Andrew Ang Discusses Asset Management (Podcast)

uh factor investor. Not only does he have a background in stats and finance from from UM Stanford, but he taught finance at Columbia and the opportunity to put his theories into actual practice at black Rock just proved to be too tempting. He had to leave UM the theoretical practice of teaching and working at Columbia that he really enjoyed to give it a shot at black Rock, and

it's worked out extremely well. If you are at all interested in quantitative investing, modeling, factor investing, anything remotely involved in the wonky goodness of mathematical theory and investing, you're gonna love this conversation. So, with no further ado, my conversation with Black Rocks Andrew Ang. My extra special guest this week is Andrew Ang. He is the head of Factor investing at black Rock, the firm manages over six

trillion dollars. He comes to us with a PhD in finance and a master's degree in statistics from Stanford and he is the author of a book called Asset Management, A Systemic Approach to Factor Investing. Andrew Ang, Welcome to Bloomberg. Thank you. Barrett's a real pleasure to be here. Thanks for coming in. You have You have a really fascinating background. You spend the first half of your career in academia,

made you decide to transition from theory to practice. Indeed, I was a professor for fifteen years at Columbia University and ended as chair of the Finance and Economics Division and was the Anne F. Kaplan Professor of Business. What's interesting is that my wife, she was born in China. Her parents have this long, very scholarly Confucian style tradition and the highest life form for them is a tenured

professor at an Ivy League institution. And I thought I was absolutely crazy and leaving that and coming to industry. My parents, on the other hand, they didn't go to university. They actually I really don't know still today what a professor does well what do you mean you're not teaching. You mean you're on vacation. And they were really proud

of me for getting a real job. So the disparity in the attitudes, well, one thing that was very interesting is my wife said to me, Andrew, you're a hypocrite, because I used to feel that a lot of academics,

and I was myself one. They're very theoretical, but they believe that the world should operate in a particular way, of course, the way that they study the world, but they he she called me a hypocrite because actually I believed so much that I accepted a job offer to come to Black Crop because I wanted to change the way that finance was practiced in accordance to the research and factors that I was doing. So let's talk about

that research a little bit. You have a background and statistics, You get a PhD in finance that really lends itself to factor investing. That sort of quantitative approach is practically made for this. But I have to ask from your research, how did you find your way to a factor investing.

I was a professor, and I did a lot of consulting while I was a professor, and I had the privilege of working for some very large institutions, including the Norwegian Sovereign Wealth Fund, and this is a very special fund.

It's a trillion dollars today, it's multiple multiples times the country's GDP, and they went through some tough times in two thousand and eight, like many institutions, and I was tasked by the Ministry of Finance representing Parliament, together with two other academics to take a deep look at the fund, to analyze it, to see where the losses were coming from,

and to make recommendations. And what we found was that despite this fund owning tens of thousands of securities dozens of active managers, what mattered at the end of the day were these factors broad and persistent sources of returns.

Macro factors like economic growth, real rates and inflation which comes through market cap indices, and then relative to those market cap benchmarks, style factors like value and momentum quality, minimum volatility explain two thirds of the variation of these active returns, and so factors really mattered, and it was entirely appropriate for Norway to have these exposures to these factors that resulted in long term superior returns. So, so let me jump in right here and ask this. You're

you're viewing a trillion dollar portfolio. You're really separating the wheat from the chaff. You're identifying what the source of returns within that trillion dollar portfolio is. Do do the managers of the Norwegian Sovereign Wealth Fund then turn around and say, we're going to move away from the parts of our portfolio that aren't performing and towards where our out performances coming from. Or did they consider that diversification

and they leave it as it was. Norway has always used different sources of return, including fundamental analysis, and they continue to do that. But what we recommended and they did adopt, was to make a very top down, deliberate decision on these factors. And as a result, Norway started directly allocating to these factors to manage, better understand their risks, to enhance their returns, and as you say, Barry too, improve the diversification. So so they seem to be pretty

well versed in understanding the academic literature. But out in the real world, which is a fair statement to say, out in the rest of the real world, how does the way most people invest differ from from what's in the textbook. What what are the big disparities between people who aren't the Norway sovereign wealth funds and and the average investor? What what's the difference in their process and in their results? Great question bear because I really think

they are more similarities than differences. But if you have to think about you know, I used to be a professor and now you're a practitioner. What what are these differences? A lot of people talk about implementation short for and a lot of a jargon, the difference with transaction costs and stale prices or stale data. But actually the real difference between academic and practice is you've got to work with a lot of people to get these things to fruition.

And as a professor, you're sitting there in your office, you're sitting there by yourself often and you just do your own thing. But to make a difference, you have dozens of people and teams that you've got to partner with in order to make a product come until an advisor shelf. Let's talk a little bit about the best way to use factors. Are they designed to manage risk or are they designed to deliver market out performance. Well, yes, actually, I think factors should be used in all facets of

the investment process. We definitely need factors to look at really what drives our returned So there is an angle for risk management, and I think your firm has exemplified that very But we also would like to use factors to enhance our returns as well, and we can do that with value, quality, momentum size, and combinations of these return enhancing factors. We can also use factors to target specific outcomes like minimizing our downside risk exposure through minimum

volatility strategies. Factors can be used for all of these, And what's really exciting is that we can ask, what's the outcome you want to achieve. Perhaps it has created a versification or put full of resilience, and we will have some combination of factors that's right for you. So here's the question that always comes up when I discuss factors with other people. It seems once everybody discovers a new idea, it's power has a tendency to sort of

fade away. Now that we know so much about factors, we know about value, we know about small cap, we know about quality, why hasn't that been arbitraged away. How is it that long term factors still deliver some degree about formants. Ultimately, that's a question of who's on the other side, because not everyone can buy cheap. For every value stock that's cheap, there's got to be a stock

that's relatively expensive. The economic rationales behind all these factors are the same reasons why we think that these sources of returns are going to persevere for a long time. And there are three. There's a reward for bearing risk, a structural impediment, and investors behavioral biases. So wait before we get to the first and the third one, which I have a feeling, I know what you're gonna say, tell me about the second one. What is the structural

impediment to buying cheap or buying quality? Well, for value, there is no structural impediment because you can buy cheap. But for minimum volatility though, this is where structural impediments come in. And if we look at the United States, there are a large number of very large funds, a lot of public pension plans, but also other large institutions that have high to to return targets but a lot of restrictions on what they can do with their investment policies.

Some of those institutions will gravitate to higher risk stocks in an attempt to meet those high told to return targets, and then underweight the low volatility or low risk stocks, and that gives rise to minimum volatility strategies. Now, if that structural impediment disappeared and suddenly all of those institutions had much more flexible investment policies than perhaps we might see minimum volatility go away. But let's go to the first and third of those right, Well, well, what about

the reward for bearing risk? And here I'll give value as an example, since you raised this before, or small cap, because I keep having discussions with people who insist that the small cap premium is all risk, and I'm not sure how true that is. And if it is largely risk that we're shown, but that's a risk that you should be comfortable bearing and will result in the long term with compensated higher returns. Now, Value a lot of value companies a little bit old fashioned. They often manufacture

things or produce services. They're very good at that, often with a lot of fixed or physical capital. And when you get into a lite economic cycle or an economic recession. It's very hard to change what your factory is currently manufactured, and so not surprisingly, those value firms tend to underperform those fixed costs. All of that physical capital give those value companies economies of scale, so they tend to perform

the best coming out from the recessions in the recovery. Now, you can't stomach these cyclical losses, and value absolutely no doubt, has had a pretty rough ride of it over the past couple of quarters, consistent where where we are in the late economic cycle. If you can't stomach that under performance, then well values not for you, but for those who can bear those risks of short term to performance, you will be compensated with a long term value premium. That's

the reward for barons. So how long is long term? Because since the OH nine crisis ended, value is under underperformed growth. That's a solid decade. We've been having an argument in my office. Is it one decade, two decades? It goes quite a while. Since value has consistently outperformed growth, What is the long term for for a factor manifesting itself as alpha. Yeah, these cycles can be three to five years, but over the last ten years value has outperformed.

But we give a little bit of a story coming into twenty six and that was a really great year for value. In fact, particularly in the last part of the year. Started before Trump's election in November, value was pretty much flat, and then there was tremendous under performance. It was until the fourth quarter of the fourth quarter Uarter four, and then through twenty eighteen we saw those losses.

Ex sorry, we find that twenty eighteen to now where in May is the fourth worst value draw down, fourth worst value draw down in almost a hundred years of data using the data set that starts in five constructed by Nobel Prize winning Gene Farmer and his longtime co author Kenneth French. Isn't that amazing fourth worth through century? That that's quite fascinating. Well again, fourth quarter of eighteen, when the market SMP fell about we saw value indexes

do much better. They fell a little bit, but not nearly as much as the growth in this disease. The fang stocks got she lacked in the fourth quarter, But here we are pretty close to near all time highs and it looks like growth has kind of caught up again. So is the expectation we're going to see some serious mean reversion and at some point in the not to distant future. Well, I believe in value, I'm a value investor.

M H. We do need to stay the course. Let's put that fourth worst draw down in context, so it's

not unprecedented. There are some worst times, and if we look at the top six to eight episodes of really bad value performance, they're characterized by an environment like what we've had late economic cycle, except our cycle today has perhaps been very prolonged to be in this late stage, and I mean I think that's a separate macro post financial credit crisis, FED intervention, etcetera, monetary policy and all

the rest of that. We also see some very severe accessions that There are two episodes in the nineteen thirties as well that are but the worst one is the late nineteen nineties in fact, and we're about half as bad as So let's talk a little bit about fixed income investors. Are they actually beginning to use factors now?

They are, and we've just introduced a few fixed income factor e t f s. That's part of the next evolutionists pushing these time tested concepts of like buying cheap and finding higher quality names, finding trends, but pushing that from where it's being mostly equities to fixed income and then to other multi assets applications like currencies and commodities, and then also to go invest in a long short manner as well, and fixed income. It's right there at

the frontier. So when I think of factor investing, I think of capsize, and I think of quality, and I think of price, namely value. Are you creating parallel versions of this for UM bonds? I mean our bonds cheaper expensive as a function relative to UM the combination of their credit quality and their forward expected cash flow based on will this default or not? How do you determine value or is it yield relative to to what the

ten your treasury is doing. All of these factors are broad and persistent, so they are seen in many different areas, but you do need some research to apply it in these different asset classes. So value it's all about buying cheap relative to intrinsic right, what's intrinsic or fundamental value for a bond? And so we can measure or apply value by looking at the yield of a bond. Well, that's equivalent to price. But we might now have intrinsic value versus a forward rate curve or versus an option

adjusted spread, for example. But we can apply the same concepts price or yield relative to a measure of intrinsic value. How does how does the risk free um treasury fit into figuring out what value is for a bond? The risk free rate operates across these different asset classes, and it's a base rate. It's sort of like the opportunity cost. Instead of parking your money in the bank, well, we're now going to take risk and were going to be rewarded for it. So it's coming across asset classes now.

The risk free rate, though in fixed income, gives you a term structure, and that term structure will translate into different factor strategies. So some people will talk about curve or row down. That's certainly a part of income investing or carry. We can also talk about risk free rates affecting different countries, and so now we think of an uh an international version of fixed income factor investing as well. Since we're talking about fixed income investing, there's now about

twelve trillion dollars of bonds that carry in negative yield. Here, I'm gonna lend you money, and I'm gonna pay you to hold my cash for me. How does that figure into factor investing for for bonds? And what does this say about the world of the cost of capital? I and almost guilty, really, because a lot of academics spent an enormous amount of time writing down very complicated models to ensure that interest rates remain positive. And what are

they now? They're they're not positive. It's almost like all that literature could have been thrown out more seriously, More seriously, what's really relevant here is the real rate rather than the nominal relative to inflation, relative to inflation, and there we've seen many episodes of negative real rates, and some of them I've I've worked with some co authors in papers about. The second is that if we think about the negative yielders, that you invest in bonds and you're

going to lose money. But we've had debt consolidations, we've had demonetizations, confiscations in the past. In the United States, we've actually seen some wealth destruction. In the nine thirties, we had a ban on individuals holding gold right, and that's a near money substitute, or at least it was at the time, because we were on the gold standard, So these negative yielding in a much order context. It's actually we've had these episodes before. Factors will continue to

have a place in this period. I think you still want to buy cheap, you still want to find these trends, you want higher quality names probably that's more important than ever. And you want to have portfolio resilience. And we can hold a combination of factors to help these investors. So you mentioned the evolution of factors and the evolution of new products. What what do you see coming down the pike?

What sort of stuff we've been hearing for a long time about these one thirty thirty portfolios, these long short et f s. What are the next things that factor investing is going to drive From the product side, we talked about some of these already pushing out these concepts from equities to fix income and other multi asset classes. But I think the real gains will come from applying data and technology. Two. The mom and dad sitting across

the table from a financial advisor. And my vision is that if you're having that conversation with an individual and that individual says I'm really worried about losing my job, they're making a statement about economic growth, and we can have some factors to help hedge that bad outcome. What's a day in the life of Andrew Ang, Like, yeah, what does that mean? Leading factor investing at black Rock

means like talk with a lot of people. I have the privilege of working with some really talented people, and I feel like a little kid in a candy store because there's all this great data and technology at Black Crock and we can put things to work and introduce new products and make it happen and have some factor analytics, data and technology all based on factors as well. So let's talk a little bit about your book. This is a serious um quantitative work. Tell us how the book

came about, and uh, who's it for. I wrote the book after working for several large sovereign institutions, sovereign wealth fronts, sovereign pension plans, and I talked all about factors, and I wanted to bring all of that knowledge that just even a decade two decades ago, were only available to really large sophisticated institutions, and I wanted to democratize access. In fact, that's our mission statement. It's to democratize the

broad and persistent democratize access to factors. And this book really put into context with case studies based on some of those, Uh, some of those institutions how to use factors in portfolios. So you said factors plural um and you mentioned Gene Farmer before, So the original Farmer French model was right. Then we got the five factor model,

then the seven factor model. And some people have made the claim that and I'm a little skeptical that most of these are of of really significant value, that there are four hun drew to a five factors. Some people have said a thousand factors. How many factors are there and how many really can be implemented? There are half a dozen macro factors and half a dozen style factors.

Macro factors drive returns across asset classes. The big three are economic growth, real rates, and inflation, and they explain about eight of the variation of returns across these different asset classes. Give us private markets. Give us those three again, economic growth, real rates, and inflation. Those are the big three, and within each different asset class, within equities, we can find pockets of securities that over the long run have

resulted in higher risk adjusted returns. Those securities that are cheap or high quality that we talked about earlier, and we can find those same patents in bonds and the commodities. We can even find them in private markets like private equity and real estate. Those are style factors and they operate within an asset class, and in equities we think

of value, quality, momentum, size, a minimum volatility. Now the criteria for these and why there's only like half a dozen macro half a dozen style, there's four criteria that whittles down the potential hundreds or thousands to just these narrows, just this narrow set. The first is that economic rationale that we talked about earlier, reward for bearing risks, structural and pediment or behavioral bias. We want very long histories

and that removes basically most of that. A lot of these, a lot of these don't don't have decades worth of history, and we would like that so that it informs how we can build those strategies and offer them. We want differentiated returns, particularly with respect to market cap benchmarks, right, what is it giving us that that that is different And then finally we want and this is a choice for black Rock, we want to be able to offer these in scale, so that means we can pass on

low costs to our clients. After him imposing all those full criteria, we're only left with that half a dozen macro half a dozen stuff quite interesting. So so what is next in factor land? Are there any yet undiscovered factors out there that might fall into either of these um two half dozen groups or have we pretty much squeezed all the juice out of the orange at this point. There's always continued development, but I think it's a little

bit like Shakespeare. You know, he wrote some great plays and sonnets back in Elizabeth E. Times, did that with quill and inc. Right, we still have well, he will be writing screenplays today. Right, Perhaps we have some streaming TV and other things like that, but there's still character and plot. But it's done in different forms. And we want to evolve buying cheap finding train, so the implementations of cost will change. We can do this better with

more efficient data and technology to lower transaction costs. We would also like to see how we can use them in portfolios. Factor analytics, factor allocation that I talked about earlier, Right, that's really what's new. But we're always going to have these half dozen macro and half dozen style. So you wrote a white paper that UM, I want to want out about a bit. The title was what does the

yield curve tell us about GDP growth? And there's a professor at UM the University at Duke University who has a recession forecasting model which has a perfect track record, at least in the limited time it's existed, it's been perfect. The fourth factor in his model is the inverted yield curve uses the five year in the three months UM and only when it's inverted for a substantial period of time, which in his measurement is ninety days a full quarter.

Last week we passed that we've already been inverted for that period of time. So I'm curious about what you found. What the yield curve means for future GDP growth? He suggests it's an indicator of recession twelve to eighteen months later. What what did you find? The YU curve has a lot of information about future economic activity, and there's always been a slowdown after a negative UM. There's always been a slowdown following a negative yelk of six quarters afterwards,

meaning an inversion. There's been actually one false positive, and that's in the late nineteen sixties, but there was still a slowdown in that period. Now that's an ode paper baron that you brought up, and we actually showed that in addition to the term spread negative term spread forecasting poor economic activity, the level of the interest rate was also pretty important too. And interest rates are fairly low now and they've actually decreased over the last couple of

months around the world. The level of that you curve also forecasts slowdowns. So it's not just the inversion, but inversion from a relatively low level also has a negative conta both the level. Low levels predict slowdowns and spreads. Negative spreads also predicts So why would low levels predict the slowdown? Is it a function of demand for capital that's used by an expanding economy or something else? This several explanations. See I'll just give one by John Taylor.

All Right, the Taylor rule? When is that? Is that still in effect? I thought we sort of didn't. Didn't we repeal the tailor rule. We've used it as the basis for many different policy and macro models, just perhaps not in its purest form to John Taylor, But it's gone through very iterations, and I think the intuition is still sound. Policymakers generally will raise interest rates when we're in very good times, right Inflation tends to pick up there and we want to take the punch bowl away.

During bad times, policymakers tend to lower interest rates to simulate economic activity. And all these types of policy interactions will give rise to when bad times come, interest rates tend to be low. So that sounds a little bit like policymakers are engaging a little bit of market timing themselves. Let's talk about another paper of yours where you look at factor timing and time series. Can an investor use factors as part of a market timing approach? Are there

better or worse times for some factors? Or should it just be full factor diversification across the board. That's a paper we just published in the General Portfolio Management not so long ago. Investors should start with a long term strategic combination too. Lots of factors, don't hold just one. If you hold just value, well, I felt it, you felt it over the last couple of quarters, it's being painful. We want lots of factors for diversification, but around that

long term strategic multi factor combination. We might think about tilting, and I like the word tilting rather than the word timing, because sometimes timing has these connotations are really short term global macro that's not what we're about. But around those strategic benchmarks you might tilt, and the paper gives a framework to think about how to do that. So first,

factors become rich or cheap, just like every asset. So wait, so we then within let's say the value factor, which is looking at stocks that might be expensive or cheap, there are times when that factor itself is expensive or chieved. That's correct, So it's a second derivative removed once for um, the underlying cheapness of it's. Now I'm gonna blow your mind because that's truthful. Momentum momentum also helps. The pilsum too has momentum. They are valuam momentum of valid momentum,

in fact, value momentum of each factor. But that's, by the way, that's the most interesting thing I've heard today. I just have to share that with you. Now that that each of these have a derivative that is reflective, it's almost like a mental brought reflexivity um or higher level, meta factor, meta factor. Okay, yeah, but so there are value and momentum effects. Will call that second one relative strength, because we want to measure this trends of these factors

to each other. I know that stocks can be cheaper or more expensive at different times, but I always assumed, Hey, the bottom least expensive let's call a third of stocks, is always going to be cheaper than everything else. I never stopped to think that, sure they're they're relatively inexpensive, but on an absolute basis, cheap stocks can be expensive. That's that meta value is really quite fascinating. How do you incorporate that into what you do? Very that's such

a really deep comment that you've just made. Because value is always cheap, So what do you mean about using value for value? So what we really mean here is if we take the value factor, how cheap is value currently relative to how cheap it's been in the past, its own its own history, right, And then we can also compare how cheap value is to other factors. And if you're a quort, you would call this a time

series and cross sectional score. And that also applies to relative strength or momentum, because momentum, by definition, the momentum factor always has the most momentum. So what you really mean here is what's the current trend of momentum relative to the past trends that momentum has had. And then once the relative strength of my even factor relative to the trends of other factors. Again, it's this time series and cross sectional. So in other words, it's which factor

is doing the best relative to other factors. That's right, And so we actually put all these and one of the you talked about a bit before about the frontiers of factor investing is factor investing is really about taking active insights things like value and momentum, but we can also apply them in other active ways. Factor tilting is one of those ways. So so let's talk about that, because years ago there were a number of models that came out and they didn't do factor tilting. They tried

to do sector tilting. They would rotate within the SMP five, within the different groups that would go from technology to healthcare, um to to finance, and they always sounded great on paper, and then in the real world they didn't do so well. So on a on on this sort of factor tilting model, how can you capture in real time those benefits. Aren't

you always going to be lagging? What do you use as a signal to say, all right, now is the time to over emphasize cap as opposed to quality or is there too much of a lag to capture that? Or do you get enough of the heads up? Hey, here's the direction this is shifting. You can move some of the portfolio quickly enough to take advantage of it. Well, I believe all types of tilting it they're hot and factor tilting. It's hard to but done in a discipline way.

There's a couple of differences to country or sector rotation, so they're nice compliments. So often we like to apply factors within a particular sector or within a particular region, and so that gives room for factor rotation to sit side by side with these others. Second, is that exposure to sectors over the long run. In fact, actually the capa and works fine. There are some academic papers on

that too. If we take a strategic portfolio that bias cheap finds, trends finds, high quality names, right, all those factors those are long term determinants or performance. Whereas static sector exposure, well, actually the market has sectors might as well, do that, but these factors, the strategic tilt gives you an uplift over the long run innovat of itself, and then around that you might incrementally add returns with the

factor rotation. And the third difference I think is that with these factors we can employ them in different ways. So we want to do this transparently. We have this paper, we've introduced some some products. We want to be active with factors. Let's not just use one signal. Let's look at definitely and how cheap something is. We talked about relative strength as well. We'll use the economic regime measures of the opportunity set or dispersion. But we want to

use all of those insights to other m HM. So so let's talk about something UM not market timing, but factor tilts. If I had could have my way, I would at the end of a recession lean as heavily towards growth as I could. Not always easy to do. Everybody is miserable. No one wants to hear you. In March O nine say okay, now is the time to buy the growth stocks UM that have done nothing but get killed for the past two years and towards the end of the cycle, and that assumes you know in

the end of the cycle is in advance. Typically we don't know till after the fact. Gradually move that tilt away from growth towards value, because if your charges, you must be fully invested at all times. On the equity side, the assumption is that in any sort of recession, be it a mild recession or something like oh, eight oh nine or two thousand oh two, you're gonna see growth gets relaxed and value is going to hold up much better. And I can't help but recall hearing this Warren Buffett

guy is washed up. That sort of value crap is never gonna work again. And as people said, that was really when he began another period of huge out performance. So, first, is that something that you can accomplish with tilts? And second, how do you get the timing right at the end of a market crash. It's pretty clear, Um, when you're closer let's let's say, closer to the end than the beginning. Um, So whether it was January O nine or juneo nine,

anywhere in that range, you're you're pretty close. You're you're much closer to the end of that than the beginning. How how does one make that determination that we want to tilt towards growth here and here's how to do it. And then at the other end of the cycle, Hey, we want to tilt more towards value here and here are the signals that send us. How would one do that.

Let's remember first, diversification, diversification, diversification, that's the key, so you have it's really hard too, I think, to to to call anything with precision or make decisions about individual factors or any type of investment. Diversification is that key, and that provides that long term strategic benchmark. But around that, if you have the rest tolerance and the capability and be active with factors, then would like to use information about how cheap a given factor is. We'll see if

the factor is trending up right versus trending down. In fact, value has been trending down over the past couple of of quarters, but value is cheap today. Would also like to see where we are in the economic cycle. The fact that we're in that late stage where we said that value firms tend to underperform. That's not very favorable

to value. We also look at dispersion. Dispersion for value, it's okay, but it doesn't scream like it's a it's a big I. We use all of those together and then we'll have an aggregate view on these different factors. Quite quite interesting. There were a few other questions I want to get to before we get to our standard um question. We we mentioned value stocks underperforming. I saw something recently that said they've underperformed for thirty five years?

Is that remote? Well, that seems wrong, doesn't it? Even? In fact, if I'll performed in the last ten years, but they've been difficult periods under the past past decade, growth is outperformed in the past. I had actually values done quite well. Value since oh not? But value, yes, value over the past uh two years has suffered. Okay, that's interesting though. I I have looked at value as let me rephrase that. I've looked at growth as doing

exceedingly well since the end of the financial crisis. Think about Amazon at dollars and Apple at twelve dollars or whatever the prices were, and they've all exploded, and I guess they're categorized as growth. Although with those prices you can really call those value stacks. You know, that's a great a great point. That comes one of the topics that I wrote about recently in my blog Andrew's Angle,

and it's growth. That's not the opposite of value, all right, And we kind of used the word well, it's certainly value for cheap. We've used the word growth to denote expensive. But actually there's two other connotations of growth which are quite distinct from the opposite of value. I mean, the first one is that a lot of growth managers will search for trends, and you'd actually like to a trend to be sustainable, and that's an aspect of momentum investing,

and that's rewarded over the long run. Another aspect of growth is something that you alluded to, is like, what's the quality actually behind that? And indeed, if you look at many growth funds, certainly they will load many of them on momentum and quality factors. Growth itself is not the opposite of value. But I think you don't want to buy expensive. If a stock does tend to be

more expensive, that is not value. It might be justifiable because it might have aspects of quality or momentum in there. So when you are defining something as a growth stock or a value stock, you know my frame of references. There's the SMP five growth group and the SMP five hundred value group, and never the twins shall meet. But I suspect you might take issue with some of the stocks they call growth in something, and I think it's

a little bit more nuanced. I would call the first generation exactly just splitting the thing into two, and today we would think a little bit harder, and many stocks will have aspects of multiple factors within that same stock. So let's talk a little bit about back testing. We're really gonna go deep into the weeds here. Um. It seems that a lot of back tests show these great returns for different combinations of factors, and then implementing them

in the real world becomes challenging. You mentioned the problems with organizations and getting everybody pulling in the same direction. Um, But there have been instances of small um hedge funds quantitative hedge funds that try to implement these and momentum is a perfect example. Momentum has some real application in real portfolios, but it seems the back tests are always

much better than the actual implementation. What is it about momentum and some of these other factors that makes it so challenging to capture what theory says in practice, momentum has pretty high turnover, So a momentum funds run at turnover above significantly about Because of that, transaction costs are crucial.

So you see some research in the literature that says, actually, we can't really do momentum and practice, and some others that will say, well, if you're very good at transaction costs optimization and you have access to transaction cost minimization in your execution, then momentum will be a favorable and profitable factor. So it's really key that you have to really look at the details once you implement a factor. The devil is always in the details. Let's let's let's

look at another one. Theoretically, high beta stocks should do really well, but your research in as implemented in black Rock has found low volatility stocks have done well. Why is it that the high beta stocks aren't capturing those gains once you have a portfolio implement implementation, it's the

low vall stocks that seem to be doing better. Yeah, and this is a paper that I wrote in the two thousands, and this paper, I'm lucky and very fortunate, has played a really important role in building out the minimum volatility and factor industry more broadly, and you've hit on the key note here that in theory we should have higher risk stocks should have higher returns, but actually we found the opposite. And in the paper my co authors and I said, the higher risk stocks have quote

abysmally low returns unquote abysmally low. And if we rank stocks based on risk, and we did this by volatility idios and critic and total volaty of the paper, subsequent papers did this by beta or downside risk measures. The general pattern is that stocks have the same expected return and then as the volatility increases, there's a very steep drop off in returns for the very high risk stocks.

And that's actually this low volatility effect. If you construct a portfolio of minimum volatility, and you can do that by holding low data stocks or stocks with low idiosyncratic risk, or both, you form a portfolio of low volatility that gives you the same return over the long run as the market, but it does so with reduced risk. The shop ratio is high not because of the numerator of the higher expected return, but it's because of the decrease

in the denominator the reduced risk. So if someone were to come to me and say, listen, I could give you market returns, but much lower draw downs, much lower volatility. Of course I want to say, I want some of that. If you're not going to get out performance for the same um volatility, well the same performance for less volatility. That seems like it's much more livable for the average investor.

And I think that's one of the great benefits for minimum volatility strategies is it just helps an investor stay the course. So you're an subject to those tremendous swings, particularly on the downside, and we can mitigate some of that downside risk with these minimum volatility strategies. Upside downside capture ratios for minimum volatility alright, you well, it's all about trying to uh participate in as few as possible of these drawdowns. It's around fifty downside and upside for

these downside upside risk capture issues. That that's really quite interesting. Um So one of the questions I mentioned to somebody I was speaking to you, and they asked a really interesting question. Do you consider factor indexes to be closer to the active spectrum or closer to the passive end of the spectrum. Where where do you put factor investing on that continuum from active to passive? Oh, this is another one of these uh yes questions. That's right. You

know that this is a bugbear of mine. I have to say barriers that everything is active and it's just a question of greater or lescent degree. I totally agree. I I've written and discussed that even the basic SMP five hundreds somebody made. That's right. That's a bunch of active decisions about one market cap rated and where do you draw the what's the free float and what gets in there? Right? And then while do you use the

SMP five founderversus some other index? Right? And then you know when we go to other asset classes, you know it's almost all active implementation. Right. So I think I would like to rephrase that question, if I may, on the difference between index or average and then taking um deviations from there. And in this context, factors are absolutely active. We're tilting towards broad and persistent sources of returns. We

don't want to hold a market cup. Folil would favor overweighting stocks that have low prices relative to intrinsic value. Those stocks that are trending up right, those stocks of high quality earnings, and those are active decisions. What we're doing it in a transparent way. It's low cost, we can put it into an easy to access fund, right, and we can put these insights into multiple asset classes too. So you keep referencing this is being done in a

transparent way. Why is that important? Because I look at places like the Shore or renaissance technologies that have generated out performance for decades, they're not transparent. Those are their secret sauce that goes into their alpha generation. Why does black Rock feel we're creating something and we want to be completely transparent in this product. I believe in active, I believe in alpha, and I define these factors as broad you see them in many places and persistently rewarded.

We've got decades of academic research, so is this a peer reviewed approach to invest in now? Alpha is actually not broad and persistent, right requires specialized skills like the firms that you've talked about. Alpham two will use sophisticated techniques with big data and machine learning. You could have a fundamental approach that news a lot about just a few stocks. The complete opposite of broad and those when

you find those skills, you should reward them. Sometimes you might be able to generate alpha insights by taking advantage of very short term high frequency market dislocations. When we find that school, we should pay up for it. But those things that have been in the literature for decades, that have been well studied, that the game is all about implementation and efficiency, well, I don't think we should be paying very expensive fees for that. We should be

giving control to the client. We should be paying less and getting more. And that's where factors come in. So so where does the transparency on some of these new models come in? Why share your findings as opposed to keeping it secret. We believe in sharing, and we know that these factors are going to endure because of that economic rationale. Right, there's always going to be the reward for bearing risk. Unless these structural impediments get removed, they're

going to be there. And investors, well, they're going to be investors. There's going to be these behavioral biases as long as these economic rationales endure, these factors are going to be with us. They're going to be cyclical. Absolutely, so sometimes there might be room for a factor tilting. But these factors are going to be with us for decades to come, and let's share this and democratize access

to all of this. That's our purpose, and we can do that so that you understand what's inside, how we exactly buy cheap and we want to make sure that you see it. So sometimes you might want to have position level information available. It helps you fit that with the rest of your portfolio, or integrate it with data and technology, and you might have better risk management. I think that approach is unusual. Not a lot of firms the size of black Rock are comfortable sharing their research.

Although I get us. Black Rock could say, hey, we're so big, we're so efficient. Here here's the secret source. You can never do this as cheaply as we could. Anyway, I'm that's my words. I'm not under means, but word. We always put the client first. So but you got I mean, not to the clients, to competitors, to other people who might say, oh, here's a new paper from black Rock, let's see if we can find something to

implement from this. I find it to be a typical, although I guess that's not Lots of firms published white papers lots of firms do that, so maybe I'm over emphasizing the transparency aspect of it. I just find that intriguing that the secret source from a particular group of funds. You guys are that open with and I guess I think, I think maybe you would agree with my wife once you called me a hypocrite because I'm I'm the ultimate true believer. There you go. So so that makes a

lot of sense to me. So let me jump to my favorite questions. This is our speed round, and we asked this of all our guests. UM, let's start with a simple question. What was the first car you've ever owned? Year making model Toyota Corolla three one point six Leader, kind of maroon color, which was really fortunate because the amount of rust and there you kind of you couldn't see. They always made good cars, but in the early days, that was a very thin metal and it was a rustbucket.

It happens a lot. I remember that drove that car across Australia. Really, Um, where you originally from? I was born in Malaysia, and uh during the late nineteen sixties and early nineteen seventies, Malaysia went through a series of race rights and my parents wanted somewhere safe to raise their family. And then White Australia Policy ended and that was actually the official name of the policy Australia was ended by Gulf Whitlam Australian Prime Minister in nineteen seventy three.

And we were one of the first Asian families after the wide Australian policy to move to Perth. And I remember growing up, I was the only non white kid in class and I was really different, kind of marked my whole worldview. UM factors really are all about walking through and being different too. I did well in school, was so thankful for UM, for the opportunities that were given to me. And and then you know, I ended up in the US for for graduate school. I got

to work on it Scotinamian who was a professor. And you know, now I'm I'm like every other person who lives in New York City. That's so, that's so interesting. So I was going to ask you a question, what's the most important thing we don't know about you? But I suspect you maybe I don't know. I'm I'm a musician. Oh really, so with the piano, I am a classical pianist. I used to play the violin, but I've always loved

the piano more. I've played in a few black rock corporate bands, so I'm trying to expand my musical genres away from thelassical towards So have you ever done like full classical m I've concertos. Have you played for audiences? How far did your music career take? Yes, I can play those. Really, that doesn't mean I'm very good at it, but I love I love playing. So so tell us about some of your mentors who helped develop the way you think about markets. I would like to answer that

in two ways. So the first one is like, who do I model myself on in black rock running a business and trying to change the world with factors? And that person is Walt Disney. Really it's not an investor. But if we look at Walt Disney, he didn't invent animated films. He didn't invent amusement parks right, or people dressed up in uh in different characters. But what he did he brought all of those together and he just by integrating all that created something new. And that's actually

what factors are doing too. We didn't invent buying cheap right. We didn't invent momentum, but bring of those together with darn too technology, Yes, we can remake the world and give people a better experience. Interesting. Just a footnote, I was at Disneyland two weeks ago. Is the first time I've ever gone to any Disney property, and it's quite

the experience too. In your fifties experience a Disney park for for the first time all ages, it is the happiest and I basically any ride, I don't care, fast, upside down, doesn't matter. I'm I'm right there, and we had a blast. It was absolutely you could see why. Oh no, I kind of get Disney. This makes a lot of sense. But but the other mentors, Yeah, you

know I I was pretty nerdy, as you can tell. Uh. And one of the weight nerdy I have not noticed in this book on quantitative factor investing, I did not notice anything at all. Uh. And when I was in school high school, I got to go to National Mathematics summer school and that was just an eye open up for that. There were people kind of like me that liked math and it really changed my life. So let's talk a little bit about investors who influenced your approach

to investing. Who were the folks that really shaped your investing worldview? If any reader or listener out there hasn't read Graham and Odd security analysis, but those were two professors that the institution I taught up for many years Columbia University. You've got to read that book. It's the basis for value. Quality is in there because they teach us that in order to estimate intrinsic value, you got to use the more permanent components of anage, things that

we use in quality today. I have to mention Bogel. When I met him for the first time, he he actually was citing some things out of my book, particularly that chapter on governance or agency theory. And one other person is Joe Grin, but just to look at look at us thematic approach to out to some capital. Yeah, he's a very interesting guy. So let's talk about books. What are some of your favorite books, be they market related, not fiction, nonfiction. What have you enjoyed reading. I like

reading popular science books. My most recent one is by Simontgomery and called The Soul of an Octopus. That amazing creatures, right, and they just look so alien, but their emotional vally in Teargent like them all like Custin we think. I'm gonna tell you something. I read that book and I stopped eating octopus afterwards. It basically and I eat pretty much everything except cauliflower and brussels sprouts. That book is the first thing I've ever read trying not to eat

brussel sprouts. I can't. I can't eat octopus anymore. They They're just too intelligent and too soulful. One of the things about popular science books that I like is even for the areas that I'm familiar with and in some cases you would say beat in the weeds with in the research, you always learned something from them, because the best ones just present information in a new way, or they just open up your frontier, like like the Simon

Comery book. Give us another I think, UM like some popular books on number theory and just physics and sciences in general. Le let's hear some titles. Well. One of them is Moonshot. It's about the American um policy. Yeah, it's amazing book as well, moon Shot. That's um who wrote that. I can't remember the full title right now. Let's let's have Google rescue us while and then you can mention it shot and we'll edit this out, uh, and I have to. It's a pretty long title. In fact,

that Soul of an Octopus is a pretty long title too. So, by the way, while I'm while I'm looking for this, I recommended that book to my friends David Nodded, who send set me that book and said thanks for the recommendation. That book made me cry. There's another one by what a Landing on the Moon Teaches? That's why I don't Richard Wiseman. There's another one very very similar to Symontgomery's book called by france To Rudin called uh, I Think

Mama's Hug, Mama's Last Hug. It's about Mama's last It's about the great apes and their their intelligence in the capacity. I'd enjoyed that one too. If if you I'm gonna put that one, I put all these on my list. But if if you like that, have you ever read Last Ape Standing? So it's basically about the thirty or

so proto human species that had come out. You know, you know chro Magnum, you know Neanderthal, but you don't know there's thirty others and how close they all came to being wiped out in the ice age, and how this particular last ape standing UM, the Homo sapiens ended up being the ones who who survived and eventually took over. But if you're at all interested in nonfiction, I always recommend that book. I've found that delightful. All right, so

we have three books. Let's jump to UM failure. Tell us about a time you failed and what you learned from the experience. I turn up at grad school, went to Stanford, and I did pretty well. My undergrad one a university medal, rote a dissertation, you know, Dunning Kruger kind of effect, and you get to grad school n Kruger, such a humbling experience. I did so badly. I thought about withdrawing. I had to take all these classes in

the statistics department. That's actually why I have this Masters of Science and Statistics was just because I was in UM the remedial program. To take all these extra things that I should have known before I entered my degree. That was a really humbling experience. So that's very high level Dunning Krueger meta cognition. I experienced that in college. It's like high school was easy. You get to college and suddenly it's like, Oh, these people are really smart

and they work really hard. I can't just you know, phone it in. I don't know what your experience was like in grad school, but it was in hindsight, pure Dunning Krueger. What did I learn is, um, you can't do it on your own. So I think everyone off my class, June and June, Mark, Maria, Eric. Without you, I could not have got through my homeworks and got that gotten through. Wow, that's that's quite interesting. So what do you do for fun? What do you do when

you're not crunching numbers? That's that's your that's your UM, that's your stress release. That's my stress relase. Sitting at a keyboard and just working your way through a Grand Masters composition. Well, right now I'm also trying to do pilates. I'm very very stiff. So my goal is to try to touch my Okay, uh, tell us what your most optimistic and pessimistic about today. It could be markets, investing, economy. What what do you most optimistic and most pessimistic about? Oh?

I love all of the opportunities that are here today, particularly for the fact is what we've been talking talking about and the great advances that we will make to put all those benefits in the hands of consumers and clients. One of my pessimistic about well, my parents were migrants.

Really glad my parents migrated and gave me opportunities in Australian then you know, living here in the US, and there's this expression I got a fairgo and people a fair go, And I'm a little pessimistic that there's increasing inequality, lack of mobility, and bottom line is we should be trying to give as many people a fair go, very very reasonable. Let's uh, let me get to my two favorite questions. Um, a millennial or someone just beginning their career in finance comes up to you and ask for

some advice. What sort of advice would you give them. It's actually advice I give myself. It was given to me by Bob Hodrick, a colleague and co author and friend, and he said, it's not your life. Don't presume to to suggest that it's it's your life either, but explain, give me, give me a little more. Do you make your choices. My preferences aren't yours, And you go and do what you think is best, and I'll go and support you the best that you can the best I can.

That's quite intriguing. Um tell us for our final question, what do you know about the world of investing today? You wish you knew thirty years ago when you were first getting started. I think very often the most important problems in investments are actually not about investing really. For institutions,

they're about management, structure, governance and incentives. And for individuals, well, you've had many guests on your show to all about tackling investors behavioral bodies, all right, and those sometimes are even more important than the actual investment problems. Sometimes the investment problem is the easy pot, all right, and then sitting the context of the investment problem in the wider portfolio or the wider structure in someone's family or an institution,

that's actually the harder problem. Quite fascinating. We have been speaking with Andrew Ang. He is the head of factor investing at black Rock and the author of Asset Management, A Systematic Approach to Factor Investing. If you enjoy this conversation, well, look up an Inch or down an Inch on Apple iTunes and you could see any of the other two hundred and fifties such conversations we've had over the past

five years and check that out. We love your comments, feedback and suggestions right to us at m IB podcast at Bloomberg dot net. I would be remiss if I did not thank the crack staff that helps put these conversations together. Attikavl Bron is our project manager. Michael Boyle is our head of booking slash producing. Michael Batnick is my head of research. I'm Barry Results. You've been listening to Master's Business on Bloomberg Radio