WEBVTT - A Quant’s Take on Meme Stocks 0:00:13.160 --> 0:00:16.680 Hello, and welcome to What Goes Up, a weekly markets podcast. 0:00:16.880 --> 0:00:19.160 My name is Mike Reagan and I'm a senior editor 0:00:19.280 --> 0:00:22.480 at Bloomberg. This week on the show, has all this 0:00:22.640 --> 0:00:25.759 rotation made you see sick? Yet? Earlier this year was 0:00:25.800 --> 0:00:28.680 the massive rotation out of big tech and other growth 0:00:28.720 --> 0:00:32.960 stocks and into more cyclical and value oriented stocks. But 0:00:33.159 --> 0:00:36.120 a whip of hawkishness from the Federal Reserve has caused 0:00:36.120 --> 0:00:38.200 everyone to sort of jumped back to the other side 0:00:38.200 --> 0:00:41.160 of the boat again and growth is outperforming once again, 0:00:41.200 --> 0:00:43.479 at least for now. Now some people are saying the 0:00:43.479 --> 0:00:45.560 market is falling for a head fake from the Fed. 0:00:45.640 --> 0:00:47.880 But we want to get into it with the head 0:00:48.080 --> 0:00:53.040 strategist at a major pioneering quantitative fund manager. But first 0:00:53.200 --> 0:00:55.400 I want to bring in our co host. And sorry 0:00:55.440 --> 0:00:57.600 to all the Charlie Pellet fans out there, but no 0:00:57.760 --> 0:01:00.160 Charlie Pellet intro this this week. And that's because as 0:01:00.200 --> 0:01:02.520 this co host is, there's no mystery about her. She's 0:01:02.560 --> 0:01:05.640 been on the show before and gotten to Charlie Pellet treatment. 0:01:05.640 --> 0:01:07.959 Her name is vill Donna hi Rich. She is a 0:01:08.000 --> 0:01:11.600 cross asset reporter at Bloomberg. Vill Donna, what do you 0:01:11.600 --> 0:01:14.600 have to say for yourself, well, I wouldn't be opposed 0:01:14.600 --> 0:01:17.600 if we had another Charlie Pellet treatment. Here you are. 0:01:17.640 --> 0:01:21.400 You're disappointed, aren't you? Everyone loves the Charlie Charlie. All right, 0:01:21.600 --> 0:01:24.440 I'm sorry. I apologize next time, but I will put 0:01:24.440 --> 0:01:27.000 out Vill Donna, as many of you know, is what 0:01:27.040 --> 0:01:30.959 I consider the chief crazy things correspondent for what goes up. 0:01:31.240 --> 0:01:33.640 Many of the crazy things I've brought to the show 0:01:33.680 --> 0:01:36.360 have been courtesy of Bill Donna. You're actually very sane 0:01:36.400 --> 0:01:39.120 and level headed for someone who is such an expert 0:01:39.160 --> 0:01:42.119 in crazy things. Though, I gotta say they're just really 0:01:42.120 --> 0:01:44.600 interesting to read. And I have what I think is 0:01:44.640 --> 0:01:47.080 a pretty good one you know today. Okay, good, I 0:01:47.120 --> 0:01:48.680 got a good one. So hopefully we don't have the 0:01:48.720 --> 0:01:50.960 same one that that would be awkward, and by all means, 0:01:50.960 --> 0:01:53.200 if you see something crazy, a reminder that we have 0:01:53.280 --> 0:01:56.000 a podcast hotline that's just sitting here waiting for you 0:01:56.040 --> 0:01:58.200 to leave us a voicemail. Vil Donna, our our old 0:01:58.200 --> 0:02:01.320 friends Sarah promised she would call the hotline and leave 0:02:01.400 --> 0:02:05.080 us some crazy things. But um alas so far, I'm 0:02:05.080 --> 0:02:08.080 like a kid on Christmas checking the voicemail and I'm 0:02:08.120 --> 0:02:11.000 nothing in my stocking. But I'm thinking maybe she's just 0:02:11.120 --> 0:02:13.919 forgotten the numbers, so I'll give the number. It's uh 0:02:14.040 --> 0:02:17.280 six four or six three two four three four nine. 0:02:17.320 --> 0:02:19.280 Oh so, please don't give us a call, leave us 0:02:19.280 --> 0:02:21.160 a voicemail and maybe we'll play it on the show. 0:02:21.560 --> 0:02:23.560 But let's get to that. Guest, as I said, he 0:02:23.680 --> 0:02:28.200 is the head of investment strategists at a big fund manager, 0:02:28.840 --> 0:02:31.560 uh that manages about six d and thirty seven billion 0:02:31.560 --> 0:02:36.200 dollars in assets. His name is West Krill, head strategist 0:02:36.360 --> 0:02:40.920 at Dimensional Fund Advisors. West, Welcome to the show, excited 0:02:40.960 --> 0:02:44.680 to be here, Thanks for having me today. Absolutely absolutely, West, 0:02:44.760 --> 0:02:46.880 I've got good news. I'm gonna start off with what 0:02:46.919 --> 0:02:49.520 we call in the industry, a softball question for you, 0:02:49.800 --> 0:02:52.440 uh so, so that's my gift to you today. But 0:02:52.440 --> 0:02:55.160 I'm just want to talk a little bit from your 0:02:55.200 --> 0:02:59.600 perspective about the approach Dimensional takes to investing. Now. Obviously, 0:02:59.639 --> 0:03:02.239 Dement sal as I said in the intro, considered a 0:03:02.360 --> 0:03:05.600 very pioneering firm that was sort of one of the 0:03:05.600 --> 0:03:08.120 first to be at the intersection of kind of the 0:03:08.160 --> 0:03:13.760 academic thinking about markets and actually managing money using those 0:03:13.840 --> 0:03:16.720 types of approaches. In the real world. For example, the 0:03:16.760 --> 0:03:21.000 founders studied under Eugene Fama and Kenneth's French Um. But 0:03:21.040 --> 0:03:23.520 I'm curious just for you to explain to us what 0:03:23.680 --> 0:03:27.639 is dimensionals approach to investing. Yeah, of course, So you know, 0:03:27.680 --> 0:03:30.680 we're founded in nineteen eighty one and we've always been 0:03:30.720 --> 0:03:34.400 built on implementing the great ideas in finance, and to 0:03:34.480 --> 0:03:36.400 your point, you know, a lot of that is cultivating 0:03:36.720 --> 0:03:39.280 these deep connections with some of the luminaries in the 0:03:39.320 --> 0:03:43.280 academic world Fama and French, like you mentioned, Robert Merton, 0:03:43.440 --> 0:03:46.960 Robert Novi, Mars. So that's been really instrumental in the 0:03:47.000 --> 0:03:49.480 way that we've built our firm. And then a central 0:03:49.520 --> 0:03:52.600 tenant to our investment philosophy is our deep seated belief 0:03:52.960 --> 0:03:55.280 in markets. So what that means is when we go 0:03:55.400 --> 0:03:59.560 to UH seek to outperform markets, we do so not 0:03:59.680 --> 0:04:02.280 by trying to outguess market prices and figure out where 0:04:02.320 --> 0:04:06.279 they've gone wrong, but by emphasizing certain groups of securities 0:04:06.480 --> 0:04:10.520 with higher expected returns based on research, very rigorous research 0:04:10.720 --> 0:04:13.600 from the academic community. And of course you know, we 0:04:13.640 --> 0:04:16.320 have a fanatical emphasis on the role of implementation. We 0:04:16.360 --> 0:04:19.680 feel that's a really critical level of expertise to have 0:04:19.800 --> 0:04:22.440 when you're trying to translate these ideas from the academic 0:04:22.480 --> 0:04:26.960 world into real world value add investments for our clients. 0:04:28.440 --> 0:04:30.520 I know you guys recently converted a bunch of your 0:04:30.720 --> 0:04:33.039 mutual funds into e t s and it was a 0:04:33.120 --> 0:04:35.599 really big deal in the world of ets, and I'd 0:04:35.640 --> 0:04:38.200 love to chat about that in a second, but maybe 0:04:38.200 --> 0:04:40.279 you can tell us a little bit about what types 0:04:40.279 --> 0:04:44.880 of things your clients and people who've been having conversations 0:04:44.920 --> 0:04:47.520 with recently have been asking you about them what's been 0:04:47.839 --> 0:04:51.520 on their minds? And I asked, because I'm thinking of 0:04:51.560 --> 0:04:54.760 all of the fund manager surveys and all these different 0:04:54.800 --> 0:04:57.400 surveys that we tend to see from from week to week, 0:04:57.880 --> 0:05:00.839 where some of the topics recently, I feel like have 0:05:01.080 --> 0:05:04.400 been changing. Where the virus used to be at the 0:05:04.440 --> 0:05:07.240 top of of mind for a lot of people and 0:05:07.480 --> 0:05:09.919 it's sort of fallen off and now it's more fed 0:05:10.000 --> 0:05:13.760 and questions around inflation, yes, certainly, I mean those come 0:05:13.839 --> 0:05:17.880 up in conversations. I would say the foremost conversation topic 0:05:17.960 --> 0:05:19.960 for us, and this has been the case really for years, 0:05:20.240 --> 0:05:24.040 is the performance of small cat value versus large cap growth, 0:05:24.080 --> 0:05:26.080 And you know, it's been interesting as you've sort of 0:05:26.080 --> 0:05:28.679 seen a cee saw in terms of the sentiment behind 0:05:28.680 --> 0:05:30.880 those questions. For a while, it was, you know, small 0:05:30.920 --> 0:05:33.760 cap value underperforming large growth concerns around that, and then 0:05:34.000 --> 0:05:36.000 when you had small cat value coming roaring back and 0:05:36.000 --> 0:05:38.080 people would start to ask how much longer can this last? 0:05:38.120 --> 0:05:40.160 And then you know, now you see that at least 0:05:40.160 --> 0:05:43.280 in this past quarter as small value has been underperforming 0:05:43.360 --> 0:05:46.799 large growth again. So you know, I think it reinforces 0:05:47.240 --> 0:05:49.920 a couple of different billion points for investors investors to 0:05:50.000 --> 0:05:53.200 keep in mind. The first is just the uncertainty around 0:05:53.200 --> 0:05:56.640 these premiums. So you know, the premise behind the small 0:05:56.680 --> 0:05:59.159 cat value stocks having higher expectory turns in the market 0:05:59.240 --> 0:06:01.800 is a very simple one. It's the idea that you're 0:06:01.839 --> 0:06:04.480 paying less for a stream of future cash flows, and 0:06:04.520 --> 0:06:07.640 that's a very evergreen concept. But we also know that 0:06:07.640 --> 0:06:11.520 stock returns are volatile, and these premiums can be negative 0:06:11.800 --> 0:06:14.359 for sustained periods of time, but they can also show 0:06:14.440 --> 0:06:18.080 up in really large magnitudes really quickly. The return difference 0:06:18.120 --> 0:06:20.480 between small value and large growth in the US as 0:06:20.520 --> 0:06:23.680 of March thirty one over the trailing six month period 0:06:24.279 --> 0:06:26.960 was sixty two percentage points. That's one of the largest 0:06:27.000 --> 0:06:29.320 return deltas over such a short period of time ever. 0:06:29.760 --> 0:06:32.240 But it's not uncommon for these premiums to show up 0:06:32.240 --> 0:06:35.920 in a hurry, and this has obvious implications for investors. 0:06:35.960 --> 0:06:38.159 It means that you need to be disciplined in terms 0:06:38.200 --> 0:06:40.720 of your approach to capturing these and it also means 0:06:40.760 --> 0:06:44.480 from an investment management standpoint, we need to be continuously 0:06:44.600 --> 0:06:47.919 pursuing these groups of stocks and a very accurate way, 0:06:48.160 --> 0:06:50.480 so that our investors know what they can expect from 0:06:50.520 --> 0:06:53.599 our investment approach, you know. So I want to talk 0:06:53.720 --> 0:06:57.400 about that what Vildana mentioned, the conversion of of some 0:06:57.440 --> 0:06:59.640 of your funds into et apps. I mean, you're still 0:07:00.000 --> 0:07:03.280 cominently a mutual fund manager, but you've you know, began 0:07:03.400 --> 0:07:06.240 the process of converting some into e t f s, 0:07:06.720 --> 0:07:09.000 And to me, I wonder, you know, in the bigger 0:07:09.000 --> 0:07:12.960 scheme of things, that seems to me like perhaps part 0:07:12.960 --> 0:07:15.840 of the natural evolution of quant investing. You know, I 0:07:15.880 --> 0:07:18.840 think back to one when you were founded, but I 0:07:18.840 --> 0:07:22.200 can't imagine the man hours and the labor required to 0:07:22.240 --> 0:07:25.400 do just a simple regression study. Say, going back you know, 0:07:25.440 --> 0:07:27.960 a few decades. It must have been, you know, and 0:07:28.200 --> 0:07:32.640 an army of of people with visors and calculators. There's 0:07:32.680 --> 0:07:36.160 all Texas instrument calculators. However, it was done. But is 0:07:36.200 --> 0:07:38.960 that part of it? Just that you know, uh, the 0:07:39.120 --> 0:07:43.320 computing power and the brain power on Wall Street is 0:07:43.400 --> 0:07:47.960 kind of caught up with the quant uh sort of strategies, 0:07:48.040 --> 0:07:50.640 and you know, it's now a lot you're able to 0:07:50.640 --> 0:07:52.320 do it a lot cheaper, able to put it in 0:07:52.320 --> 0:07:55.520 an ETF rapper, and and do it at a much 0:07:55.640 --> 0:07:59.160 less cost basis than than you would say, years ago 0:07:59.640 --> 0:08:02.000 in the equal fund space. Is does that sound right? 0:08:02.080 --> 0:08:05.480 Is it? Is it kind of part of that evolution? Well, 0:08:05.520 --> 0:08:07.000 I think that, you know, the E t F conversion 0:08:07.080 --> 0:08:10.320 was was a very exciting thing for us because that conversion, 0:08:10.360 --> 0:08:13.120 that type of event had not happened at that scale before. 0:08:13.640 --> 0:08:16.960 And those particular strategies that were converted are managed with 0:08:17.000 --> 0:08:20.400 an eye towards minimizing the tax impact for investors, and 0:08:20.440 --> 0:08:22.880 the et F rapper gives you another tool in the toolkit, 0:08:23.400 --> 0:08:26.440 uh to mitigate or to increase the tax efficiency of 0:08:26.480 --> 0:08:29.040 those strategies. And so that was a very important thing 0:08:29.080 --> 0:08:31.200 for us. But we like to say we're wrapper agnostic. 0:08:31.240 --> 0:08:33.040 You know, we believe both the mutual fund and et 0:08:33.160 --> 0:08:35.560 f rappers those type of vehicles do have a place 0:08:36.000 --> 0:08:39.080 depending on an investor's objectives. But I think one of 0:08:39.080 --> 0:08:41.240 the things you're kind of hinting at with this what 0:08:41.360 --> 0:08:43.920 i'll call the rise and systematic investing. You know, that's 0:08:43.960 --> 0:08:47.520 something that we have noticed, even going back further again 0:08:47.559 --> 0:08:49.960 to your point. You know, you mentioned how the ability 0:08:50.040 --> 0:08:55.199 to identify factors within the investment data, uh is a 0:08:55.240 --> 0:08:56.520 lot easier now that it used to be. You know, 0:08:56.520 --> 0:08:59.600 We're used to have computers the size of entire rooms 0:08:59.640 --> 0:09:02.000 like the and I'm sitting in that you needed to 0:09:02.040 --> 0:09:04.959 run regressions to identify these kind of parameters. Uh. Yeah, 0:09:05.000 --> 0:09:06.400 Now it's much timplt. You could probably do it on 0:09:06.400 --> 0:09:09.400 a smartphone. At this point. There is actually an academic 0:09:09.440 --> 0:09:11.720 by the name of Campbell Harvey who keeps track of 0:09:11.760 --> 0:09:13.720 all of the factors that have been identified in the 0:09:13.720 --> 0:09:16.760 academic literature, and last time I checked, it was up 0:09:16.760 --> 0:09:20.200 over five hundred. Uh And in fact, another academic named 0:09:20.240 --> 0:09:24.400 John Cochrane refers to this as the factors zoo Um. Now, 0:09:25.160 --> 0:09:27.240 this is not to say that there's that many, maybe 0:09:27.320 --> 0:09:30.920 hundreds of different distinct sources of expected returns. A lot 0:09:30.960 --> 0:09:33.480 of these are probably variations of the same economic concept 0:09:34.160 --> 0:09:36.880 that are repackaged, but I think it does bring the 0:09:36.920 --> 0:09:40.600 conversation back to the importance of implementation. It's one thing 0:09:40.679 --> 0:09:43.840 to identify a group of securities that, based on historical 0:09:43.920 --> 0:09:47.040 data while outperform in a simulation. Bringing that to a 0:09:47.120 --> 0:09:51.000 real world investment solution where you deliver the outperformance net 0:09:51.040 --> 0:09:54.080 of implementation costs is a different story altogether. And I'll 0:09:54.080 --> 0:09:56.520 give you one really simple example. The Russell two thousand, 0:09:56.600 --> 0:09:59.200 a small cap index we know from the research as 0:09:59.200 --> 0:10:03.319 small cap secure. These have higher expected returns than large caps. Well, 0:10:03.360 --> 0:10:06.599 the small cap Russell two thousand index has historically underperformed 0:10:06.640 --> 0:10:09.640 the Russell one thousand index going back to seventy nine. 0:10:10.040 --> 0:10:12.960 So that's one example. We're just identifying a group of 0:10:13.000 --> 0:10:16.240 stocks you expect to have higher returns. Doesn't always pan 0:10:16.280 --> 0:10:19.160 out an investment vehicle. You really need this level of 0:10:19.200 --> 0:10:23.480 expertise and the research, design, management, and last but not least, 0:10:23.520 --> 0:10:26.440 trading of a strategy to capture these sources of higher 0:10:26.480 --> 0:10:38.280 expector returns for investors. I want to ask you and 0:10:38.800 --> 0:10:42.080 Mike and I were chatting about this right before our conversation. 0:10:42.160 --> 0:10:44.560 But when it comes to some of those factors, does 0:10:44.600 --> 0:10:47.439 it feel like all of the good ones have already 0:10:47.440 --> 0:10:50.920 been sort of discovered and exploited and repackages, you say, 0:10:51.080 --> 0:10:54.640 or is there something else out there that you you're 0:10:54.679 --> 0:10:58.080 finding really exciting? I think that's certainly a challenge, you know, 0:10:58.160 --> 0:11:00.679 especially let's say you're a finance student these days compared 0:11:00.720 --> 0:11:02.800 to one thirty years ago, to find something that hasn't 0:11:02.800 --> 0:11:07.320 already been discovered. There's certainly the incentive to try and 0:11:07.360 --> 0:11:10.520 look for something that's new. Um, But I think that, 0:11:10.640 --> 0:11:12.840 you know, just because some of these core kind of 0:11:12.880 --> 0:11:16.760 acid allocation determining building blocks like size, value or profitability, 0:11:17.280 --> 0:11:20.160 you know, even if you can't add on to those necessarily, 0:11:20.280 --> 0:11:22.120 there's a lot of other inputs into a strategy that 0:11:22.160 --> 0:11:23.880 need to be taken into account. And that's where you know, 0:11:23.920 --> 0:11:26.400 some of the really exciting research has been done, uh, 0:11:26.440 --> 0:11:28.360 you know, internally with our research team, where we look 0:11:28.400 --> 0:11:31.080 at things like this, where you find shorter term drivers 0:11:31.080 --> 0:11:33.640 of expected returns that are really tradeoffs that you have 0:11:33.760 --> 0:11:37.439 to balance against things like size, value or profitability. You know, 0:11:37.520 --> 0:11:40.760 if you think about a value strategy, how to stocks 0:11:40.880 --> 0:11:43.840 often become value stocks while it's following a period of 0:11:43.880 --> 0:11:47.040 relative underperformance versus their peers. What do we know from 0:11:47.040 --> 0:11:50.280 the phenomenon of momentum within the cross section of stocks. Well, 0:11:50.280 --> 0:11:54.040 stocks that have had relatively poor returns uh in previous 0:11:54.080 --> 0:11:57.800 periods tend to continue to have relatively poor returns in 0:11:57.840 --> 0:12:01.199 the short run. And so addition, all sources of information 0:12:01.240 --> 0:12:04.000 about expector returns like that are really crucial to Again, 0:12:04.080 --> 0:12:07.479 even for these well established factors like size, value, and profitability, 0:12:07.840 --> 0:12:10.080 making sure that we capture our fair share of those 0:12:10.440 --> 0:12:14.319 still a very important part of implementation. Uh, what's I'm 0:12:14.320 --> 0:12:16.440 great glad you brought up Cam Harvey. We've had him 0:12:16.480 --> 0:12:19.280 on the show a few times. Not in a while, though, 0:12:19.280 --> 0:12:21.920 But listeners, if you wanna hear more of the thoughts 0:12:21.920 --> 0:12:23.920 of Camp, scroll back on the on the phone a 0:12:23.920 --> 0:12:26.319 few a year or two and we had a couple 0:12:26.360 --> 0:12:28.520 of good episodes with Cam. I getting back on. But 0:12:28.600 --> 0:12:31.280 wes I wanna talk about what I What I mentioned 0:12:31.320 --> 0:12:34.199 at the top of the show is basically what appears 0:12:34.240 --> 0:12:36.920 to be kind of a reversal in the rotation back 0:12:36.960 --> 0:12:41.480 to growth and tech leadership. Now, Uh, maybe the thinking 0:12:41.600 --> 0:12:43.120 is the FED took a little bit of the wind 0:12:43.160 --> 0:12:45.480 out of the sales of the reflation trade that was 0:12:45.840 --> 0:12:49.160 boosting Uh, you know, the banks, the energy companies, the 0:12:49.440 --> 0:12:52.400 real cyclical and value sectors of the market. How are 0:12:52.440 --> 0:12:55.040 you thinking about that? Is uh, you know, and Bildad 0:12:55.080 --> 0:12:57.160 has written about this and some others that a lot 0:12:57.160 --> 0:12:59.960 of people think this is kind of a wrong react 0:13:00.120 --> 0:13:03.240 and from the market to rotate this aggressively back into growth, 0:13:03.280 --> 0:13:06.000 that there's still some jewice left to be squeezed out 0:13:06.000 --> 0:13:08.840 of the value and cyclical trade. How are you thinking 0:13:08.840 --> 0:13:11.880 about it? Well, we can start with first principles when 0:13:11.880 --> 0:13:14.200 it comes to why we would believe any value premium 0:13:14.280 --> 0:13:17.439 or size premium or profitability premium in the first place. 0:13:17.520 --> 0:13:19.960 And it's based on the fact that there are differences 0:13:19.960 --> 0:13:22.480 and discount rates across stocks. Right, Investors are going to 0:13:22.600 --> 0:13:26.719 require different rates of return to hold different stocks. Just 0:13:26.800 --> 0:13:28.800 like if you had a whole population of people went 0:13:28.840 --> 0:13:30.600 to the bank for alone, they're likely to get different 0:13:30.600 --> 0:13:33.680 interest rates from the bank, and so it's similar that 0:13:33.760 --> 0:13:36.360 we would expect something like that to be true for 0:13:37.000 --> 0:13:40.480 first stock discount rates, size, value, and profitability are just 0:13:40.520 --> 0:13:44.000 based on using price combined with fundamentals to identify these 0:13:44.040 --> 0:13:47.680 differences and expect to returns, which means that every single day, 0:13:47.760 --> 0:13:50.560 based on the information known to market participants, there's some 0:13:50.559 --> 0:13:54.240 stocks with higher expected returns than others. And that's what 0:13:54.280 --> 0:13:56.959 we're talking about with these expected premiums, such as the 0:13:57.040 --> 0:13:59.839 value premium. So we expect this premium every day, and 0:13:59.840 --> 0:14:03.640 I know from the data that these premiums can be volatile. 0:14:03.640 --> 0:14:05.760 If you just look on a rolling you know, one 0:14:05.840 --> 0:14:09.720 year basis about of twelve month periods going back to 0:14:09.760 --> 0:14:13.959 the nineteen twenties, and the US growth is outperformed value, 0:14:14.160 --> 0:14:16.160 and I think that really hints at this notion of 0:14:16.200 --> 0:14:21.080 the difference between realized returns and expector returns. So many 0:14:21.080 --> 0:14:24.520 people had attributed the strong performance of growth stocks versus 0:14:24.600 --> 0:14:27.480 value and you know, kind of that decade leading up 0:14:27.480 --> 0:14:29.680 to the big turnaround for value recently, and they kind 0:14:29.680 --> 0:14:32.120 of laid that at the feet of the FED. But 0:14:32.200 --> 0:14:34.720 when you look at the performance of those growth stocks 0:14:34.760 --> 0:14:37.640 over that period where they were churning out twenty per 0:14:37.760 --> 0:14:39.880 year in terms of returns, you have to ask yourself 0:14:39.880 --> 0:14:43.000 as an investor, do I believe the expected return for 0:14:43.040 --> 0:14:47.080 this asset classes that seems awfully high and I think 0:14:47.080 --> 0:14:48.720 we would look at that and say a good portion 0:14:48.800 --> 0:14:52.840 of that was an unexpected component of the return that 0:14:52.920 --> 0:14:55.480 might have been based on great success for some of 0:14:55.480 --> 0:14:57.960 these companies, that could have been unexpected to a certain extent. 0:14:58.560 --> 0:15:00.440 Certainly when you look at their valuation as they were 0:15:00.480 --> 0:15:03.920 creeping up, they were still are very very high. Um. So, 0:15:03.960 --> 0:15:07.360 when I think about is the question of is there 0:15:07.360 --> 0:15:10.840 any juice left exqueeze from this limon? My question would be, well, 0:15:10.880 --> 0:15:13.240 what's changed about your expectation for the value premium? As 0:15:13.320 --> 0:15:15.800 long as you believe that low prices associated with higher 0:15:15.800 --> 0:15:19.240 expector returns, there's plenty of juice left to squeeze because 0:15:19.240 --> 0:15:22.200 we still expect a value premium every single day, you 0:15:22.200 --> 0:15:24.920 know us. I'm curious how your approach fits in with 0:15:25.000 --> 0:15:26.720 the year like this, Uh, you know, and I know, 0:15:26.840 --> 0:15:31.120 being anchored in sort of the academic approach of investing 0:15:31.160 --> 0:15:36.280 and very much anchored to the efficient market hypothesis at dimensional. 0:15:36.960 --> 0:15:39.480 Then boy, we enter a year like one, right, and 0:15:39.520 --> 0:15:42.239 we've got all of a sudden, all the discount brokerages 0:15:42.360 --> 0:15:45.120 just completely get rid of commissions. You've got all these 0:15:45.160 --> 0:15:48.280 people stuck at home. Uh, they can't go out. They 0:15:48.280 --> 0:15:50.760 can't bet on sports. You know, they've got a lot 0:15:50.760 --> 0:15:53.640 of spare cash, whether it be because of that or 0:15:53.680 --> 0:15:57.880 because of the stimulus from the government and whatnot. And 0:15:57.920 --> 0:16:00.840 we have this phenomenon like the at its stocks just 0:16:00.960 --> 0:16:04.120 going going absolutely nuts. And it's hard to for me 0:16:04.160 --> 0:16:06.520 to sort of wrap my head around how a student 0:16:06.520 --> 0:16:09.480 of sort of efficient market theory can can kind of 0:16:09.760 --> 0:16:13.880 operate in that environment. I mean, Um, does it change 0:16:13.880 --> 0:16:16.800 your approach at all to see this type of behavior? 0:16:17.600 --> 0:16:20.880 And half jokingly, I asque is there perhaps a Reddit 0:16:20.960 --> 0:16:23.000 factor that can be exploited? You know, is there a 0:16:23.000 --> 0:16:26.560 Wall Street bets factor that you could somehow quantify and 0:16:26.560 --> 0:16:28.960 and try to play with and and feel free to 0:16:28.960 --> 0:16:30.800 tell me I'm crazy for thinking that. I've I've heard 0:16:30.800 --> 0:16:33.200 it before, but I'm just curious how you think about 0:16:33.240 --> 0:16:37.040 a year like this, Um, with that academic background, that 0:16:37.120 --> 0:16:42.160 efficient markets theory background, Uh, with the market that's a 0:16:42.160 --> 0:16:45.040 lot of times just being driven by day traders, you know, 0:16:45.480 --> 0:16:48.160 place some trades based on what they read on Reddit 0:16:48.200 --> 0:16:49.720 and what they think the crowd, where they think the 0:16:49.720 --> 0:16:52.240 crowd is going to go next. Well, I think it 0:16:52.320 --> 0:16:55.760 reinforces the need for flexibility within your investment approach and 0:16:55.840 --> 0:16:58.880 having a daily process. So you know, when we look 0:16:58.880 --> 0:17:01.400 at the price change for a visual securities, I mean 0:17:01.400 --> 0:17:03.520 we know it can happen because of maybe a change 0:17:03.520 --> 0:17:05.720 in the expectation for the future for the cash flows 0:17:05.720 --> 0:17:07.720 of the firm. It could reflect a change in the 0:17:07.760 --> 0:17:11.200 discount rate that's assigned to those expected future cash flows. 0:17:11.320 --> 0:17:14.520 Very difficult, if not impossible, to disentangle those two effects. 0:17:14.560 --> 0:17:17.200 But what we do know is that when price is higher, 0:17:17.720 --> 0:17:20.639 expect to returns are lower. So where that's relevant is 0:17:20.680 --> 0:17:23.040 if you have a strategy, like say one that's focused 0:17:23.040 --> 0:17:24.960 on small cat value stocks. Well, if you have a 0:17:25.000 --> 0:17:27.520 company like one of the ones you're mentioning that started 0:17:27.520 --> 0:17:29.320 off a small cat value and all of a sudden 0:17:29.359 --> 0:17:31.960 it's prices now making it one of the largest two 0:17:32.000 --> 0:17:34.199 or three companies in the US, well, then at that 0:17:34.240 --> 0:17:36.720 point it's not really fitting the definition of higher expected 0:17:36.760 --> 0:17:39.960 returns in accordance with a small cat value portfolio. So 0:17:40.000 --> 0:17:42.439 if I have a daily process, then I can make 0:17:42.480 --> 0:17:44.800 the determination to sell that out of the portfolio at 0:17:44.840 --> 0:17:47.960 that time. It's funny when you look at, uh, you know, 0:17:48.000 --> 0:17:50.000 some of the index approaches. You can use the Rustle 0:17:50.040 --> 0:17:52.679 two thousand value as an example, where as of May 0:17:52.760 --> 0:17:56.280 thirty one, you've got game Stop and AMC still within 0:17:56.320 --> 0:17:58.480 the index, and at that time they were accounting for 0:17:58.520 --> 0:18:02.200 about one and a half percentage point of the index. Uh. 0:18:02.240 --> 0:18:03.919 And you know, you might even think of that is 0:18:04.080 --> 0:18:06.679 a almost a Yao Ming like outlier, like if you 0:18:06.720 --> 0:18:09.639 had Yamming visiting a kindergarten class in the size of screpancy. 0:18:09.800 --> 0:18:11.239 Kind of the picture you would get if you think 0:18:11.280 --> 0:18:14.439 about those two companies in a small value index. But 0:18:14.520 --> 0:18:17.159 they weren't alone. In fact, you had about fifteen percent 0:18:17.240 --> 0:18:19.919 of the Russell two thousand values holdings were actually in 0:18:19.960 --> 0:18:23.159 the top one thousand largest in the US, which is 0:18:23.200 --> 0:18:26.240 obviously the domain of the Russell and thousand indusicries. So 0:18:26.640 --> 0:18:28.800 you know, again that's kind of a function of the 0:18:28.840 --> 0:18:31.879 way that indusseries do their rebalancing in the case of 0:18:31.880 --> 0:18:33.840 the Russell in disease once per year. We believe in 0:18:33.920 --> 0:18:37.080 having a daily process that we can reflect changes in 0:18:37.160 --> 0:18:42.080 market prices throughout the year and rebalance our portfolios incrementally, 0:18:42.200 --> 0:18:43.960 and you need flexibility to do that. You have to 0:18:44.000 --> 0:18:48.280 flex flexibility across names through time and individual names, so 0:18:48.359 --> 0:18:50.640 you're not beholding the one individual trade. In that way, 0:18:50.640 --> 0:18:53.680 you can dynamically react to the way prices changed to 0:18:53.840 --> 0:18:57.320 continuously pursue higher expector returns and manage risk at the 0:18:57.359 --> 0:19:00.600 same time. I gotta say, I would to see Yao 0:19:00.720 --> 0:19:03.800 Ming visited kindergarten class. I'd I'd pay, I'd pay cover 0:19:03.920 --> 0:19:09.399 charts for that, Dott, I'm sure you would. Most of 0:19:09.440 --> 0:19:15.560 my sports jokes go over my head. Sorry about that. 0:19:15.720 --> 0:19:17.720 But but to go back to what Mike was saying 0:19:17.720 --> 0:19:22.240 about this year, Um, you know, returns have been really great. 0:19:22.760 --> 0:19:24.600 I think we were checking the numbers just this morning. 0:19:24.600 --> 0:19:26.680 It's been the second best first half of the year 0:19:26.760 --> 0:19:29.159 in about two decades or so. And then at the 0:19:29.200 --> 0:19:34.120 same time you have all these naysayer's warning about bubble 0:19:34.560 --> 0:19:37.920 and pockets, bubbles and pockets of the markets that are 0:19:38.119 --> 0:19:41.119 sort of bubblicious, if I can use that word. But 0:19:41.400 --> 0:19:44.880 is that thanks is that a prevalent sense right now 0:19:45.320 --> 0:19:48.840 or is it just uh something that you here all 0:19:48.840 --> 0:19:51.960 the time anyway, or is there sort of this sense 0:19:52.080 --> 0:19:55.119 of paranoia that's just a bit more prevalent just because 0:19:55.600 --> 0:20:00.840 the market has been doing so well for the last year. Well, 0:20:00.880 --> 0:20:03.720 the danger with using the expectation or the fear of 0:20:03.760 --> 0:20:08.360 a bubble to influential asset allocation decisions is the possibility 0:20:08.359 --> 0:20:11.120 that you might be wrong in the enormous opportunity costs 0:20:11.359 --> 0:20:13.760 for doing so. And again, you know, I keep on. 0:20:13.840 --> 0:20:16.119 I think twenty was a great example of all the 0:20:16.160 --> 0:20:18.480 case studies that you can use where if you look 0:20:18.480 --> 0:20:22.400 at the flows that we're going into money market funds 0:20:22.800 --> 0:20:25.760 in Q one of I mean, it was close to 0:20:25.800 --> 0:20:29.200 seven billion of dollars presumably going out of equities into 0:20:29.280 --> 0:20:32.240 money market funds, and then what happens subsequent to the 0:20:32.280 --> 0:20:33.800 end of Q one that year, Will you had any 0:20:33.840 --> 0:20:37.560 enormous tear We had equities globally, you know, delivering thirty 0:20:37.600 --> 0:20:40.960 some percentage points worth of return over the next two quarters. 0:20:41.000 --> 0:20:44.200