Potential opportunities in quantitative and passive investing

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From geopolitical risks to concerns about the future path of interest rates, there are no shortage of issues for investors to weigh. Now, given that backdrop, what role can strategies like quantitative and passive investing play in an environment like this?

Joining us now to discuss, Julien Palardy, Managing Director and Head of Quantitative and Passive Investing at TD Asset Management. Julien, great to have you here. Welcome to the show.

Thanks for the invitation, Greg.

All right. So since it is your first time on the program, let's give the viewers a bit of an overview of some of the strategy that your team oversees.

Yeah. We have quite a few strategies. Typically, the strategies are going to fall either between quantitative and passive. And within the quantitative space, you could think of strategies that fit different types of objectives for investors.

So on one end, you would have alpha-driven strategies that seek to beat the markets. You would also have risk-driven strategies that focus on reducing risk relative to the market. So those would be named typically low volatility strategies.

Then you would have other-- I'm not going to say alternative strategies. They're fairly common, but the objective could be slightly different than just returns or risk.

It could be dividend strategies, where the goal could be to achieve a fairly reasonable dividend yield versus the market, but maintaining the dividend yield through time, or the dividends through time by avoiding dividend cutters, or growing the dividends as well. So that would be a bit different than just pure returns or risk, but it still fits objectives that investors would typically have.

All right. So let's start breaking some of them down. You mentioned quantitative, passive, dividend strategies. Let's start with the quant side of it. Explain a little bit more. For some people, some investors, they say, I've heard the term quantitative investing. I don't really get what it means.

Typically, quantitative strategies are all about delivering an objective-- I talked about risk returns as well-- but using mathematical models, so working with statistics, massaging data, and trying to extract from data as much information as possible about the future risk of stocks or correlations between stocks, or the future returns of stocks as well.

So this would be for alpha strategies. So it comes down to turning data into usable information into forecasted returns, and then building portfolios around this. That's also an important part of quant strategies. You want to build portfolios that will allow you to generate either returns as systematically as possible through time, or reduce risk in the most possible robust manner through time as well.

OK. So that's interesting on the quantitative front. So the passive stuff-- how does that differ from quantitative?

It's quite different, although some of the tools are going to be fairly similar. So when it comes to passive investing, typically, those strategies are going to be tracking a specific index. And the goal here is to be as close as possible to the index through time. So you try to match this as perfectly as you can.

And the outcome that you're going to get is going to be entirely a function of what the index is going to do. So most of those indices typically would be cap-weighted, but there's also growing space, where there are indices that are not cap-weighted. They follow specific approaches or strategies.

Or I would call them quite often recipes. They're quant strategies, but on the light side of things, so typically, a bit simpler than the full quant strategies that we have on our team.

And there's an increasing number of those indices. And passive strategies can be tracking those indices as well. And this differs from quant, where you have complex models that seek to either outperform the markets or reduce risk. That wouldn't be typically the case for passive strategies.

The tools could be similar. So we have a fairly systematic approach on the entire team across quant and passive. We use optimizers, for example, but when it comes to passive, it's really with the objective of matching specific indices, like the S&P 500, for example.

All right. Let's talk dividend investing. Obviously, I think people well understand how that works. At the same time, I think the question for a while now has been, is this a favorable environment for dividend investing?

I would think so. In fact, it could be always a favorable environment for dividend strategies in the long run at the very least, but right now, what we face is, at least in Canada, a situation where it's very likely that the Bank of Canada is going to cut rates this year.

We've seen already a spread building up between Canadian bond yields and US bond yields. So this is a clear indication that the markets expect that there's going to be some divergence to some degree in terms of monetary policies north and south of the border.

And in this type of environment, there may be value in going out there to find sources of perpetual yield that you could lock in. And this could be given by dividend yielding stocks. And the key here is to focus on quality. So you want to make sure that you buy stocks that are not going to cut their dividend in the near future.

If there's a recession, for example, you want those dividends to remain as robust as possible in a downturn. So right now is a great opportunity to lock in a yield that's going to be higher than what you can get with, let's say, government bonds in Canada.

The yield could be in the range of 1% above that. And hopefully, it could be higher for the foreseeable future. Let's say bond yields go down. Those dividends will keep getting paid and, hopefully, can even grow in the future.

That's a key point, too, I think when it comes to dividend investing. You talk about quality names that will continue to support that dividend. I also know when people look into this space, they talk about not only, OK, here's the dividend right now. Do they have a history of growing that dividend? And will they continue to grow it?

Exactly. So ultimately, there are some key factors that we can look at when it comes to quality. And we do manage ETFs on our team that focus first on quality. So literally, we read out, from our investment universe, the companies that are most likely to cut their dividend or where the dividends are not sustainable.

And then we have an optimization process where we focus on maximizing the quality of the stocks that we hold subject to a constraint on dividend yield. So we don't go the other way around, where we try to maximize yield first and then look for reasonable quality stocks.

We really look for the best quality stocks we can get subject to certain dividend yield that they can allow investors to achieve.

Now, another strategy that hasn't gotten a lot of attention lately, considering how the markets performed last year-- but if I dial back to about 2022, I think it was low volatility was in the headlines a lot. Obviously, that was a very tumultuous year. What's happening in the space right now?

I would say that low volatility loves the favor of investors quite a bit recently because people tend to forget risk in strong up markets. So we've seen last year-- and in fact, it's continuing this year as well-- a fairly concentrated market rally.

The market rally has broadened out a bit in cyclical sectors, but the low vol stocks are largely left out of this. So defensive sectors are left out of the rally so far this year and last year. And as a consequence, investors are shying away from low volatility strategies, but unfortunately, empirical evidence is showing us that it's in periods like these that it's typically the best time to buy low vol.

So if we went back to the '90s, we would have seen a similar period in the late '90s, in '98, '99. And this would probably have been the best time to get into low vol, or at the very least, the worst time to get out of low vol.

But unfortunately, most of the market is quite often thinking about what's done well recently. And they focus on this. So I think low vol is going to be out of favor in market conditions like these, but they're going to come back in favor if there's a market correction or a market crash at some point.

A lot of interesting stuff there, Julien-- a lot of varied mix of strategies. So how do you build a team to run all these kinds of strategies? What kind of backgrounds do your people have?

So when I joined the team 17 years ago, or 18 years ago, most of the people on the team had backgrounds in financial economics and finance. We all had master's degrees and, in some cases, PhDs. We had one PhD in physics that was an exception because the person was working on bond models and fixed income models in general.

And nowadays, I would say that we diversify the backgrounds quite a bit. The type of hires that we do on the team tend to have technical backgrounds, but in different fields. So we're going to have people in computer science. We have an individual who did his PhD in combinatorics.

We have another one who did his PhD in maths. We have someone who did a PhD in cognitive sciences, so quite interesting background, but spent a few years in finance. So they're all familiar with finance quite a bit, but unlike our backgrounds from back in the days, we don't necessarily hire people in finance or economics anymore.

In fact, sometimes, I'm joking that I'm not sure that today I would be hiring myself on the team. So even though I lead the team, I've been lucky to join 17, 18 years ago. But today, we look for people who can do a lot of-- first of all, they need to know how to code.

That's a mandatory requirement on the team. But the second thing that we're looking at is bringing a diverse set of backgrounds so that we can complete each other when it comes to doing research projects, for example. So we look at diversity of knowledge and skill sets.



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