations from cap-weighting are just factor tilts.

(0:53:06) Equal weighting as an acceptable strategy—if investors understand and accept the trade-offs.

(0:57:18) Listener feedback, enthusiasm jokes, and discussion about Spotify video uploads and audio speed.

Read The Transcript:

Ben Felix: This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from three Canadians. We're hosted by me, Benjamin Felix, Chief Investment Officer, Dan Bortolotti, Portfolio Manager, and Ben Wilson, Head of M&A at PWL Capital.

Ben Wilson: Welcome to episode 394 of the podcast. We got an interesting topic to discuss today. Look forward to getting into it.

Ben Felix: I don't know if anybody noticed that unenthusiastic pause after I said the introduction there, but we did get some feedback that our enthusiasm has fallen since episode 80, back with me and Cameron. So we're going to work on our enthusiasm. I just want everyone to know we will read that feedback at the end of the episode, which we appreciate. We genuinely appreciate the feedback. It was just funny to read.

Dan Bortolotti: Well, the listener just said we sounded tired, which is accurate.

Ben Felix: We sound tired and that there are long, long pauses. Nobody says anything.

Ben Wilson: You said compared to episode number 80. Well, we're now at 394. Yeah. It's tired. It's a lot of work, but it's still exciting to be part of it.

Ben Felix: I've aged. I've aged a lot. I'm a little more tired than I was in episode 80. It's true.

Dan Bortolotti: You've been through a lot, Ben.

Ben Felix: I don't know if we said this is episode 394.

I do want to say real quick before we get into the topic that an area that PWL has been increasingly active in working with clients in is with institutions. So that's things like foundations, endowments, reserve funds for not-for-profit organizations. The institutional space is fascinating.

There are not a lot of firms out there that are working with institutions and just telling them to buy index funds. Warren Buffett has had some great comments about the institutional space over the years, about how consultants, institutional consultants are not going to tell you to buy index funds because it is their job to find stuff that is better. That's just not the advice that you tend to get in the institutional world.

But I can tell you from our experience working with institutions, it's for the investment committees that get it, that they're tired of seeing poor performance. They're tired of having to turn over their managers every few years because they're not performing as well as they were supposed to be. They find it very refreshing to hear that there's a firm that will just say, we will buy index funds for you and help you manage your asset allocation and spending policy over time.

It's not a service that really exists in that space. Anyway, if there's anybody listening that is on an investment committee, an institutional investment committee that would be interested in hearing what it looks like to work with a firm like PWL, we would love to talk to them.

Ben Wilson: Yeah. I think the most interesting part about that is the fact that most financial institutions that are providing services to these institutional clients is it's simply the investment management, whereas we're taking a different angle and offering some financial planning that's applicable to institutions. Obviously, not the same as personal financial planning, but we can apply it in a context that's relevant to them.

That's a new offering that the ones that we've talked to, at least, have not experienced.

Ben Felix: You're absolutely right, Ben. I've seen it from the PWL perspective because we work with some institutions, as I mentioned, but then I've also seen it as a volunteer on investment committees. Like you said, it is the conversations that most institutional managers are having with their clients are not about asset allocation, not about spending policy.

It's the financial planning stuff that you're talking about. It's all about performance.

Ben Wilson: How you're justifying that you're going to outperform beta and how can you prove that over this next X period, you're going to do better?

Ben Felix: Like I said, I think it's refreshing for when investment committees that are prepared to hear it hear the PWL message and they're like, oh, those benchmarks we keep underperform, we can just invest in those? That's great. All that to say, it's an area that I think we're having some success in.

PWL is having some success in and we would love to grow that part of our business. If anyone listening has a way to put us in touch with an institution that they care about, we would love to talk to them. The topic that I have for today is, there were a couple of topics I was telling you guys earlier.

There are a couple of topics that over the last, I don't know, three, four, five years consistently came up in the comments on the videos on my YouTube channel and that I just kept ignoring. One of them was covered calls, which I finally dove into and we've done a whole bunch of content on that now, which was super fun for me, not for many of the people consuming the content. They got angry.

That's okay. The other one is the one we're going to talk about today, which is equal weighted index funds. People hear us talk about, index funds are good.

They're low cost and systematic and all that stuff. Then they hear us talk about things like we did an episode recently where we talked about index concentration. We talked about diversification being important.

We talked about the skewness in stock returns, where a small number of stocks affect most of the performance being something the investor should care about. People hear arguments like that and they make this logical step to, okay, well, why don't we just use equal weighted index funds? It's an interesting question.

I finally decided it was time to cover that topic. I don't think this is as exciting as covered calls.

Dan Bortolotti: Following on our theme of declining enthusiasm, tonight we're going to talk about equal weighted index funds.

Ben Wilson: I was about to make the same joke. What a way to start the episode. This is not exciting.

Ben Felix: Trying to live up to expectations here. Live down to expectations? I don't know.

Market capitalization weighting or market cap-weighting, which is what most index funds do, that assigns index weights based on each company's size. That's like most index funds are market cap-weighted. That's what people are used to hearing when they hear about an index fund.

An equal weighted index fund, as its name implies, equally weights all of the stocks in a market or market segment. We're going to talk later about the S&P 500 and the S&P 500 equal weight. The S&P 500 is capitalization weighted and the equal weighted S&P 500 is, as you can guess, equal weighted.

It assigns the same weight to every stock that's in the S&P 500. I think it does seem like it would be a solution to a lot of the perceived problems that market cap-weighted indexes have today, like high valuations, particularly in the US market, and high levels of concentration in the top stocks. We talked about in a recent episode how that is at a more extreme level than we've seen throughout history.

Equal weighting might be a solution if that is a problem that needs to be solved. Then the other interesting thing, and this is another thing that comes up in the comments on my videos a lot, is that equal weighting has actually outperformed cap-weighting going back decades. In recent history, not as much, but if we go back to the 1970s, which is when we have data, back-tested data for the S&P 500 equal weight, it has outperformed.

There is an S&P 500 equal weight index fund that has, since inception in 2003, outperformed SPY. It's interesting. There's an interesting logical argument, and then there's some interesting performance data, but the thing that we're going to talk about is that it introduces its own unique risks, costs, and inefficiencies.

Dan Bortolotti: It's a bit surprising, isn't it, the outperformance? I know we're going to get into the reasons why that might happen, but at least at first blush, you think of just how successful large cap stocks have been in recent history. By dramatically underweighting them in the S&P 500, you would have achieved outperformance. I think that's pretty surprising.

Ben Felix: The start date matters a lot. I think it comes up in the data that we'll talk about here, but that fund, Invesco S&P 500 equal weight ETF, it's outperformed since 2003, which is when it launched. That was in the middle of the lost decade where large caps did really poorly.

Dan Bortolotti: Well, that's right after the dot-com bust, right? Just when the recovery is beginning.

Ben Felix: If we move forward two years, there's a Dimensional fund that I'll talk about some data for, I think, in here too. It launched two years later. If we do that same comparison, compare S&P 500 to the equal weight to the Dimensional fund, the S&P 500 has outperformed both just by starting two years later.

Dan Bortolotti: Yeah. I would think over the last 10 years. I don't know, but I'm thinking it was probably pretty significant underperformance for the equal weighted in recent years.

Ben Felix: Yeah. Let's look at that.

Dan Bortolotti: 20 plus years of data.

Ben Felix: I don't have that in my notes here, but I'm just going to look that up as we're going here, because I think it is pretty interesting. This is a podcast where we can do stuff like that.

Dan Bortolotti: It's hard to imagine now somebody actively wanting 0.2% of their index fund to be each company, right? When you think of the enormous companies at the top of the S&P 500 and your decision is, I want 0.2% of those.

Ben Felix: Check this out. Going back to inception, it's super close. I have those data in my notes, but going back to inception, equal weight is outperformed by nine basis points annualized, but that gap closed a lot. In a recent history, for most of its life, it was ahead by quite a bit, but if I go to just the last 10 years, the equal weight S&P 500 ETF has returned 12.93% annualized. It's still great, but the SPY has returned 15.73% to your point, Dan.

Ben Wilson: It's a big difference.

Dan Bortolotti: Three percentage points annualized for a decade is a lot, but still, that must mean that the advantage in the earlier, the first half of that sample must have been pretty huge too.

Ben Felix: People that are watching will see it in the chart, or if you're listening on Spotify, because we started uploading the videos there, you should be able to flip the video on and see the chart. It is that, Dan. It opens up a lot in the early sample and then the gap closes in more recent history.

Ben Wilson: To your point, Dan, it's interesting. People that might want 0.2% of their portfolio, it almost goes against human behavior because people tend to want to follow where the returns have been hitting, even if that's in itself, not the most rational choice, but it's just interesting that you'd go so far the other way too.

Dan Bortolotti: Yeah, the perception that the large cap stocks are so overvalued, I guess, is pervasive now.

Ben Felix: That's the big thing, I think. I got this comment a lot on my video on where I talk about market concentration because of the AI bubble. We did that same topic in the podcast, but that's where a lot of people came in and said, well, why don't we just equal weight?

Equal weighting does solve that problem. It mechanically will not have the same level of concentration as a market cap-weighted index. It's kind of neat that it solves that problem, but I think the real issue is that it's not the right problem to solve.

The way that you're solving it brings in a whole bunch of other issues that we're going to talk about. The trade-offs, there's the trade-offs and then there's also the context. I think those are the two things that we have to think about.

The trade-offs are you're introducing some downsides by doing this and the context is, and you mentioned this, Dan, the context is why did that performance that we see historically happen? Then I'm going to talk about why I think the benefits of equal weighting, because there are some, can be achieved more efficiently without introducing the drawbacks of equal weighting. Okay.

Just some quick background to start. Maybe this is self-evident to listeners. I don't know.

Worth going through. When you create a stock index, so an index is a representation of something, of a market or a market segment or an industry or whatever. One of the most fundamental questions that you have to answer is how you're going to weight the stocks in your index, because an index is two things.

It's a list of names and weights. You can get your list of names, great, but now you have to figure out how you're going to weight them. Even within market capitalization weighting, there's different tweaks that you can make.

That's not even black and white, but generally speaking, market capitalization weighting means holding stocks at their market capitalization weights. Obviously, I guess, based on the name and the market capitalization is what the entire company is worth on the stock market. It's like, how much would it cost to buy every single share of Apple or Shopify here in Canada?

That's its market capitalization. A larger company, a company with a larger market capitalization is going to make up a larger portion of a market capitalization weighted index than a smaller company. Again, maybe that's obvious, but worth reviewing.

Equal weighting, again, obviously is going to assign equal weights to all of the stocks, regardless of their market capitalization. These two approaches, you can take the same set of stocks. I mean, the example we'll talk a lot about is the S&P 500.

You've got the same list of names, but materially different weights. You end up with two very, very different portfolios. I think that the logic of market capitalization weighting is pretty simple.

The market has determined how much weight each stock should have. That's why it's often referred to as passive. Market cap-weighted indexing is often referred to as passive investing, because you are passively allowing the market to determine the weights of the stocks that you own.

It's like letting water find its own level, instead of constantly trying to tweak and adjust and control it. It's an equilibrium approach to portfolio construction. The nice thing about that is that you don't have to make a whole lot of decisions.

You just accept what the market has given you. The weights just are. Then another benefit that I think matters practically is that because the index represents the market as the market exists, it doesn't need to be rebalanced very often.

As stock prices evolve, the market capitalization weighted index evolves in exactly the same way as the market, without needing to make a whole lot of trades. Now, there's some nuance to that too. We had our episode with Marco Salmon a while ago, talking about all of the trading that indexes do actually have to do to perfectly reflect the market.

Generally speaking, if a small stock gets bigger, you don't have to do anything, because its market cap has changed and its weight in your index will have changed automatically, just by its price having changed or its value having changed.

Dan Bortolotti: That's actually a point where it's stressing, I think, because I have certainly experienced people. In fact, I've read it even in financial articles by people who should know better, who say things like, one of the problems with cap-weighted indexes is that as the big companies go up in price, the fund managers have to buy more and more of that stock in order to... It's like, no, that's not how it works.

The weight of that stock adjusts automatically, of course. This idea that it's kind of a feedback loop, the overvalued stock attracts more and more money and becomes even more overvalued is just not how it works. As you say, one of the nice advantages of the cap-weighted index is that it's basically self-regulating.

Behind the scenes, there needs to be some work done in order to replicate the index, as you said, but it's not about buying more of stocks as they become bigger.

Ben Felix: I hate that my brain goes to these places, but there is some research coming out that the continued flows into index funds, not through the mechanism that you're talking about, Dan, not because the companies have to buy more of the big stocks, but just through an asset pricing mechanism and a, not liquidity, a price elasticity mechanism. There may be some effects on the prices of larger stocks from an increased index fund ownership. There are a couple of interesting papers on that.

I was looking through those recently preparing them. I'm moderating a panel between some folks from Vanguard and S&P in New York City in a couple of weeks, and they're down to get right into these tough questions about how are index funds affecting the market. Anyway, I was looking at that research recently, which is why it's on my mind.

You're completely right, Dan, that if a big company goes up in price, it does not mean the index fund company has to buy more shares. From that perspective, they're neutral, but there's potentially other effects that may not be neutral. Because this is a super nerdy podcast, we have to talk about them.

Ben Wilson: Curious, the equal weighted ETFs, is there higher trading costs on average compared to the market cap-weighted ETFs?

Ben Felix: Not explicit costs. In Canada, mutual funds have to report something called the trading expense ratio, which is the explicit costs, like the trade ticket fees that they pay to trade. For both, there is an S&P 500 equal weighted index fund available in Canada.

Its TER was for most years zero, for a couple of years it was maybe 0.01%, so it's really, really low. I was wondering about that too, Ben. There are two components to trading costs.

There's explicit costs, which is like explicit fees that you pay, like commissions that you pay to trade. Those have obviously come down a lot in recent years. Then there's also implicit costs.

There's a cost to crossing the bid-ask spread when you trade, which does not show up in the TER and doesn't show up really in any reporting, but there is an implicit cost there. The turnover level for the equal weighted funds, and we'll talk about this later, is much higher. While it does not show up in a higher trading expense ratio, it is absolutely a cost that investors are bearing.

Ben Wilson: Yeah, that's what I was anticipating would be the case. To maintain those equal weightings, it'd be a lot more turnover for sure.

Ben Felix: Yeah, so we'll talk about the turnover. It comes with a couple of interesting implications. One is costs, but the other one is momentum.

Dan Bortolotti: You'd think taxes would be an issue too, right? That there would just be more and more gains realized, but my guess is these well-managed funds just do a whole lot of tax loss selling and a lot of offsetting because you're doing both, I guess, right? You're selling in both directions and you're never going to be able to map them perfectly, but you can probably do some pretty decent tax management.

I don't think there's any evidence that these funds distribute a lot of capital gains to their investors. I don't know, but I've not heard that criticism in the past.

Ben Felix: I thought about looking that up. In the US, probably less of an issue just because of their capital gains management tools that they have available to them for a US listed ETF. I should have looked at that for the Canadian ETFs, though that would be – we can look that up later and maybe follow up in a future episode.

It's interesting comparing on stuff like that, but also just the reporting differences. The US funds, as far as I know, don't report on a trading expense ratio. The reporting on turnover is also tougher to pin down.

Canadian mutual funds are required twice a year to file an MRFP, a manager report on fund performance. It has a whole bunch of ratios in it that are super useful. That's where the MER is reported, the management expense ratio, but we also have a trading expense ratio where you can see the additional costs of trading, which for some funds can be pretty high.

They also report on the turnover, but it'll be five years at a time of data that they'll put in this MRFP. As far as I can gather from looking at US filings, they don't have the same level of data. It's usually one year at a time for ratios like that if they're in there at all.

For trading expense ratio, someone can correct me if I'm wrong, but I don't believe there's a place that that's reported.

Ben Wilson: Depending on the fund size, the amount of a new investor flows into a given ETF would also reduce the need for trading and realizing gains, I would expect.

Ben Felix: Yeah, it could to an extent. We've got the capital gains refund mechanism in Canada. Anyway, we'll look it up.

It's a good question. Back to market cap-weighting. One of the perceived problems with market cap-weighting is that it can result in high weights in a relatively small number of stocks.

That's something that we are seeing relative to its own history, pretty extreme version of in the US market right now. Now, you look back through history and we will put a chart up showing this for the US market. Index concentration ebbs and flows naturally over time as businesses become increasingly successful or less successful and earn a larger share of the market.

This has happened throughout history where some new technology becomes really impactful and a couple of companies or a company really capitalize on that market and do a really good job creating a product or at least selling a product. They make a lot of money and their stock price gets really valuable and they become a large part of the market. You go back through history.

There's like IBM, AT&T, GM. I think Chevron's been up there or Exxon, not Chevron. Yeah, it happens.

Right now, it's all tech. Now, market concentration seems like it should be concerning. It kind of is, but we talked about this in the past video too.

The historical relationship between market concentration and future returns has been really weak historically in the US and other countries around the world, same kind of thing. For the past video, we sorted 10 year future US market returns on their starting level of market concentration. There's really no relationship there economically or statistically.

You look at other countries, they have been historically and are currently more concentrated in the US market, even though the US market is as concentrated as it's ever been. Those other countries have performed just fine.

Dan Bortolotti: That one's a little more surprising, because I mean, the US market, sure, it's concentrated, but it's also 3000 plus stocks in a total market fund. What's the market concentration in Finland? I mean, small countries with small markets and a couple of big companies can face enormous concentration risk.

I might not want a cap-weighted index in a country that had 10 large cap stocks, but in one that has 500, I'm okay with that. The number of overall stocks in the fund has to come into the decision too, right?

Ben Felix: I agree. It is interesting that you can look at countries that have been, at times, like you said, Dan, really, really concentrated, and they've performed kind of fine.

Dan Bortolotti: Intuitively, that's surprising, but it is what it is.

Ben Felix: I do have some data around. We'll post the image in the video. I don't know if I'll be able to find it in my, where I have it stored at the moment.

There was one, I think it was Hong Kong, that had had a very, very concentrated stock market 10 years ago. Then the subsequent 10 years, it was able to outperform the US market by a bit.

Dan Bortolotti: It's interesting, like you said, how it ebbs and flows.

Ben Felix: Oh, it's Taiwan, sorry. Excuse me, not Hong Kong. Taiwan had more than 40% of its market concentrated in the top seven stocks in November 2015.

For the subsequent 10 years, it outperformed, well, every other market in my sample, and also the US market.

Dan Bortolotti: That means, though, that the fact there was significant outperformance means there's also the potential for significant underperformance. In other words, the concentration likely leads to greater volatility in that case, because you're just not that well diversified. Portfolios get less volatile as you add stocks up to some equilibrium point, but 10 stocks with a few with large concentrations is going to be a volatile portfolio that could have very great outperformance, but just as likely to have great underperformance, I gues

Ben Felix: I wouldn't invest 100% of a portfolio in the Taiwan index.

Dan Bortolotti: Half-weighted index, no.

Ben Felix: You're just buying Taiwan semiconductor at that point, which is why that index is so concentrated, I believe.

Anyway, I agree with all that. Concentration is probably not. If you could choose, you might want a little bit more diversification than concentration, but at the same time, those really large companies, they of course can have major idiosyncratic risks, but from the perspective of volatility, they don't tend to be that volatile, and that does show up in the equal weight data.

We'll get there in a second. Well, that's actually the next point I was going to cover in my notes here. It's a really interesting question to think about whether having a high weight in large companies in a market cap-weighted portfolio is riskier than having large overweights to smaller companies and underweights to larger companies in an equal weighted portfolio.

To your point, Dan, okay, it's bad to have concentration in a handful of large stocks or a large stock. That's likely true. Is it riskier or safer to have a portfolio that has a lot more weight in the smallest companies and a lot less weight in the largest companies?

It depends. I think about risk, I guess, from the perspective of reducing idiosyncratic company specific risk, probably less risky, but I don't think that the answer, all things considered, holistically is black and white. I think there's a pretty good argument that the extreme over and underweighting of an equal weighted portfolio is riskier than accepting a high level of concentration in larger companies in a cap-weighted portfolio.

Ben Wilson: Intuitively, with the higher weight to the small cap, or the smaller companies, you'd expect more volatility in the equal weighted portfolio over time. Smaller companies tend to have higher volatility.

Ben Felix: I agree. That's exactly it. The additional risk of equal weighting does show up as volatility, like you said, Ben.

If we look at the S&P 500 and the S&P 500 equal weight, the equal weight has quite a significantly higher 15-year standard deviation, like how much variability there has been in returns. It's been quite a bit higher for the equal weight fund. The reason, and Dan, you had this question when we were chatting about this earlier.

The reason is that larger stocks that an equal weighted index underweights tend to be less volatile than the smaller and lower priced stocks that they overweight. Then another interesting point there is that equal weight indexes, just again, because of what makes up the smaller portion, the smaller companies in an index, equal weight indexes tend to be short the low volatility factor. They've got more exposure to high volatility stocks, which is an independent factor relative to company size.

You can have small companies. You can have highly volatile small companies. They'll tend to be emphasized in an equal weighted portfolio.

That's the volatility piece. The other interesting piece, and it's related, but volatility is one way to think about risk. We can also think about risk from a multi-factor perspective.

What kind of stocks does the equal weighted fund have exposure to? You're going to end up with a tilt toward small caps. You're going to end up with a tilt toward value stocks.

Again, if we go back to Fama and French asset pricing theory, those are theoretically being priced as riskier by the market. Again, come back to that question of is equal weighting riskier or safer? Okay, well, it's more volatile.

It's more exposed to stocks. The market is pricing as riskier. It's less concentrated, but then it's back to that question of is market concentration the right problem that we should be trying to solve with this tool, with equal weighting?

The other reason these things are popular right now, or that people are thinking about them right now is market valuations. I just mentioned that if you go equal weights, you're going to emphasize smaller and lower priced companies. Market cap-weighted market valuations in the US market are high right now relative to their own history.

They're just high. That one does have more of a relationship with future returns. I mentioned market concentration of future returns, not a super strong relationship.

If you go and look at valuations in future returns, it's noisy, but there is a relationship there. Equal weighting does have this natural tilt away from the largest and highest priced stocks. One way to look at that is the price to earnings and price to book ratios of an equal weighted S&P 500 fund and S&P 500 fund.

The equal weighted is much cheaper on both metrics. That's kind of like part one. Okay, so what's equal weighting doing?

It's producing concentration in the biggest names. Cool. It's giving you a tilt toward smaller, lower priced companies and higher volatility companies.

Cool. That's not necessarily a bad thing. People who listen to this podcast know that we talk about tilting toward certain types of companies as opposed to just accepting market cap-weights all the time, although that is also a fine strategy.

The problem with equal weighting is that if you want to get exposure to those types of stocks, there are probably more efficient ways of accomplishing that. I will get into some more detail on that in a minute. But one other important point on equal weighting, there's probably a way to control for this, but from the ones I've looked at, they don't tend to control for it.

Equal weighted indexes are going to tend to have materially different sector exposures. Actually, I guess there isn't really a way to control for it. I don't know how you would, if you're equal weighting all the stocks in an index, that's it.

Those are the weights. You can't really adjust that other than excluding stocks from certain industries, I guess.

Dan Bortolotti: I wonder if there has been equally sector weighted strategies where you take, what is there, 10 or 11 or 12 economic sectors, depending on which classification system you use, and you allocate 10% of the portfolio to each of the economic sectors. Obviously, it's hugely skewed compared with the market as a whole, because small consumer discretionary retailers and things are going to be just naturally much smaller companies than tech giants. You could argue, well, you're getting equal exposure to all of the various economic risks in the business community, but I don't know.

I mean, it sounds logical, but I don't know if it's a thing.

Ben Felix: It's a thing. I don't know if there are products, but I didn't dig into it because it just wasn't the direction that I was going in, but there was a paper, an article, I can't remember what it was, that did talk about equal weighting countries and equal weighting sectors as a potential strategy. It's something people have thought about and written about.

The sector exposures with equal weighting, again, naturally, for the reason you said, Dan, the different sectors are represented at different weights in the market cap-weighted index. Some sectors tend to be bigger because they have bigger companies in them. If you go and equal weight everything, you're going to end up with a whacked out sector mix.

That's, again, taking on sector risk that's different from the market. I would tend to call that an unpriced risk, a diversifiable risk that most investors probably don't want to take. Again, if we look at these two S&P 500 ETFs, the market cap-weighted and the equal weight as an example, we'll put the chart up in the video, but you can see that the sector compositions are materially different with a big underweight to technology if you go equal weights and an overweight to industrials.

Ben Wilson: The interesting thing there is even though some of the big companies are tech, if you underweight all of those companies, then you're underweighting tech as a whole, which tech companies are often jockeying for position in terms of their stock price, so you're potentially missing out on some of that tech return. If other markets do well, like it's just interesting the impacts of taking this equal weighted approach versus the market cap-weighted. As you said, it's more of an active approach where you're saying, I want equal weights rather than letting the market decide how, which stocks are valued more than others.

Ben Felix: I would call it an unintended consequence. You're trying to solve, markets are concentrated and valuations are high. Equal weighting is a solution.

Okay, but you're introducing, we've talked about a few different things. You're introducing a sector over underweights, security level significant over and underweights. The other issue that you're introducing that we'll talk about next is rebalancing.

We talked about it a little bit earlier. I don't know if that one gets enough attention when people think about equal weighting. When a smaller company gets larger, as we talked about earlier, a market cap-weighted index doesn't do anything.

It's just, it is. An equal weight index has to sell down that position back to equalize its weights at its next rebalancing. They tend to rebalance quarterly.

Then the same thing happens when a large company gets smaller. Again, looking at the S&P 500 equal weight ETFs. These are Canadian listed versions because those are, as I mentioned earlier, we get the MRFP report where we can see the turnover.

The five-year plus the six-month period for this interim MRFP, which is what we're looking at, the turnover has been 10 times higher for equal weight than it has for market cap-weight.

Ben Wilson: Wow. That's substantial.

Ben Felix: Like we talked about earlier, that comes with implicit and explicit trading costs. In this case, the explicit trading costs are not much different, but the implicit trading costs, even though we don't see them in reporting, are definitely there. They definitely make a difference.

I alluded to this earlier. The other issue that comes with this frequent rebalancing, the specific timing of rebalancing for equal weighted funds is momentum. Very well documented empirical phenomenon where stocks that have recently done well tend to continue to do well for a time.

Those that have recently done poorly tend to continue to do poorly. Equal weight funds, in order to maintain their equal weights, are always selling what has done well recently and buying what has done poorly.

Ben Wilson: In a way, it's an anti-momentum strategy.

Ben Felix: Exactly. It is a negative momentum strategy. It's just systematically trading against momentum because of its design and construction.

One of the things I did to look at this is I ran just a simple multi-factor regression. I used the Fama-French five factors plus momentum. Regression is just a statistical test that shows us what's driving a fund's returns, like taking a blood test for yourself to see what's in your system, except we're doing it using time series data for an investment fund.

Looking at the multi-factor regression for the equal weight S&P 500, you can see that it loads. We'll put a picture of the regression results in the video, but people absolutely want to see that. Nobody can say that we're boring if we're showing pictures of multi-factor regression.

Dan Bortolotti: It doesn't get more exciting than that.

Ben Felix: That's what I'm saying, Dan. You can see it loads positively on the size and value factors.

There's some interesting loadings on investment and profitability as well. Then there's a big negative momentum factor loading. They're all statistically significant, so they're like real patterns, not just noise that we're observing there.

There's a high likelihood that it is truly exposed to those factors. What that means is that this equal weight fund has more exposure to small cap and value stocks than a market cap-weighted total market index fund would, and that it's trading in the opposite direction of momentum, which that is exactly what you'd expect based on the equated indexes structure. It's, as we've talked about, naturally overweight smaller and cheaper stocks, and underweight larger, more expensive stocks.

It, by construction, is going to trade against momentum systematically.

Dan Bortolotti: In fairness, and we were chatting about this before, that's true of any rebalancing strategy. So we would generally rebalance portfolios when equities are overweighted, and that has the same kind of anti-momentum effect. But I think it can be constrained by not doing it too slavishly.

For example, for our clients, we only rebalance once the portfolio is about five percentage points off its target. So if your target is 70% stocks, we're not rebalancing when it's 71. We are going to let it run a little bit.

Now, that is primarily to reduce trading costs and capital gains and whatnot, but baked into that, there is a little bit of momentum allowance, let's call it. I wonder, you would know this better than me, Ben, but the momentum period is, I seem to remember it's somewhere like three to 12 months is kind of before it starts to fade. You don't know whether it's three or 12, that's why you can't systematically trade it.

But if it's within that timeframe, maybe you don't rebalance the equal weighted index fund quarterly. Maybe you only do it semi-annually or even annually. You accept that at the end of that rebalancing period, it's not going to be equal weighted.

There's probably a few that have crept way up, but you accept that as a trade-off. That the tracking error versus the perfect equal weighted index might be a little higher, but you have allowed for a little bit of that momentum to do its thing. I'm sure these have all been questions considered by the index providers.

Ben Felix: I mean, that's one of the big product design questions is how consistent do you want your exposure to be? In this case, we want consistent exposure to equal weights. Cool.

The day after you rebalance, you're not going to have equal weights anymore and the year after, it's going to be way off. But to your point, if you rebalance more frequently, you're taking a bigger negative momentum position. Yeah, that trade-off is this S&P 500 one that we were talking about, they're doing it quarterly.

Is there an optimal rebalancing frequency? It depends on how strong your preference for equal weights is, I guess, and how you want to make those trade-offs. There's also the difference between, I guess these guys would be short cross-sectional momentum, like in the cross-section of stocks.

You don't take all the stocks in the market. Some of them are going up, some of them are going down, which is a little different from time series momentum where the market as a whole, after it's done well, tends to continue doing well. These guys are short cross-sectional momentum.

Anyway, how much does that matter? To the extent the momentum still exists, it probably matters quite a bit. It has mattered to the past performance of these funds.

Portfolio Visualizer, which is one of the tools that I use to look at the factor regressions, it has a new chart that's really cool. It shows you the past performance by year in a graph, but it breaks down the performance by the contribution from each factor that you ran in your regression. You can see, usually there's a big contribution from the market factor and there's smaller contributions, positive or negative, from each of the other factors.

It's a really interesting way to look at past returns. Momentum has definitely – being short momentum has hurt, but so has, in recent history, being long value and size has also hurt. The big question that we have to ask if we're thinking about should we invest in equal-weighted funds is if you want exposure to smaller and lower-priced stocks, we have to ask, is equal-weighting the most efficient way to get there?

That is the fundamental question. What problem are we trying to solve? We don't want concentration in the largest stocks.

We don't want high valuations to hurt our future returns or our expected returns. We consider equal-weighting as a potential solution, but it comes with these other trade-offs that we've talked about. Then the next question is, how else could we solve this problem?

These concerns that we have. It's actually interesting to look at the Dimensional Core Equity 1 fund, a mutual fund, but it also has an ETF version more recently. We're talking about mutual fund because it has more historical data.

This is the part that's cool to see. It has roughly similar. It's not quite as heavily tilted as the equal-weighted S&P 500, but it has roughly similar exposures to the small cap and value factors as the equal-weight S&P 500 fund.

The big difference is that Dimensional is not naively getting those exposures by equal-weighting. They're being super intentional, oh my goodness, about targeting specific types of stocks. Similar fees, kind of a wash.

We're talking about the mutual fund. There is an ETF. I always worry about that with Dimensional.

People will hear me talk about Dimensional, like, well, I can't access that anyway. In Canada, that's still true. In this case, the fund we're talking about has a US listed ETF that's available to anyone and it's implementing the same strategy as the mutual fund.

You end up with roughly similar exposures to the different factors that the equal-weight fund has exposure to, but Dimensional is limiting their sector divergence from the market. Dimensional places a cap on sector weight differences relative to their benchmark to avoid taking those big sector bets. They also apply a rule when they trade to avoid selling recent winners and buying recent losers, all else equal.

Dimensional will always have a list of potential candidates that they can buy or sell in order to meet the exposures that they want. If they have two different candidates, but one has the wrong momentum exposure, they will avoid trading that one and they'll trade something else. They also have the flexibility to do that because they're not index funds, they're not rebalancing on a quarterly schedule or whatever.

Then turnover is another big one. Again, they have similar tilts roughly, but Dimensional has a much more modest turnover, like a fraction of the turnover. A big part of the reason for that is that while Dimensional is tilting toward the smaller and lower priced stocks, they're anchoring to market cap-weights.

They start with market cap-weights and then they apply modest tilts to get where they want. Dimensional actually has a paper on this where they look at this, different weighting schemes for systematic equity strategies. They talk about how minimizing unnecessary deviations from market cap-weights means less aggressive rebalancing requirements.

It doesn't perfectly address the concentration issue. It sort of does. Just by tilting away from the biggest stocks and toward the smaller stocks, it is less concentrated than say the S&P 500 of the US total market, but it still has a pretty high percentage in the top stocks.

I find it really interesting how close the factor regression loadings are. The Dimensional fund and the equal weighted fund are pretty similar, but the interesting thing is Dimensional does not have that negative loading on the momentum factor, which again is by design. The equal weighted fund is systematically trading against momentum and Dimensional is being careful not to trade against momentum.

The Dimensional mutual fund here launched in 2005, compared it to the equal weight S&P 500 ETF and the S&P 500 equal weight and the S&P 500. Over that period, the Dimensional fund has outperformed the equal weight fund. Both have underperformed the S&P 500.

You made this point earlier, Dan. It's been really hard to beat the S&P 500 in recent history.

Dan Bortolotti: That's a 20 year period though, right?

Ben Felix: Yeah. Back to 2005, that's right.

Dan Bortolotti: It's always hard to beat the S&P 500.

Ben Felix: That is true. This recent period, especially. Always, I agree.

Going back to 1971, which is where back test data for the S&P 500 equal weight start, in that period, equal weighting looked really good compared to the market cap-weighted S&P 500. That is a period where small cap and value stocks did perform well. It was a stock pickers market. I'm just kidding.

Dan Bortolotti: Every year since 1971, it has been a stock pickers market.

Ben Felix: I did run regressions on these again on the indexes. Again, very similar results where the performance is largely explained by higher exposure to small cap and value stocks with a negative contribution from momentum in the case of the equal weighted fund. Then I also had the Dimensional US Core Equity 1 index.

This is not the fund anymore. This is the index that Dimensional calculates after the fact. They calculated it recently going back to the 1970s using their current implementation for that strategy.

This index has the momentum screen. It has tilts toward small cap value profitability and all that stuff, but that was not in live funds until relatively recently. Dimensional didn't even exist in 1971.

Just to be clear, this is a back test calculation based on the current strategy. Again, roughly similar exposure to small cap and value stocks and a much lighter exposure to momentum and nearly identical performance to the equal weight S&P 500 over this full period. That's going back to 1971 up until, I think, November 2025 is when that ended and the Dimensional fund was much less volatile.

To double reiterate, that is back test data, both for the equal weighted fund and for the Dimensional fund. It's one thing to say, well, yeah, this thing beat the S&P 500 going back to 1971. It didn't actually.

The back tested index did, but that was not a live fund that was being traded. It was probably more expensive to trade small cap, smaller companies in 1971 than it is today. Who knows what the actual performance would be, but that's just the back test data.

There is a funny saying in finance that you'll never see a back test you don't like. I know I haven't. I've never seen one.

Dan Bortolotti: You've probably done a few, but you just haven't shared them with us.

Ben Felix: You don't share those ones. You keep them secret.

Dan Bortolotti: Exactly. They're quietly taken out back and shot.

Ben Felix: So despite the back testing issues that do exist, I think it's still pretty interesting to see the same kind of trend that we see in the live funds has existed in the back test calculations. The result is similar where exposure to smaller and cheaper stocks and negative momentum really explains most of the results of the equal weighted index performance. Equal weighting, it seems really appealing right now because there's high concentration in the top stocks in the market cap-weighted index.

There's high market valuations in the US market and that stuff's making people nervous. So they look around and they say, oh, equal weighting, that's maybe a solution. Then I think you go and look up an equal weighted fund and you say, oh wow, this is actually outperformed the S&P 500 since inception.

Maybe this is a good solution, but I think the issues that it comes with, it comes with some meaningful baggage. Equal weighting results in large over and underweights at the individual stock and sector levels, results in high portfolio turnover and it gives you the systematic bet against momentum, which is maybe not a bet you want to take or make. The other big point here is that the strong past returns, which are a real thing, but the strong past returns of equal weighting are largely explained by tilts toward smaller and lower priced stocks, not some equal weighting magic.

The implication for investors is that if you do want to tilt smaller and lower priced stocks, you can do it without introducing the downsides of equal weighting and I think Dimensional is doing something like that. There are other fund companies doing it too. Dimensional is just a good example because they have funds with long histories, but they are tilting towards smaller and lower priced stocks and some other factors too while controlling for sector exposure, limiting portfolio turnover and intentionally avoiding trading against momentum.

I do want to just say real quick that Dimensional did not pay me or us or otherwise incentivize us in any way to talk about their funds in this episode, but we do use Dimensional funds at PWL. They're Canadian funds in some of our clients' portfolios. We did a video a while ago explaining Dimensional's history and their long-term performance compared to comparable Vanguard funds.

The last thing I have here is there is a 2023 paper in the Journal of Portfolio Management. Why Do Equally Weighted Portfolios Beat Value-Weighted Ones? In that paper, they pretty much corroborate what we talked about in this episode.

They find that applying a factor lens explains most of the variation in the return spread of equal-weighted equity portfolios relative to value-weighted ones, that's market cap-weighted, with the biggest contributor being the size factor. They always talk about the negative momentum loading and the negative low volatility factor loading. That's it.

I wouldn't use these things. I don't know. I don't know what you guys think.

Ben Wilson: I find it fascinating just like reflecting on the ETF slop episode and just like investor behavior in general. Investors are always looking for the next best way to win or beat the market. There's always uncertainty.

I've had many conversations in the past week of what's going to happen with Trump, the high valuations. These conversations happen all the time no matter what the market's doing. You can see the appeal in these types of products to investors.

It's like, oh, well, this product fights against this, but you need to think through all those implications. Is the portfolio designed in such a way to capture the academic evidence or to capture what you want to return? Second, just pick a strategy that you can remain disciplined to.

That is one of the best ways to beat or stay on track, I guess is what I'm trying to say. I've said that a couple of times to clients this week. The best defense against uncertain times is a diversified portfolio and a disciplined strategy.

Dan Bortolotti: I think too that, because I've spent a lot of time looking at these various weighting strategies and how they match up against market cap-weighting. My conclusion has always been that there's a lot of different ways to get exposure to the risks that you want. Frankly, it always kind of bothered me a little bit.

If a study like this says, well, equal weighting didn't really outperform because it was equal weighted, it outperformed because there was greater exposure to a smaller value. Okay, but maybe the people who designed the strategy were trying to get access to cheaper and smaller stocks. We can't just kind of wave our hands and dismiss that as a bad strategy because it wasn't articulated in the title of the ETF.

I think the point, which I think you've made very well, Ben, is that if your goal is to get exposure to these different risk factors in a way that is different from the market cap-weighted strategy, then what is the most efficient way you can get that exposure? We've talked many times about the various merits of Dimensional versus traditional index. One thing I've always said is, if your goal is to get the factor exposure like we've described, Dimensional does seem to me to be the best way to do it.

The funds are so thoughtfully constructed to do exactly what you've described here, which is try to get the positive risk exposure that you want without giving up too many of the trade-offs. That's what they're so good at. I think it's just a bit of a subtle point.

There's all kinds of different fundamentally weighted indexes were huge like 20 years ago, and that had a really good story behind it too. Then when you broke it down and you did these regressions, it was kind of like, it's a value fund or it's a midcap value fund. Okay, whatever you want to call it, the question is, maybe those factors are worth trying to access, but maybe there's a better way to get it.

Cheaper, less turnover, fewer trade-offs. At the end of the day, what I've always struck too is, if you have enough data, if you can back test 40 or 50 years, almost everything comes out the same. If you go through enough market cycles, there's no strategy that consistently beats cap-weighting.

Sometimes it might be best to just accept that if you're going to hold for the very long term, the cheapest and most efficient way to do it is with a cap-weighted index.

Ben Felix: I agree with that. I've got to mention this. There's a very, very funny slide deck on the internet.

Still exists. I just found it as you were talking there, Dan, because you reminded me about it. It's Cliff Asness critiquing Rob Arnott who created fundamental indexing.

We can show the slides here because they're pretty funny. Cliff writes, this is a presentation that Cliff gave at some point. It's from 2007.

Cliff says, I'm going to share with you a fictionalized dialogue between myself and Rob. It's obviously made up, but it approximates our real life interchanges on this topic and sums up the issues pretty well. It's got a picture of Rob and Cliff and it says, our good looking protagonists.

It has Rob saying, we've had both these guys on this podcast, by the way, both great episodes. Rob says, I have invented a theory about how massive bodies are pulled toward each other. I call it fundamental attraction.

Cliff says, yes, Rob, we know about this. We call it gravity. Then Rob says, you don't understand.

It makes remarkably accurate predictions. Yes, we know. It's called gravity, but it works everywhere.

We've tried it. This is really amazing. Rob, listen to me.

We call it freaking gravity. Then Rob says, I better hurry up and trademark this. Anyway, it's a joke about how fundamental indexing was really just value investing all along. Pretty funny.

Dan Bortolotti: That was my point here was that an equal weight index is essentially a strategy to overweight small underpriced stocks and underweight large cap overvalued stocks, which is not a crazy idea. It just might not be the best way to do that if your goals are to adjust your risk exposure in that way.

Ben Felix: I think that's a very good point and it's an interesting question. I said that I wouldn't use equal weighted index funds, but if someone said, I think factor investing is a bad idea, but I really like equal weighted indexing. I think that's a better solution than market cap.

It's like, okay, you're going to get the factor exposure anyway. It's maybe a little bit less efficient than some other thing that you could do more efficiently, but if you're okay with tracking error relative to the market, maybe it's not so bad. I mean, there is, it has performed well historically. It's a fact.

Dan Bortolotti: Over very long periods, it hasn't really performed that differently.

Ben Wilson: It's essentially a factor tilt strategy in disguise because it's not named in such a way that it's tilting to the factors. It's equally weighted by definition. It's tilting to smaller companies.

Ben Felix: Right. In the live fund data since 2003, it's performed about the same as the S&P 500. Over the longer periods, like going back to 1970 in the back test, it's outperformed by quite a bit.

Over any interim period, it has had quite a bit of tracking error relative to. That's another thing I didn't talk much about, I guess, but Dimensional's anchoring to market weights should reduce your tracking error relative to the market, whereas equal weighting, you're going to have more tracking error. To the extent that people care about that, but again, if someone said, I don't think factor investing makes sense, but I don't want to market cap-weight, so I'm going to equal weight and I'm okay with tracking error.

Dan Bortolotti: Eh, all right. Well, then you're also okay with factor investing, you just don't appreciate that you are.

Ben Felix: Oh, true.

Dan Bortolotti: That's the point here, is that you say that you don't believe in factor investing, but then you're attracted to a strategy that overweights specific knowable, identifiable factors, just in a way that, as you described, in disguise. I think that, honestly, factor regressions have proved that active management is just various forms of getting factor exposure. It's just not identified in that way.

Certainly, before the research was done, people didn't even know that. They might have had some intuition that that made sense. They couldn't quantify it, but most strategies that deviate from market cap-weighting are some form of factor investing.

If they're diversified and systematic, if they're throwing darts at a stock page, it's different, but these kinds of systematic strategies are just generally some attempt at getting exposure to those factors, even if the people implementing them don't realize it.

Ben Felix: There was one paper I came across. I didn't dig into it in detail, but they did actually look at the throwing darts at a dartboard strategy.

Dan Bortolotti: That beat market cap-weighting too.

Ben Felix: It did. That was the point of their papers. They had a whole bunch of non-standard weighting schemes and they compared them to market cap-weighting and the one where they just randomly picked stocks.

I don't know how they weighted them or anything. I'd have to go back to the paper, but it outperformed in their construction.

Dan Bortolotti: There was a couple of papers at some point that did that, where they looked at dozens of strategies and they literally came up with everything beat market cap-weighting. I wrote an angry blog post about it at the time because I said, this is great that apparently every strategy beats market cap-weighting. Where are all the investors that are beating market cap-weighting?

Because it's one thing to create some abstract hypothetical strategy that no one implements. Then where are all the people who are beating the market if every strategy beats market cap-weighting? Take it with a gigantic grain of salt as a practitioner versus someone just looking at the theory. Not a lot of things beat cap-weighting consistently.

Ben Felix: That's a great point. The people would have had to stick with those non-standard strategies for whatever period of time and they highly likely wouldn't have. Even if they identified the strategy, sticking with it would be not so easy.

It's got to be the same paper because that's like a 2009 paper, which is when you were.

Dan Bortolotti: Yeah, I think that's the one. It drove me nuts at the time, I have to admit.

Ben Felix: I'm sorry for bringing it up and making you.

Dan Bortolotti: Yeah, no, no. It's a pleasant memory. Yeah, I'm much more chill about these things now.

Ben Felix: Should we get into these reviews and feedback here?

Dan Bortolotti: Yeah, let's do it. I think we ended with a burst of enthusiasm for the record.

Ben Felix: I would say so. I don't know. Maybe it ebbed and flowed.

Ben Wilson: For the people that made it this far, you got enthusiastic at the end.

Ben Felix: That's right. I'll read the disclaimer, but does one of you guys want to read the?

Ben Wilson: Yeah, I can do it.

Ben Felix: All right. I've talked a lot today. We do have a review from Apple podcasts to read.

Under SEC regulations, we are required to disclose whether a review, which may be interpreted as a testimonial, was left by a client, whether any direct or indirect compensation was paid for the review, or whether there are any conflicts of interest related to the review. As reviews, including this one by Flint Abatee Flonatin2, are generally anonymous, we are unable to identify if the reviewer is a client or disclose any such conflicts of interest. But as we always say, we have never paid for a review, so we're not too worried about that anyway. Go ahead, Ben.

Ben Wilson: Here it is. It's the best podcast for financial literacy. This podcast has pushed me through most of the Dunning-Kruger effect.

Interesting, most of the Dunning-Kruger effect. I started listening to this podcast after learning the Canadian Couch Potato basics from Dan's blog in the 2010s. I've related to the two shaved head hosts, but I'm willing to accept that Ben's hair genes are just better.

After the years listening to the podcast, I've pushed through the pit of despair and now on the slope of enlightenment. Your varied approach on broad or specific topics along with topics on happiness and utilizing time has been amazing. My wife does not enjoy my summaries to her, but regardless, thank you so much for your efforts by improving our lives.

My wife doesn't really enjoy talking about finance either, so you're not alone in that.

Ben Felix: I guess apologies to the reviewer's wife for having to listen to a summary about equal weighted index funds.

Ben Wilson: My wife pretends to care, but she definitely does not care. I don't know about yours.

Ben Felix: We don't talk about this stuff much.

Ben Wilson: I mean, anything to do with finance or work, it's like not interested at all.

Ben Felix: It just doesn't come up. If I were to talk about it, my wife would at least pretend to be interested, but we just don't talk about it much. Okay, then there's one.

This was from YouTube, but I thought it was – I just wanted to read it.

Dan Bortolotti: Well, we've been foreshadowing it for the whole episode here, so we've got to read it now.

Ben Felix: So they said, hey guys, let me preface this by saying that I love your show. I'm finally not lost when it comes to finance and it's all thanks to the PWL crew and your commitment to educating us once a week. So for that, you will have my eternal gratitude.

Having said that, I discovered your podcast about one year ago. I've listened to about 150 of the episodes, started with more recent ones, but have now decided recently to start listening from the beginning. I'm up to episode 80.

I would like to give some constructive criticism if you would hear it. Not only will we hear it, we will share it with our entire audience. Your most recent episodes, I find, are missing enthusiasm.

The team sounds a bit more tired as if they're just going through the motions. This episode in particular, this was, I think, the ETF slop episode. I personally noticed two to three gaps where no one was talking and I thought my earphones had lost connection.

I was about to go check them and the conversation started again. Compare this to episode 80, I don't even know what episode 80 was about, where Cameron and Ben sound much more into the conversation. It's a marked difference.

I'm writing this because I want you guys to continue succeeding. Don't lose your momentum factor, Ben.

Dan Bortolotti: We might've just been taking a sip of water. I mean, let's not read too much into those two second pauses.

Ben Felix: Didn't mention you guys. What's your momentum factors?

Ben Wilson: Two seconds feels like an eternity, but it's not really that long.

Dan Bortolotti: How can you not get excited about that?

Ben Felix: I remember that episode, episode 80. A planning checklist, portfolio concentration on leverage. That was fun.

Dan Bortolotti: I'm all a tingle just thinking about it. I'm going to go back and re-listen.

Ben Felix: Very funny. Anyway, I thought we'd share that feedback from a listener. We do always appreciate getting feedback.

What else was I going to say? Oh, we started uploading the videos of the episodes to Spotify. There's a thing on Spotify where you can upload audio, which we've historically done, or you can upload video, which we are now doing, but you cannot upload both.

Dan Bortolotti: Interesting.

Ben Felix: People who have been listening to our podcast on Spotify can now watch, which is cool. The trade-off though, is that they have to listen to the audio of the video.

Some listeners may be aware because we've talked about this a couple of times. The audio edit is different from the video edit. We speed up the audio by about 10% and all those gaps that our YouTube viewer was concerned about, they get cut from the audio edit.

So it's much tighter and it goes a little bit faster. So people listening on Spotify are probably thinking, why are these guys so slow? We are no longer sped up by 10%.

I don't know. We thought people might like to see the video, but people are now complaining that it's too slow. I guess you can go and speed it up in your app now that the audio is slowed down a little bit.

Dan Bortolotti: We are 15% more enthusiastic on the podcast feed.

Ben Wilson: I can assure you of that.

Ben Felix: Oh, the other thing there, we made all this fuss about the disclaimer, which people loved, the people who did listen to it. Dan, you did a great job writing that.

People did think it was funny and it was less painful to listen to, which was the objective. In the video edit though, we don't actually put the disclaimer because it shows up on the screen in text at the end of the episode. And so now the Spotify episode, because it has the displayed text disclaimer, no longer has the audio disclaimer.

So people who didn't like the disclaimer coming through their audio, they can now listen on Spotify, but they're going to have to listen to the slow down. A lot of trade-offs here. I don't know.

Dan Bortolotti: I think everyone should watch and listen. You'll retain much more if you go through it twice.

Ben Felix: Yeah, that was true. They could listen to the audio edit and watch the video edit, but not listen to the video edit. Well, I guess they're still going to listen to it.

Dan Bortolotti: And who doesn't have three hours a week to do both?

Ben Felix: I agree, Dan. Double up. I think that's it. All right. Anything else for you guys?

Ben Wilson: I'm good.

Ben Felix: Thanks guys.

Ben Wilson: That's it for me.

Ben Felix: Try and finish with some enthusiasm here. I don't know. Three cheers. All right. Thanks everyone for listening. See ya.

Disclaimer:

Portfolio management and brokerage services in Canada are offered exclusively by PWL Capital, Inc. (“PWL Capital”) which is regulated by the Canadian Investment Regulatory Organization (CIRO) and is a member of the Canadian Investor Protection Fund (CIPF). Investment advisory services in the United States of America are offered exclusively by OneDigital Investment Advisors LLC (“OneDigital”). OneDigital and PWL Capital are affiliated entities, and they mostly get on really well with each other. However, each company has financial responsibility for only its own products and services.

Nothing herein constitutes an offer or solicitation to buy or sell any security. Occasionally we tell you not to buy crappy investments in the first place, but that’s not the same thing as telling you to sell them.

This communication is distributed for informational purposes only; the information contained herein has been derived from sources believed to be “truthy,” but not necessarily accurate. We really do try, but we can’t make any guarantees. Even if nothing we say is fundamentally wrong, it might not be the whole story.

Furthermore, nothing herein should be construed as investment, tax or legal advice. Even though we call the podcast “your weekly reality check on sensible investing and financial decision making,” you should not rely on us when making actual decisions, only hypothetical ones.

Different types of investments and investment strategies have varying degrees of risk and are not suitable for all investors. You should consult with a professional adviser to see how the information contained herein may apply to your individual circumstances. It might not apply at all. Honestly, you can probably ignore most of it.

All market indices discussed are unmanaged, do not incur management fees, and cannot be invested in directly. Which is a shame, because it would be awesome if you could.

All investing involves risk of loss: including loss of money, loss of sleep, loss of hair, and loss of reputation. Nothing herein should be construed as a guarantee of any specific outcome or profit.

Past performance is not indicative of or a guarantee of future results. If it were, it would be much easier to be a Leafs fan.

All statements and opinions presented herein are those of the individual hosts and/or guests, are current only as of this communication’s original publication date. No one should be surprised if they have all since recanted. Neither OneDigital nor PWL Capital has any obligation to provide revised statements and/or opinions in the event of changed circumstances.

Is there an error in the transcript? Let us know! Email us at info@rationalreminder.ca.

Be sure to add the episode number for reference