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Speaker 1: Hello, and welcome to another edition of the Odd Thoughts Podcast.

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Speaker 1: I'm Tracy Hallaway and I'm Joe Wisenthal. So, Joe, I

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Speaker 1: think you're going to enjoy today's episode because we're going

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Speaker 1: to talk about one of the most intractable, most difficult

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Speaker 1: problems in all of finance and investing. It starts with

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Speaker 1: the ce Do you know where I'm going? Yeah. If

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Speaker 1: you hadn't told me it was going to start with

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Speaker 1: the CEA, then my mind was not. I didn't totally

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Speaker 1: know what you were about to say, But I think

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Speaker 1: I'm pretty sure with that letter hint. Okay, So I

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Speaker 1: just gave it away, which wasn't my intention. But today

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Speaker 1: we're going to talk about correlations. Uh. And correlations historically

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Speaker 1: have been quite difficult for banks and investors to model.

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Speaker 1: And there's one correlation in particular. It's sort of the

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Speaker 1: grand daddy of them all, and it tends to underpin

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Speaker 1: a lot of investing. And over the past few years,

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Speaker 1: we've seen more and more people start to question whether

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Speaker 1: or not it actually exists in the way that we

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Speaker 1: think it does, and whether or not that correlation, that

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Speaker 1: particular relationship is going to hold true in the future

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Speaker 1: and now I definitely know that you know what I'm

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Speaker 1: talking about. Right. Of course, a lot of people have

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Speaker 1: portfolios consisting of some slug of equities which are perceived

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Speaker 1: as being risky assets, and some chunk of safety assets

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Speaker 1: like bonds, and over the long uh, well, over the

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Speaker 1: short term, you sort of expect them to move in

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Speaker 1: opposite directions, and so on days when people are scared,

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Speaker 1: your safety ssets rise and your risky ssets fall, and

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Speaker 1: vice versa on bullish days. But none of this is guaranteed. Basically,

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Speaker 1: just because for some period of time two different assets

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Speaker 1: may have behaved and had some relationship does not necessarily

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Speaker 1: mean that that relationship will persist forever. And hence a

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Speaker 1: good portfolio is not a easy thing to achieve. Right,

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Speaker 1: So you think about a standard portfolio, and the thing

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Speaker 1: that usually comes up is sixty forty, right, that particular

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Speaker 1: breakdown between bonds and equities. It's supposed to be a

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Speaker 1: diversification play. The two asset classes are supposed to move

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Speaker 1: in different directions. But we have actually seen a couple

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Speaker 1: of times this year where they didn't do that, where

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Speaker 1: bonds and stocks fell in tandem, And of course a

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Speaker 1: bunch of people started asking whether or not this was

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Speaker 1: the start of a historic break in that relationship. So again,

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Speaker 1: this is probably one of the most important correlations in

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Speaker 1: all of modern investing. Early February we saw that where

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Speaker 1: we saw stocks and bonds get sold off together and

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Speaker 1: basically people who thought of themselves as being prudent diversified

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Speaker 1: investors were left with nowhere to hide. It was just

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Speaker 1: right across the board. Since then, things have mellowed out

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Speaker 1: and diversified investors have done a little bit better, but

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Speaker 1: it did. It does make you wonder whether that was

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Speaker 1: a warning or at least a message there. Just because

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Speaker 1: you are seemingly diversified does not mean that some part

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Speaker 1: of your portfolio is always going to work or heade

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Speaker 1: against the other parts. Absolutely, So we are going to

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Speaker 1: dig into both those concepts, correlation and diversification, and we

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Speaker 1: have the perfect person who's going to talk about it

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Speaker 1: with us, a guy that's been doing a lot of

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Speaker 1: research on this exact topic. His name is for Ruke Javraj.

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Speaker 1: He his head of investment Strategies research over at Barclay's.

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Speaker 1: For Ruth, thanks so much for joining us, Thanks for

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Speaker 1: the invitation. So did we get it right? In our intro,

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Speaker 1: is correlation that difficult for people to model? Is it

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Speaker 1: a sort of ongoing intractable issue in finance? That's exactly right.

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Speaker 1: I mean, fundamentally, correlation, irrespective of where you're measuring and

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Speaker 1: across asset classes or across stocks, et cetera, is time varying,

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Speaker 1: and I think we're all very familiar with the fact

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Speaker 1: now that it varies through time. Historically, there was an

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Speaker 1: opinion about in particular, between the correlation of stocks and bonds,

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Speaker 1: that they were positively correlated, and over the long run,

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Speaker 1: depending upon the sample of data that you're using, you

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Speaker 1: can't find that they were positively correlated during certain periods.

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Speaker 1: But you know, post then there was almost a structural

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Speaker 1: break between the relationships of stocks and bonds and they

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Speaker 1: became more negatively correlated. Bonds were seen as almost flight

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Speaker 1: to quality asset when risk was off the table. And

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Speaker 1: so ultimately we are seeing that there's more variation in

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Speaker 1: that correlation number through time, which means that it's harder

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Speaker 1: to model, it's more difficult as an input into your

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Speaker 1: portfolio construction methods, and there's because of the increase in

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Speaker 1: the market participation, so there's more investors who are trading

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Speaker 1: stocks and bonds in the market, from institutional through to

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Speaker 1: retail investors, there's just more noise around estimating this correlation,

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Speaker 1: and so it's a becoming an even more sensitive parameter.

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Speaker 1: I would say, in particular, as you mentioned, between stocks

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Speaker 1: and bonds. I want to go back a little bit

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Speaker 1: because diversification within a portfolio is one of these mantras

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Speaker 1: you always hear, but you always hear it's like, oh,

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Speaker 1: you should be diversified. Maybe some people know what that

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Speaker 1: means to be diversified, others don't. It's a fairly modern concept,

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Speaker 1: isn't it. This idea of diversification in the last several decades,

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Speaker 1: and this idea of having portfolios with distinctly different behaving

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Speaker 1: asset classes has not always been something that the investment

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Speaker 1: community understood. I think that's a fair assessment. I wouldn't

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Speaker 1: say diversification is a modern concept. I think at least

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Speaker 1: I've come from a very academic background, having done my

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Speaker 1: PhD in the topic of stop one correlation, by the way,

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Speaker 1: so this is the subject that is very close to

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Speaker 1: my heart, and ever since returns, risk and the relationship

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Speaker 1: between assets have been looked at by the academic community.

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Speaker 1: The principles of diversification have been well known from a

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Speaker 1: theoretical perspective. I should say, when I met Madern, I

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Speaker 1: met like the last sixty yeah since yeah, okay, so

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Speaker 1: not so. Modern investing has been around for hundreds, but

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Speaker 1: it's really only since the mid nineteen hundreds that people

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Speaker 1: have rigorously approached this idea of what it means to

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Speaker 1: have a diversified part. That's true, and it's become more

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Speaker 1: in focus, you know, as of the last you know,

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Speaker 1: several decades. In particular, for instance, commodities is being seen

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Speaker 1: as an asset class which can truly diversify your stocks,

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Speaker 1: your bonds, your f X exposure, mainly because it just

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Speaker 1: operates in a completely different way to the traditional asset classes.

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Speaker 1: So I mean, diversification as a concept is very well

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Speaker 1: understood and intuitive. Of course, you want to know, not

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Speaker 1: put all of your eggs in one basket, but how

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Speaker 1: do you go about doing that is the crux of

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Speaker 1: the problem, and correlations are very much at the focus

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Speaker 1: of how one goes about doing that and the course

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Speaker 1: of that estimation or trying to get it right. In

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Speaker 1: terms of forecasting, correlations is the most important question, and

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Speaker 1: that's that's really where the crux of the issue is.

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Speaker 1: I e. You know, historically we can look at the

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Speaker 1: realized correlation between asset classes depending upon how we look

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Speaker 1: at the data, and we can see that at various

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Speaker 1: three time. But does that mean what we're inferring from

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Speaker 1: history is going to apply going forward. So there is

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Speaker 1: a kind of mismatch between realized and then expected future correlations,

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Speaker 1: and that is, you know, where most of the research

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Speaker 1: currently exists in trying to really forecast what those correlations are.

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Speaker 1: So I have a variation of Joe's question before we

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Speaker 1: dig into forecasting correlation, but why did the bondstock split

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Speaker 1: or bondstocks diversification become the sort of standard portfolio model,

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Speaker 1: Like why didn't we have people say I'm going to

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Speaker 1: have stocks and commodities of some sort for instance. Yeah,

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Speaker 1: I mean it's a good question. But stocks and stocks

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Speaker 1: and bonds are the two fundamental asset classes that investors

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Speaker 1: used to use in order to manage their assets and

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Speaker 1: have growth on over time. So stocks are clearly obvious

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Speaker 1: people are looking to participate in the growth of corporate

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Speaker 1: profits and related economies, and bonds is because that's the

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Speaker 1: other side of the financing equation stocks is equities, bonds

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Speaker 1: is in essence, you know, you're lending money for either

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Speaker 1: government or companies to use it to invest in capex projects.

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Speaker 1: And so there are two sides of the of the

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Speaker 1: you know, I would say investing coin and those are

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Speaker 1: the two fundamental sides, and they're linked intrinsically by ultimately

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Speaker 1: you know, macroeconomics um and what economies together with sectors

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Speaker 1: and regions are doing. And so that's why stocks and

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Speaker 1: bonds were looked at as the first asset classes to

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Speaker 1: combine together. You mentioned that in more recent times there's

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Speaker 1: been a lot of interest in commodities as a source

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Speaker 1: of portfolio diversification. What is your view on that, because

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Speaker 1: in addition to sort of being uncorrelated as a key

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Speaker 1: preconditioned to adding from positive diversification, you also have to

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Speaker 1: have some sort of positive expected return because you could

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Speaker 1: add a source of uncorrelation like say betting on baseball games,

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Speaker 1: which won't be tied to the background economy, but that's

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Speaker 1: probably going to be a dragon your portfolio if you're

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Speaker 1: average gambler. So in your view, do commodities fit the

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Speaker 1: bill where either sufficially uncorrelated and be you can assume

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Speaker 1: that they will add money to your portfolio over some

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Speaker 1: period of time. Yeah, So I mean that's a good question.

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Speaker 1: Commodities is a very i would say interesting asset class

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Speaker 1: because it evolves basically based upon the applied demand dynamics

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Speaker 1: of individual commodities that are being produced, and so it's

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Speaker 1: almost operates independently because as individuals and societies, we actually

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Speaker 1: have a demand and let's say natural resources, gas oil,

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Speaker 1: et cetera. And you know that's almost separate from how

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Speaker 1: participants or individuals interact with financial markets. So you have

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Speaker 1: these two different segments of society that people are looking

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Speaker 1: or investing or consuming, and in essence they're not intrinsically linked.

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Speaker 1: Now they've become more so through time as people have

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Speaker 1: looked more to commodities markets to include into their portfolios,

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Speaker 1: as you can imagine. But that's initially why there was

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Speaker 1: a motivation to include it. But you know, as of

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Speaker 1: the last let's say, you know, five to seven years,

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Speaker 1: our commodities as in focus as they were the last

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Speaker 1: twenty years. No, and that's mainly because we saw the

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Speaker 1: big commodity rise and then crash and as subsequent kind

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Speaker 1: of For instance, the relationship with gold and oil after

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Speaker 1: the global financial crisis has meant their investors haven't naturally

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Speaker 1: used them in the ways that they have done historically.

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Speaker 1: So it's a very interesting asset class that you know

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Speaker 1: involves almost independently of others, whereas things like credit, for instance,

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Speaker 1: are very much equity like and so those are kind

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Speaker 1: of seen, as I would say, another way to achieve

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Speaker 1: equity light returns. But the average returns historically have been

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Speaker 1: higher in certain regions, and so that's why, you know,

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Speaker 1: commodities were seen as kind as outlier that could be

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Speaker 1: included in the portfolio for diversification. Right. I just got

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Speaker 1: a flashback to a circa two thousand nine when we

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Speaker 1: had a bunch of commodities funds launching that specifically were

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Speaker 1: aimed at providing uncorrelated returns for investors. But of course

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Speaker 1: those uncorrelated returns turned out to be negative and a

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Speaker 1: bunch of them closed shop soon after. Moving on to

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Speaker 1: the bigger question what we're discussing earlier, why does correlation

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Speaker 1: tend to vary over time? What are the prevailing theories?

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Speaker 1: What I will say is that from my perspective in

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Speaker 1: the research that I've done. There are almost two different

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Speaker 1: forces at work, the first being kind of a Macari

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Speaker 1: kind of story. So, in fact, one of my first

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Speaker 1: papers for my PhD was looking at the time variation

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Speaker 1: between the correlation of stocks and bonds using macroeconomic variables,

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Speaker 1: and I did it in a very theoretical way to

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Speaker 1: show that you know, through time there are kind of

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Speaker 1: new information on cash flows two companies, interest rates, and

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Speaker 1: the kind of risk premium i e. You know, what

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Speaker 1: return should be delivered for the risk that you're being

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Speaker 1: exposed to. That cause for the change in the relationship

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Speaker 1: between stocks and bonds, and these macroeconomic forces, together with

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Speaker 1: interest rates and inflation, cause the variation to to really

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Speaker 1: change through time. Now that's one side of the story.

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Speaker 1: The second is more of a kind of more pragmatic

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Speaker 1: market practitioner approach. And this is what I was alluding

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Speaker 1: to earlier in that, you know, I would say pre

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Speaker 1: eighties the way the investors interacted with markets is very

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Speaker 1: different from posties and nineties, where almost financial markets were

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Speaker 1: opened up to everyone, retail investors, mom and pop investors

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Speaker 1: on the street, et cetera. Through the creation of et

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Speaker 1: F vehicles and so now the way that market participants

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Speaker 1: interact with markets is very different from what it was

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Speaker 1: thirty fourty years ago, where it's mainly institutionally driven, and

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Speaker 1: as such that is causing a change in the relationship. So,

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Speaker 1: as you mentioned earlier in February of this year, you know,

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Speaker 1: we saw the stocks and bombs sold off at the

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Speaker 1: same time. Now, that's a very short time frame to

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Speaker 1: evaluate the relationship. But the point being is it happened

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Speaker 1: we've observed that in practice. Now would we have seen

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Speaker 1: that dynamic if people weren't actively trading the market so

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Speaker 1: frequently as they are now, Perhaps not. But point being

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Speaker 1: is there are these two forces at work, the macroeconomic

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Speaker 1: story as well as the kind of market participants story. Yeah,

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Speaker 1: I feel like this market participation story and the ease

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Speaker 1: with which people can access these asset classes is probably

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Speaker 1: something we don't discuss enough when thinking about big trends.

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Speaker 1: I'm thinking about how a lot of big institutions, some

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Speaker 1: of the college endowments, they've been very big into by

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Speaker 1: forestry and timberland as basically another asset class that could

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Speaker 1: be offered diversification. But if I can access the same

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Speaker 1: thing now, you know, at one point I imagine people

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Speaker 1: had to take flights all around the world to inspect

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Speaker 1: a forest and actually sort of make a deal with

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Speaker 1: someone about whether they would get some royalties. Now, I

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Speaker 1: could probably just go onto my brokerage account and invested

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Speaker 1: some forestry e t F and if in February of

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Speaker 1: this year I'm panicking and worried, I'll just sell that

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Speaker 1: along with my stocks and my bonds because I need

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Speaker 1: to pay my bills. That's a pretty fundamental change in

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Speaker 1: the sort of flows in and out of this market. Yeah,

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Speaker 1: that's right. I mean that's a function of financial innovation.

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Speaker 1: So you have more people looking at creating products linked

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Speaker 1: to things that perhaps are liquid, like forestry or even

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Speaker 1: private equity, And you're right, that ultimately changes the dynamic somewhat.

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Speaker 1: It creates this perception of, you know, something's happening in

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Speaker 1: the forestry market or the private equity market that we

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Speaker 1: can observe from market variables like an e t F

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Speaker 1: there is linked to a index that is used to

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Speaker 1: try and replicate the exposure to forestry of privorate equity.

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Speaker 1: But you know, is it genuine, is it true? You know,

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Speaker 1: is it really linked to the underlying fundamentals of that

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Speaker 1: particular asset class quote unquote asset class, and so, you know,

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Speaker 1: it does change the way that investors think and ultimately

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Speaker 1: add exposures into their portfolio. Certainly, so it sounds like

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Speaker 1: we're saying that because of the way that the market

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Speaker 1: has evolved and developed, that correlation regimes have the potential

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Speaker 1: to change more quickly than they had in the past.

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Speaker 1: But you still kind of needed a trigger in the

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Speaker 1: form of, I guess, a change in the macroeconomic environment.

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Speaker 1: So what should we be looking out for when it

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Speaker 1: comes to, you know, those sorts of triggers in the

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Speaker 1: correlation regime? What have you found to be most valuable?

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Speaker 1: The first thing to say, and it's said by pretty

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Speaker 1: much everyone, correlation is not causation. And that's why I

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Speaker 1: alluded to the fact that the you know, in my view,

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Speaker 1: there are these two forces at work, the macro story

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Speaker 1: as well as the kind of market story, which are

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Speaker 1: the causation reasons for why we see correlation changing through

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Speaker 1: time and how they interact is obviously a very complicated

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Speaker 1: and interesting thing to observe. But you know, what should

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Speaker 1: we be looking for? That's a good question. I think

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Speaker 1: ultimately this is certainly probably informed with the work that

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Speaker 1: I've done with Bob Shiller, who's one of our partners

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Speaker 1: on the Barclays COS platform, in that the more data

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Speaker 1: that you have, the better. I mean, his research work

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Speaker 1: with John Campbell goes back to the eight hundreds where

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Speaker 1: he has a data serve SMP back to seventy one,

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Speaker 1: and I'm a big believer now that we should obtain

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Speaker 1: as much data as possible because then we can almost

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Speaker 1: infer structural relationships between asset classes where we have that data.

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Speaker 1: And as such, if we are then able to monitor

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Speaker 1: correlation through time on a real time basis. Now because

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Speaker 1: we have daily observations or intra day observations, we can

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Speaker 1: see if there are structural dislocations versus what we've observed

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Speaker 1: in the past. If we observe that, okay, it's a flag,

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Speaker 1: and then we start to look closer at well, why

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Speaker 1: is that happening? And if we can justify it from

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Speaker 1: a macrec normic perspective or a market participant perspective, then

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Speaker 1: I think we can be comfortable about the changes and

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Speaker 1: the volatility in the correlation numbers that we're seeing, and

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Speaker 1: as such, it then is still a very good and

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Speaker 1: fundamental input into our portfolio construction techniques, if you will. So,

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Speaker 1: I think knowing well or feeling that we understand what

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Speaker 1: the relationship has been between assets historically and trying to

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Speaker 1: justify why we're seeing changes now is the big part

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Speaker 1: of our kind of the challenges that we have for

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Speaker 1: the investing space, and that's how I would approach that

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Speaker 1: particular problem. So in light of that, going back to

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Speaker 1: the starks bonds portfolio correlations, it's been really nice for

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Speaker 1: investors that inflation has generally been on the decline for

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Speaker 1: almost forty years because a starks have gone up, but

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Speaker 1: disinflation is just good for bonds, and bond has become

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Speaker 1: more valuable as flation goes down. In light of the

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Speaker 1: longer term data that you've looked at, how much is

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Speaker 1: the durability of this portfolio and the strength of say

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Speaker 1: sixty forty portfolio, how much is it a function of

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Speaker 1: this very banangn macro environment that we've seen. Ultimately, the

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Speaker 1: sixty forty portfolios designed where it was suggested as a

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Speaker 1: route to diversify equity risk into fixed income risk, and

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Speaker 1: inflation eats ultimately at the real returns that you earn

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Speaker 1: on your portfolio. And so generally the portfolio has helped

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Speaker 1: by inflation coming down through time. So that's obviously a

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Speaker 1: benefit to the end investor in that particular respect, but

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Speaker 1: also inflation, arguably it is the super interesting variable because

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Speaker 1: at least from my perspective, it's managed far more closely

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Speaker 1: now than it has been done historically. If you think

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Speaker 1: about central banks, pretty much, they have an inflation target

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Speaker 1: and everything revolves around hitting that target these days, and

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Speaker 1: they use all of their tools at their disposal to

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Speaker 1: try and do that. And so you know, going back

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Speaker 1: to a place where you know we're going to have,

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Speaker 1: you know, these high inflation numbers I think is I mean,

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Speaker 1: it's always possible, given especially given the period of quantity

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Speaker 1: of easing that we've gone through in the developed economies,

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Speaker 1: but you know, there's so many other forces at work

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Speaker 1: these days, then I'm not sure we will end up

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Speaker 1: going back to those levels. And so that's something that

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Speaker 1: is of I would say a good thing for the

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Speaker 1: end investor when it comes through to their their overall portfolios.

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Speaker 1: So we've made it this far talking about bonds and

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Speaker 1: stark correlation without mentioning risk parity, but I'm going to

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Speaker 1: ruin it now, so whenever people talk about market correlations,

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Speaker 1: or even whenever they talk about sell offs recently, risk

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Speaker 1: parity always seems to come up. And there's this notion

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Speaker 1: that risk parity these are strategies sort of balanced portfolio

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Speaker 1: strategies stocks and bonds, where they apply leverage to the

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Speaker 1: bond the fixed income portion of the portfolio to boost returns.

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Speaker 1: There's a notion that risk parity is either in great

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Speaker 1: danger if the correlation regime ever shifts, or that risk

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Speaker 1: parity is somehow going to exacerbate market volatility by sort

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Speaker 1: of messing with correlations in the market. How do you

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Speaker 1: view risk parity and what is its susceptibility and its

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Speaker 1: relationship with correlation. I mean, that's a good question in

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Speaker 1: terms of its relationship with the correlation. But before answering that,

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Speaker 1: it's good to step back and think about why risk

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Speaker 1: parity basically became into favor and you know what it's

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Speaker 1: being used for now. So risk party, as a let's

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Speaker 1: say concept, was ultimately a way to increase your exposure

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Speaker 1: two bonds versus stocks, and in essence allocating let's say

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Speaker 1: six to bonds and stocks, so dialing stocks down further,

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Speaker 1: and it's a function. Ultimately, you know, the weights that

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Speaker 1: you're applying the asset classes, or the way that you're

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Speaker 1: applying leverage is a function of, in this case, estimating

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Speaker 1: the risk from the asset classes. So of course, the

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Speaker 1: risk parity is known very well as the fact that

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Speaker 1: fixed income has a lower risk than equities, so we

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Speaker 1: overweigh equities, sorry, fixed income more versus equities so that

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Speaker 1: we balance the risk contribution coming from each individual asset class.

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Speaker 1: And as such that meant that your overweight bonds relative

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Speaker 1: to equities. Fundamentally, now, ris parity funds did fantastically well

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Speaker 1: during the yields collapsing because obviously bond did well. The

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Speaker 1: returns to bonds what up. So you know, up until

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Speaker 1: the point where you know, yields are their lowest that

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Speaker 1: we've ever seen historically. For a persistent amount of time

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Speaker 1: since the global financial crisis, there has been this concern

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Speaker 1: that risk parity funds and approaches are not going to

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Speaker 1: be good going forward because we're overweight bonds, but expected

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Speaker 1: returns are lower than they have been historically because yields

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Speaker 1: have to rise. So with that being said, there's a

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Speaker 1: huge debate on Okay, we understand the popularity of risparity,

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Speaker 1: but we don't necessarily understand the forward popularity of respiraity

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Speaker 1: or the efficacy of that approach going forward. And that's

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Speaker 1: also a function of the fact that the correlation dynamic

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Speaker 1: has changed through time. So historically, you know, the correlation

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Speaker 1: between you know, stocks and bonds was positive. If you

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Speaker 1: could put a little bit more weight on bonds with

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Speaker 1: deals collapsing, you'll earn more returns. That's great, But now

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Speaker 1: they've become negative. So in essence, they're more diversified as

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Speaker 1: asset classes. But risk parity ignores the expected return component,

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Speaker 1: and they expected return component on bonds in general is lower.

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Speaker 1: So is it sensible to overweight your portfolio to bonds

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Speaker 1: now given where we are most saying no? And so

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Speaker 1: that's why this is an interesting question, because correlations will

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Speaker 1: inform us that it's good to be diversified across docks

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Speaker 1: and bonds because they have a somewhat negative relationship at

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Speaker 1: the moment, but again vary through time. But the expector

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Speaker 1: returns are not great for bonds, So what does one

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Speaker 1: do and in a risk parity setup that's not really

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Speaker 1: accommodated for And that's why risk parity is something that

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Speaker 1: is it's certainly a very interesting concept. It's been used

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Speaker 1: successfully in the past, but we really need to question

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Speaker 1: if that's the right approach going forward for our stock

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Speaker 1: bond mix. What about the aspect of the question of

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Speaker 1: whether the parity funds or risk parity strategies can themselves

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Speaker 1: be a source of financial market instability. So you get

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Speaker 1: some maybe yield back up and there's a liquidation of bottoms,

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Speaker 1: and then that causes selling over all of the strategy.

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Speaker 1: Every time we get one of these sharp down drafts,

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Speaker 1: people point to if they don't point to risk parity,

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Speaker 1: they point to some other systematic strategy in which there's

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Speaker 1: some mechanicals selling. How much does that concern you? So

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Speaker 1: I think it's a concern because there are certainly more

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Speaker 1: instruments and vehicles ets in disease that are rules based,

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Speaker 1: whereby if there's a shock to the market, there's a

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Speaker 1: sell off and that activates other triggers and let's say

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Speaker 1: quant portfolios, which further sells off, and then that causes

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Speaker 1: an increase in the realized volatility of those asset classes.

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Speaker 1: So I think it's it's definitely a concern, and it's

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Speaker 1: a concern in more I would say, very specific asset

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Speaker 1: class or areas. So risk priorities an element that's widely

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Speaker 1: discussed because there's so much money invested in risk parity

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Speaker 1: type funds and instruments. I mean, the estimate that I

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Speaker 1: heard the other day is that there's over four billion

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Speaker 1: in risk parity type solutions. So when all of this

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Speaker 1: money is moving at the same time, given the nature

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Speaker 1: of dynamics, we're seeing these increases in volatility, So we

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Speaker 1: have to think about it from a kind of mark

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Speaker 1: to market daily perspective. It's a concern, but remember why

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Speaker 1: we're doing this in the first place, which waning to

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Speaker 1: achieve outperformance versus let's say the sixty benchmark on average

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Speaker 1: three time. So if investors a patient and ride out

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Speaker 1: those volatility shocks in certain cases, as long as the

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00:27:46,640 --> 00:27:50,320
Speaker 1: portfolio has been set up well, you're still expecting to

432
00:27:50,359 --> 00:27:53,800
Speaker 1: do better, and so there's more noise, I would say,

433
00:27:53,800 --> 00:27:56,960
Speaker 1: but that doesn't necessarily change the structural effects, which is

434
00:27:56,960 --> 00:28:00,199
Speaker 1: why we ultimately we should be positioning our portfolio is

435
00:28:00,240 --> 00:28:04,040
Speaker 1: based upon our objectives and the structural things we want

436
00:28:04,080 --> 00:28:08,240
Speaker 1: to achieve. So basically, I think that as long as

437
00:28:08,280 --> 00:28:14,119
Speaker 1: we position our portfolios accordingly based upon the objectives we're

438
00:28:14,160 --> 00:28:16,760
Speaker 1: trying to achieve in the long run, whether that's the

439
00:28:17,440 --> 00:28:20,240
Speaker 1: investment objective over one year or five years or further

440
00:28:21,119 --> 00:28:24,720
Speaker 1: then riding out the short term shocks, if you will,

441
00:28:25,720 --> 00:28:29,919
Speaker 1: will always serve us well rather than playing into the

442
00:28:30,000 --> 00:28:35,359
Speaker 1: behavioral aspects of markets and also the implementation aspects of

443
00:28:35,400 --> 00:28:39,240
Speaker 1: these kind of rule based methodologies. Yeah, I wanted to

444
00:28:39,280 --> 00:28:42,000
Speaker 1: ask you something related to that point, But we're talking

445
00:28:42,040 --> 00:28:46,720
Speaker 1: a lot about risk parity, systematic funds, quantitative funds, all

446
00:28:46,760 --> 00:28:52,080
Speaker 1: that kind of stuff. How adaptable are those investment models

447
00:28:52,120 --> 00:28:56,160
Speaker 1: and how quickly do they respond to changes in the

448
00:28:56,200 --> 00:28:59,880
Speaker 1: way the market is behaving, like would would they bear

449
00:29:00,240 --> 00:29:05,160
Speaker 1: very very quickly adapt rules that they had previously been

450
00:29:05,200 --> 00:29:10,400
Speaker 1: relying on in order to respond to a new market behavior.

451
00:29:10,960 --> 00:29:15,640
Speaker 1: So this space has obviously become super coveted. So systematic

452
00:29:15,800 --> 00:29:18,720
Speaker 1: strategies in general, there's been a huge growth in the

453
00:29:18,760 --> 00:29:21,920
Speaker 1: a U M and these types of strategies, both in

454
00:29:22,040 --> 00:29:27,920
Speaker 1: terms of investors allocating to bank index products as well

455
00:29:27,960 --> 00:29:32,200
Speaker 1: as you know, fun solutions from masset managers. The reality

456
00:29:32,400 --> 00:29:35,840
Speaker 1: is the business of our groups, and I'm very much

457
00:29:36,000 --> 00:29:39,560
Speaker 1: one of the members of this community. Is that we're

458
00:29:39,600 --> 00:29:43,120
Speaker 1: constantly looking at how best to do things, how best

459
00:29:43,160 --> 00:29:48,400
Speaker 1: to manage risk, the sensitivity of the rules or parameters

460
00:29:48,440 --> 00:29:52,440
Speaker 1: that we're setting. And as such, I would say that

461
00:29:53,640 --> 00:29:57,560
Speaker 1: in certain cases it's very rapid and reactive, but that

462
00:29:57,600 --> 00:30:00,280
Speaker 1: may not necessarily be a good thing. So some times

463
00:30:00,280 --> 00:30:03,160
Speaker 1: you find that, especially on the asset management side, they

464
00:30:03,240 --> 00:30:07,040
Speaker 1: update the rules or change their parameters quite frequently. But

465
00:30:07,120 --> 00:30:08,800
Speaker 1: how do they How do we know that? You know,

466
00:30:09,280 --> 00:30:12,320
Speaker 1: in essence, when that strategy was designed. It's based upon

467
00:30:12,480 --> 00:30:16,680
Speaker 1: historical data. So if you see one or two observations

468
00:30:16,720 --> 00:30:21,320
Speaker 1: of these, yeah, I would say massive changes in the

469
00:30:21,360 --> 00:30:23,880
Speaker 1: ways that the returns are being delivered, Does that justify

470
00:30:24,080 --> 00:30:27,520
Speaker 1: changing your parameters based upon all of the analysis that

471
00:30:27,560 --> 00:30:31,240
Speaker 1: you've done historically over the last thirty or forty years. Again,

472
00:30:31,240 --> 00:30:34,080
Speaker 1: it's a question of research. So sometimes I think the

473
00:30:34,120 --> 00:30:37,520
Speaker 1: industry may try to change things rapidly, but is that

474
00:30:37,560 --> 00:30:41,520
Speaker 1: the best thing for the actual product, for markets, for investors.

475
00:30:42,320 --> 00:30:45,280
Speaker 1: And so at least you know, our group Barclays is

476
00:30:45,400 --> 00:30:49,080
Speaker 1: very concerned and constantly monitoring these things, and we tend

477
00:30:49,120 --> 00:30:53,920
Speaker 1: to want to design strategies where we're extracting an economic

478
00:30:53,960 --> 00:30:57,360
Speaker 1: source of return which has been shown to be there

479
00:30:57,400 --> 00:31:00,880
Speaker 1: in the long run, and we that will be they're

480
00:31:00,960 --> 00:31:04,160
Speaker 1: going forward. If there are slight variations and how that

481
00:31:04,240 --> 00:31:08,640
Speaker 1: return premium is delivered, then either you know, we we

482
00:31:08,720 --> 00:31:11,640
Speaker 1: need to update our prize on the research, or we

483
00:31:11,680 --> 00:31:14,600
Speaker 1: need to really believe in what we've done and manage

484
00:31:14,600 --> 00:31:18,120
Speaker 1: through the risks, and in such cases then we choose

485
00:31:18,160 --> 00:31:22,320
Speaker 1: not to change those rules or updates. Being dynamic is

486
00:31:22,360 --> 00:31:26,280
Speaker 1: not necessarily a good thing all the time. Sometimes you

487
00:31:26,320 --> 00:31:29,560
Speaker 1: need to just realize that there are these short term

488
00:31:29,600 --> 00:31:32,320
Speaker 1: noise effects that you just need to know right through

489
00:31:32,360 --> 00:31:36,520
Speaker 1: if you will. There are some historical sources of return

490
00:31:36,720 --> 00:31:40,000
Speaker 1: in market that right now people are talking about is

491
00:31:40,040 --> 00:31:43,840
Speaker 1: having been kind of busted. Whether it's value stacks that

492
00:31:43,920 --> 00:31:46,520
Speaker 1: haven't done as well, haven't reverted to the mean as

493
00:31:46,560 --> 00:31:51,600
Speaker 1: people expected, or various trend following or momentum strategies that

494
00:31:51,800 --> 00:31:56,960
Speaker 1: haven't added much diversification to people's portfolio. So I guess

495
00:31:56,960 --> 00:31:59,280
Speaker 1: this is exactly what you're saying. When you look at

496
00:31:59,400 --> 00:32:04,000
Speaker 1: these strategies which are designed to give people sources of diversification.

497
00:32:05,200 --> 00:32:08,080
Speaker 1: How do you think about applying the test to determine

498
00:32:08,520 --> 00:32:11,320
Speaker 1: is this just a very long period that will mean

499
00:32:11,400 --> 00:32:14,520
Speaker 1: revert or has there been some sort of trend break

500
00:32:15,040 --> 00:32:17,959
Speaker 1: that will say, yeah, it's time to move on and

501
00:32:17,960 --> 00:32:21,280
Speaker 1: look for some new sources of alpha. That's a great question,

502
00:32:21,360 --> 00:32:25,320
Speaker 1: and it's very topical for the alternative risk premier space

503
00:32:25,520 --> 00:32:28,040
Speaker 1: over the last six to nine months, because in general

504
00:32:28,160 --> 00:32:33,240
Speaker 1: the space hasn't delivered the returns for the risk that

505
00:32:33,280 --> 00:32:37,400
Speaker 1: we're taking that is in line with historical norms. Across

506
00:32:37,600 --> 00:32:41,760
Speaker 1: the various providers to this space, everyone's being asked the

507
00:32:41,800 --> 00:32:44,920
Speaker 1: same question. But what's really interesting is when you go

508
00:32:45,000 --> 00:32:46,760
Speaker 1: back to the data and this is what we use

509
00:32:46,880 --> 00:32:50,280
Speaker 1: and the economics about how we've designed these strategies. And

510
00:32:50,400 --> 00:32:54,720
Speaker 1: for instance, and the example of let's say value investing

511
00:32:54,720 --> 00:32:57,520
Speaker 1: in the cross section of stocks, when you look at

512
00:32:57,560 --> 00:33:01,560
Speaker 1: the data, we've been there before. You know, we've we've

513
00:33:01,600 --> 00:33:04,360
Speaker 1: seen the fact that there are certain periods in certain

514
00:33:04,400 --> 00:33:08,160
Speaker 1: cases for value or the size effect where it hasn't

515
00:33:08,160 --> 00:33:12,040
Speaker 1: worked for a period of five, seven, ten years, but

516
00:33:12,200 --> 00:33:16,480
Speaker 1: then it reverted. So looking in the data, we're not

517
00:33:16,560 --> 00:33:18,640
Speaker 1: in this case. We're not in this place where we

518
00:33:18,680 --> 00:33:22,880
Speaker 1: feel there's a structural dislocation in the relationship of the

519
00:33:22,920 --> 00:33:27,520
Speaker 1: returns being generated versus how people are going about investing

520
00:33:27,560 --> 00:33:31,880
Speaker 1: in let's say value stocks, and as such we ultimately

521
00:33:31,920 --> 00:33:35,160
Speaker 1: need to write through the cycle. These things are cyclical

522
00:33:35,200 --> 00:33:39,200
Speaker 1: in nature. They're based upon macroeconomics, which as we know,

523
00:33:39,280 --> 00:33:43,680
Speaker 1: have very long cycle effects, and so I wouldn't say that,

524
00:33:43,800 --> 00:33:46,960
Speaker 1: you know, we're as worried, but that being said, the

525
00:33:47,000 --> 00:33:49,280
Speaker 1: other side of the coin. So that's a very general comment,

526
00:33:49,440 --> 00:33:51,400
Speaker 1: but the other side of the coins that the devil

527
00:33:51,560 --> 00:33:55,040
Speaker 1: is in the detail. So different implementations will give you

528
00:33:55,240 --> 00:33:58,680
Speaker 1: answers of different results. So, for instance, in the in

529
00:33:58,760 --> 00:34:02,040
Speaker 1: the value space, you know, using the book to market ratio,

530
00:34:02,120 --> 00:34:06,520
Speaker 1: which was the original factor characteristic motivated by Farmer and French,

531
00:34:07,840 --> 00:34:11,040
Speaker 1: may provide a different side of the value premium from

532
00:34:11,040 --> 00:34:15,360
Speaker 1: say the cape ratio, which is something that Professor Schiller

533
00:34:15,480 --> 00:34:20,200
Speaker 1: obviously advocates for, or even things like let's say total

534
00:34:20,320 --> 00:34:24,480
Speaker 1: yield or other factor characteristics. So there are ways to

535
00:34:24,520 --> 00:34:29,839
Speaker 1: diversify the specific risk associated with choosing one factor characteristic,

536
00:34:29,880 --> 00:34:32,960
Speaker 1: which is a sensible approach, and I know it's something

537
00:34:33,040 --> 00:34:36,719
Speaker 1: that various participants will advocate for. I think, you know,

538
00:34:36,760 --> 00:34:38,759
Speaker 1: as long as we continue to look at doing things

539
00:34:38,800 --> 00:34:42,839
Speaker 1: from a sensible macroeconomic way where we diversify the way

540
00:34:42,920 --> 00:34:46,360
Speaker 1: we access. In this case, you value stocks and the

541
00:34:46,520 --> 00:34:49,279
Speaker 1: value in the cross section of stocks, then that's the

542
00:34:49,280 --> 00:34:53,600
Speaker 1: best way for investors to continue to reap the premium,

543
00:34:53,640 --> 00:34:57,160
Speaker 1: even in a period where perhaps that premium is not

544
00:34:57,200 --> 00:35:01,360
Speaker 1: as high as it has been historically. All right, well, Farruke,

545
00:35:01,520 --> 00:35:05,480
Speaker 1: that was really a fascinating conversation and a ton to

546
00:35:05,600 --> 00:35:09,520
Speaker 1: really think about going forward as we sort of continue

547
00:35:09,560 --> 00:35:12,480
Speaker 1: to debate whether or not we're seeing a temporary or

548
00:35:12,520 --> 00:35:15,760
Speaker 1: a sort of lasting shift in the relationship between bonds

549
00:35:15,800 --> 00:35:20,600
Speaker 1: and stocks. Brup Savage, head of Investment Strategies Research at Barclay's,

550
00:35:20,640 --> 00:35:38,200
Speaker 1: Thank you so much, Thank you for joining never much so, Joe.

551
00:35:38,320 --> 00:35:43,640
Speaker 1: I found that conversation really really topical and fascinating, and

552
00:35:44,320 --> 00:35:46,840
Speaker 1: you know, I thought we set it up reasonably well

553
00:35:46,960 --> 00:35:49,040
Speaker 1: in the sense that this is one of the most

554
00:35:49,160 --> 00:35:53,600
Speaker 1: difficult concepts in all of investing to really think about,

555
00:35:53,760 --> 00:35:56,680
Speaker 1: and you know, much less to capture or to model

556
00:35:57,000 --> 00:35:59,960
Speaker 1: in an effective way. I totally agree, you know how

557
00:36:00,239 --> 00:36:03,280
Speaker 1: like both of us go on TV and we write

558
00:36:03,360 --> 00:36:06,480
Speaker 1: articles sometimes and people will be like, Oh, I like

559
00:36:07,000 --> 00:36:09,800
Speaker 1: cyclical stocks right now, or I like tech stocks right now,

560
00:36:09,960 --> 00:36:14,120
Speaker 1: or I like emerging markets, and all that's fine and good,

561
00:36:14,640 --> 00:36:18,759
Speaker 1: But in my dream all conversations and markets would be

562
00:36:18,800 --> 00:36:23,040
Speaker 1: about portfolio strategy, because it wouldn't. It's it never makes

563
00:36:23,040 --> 00:36:26,399
Speaker 1: sense to just go into emerging markets. It only makes

564
00:36:26,440 --> 00:36:28,800
Speaker 1: sense to think about what weights you want to apply

565
00:36:28,960 --> 00:36:32,080
Speaker 1: to emerging markets in light of everything else, and give

566
00:36:32,120 --> 00:36:35,560
Speaker 1: it the various risk profiles. And so that conversation that

567
00:36:35,600 --> 00:36:38,400
Speaker 1: we just had is sort of the conversation on some

568
00:36:38,520 --> 00:36:42,000
Speaker 1: level that I wish all of our discussions were based on. Oh,

569
00:36:42,040 --> 00:36:44,880
Speaker 1: you're absolutely right, except I think all our TV discussions

570
00:36:44,920 --> 00:36:47,479
Speaker 1: would end up being about three hours long because first

571
00:36:47,520 --> 00:36:51,439
Speaker 1: week that's discussed broad portfolio construction, and then we get

572
00:36:51,480 --> 00:36:54,760
Speaker 1: into individual calls. But you're absolutely right. The context matters,

573
00:36:54,800 --> 00:36:56,600
Speaker 1: and it's a little bit silly to be talking about

574
00:36:56,640 --> 00:36:59,160
Speaker 1: should you buy or sell emerging market equities if you

575
00:36:59,160 --> 00:37:01,239
Speaker 1: don't know what the rest of the portfolio looks like.

576
00:37:01,760 --> 00:37:04,160
Speaker 1: The other thing that I was thinking about during that

577
00:37:04,200 --> 00:37:09,120
Speaker 1: conversation was there's an interesting theme in there about, you know,

578
00:37:09,160 --> 00:37:13,360
Speaker 1: the short term changes versus these sort of long term fundamentals,

579
00:37:13,360 --> 00:37:15,959
Speaker 1: and we've been seeing that crop up in the corporate world. Now.

580
00:37:16,280 --> 00:37:20,479
Speaker 1: It's interesting to hear something vaguely similar when it comes

581
00:37:20,480 --> 00:37:25,920
Speaker 1: to investing. Yeah, absolutely, And this idea too that you know,

582
00:37:26,000 --> 00:37:29,160
Speaker 1: you have to obviously look at the macroeconomic backdrop, but

583
00:37:29,320 --> 00:37:32,680
Speaker 1: also just the market structure backdrop is another thing that

584
00:37:32,760 --> 00:37:35,839
Speaker 1: I just don't think we talked about enough right now.

585
00:37:36,000 --> 00:37:38,479
Speaker 1: It would be as easy as it. I could buy

586
00:37:38,680 --> 00:37:43,759
Speaker 1: sup SP t F really easily, or I could buy

587
00:37:43,800 --> 00:37:46,440
Speaker 1: a Japanese government bond E t F really easily. I

588
00:37:46,480 --> 00:37:48,920
Speaker 1: think one of those exists that was just not a

589
00:37:48,960 --> 00:37:52,800
Speaker 1: thing that was available to me or to the average

590
00:37:52,800 --> 00:37:56,960
Speaker 1: investor several years ago. And it's almost impossible to imagine

591
00:37:57,000 --> 00:38:01,680
Speaker 1: that that hasn't changed the relationship between two asset classes

592
00:38:02,080 --> 00:38:04,440
Speaker 1: that may have been once very disparate and represented a

593
00:38:04,480 --> 00:38:07,880
Speaker 1: source of diversification, and now they're just h you know,

594
00:38:07,920 --> 00:38:10,920
Speaker 1: the difference is just a ticker symbol on a online

595
00:38:10,920 --> 00:38:14,840
Speaker 1: brokerage account. Right, You can rebalance your entire portfolio with

596
00:38:14,880 --> 00:38:18,040
Speaker 1: the click of a button essentially, Yeah, right, And it's

597
00:38:18,080 --> 00:38:21,840
Speaker 1: just this these things that we create the relationship. I

598
00:38:21,880 --> 00:38:25,080
Speaker 1: always think about long term capital management that hedge funds

599
00:38:25,080 --> 00:38:28,040
Speaker 1: that blew up. They bought a bunch of assets that

600
00:38:28,120 --> 00:38:31,319
Speaker 1: were seemingly totally diversified and shouldn't have been correlated with

601
00:38:31,320 --> 00:38:34,120
Speaker 1: each other, but by virtue of the fact that they

602
00:38:34,120 --> 00:38:37,360
Speaker 1: were the one entity that held them all, they then

603
00:38:37,400 --> 00:38:42,720
Speaker 1: became the source of correlation. And everyone knew they owned

604
00:38:42,760 --> 00:38:45,239
Speaker 1: all these assets, so people have traded against them, and

605
00:38:45,320 --> 00:38:50,359
Speaker 1: so they they essentially created a correlated managed to create

606
00:38:50,360 --> 00:38:53,759
Speaker 1: a portfolio of correlated assets from things that without l

607
00:38:53,760 --> 00:38:57,359
Speaker 1: T c M in the market, would have been uncorrelated. Joe,

608
00:38:57,400 --> 00:38:59,800
Speaker 1: We're going to have to do another Odd Thoughts series

609
00:39:00,080 --> 00:39:04,759
Speaker 1: famous miscalculations of correlation throughout history. So first we're gonna

610
00:39:04,800 --> 00:39:07,000
Speaker 1: do we have to do our accounting series, because last

611
00:39:07,040 --> 00:39:10,080
Speaker 1: episode we talked about how we needed an accounting series,

612
00:39:10,160 --> 00:39:12,279
Speaker 1: and now we need a whole another series on a

613
00:39:12,480 --> 00:39:16,560
Speaker 1: portfolio structure. I'm into it. God, Okay, al right, Well

614
00:39:16,840 --> 00:39:18,440
Speaker 1: let's call it a day then, because it seems like

615
00:39:18,480 --> 00:39:19,640
Speaker 1: we're going to have a lot of work to do

616
00:39:19,719 --> 00:39:22,840
Speaker 1: in the future. This has been another episode of the

617
00:39:22,880 --> 00:39:25,719
Speaker 1: Odd Loots podcast. I'm Tracy Alloway. You can follow me

618
00:39:25,840 --> 00:39:28,759
Speaker 1: on Twitter at Tracy Alloway and I'm Joe wisn't All.

619
00:39:28,880 --> 00:39:32,560
Speaker 1: You can follow me on Twitter at the Stalwart and

620
00:39:32,640 --> 00:39:36,239
Speaker 1: you can follow our producer on Twitter tofur Foreheads. His

621
00:39:36,320 --> 00:39:39,759
Speaker 1: handle is at Foreheads t and you should follow the

622
00:39:39,840 --> 00:39:45,160
Speaker 1: Bloomberg head of podcast, Francesca Levi on Twitter at Francesca Today.

623
00:39:45,160 --> 00:40:00,920
Speaker 1: Thanks for listening a