WEBVTT - DFA’s Schneider on Systematic Flexible Investing 0:00:14.360 --> 0:00:17.520 Welcome to Inside Active, a podcast about active managers that 0:00:17.560 --> 0:00:20.640 goes beyond sound bites and headlines and looks deeper into 0:00:20.680 --> 0:00:25.760 their processes, challenges, and philosophies and security selection. I'm David Cohne, 0:00:25.840 --> 0:00:28.960 I lead mutual fund and active research at Bloomberg Intelligence. 0:00:29.360 --> 0:00:29.720 Today. 0:00:29.880 --> 0:00:35.040 My cost is Christopher Kine, us quantitative strategist at Bloomberg Intelligence. Chris, 0:00:35.040 --> 0:00:36.200 thanks for joining me today. 0:00:36.400 --> 0:00:37.440 Thank you so much for having me. 0:00:37.520 --> 0:00:39.400 David, So, I wanted. 0:00:39.159 --> 0:00:43.479 To ask you about the small cap BMVP portfolio, as 0:00:43.520 --> 0:00:46.560 I really think it's partin into our discussion today. How 0:00:46.600 --> 0:00:49.920 has the focus on certain factors helped that portfolio up 0:00:49.960 --> 0:00:52.040 perform an index like the Russell two thousand. 0:00:53.040 --> 0:00:56.720 Sure, so, our small cap BMVP multi factor portfolio is 0:00:56.800 --> 0:00:59.720 very similar to our large cap version. So it's a 0:01:00.360 --> 0:01:06.120 only multi factor portfolio using four main factors, which is value, momentum, 0:01:06.160 --> 0:01:11.039 low volatility, and profitability. So our small cap version beat 0:01:11.040 --> 0:01:14.480 the Russell two thousand equweight index by about ten percentage 0:01:14.480 --> 0:01:16.959 points this year or last year, I should say, up 0:01:17.000 --> 0:01:19.720 about twenty percent versus about ten to eleven percent for 0:01:19.760 --> 0:01:22.800 the index. You know, it's not really a mystery why. 0:01:22.880 --> 0:01:25.240 You know, most of the factors did work in small 0:01:25.280 --> 0:01:28.440 caps last year similar to large caps. Would I would 0:01:28.440 --> 0:01:32.360 flag that value seem to work a bit better, you know, 0:01:32.440 --> 0:01:34.640 in small caps, but the devils and the details kind 0:01:34.640 --> 0:01:38.240 of about how you define value. But yeah, it's been 0:01:38.240 --> 0:01:41.399 a strong factor year for both market capitalizations and hopefully 0:01:41.400 --> 0:01:43.920 continues great well. 0:01:43.959 --> 0:01:45.880 I think our guests can add some color to our 0:01:45.880 --> 0:01:49.760 discussion on factors. I'd like to welcome Joel Schneider, Joel's 0:01:49.800 --> 0:01:54.080 deputy head of portfolio management at Dimensional Fund Advisors. Joel, 0:01:54.120 --> 0:01:55.360 thank you for joining us today. 0:01:55.640 --> 0:01:57.640 Hey David, Hey Chris. Happy to be here. 0:01:58.600 --> 0:02:02.760 So before we die into factors and discussion in general, 0:02:03.000 --> 0:02:04.640 we'd love to hear how you got your start in 0:02:04.680 --> 0:02:05.600 the investment business. 0:02:07.200 --> 0:02:10.200 Yeah. Sure. I'll start with the short answer first, which 0:02:10.240 --> 0:02:14.320 is serendipity, meaning I didn't really set out to work 0:02:14.320 --> 0:02:18.280 in investment management. The longer answer is, you know, I 0:02:18.320 --> 0:02:20.560 was one of those inquisitive kids that used to take 0:02:20.600 --> 0:02:24.880 things apart to understand how they worked, and it's probably 0:02:24.880 --> 0:02:27.840 no surprise I wound up in engineering, but before I 0:02:27.880 --> 0:02:31.800 got there. After school, growing up, I used to go 0:02:31.840 --> 0:02:34.960 over to my grandparents' house and my parents both worked, 0:02:34.960 --> 0:02:37.639 so my grandparents watched US for a couple hours, and 0:02:37.919 --> 0:02:41.920 my grandpa would always watch CNBC, and so it was 0:02:42.480 --> 0:02:45.520 riveting for me, as a young person that like numbers, 0:02:45.840 --> 0:02:48.320 to see all these prices flying by, to see all 0:02:48.320 --> 0:02:52.959 these company fundamentals being talked about. But there was sort 0:02:52.960 --> 0:02:55.639 of a randomness to the stock market that never really 0:02:55.639 --> 0:02:57.600 made a lot of sense to me, so I sort 0:02:57.600 --> 0:03:00.160 of put that interest aside. I ended up going to 0:03:00.240 --> 0:03:03.920 college and studying computer engineering, and then I worked at 0:03:03.919 --> 0:03:07.160 Lockey Martin and I designed communication systems for the Navy 0:03:07.200 --> 0:03:10.400 and the Air Force. And as I was there, I 0:03:10.480 --> 0:03:12.959 began to realize that if I was going to progress 0:03:13.040 --> 0:03:17.840 in that role, I needed to learn corporate finance. So 0:03:18.240 --> 0:03:21.280 to be the head of a large program, or to 0:03:21.360 --> 0:03:24.040 be the head of a division, you had to have 0:03:24.080 --> 0:03:26.840 your own P and L. So I needed to understand 0:03:26.840 --> 0:03:29.639 corporate finance better than I did. So I went back 0:03:29.639 --> 0:03:32.120 to business school at University of Chicago to get an MBA, 0:03:33.320 --> 0:03:37.000 and while I was there, I learned that there were 0:03:37.040 --> 0:03:39.840 a lot of theories and frameworks and evidence that actually 0:03:39.880 --> 0:03:43.600 explained how financial markets worked, So to me, this was 0:03:43.600 --> 0:03:47.760 really cool. There were valuation frameworks like discounter cash flow 0:03:47.800 --> 0:03:51.760 models that help you value companies. There were portfolio theories 0:03:51.800 --> 0:03:54.920 that talked about the benefits of diversification based on the 0:03:54.920 --> 0:03:59.640 covariance of different assets. There was arbitrage pricing theories that 0:04:00.080 --> 0:04:03.320 helped explain how the prices of different financial instruments were 0:04:03.320 --> 0:04:06.240 all kept inlign with each other. And then importantly for 0:04:06.280 --> 0:04:09.320 today's discussion, there were factor pricing models that helped explain 0:04:09.480 --> 0:04:14.280 what drove returns in equities and bonds. And so after 0:04:14.360 --> 0:04:17.719 seeing all this, and actually really importantly to me was 0:04:18.000 --> 0:04:22.760 these weren't just theories. People were actually rigorously testing them 0:04:23.080 --> 0:04:26.560 using the scientific method which I'd come to learn in engineering. 0:04:27.400 --> 0:04:30.120 So all of this allowed me to see through the randomness. 0:04:30.760 --> 0:04:33.760 And when I graduated from University of Chicago, there's really 0:04:33.800 --> 0:04:36.320 no place other that I wanted to work than dimensional 0:04:36.560 --> 0:04:39.320 because we'd been associated with a lot of the academics 0:04:39.680 --> 0:04:42.720 that founded a lot of those frameworks and did a 0:04:42.720 --> 0:04:43.480 lot of that research. 0:04:45.080 --> 0:04:47.840 That's great, and so you know, actually, let's talk about 0:04:47.880 --> 0:04:50.960 dimensional or you know DFA as I call it. And 0:04:51.000 --> 0:04:53.080 I'm sure a lot of others, and I know many 0:04:53.080 --> 0:04:55.560 of our listeners know of DVA, but we'd love to 0:04:55.600 --> 0:04:59.200 hear you know, from your I guess experience working there, 0:04:59.320 --> 0:05:02.560 you know the basic tenants behind the DFA investment philosophy. 0:05:04.279 --> 0:05:07.280 Yeah, sure, if you don't mind to understand our philosophy, 0:05:07.440 --> 0:05:09.520 and might be helpful if I spend a couple minutes 0:05:09.560 --> 0:05:13.800 describing our background in our history. So, yeah, we've been 0:05:13.839 --> 0:05:18.039 around for about four decades and we've become one of 0:05:18.040 --> 0:05:22.600 the largest investment managers and more recently the largest active 0:05:22.640 --> 0:05:25.520 ETF manager in the world, and we manage about eight 0:05:25.600 --> 0:05:30.080 hundred billion dollars of publicly traded securities, so across equities, 0:05:30.080 --> 0:05:33.719 fixed income, real estate, and commodities. And we have this 0:05:33.839 --> 0:05:39.240 really deep academic heritage and so a lot of our investments, 0:05:39.240 --> 0:05:42.320 and specifically our investment philosophy that you asked about, is 0:05:42.400 --> 0:05:45.839 rooted in research that's been done by multiple Nobel Prize 0:05:45.839 --> 0:05:49.640 winners as well as many other leading academics. And what 0:05:49.680 --> 0:05:53.919 we see as our job at Dimensional is to implement 0:05:54.720 --> 0:05:59.280 their research in real world portfolios. So what that ends 0:05:59.360 --> 0:06:03.280 up looking like is we run very low cost, broadly 0:06:03.320 --> 0:06:10.440 diversified portfolios, but they are not exactly indexed. So we 0:06:10.800 --> 0:06:16.279 have active strategies that actually outperform our benchmark index is 0:06:16.320 --> 0:06:18.960 at a greater rate and over longer periods of time 0:06:19.720 --> 0:06:22.839 than most other managers. In fact, I'm not aware of 0:06:22.839 --> 0:06:25.760 anyone that has sort of the types of numbers we have, 0:06:26.000 --> 0:06:27.920 So just to give you a sense of what those are, 0:06:28.520 --> 0:06:30.640 if you were to go back over the last decade 0:06:30.960 --> 0:06:34.920 and say what percentage of managers beat their benchmark index 0:06:35.800 --> 0:06:38.200 in the industry, it's a pretty low number. It's only 0:06:38.279 --> 0:06:42.280 twenty three percent of managers. But at dimensional seventy eight 0:06:42.279 --> 0:06:45.160 percent of our funds have beating their benchmark index over 0:06:45.160 --> 0:06:47.520 the last ten years. And if you extend that over 0:06:47.600 --> 0:06:51.360 twenty years, it gets even worse. For the industry, only 0:06:51.440 --> 0:06:54.960 eighteen percent of funds have beaten their benchmarks, but ninety 0:06:54.960 --> 0:06:58.200 two percent of our funds have. And so I want 0:06:58.200 --> 0:07:00.760 to get into the investment philosophy now to sort of 0:07:00.800 --> 0:07:04.080 explain how we do that. But a key insight, remember 0:07:04.080 --> 0:07:06.600 when I said our job is to implement the best 0:07:06.600 --> 0:07:11.000 ideas in finance. Well, our co founders actually founded some 0:07:11.040 --> 0:07:13.800 of the first index funds in the early nineteen seventies, 0:07:14.440 --> 0:07:19.080 and in doing that they came to realize that trading 0:07:19.320 --> 0:07:21.360 in a really rigid way where you have to buy 0:07:21.360 --> 0:07:23.160 and sell the stocks that the index tells you to 0:07:24.360 --> 0:07:27.240 is a recipe for high trade and cost, and so 0:07:27.680 --> 0:07:31.920 they realize back then that there's a difference between passive 0:07:32.320 --> 0:07:35.400 and indexed. So I think this may help us in 0:07:35.440 --> 0:07:38.840 our conversation today. But I just wanted to find passive 0:07:39.640 --> 0:07:44.160 and active, or sorry, passive and index For passive, I 0:07:44.160 --> 0:07:47.920 think that means just treating market prices is fair and 0:07:48.000 --> 0:07:52.960 generally holding securities at their marketcap weight. For indexed, that 0:07:53.120 --> 0:07:57.960 is an implementation approach. It's basically where you are forced 0:07:58.000 --> 0:08:00.840 to buy and sell securities when some third party index 0:08:00.880 --> 0:08:04.400 provider tells you to. And so a lot of the 0:08:04.480 --> 0:08:07.760 key to doing better than indexes is avoiding that type 0:08:07.760 --> 0:08:12.360 of implementation. All right, So that was a really long 0:08:13.320 --> 0:08:15.480 way to get to your question. But in terms of 0:08:15.480 --> 0:08:19.600 our investment philosophy, I think it boils down to in 0:08:19.600 --> 0:08:25.080 competitive liquid markets, prices are generally fair, they're forward looking, 0:08:26.160 --> 0:08:31.760 and they already represent a consensus prediction about the future. 0:08:32.520 --> 0:08:34.959 And so the challenge that a lot of traditional active 0:08:34.960 --> 0:08:37.560 managers have had is that they're trying to outguess those 0:08:37.559 --> 0:08:41.640 market prices. And as we all saw yesterday in the news, 0:08:42.640 --> 0:08:46.800 all of a sudden there was news that the Chinese 0:08:46.880 --> 0:08:50.240 company behind deep Seek had this great new AI model 0:08:50.559 --> 0:08:54.040 that challenged the business model of some of the US 0:08:54.080 --> 0:08:57.920 based companies and the suppliers of chips, and so really 0:08:58.000 --> 0:09:01.559 quickly prices adjusted, and I didn't really see a lot 0:09:01.559 --> 0:09:04.360 of people out there calling that ahead of time. So 0:09:04.640 --> 0:09:08.000 markets are moving in real time. Prices are adjusting, and 0:09:08.040 --> 0:09:12.240 so our philosophy is embrace that, just make use of it. 0:09:12.600 --> 0:09:17.079 And so it starts with just saying the prices are 0:09:17.120 --> 0:09:20.240 what they are, they're a reasonable prediction. How do we 0:09:20.400 --> 0:09:24.240 bring other pieces of information to combine with the price 0:09:24.880 --> 0:09:28.400 to understand which stocks have higher or lower future expector 0:09:28.400 --> 0:09:33.960 returns given that price today? And so that to many 0:09:33.960 --> 0:09:37.000 people they call that factor investing. But you're combining different 0:09:37.840 --> 0:09:41.720 variables or financial metrics from companies' income statements or balance 0:09:41.800 --> 0:09:45.240 sheets with the price to make some inferences about which 0:09:45.240 --> 0:09:47.560 stocks are likely to do better in the future. 0:09:49.000 --> 0:09:51.040 No, that makes sense. I do want to touch upon 0:09:51.080 --> 0:09:55.200 what you said about indexing and passive and so, you know, 0:09:55.240 --> 0:09:58.839 this being a podcast focused on active management, if you 0:09:58.840 --> 0:10:02.599 could further elaborate on what you consider the inefficiencies of indexing. 0:10:02.920 --> 0:10:05.920 You know, you mentioned you know the news yesterday and 0:10:06.360 --> 0:10:09.440 you know obviously, you know, holding an index, you know 0:10:09.600 --> 0:10:11.760 that that becomes an issue, and so i'd just love 0:10:11.800 --> 0:10:12.760 to hear more about that. 0:10:14.400 --> 0:10:20.439 Yeah, for sure. So again, indexing to us is an 0:10:20.440 --> 0:10:26.560 implementation decision, and it's basically outsourcing your trading decisions to 0:10:26.640 --> 0:10:31.480 some third party index provider. And I think there's multiple 0:10:31.480 --> 0:10:36.480 issues when you outsource to them. Now, if we step back, 0:10:36.520 --> 0:10:39.120 a lot of people think indexing is really sort of 0:10:39.200 --> 0:10:43.319 low cost, and I would actually take issue with that. 0:10:43.440 --> 0:10:47.320 I think it's low fee, but it's not necessarily low cost. 0:10:48.080 --> 0:10:49.520 And what I mean is that there's a lot of 0:10:49.600 --> 0:10:54.120 hidden costs involved with indexing. A big one of those 0:10:54.440 --> 0:10:57.720 is that the indexers are all forced to trade the 0:10:57.760 --> 0:11:00.520 same names on the same day, the same time as 0:11:00.559 --> 0:11:04.000 all the other indexers. And so a really fun analogy 0:11:04.080 --> 0:11:06.720 is it's sort of like buying roses on Valentine's Day? 0:11:07.440 --> 0:11:10.360 Do you think you're going to get a good price? No, Right, 0:11:10.400 --> 0:11:12.960 if you bought roses a week or two before or after, 0:11:13.000 --> 0:11:14.480 you're going to get a much better price than if 0:11:14.480 --> 0:11:17.600 you're buying them on that day. So that's called the 0:11:17.640 --> 0:11:21.480 index reconstitution effect. And you guys may know these numbers 0:11:21.480 --> 0:11:24.800 better than me, but if you look at the growth 0:11:24.840 --> 0:11:29.240 of indexing, the total dollars chasing after the same names, 0:11:30.559 --> 0:11:32.120 I saw numbers las year at the end of last 0:11:32.160 --> 0:11:35.880 year around like twelve trillion dollars in index products. So 0:11:36.120 --> 0:11:39.000 that means that when there's these rebalance events, you've got 0:11:39.120 --> 0:11:42.120 billions of dollars, tens of billions of dollars that are 0:11:42.160 --> 0:11:45.760 all chasing the same stocks. And what that does is 0:11:45.800 --> 0:11:49.600 it tends to on average, push up prices of names 0:11:49.600 --> 0:11:52.240 that are being added to the index and pushed down 0:11:52.320 --> 0:11:56.360 prices of names that are being dropped. And our research 0:11:56.480 --> 0:11:59.360 we actually just did an updated set of research papers 0:11:59.360 --> 0:12:01.640 on this. There's a lot of academic work about ten 0:12:01.720 --> 0:12:04.320 years ago, so we decided to do an update for 0:12:04.360 --> 0:12:06.800 the next decade. We looked at both US and non 0:12:06.880 --> 0:12:11.320 US equity indices, and we found that prices get pushed 0:12:11.320 --> 0:12:16.400 by about four percent on average. Four percent. I don't 0:12:16.440 --> 0:12:18.679 know if that feels like a big or small number 0:12:18.800 --> 0:12:21.480 to the people listening, but let me just put that 0:12:21.520 --> 0:12:25.280 in context a little. Let's say an index has five 0:12:25.320 --> 0:12:29.200 percent turnover a year. It's pretty low turnover. Eight Well, 0:12:29.280 --> 0:12:32.080 if five percent of your portfolio is getting four percent 0:12:32.200 --> 0:12:35.880 worse prices that's a potential drag of twenty basis points 0:12:35.880 --> 0:12:39.800 a year. Now, when people think of the low expense 0:12:39.960 --> 0:12:43.960 ratios or management fees of indexing, that twenty basis points 0:12:43.960 --> 0:12:48.240 of hidden performance drag is in many cases much bigger 0:12:48.280 --> 0:12:50.720 than the fee they're paying, So really their total cost 0:12:50.760 --> 0:12:52.600 of ownership is a lot higher than they think it is. 0:12:53.760 --> 0:12:54.080 Now. 0:12:54.640 --> 0:12:59.800 The challenge with seeing that is both the index and 0:12:59.840 --> 0:13:04.000 the index fund suffer from that because they're both adding 0:13:04.040 --> 0:13:07.840 the stocks at the close on the rebalanced day. So 0:13:08.800 --> 0:13:11.360 your index fund will have maybe no tracking here with 0:13:11.400 --> 0:13:15.160 your index, but both of them have that performance drag 0:13:15.280 --> 0:13:18.800 baked in. So I think that's one of the biggest 0:13:18.880 --> 0:13:22.960 inefficiencies of indexing. I think there's other ones, though we 0:13:22.960 --> 0:13:25.240 can get into this a little bit later, especially when 0:13:25.240 --> 0:13:29.000 you're trying to capture factor. Premium indexes have a lot 0:13:29.000 --> 0:13:32.200 of style drift, and that becomes a big issue. I 0:13:32.200 --> 0:13:35.080 heard Chris at the beginning talking about capturing some of 0:13:35.080 --> 0:13:39.040 the premiums within small cap like profitability and value. Well, 0:13:39.280 --> 0:13:42.440 if the Russell two thousand is only rebalancing once a 0:13:42.520 --> 0:13:45.800 year in June, then that means they've got eleven months 0:13:45.840 --> 0:13:48.520 where the stocks they hold have drifted. Many have become 0:13:48.600 --> 0:13:54.680 midcaps or large caps, and so the index style drift 0:13:54.720 --> 0:13:57.360 is a major issue. And then you know, I talk 0:13:57.440 --> 0:14:00.480 with a lot of institutional clients and one of the 0:14:00.520 --> 0:14:04.160 things that they've come to really realize is that a 0:14:04.160 --> 0:14:07.200 lot of their index managers may be charging them a 0:14:07.320 --> 0:14:10.960 very low management fee, but then they're keeping a pretty 0:14:11.040 --> 0:14:15.040 large percentage of the securities lending profits from those stocks, 0:14:15.679 --> 0:14:18.200 and in some ways that serves as sort of a 0:14:18.240 --> 0:14:20.920 shadow management fee, right it looks like you're only paying 0:14:20.960 --> 0:14:23.520 a couple BIPs and expensory sue or in management fee, 0:14:23.840 --> 0:14:26.800 but then they're keeping a slug of the sect lending 0:14:27.080 --> 0:14:30.160 revenues for themselves. So those are just some of the issues. 0:14:30.160 --> 0:14:31.960 I'm sure we'll get into more of them later. But 0:14:32.680 --> 0:14:35.480 there's there's definitely issues with index implementation, and you can 0:14:35.480 --> 0:14:38.560 do better than indexing by not being so rigid. 0:14:39.400 --> 0:14:43.880 No makes sense, and so you know, switching from passive 0:14:43.960 --> 0:14:46.400 over to active, and you know, I know Chris has 0:14:46.400 --> 0:14:48.880 a bunch of questions for you in terms of you know, 0:14:49.000 --> 0:14:51.760 factors as you touched upon a little bit, but I 0:14:51.760 --> 0:14:53.960 would just love to hear you know, what factors in 0:14:54.040 --> 0:14:59.119 the research at Dimensional have you found that historically driven performance. 0:14:59.560 --> 0:15:02.440 Yeah, I think the answer to that depends on what 0:15:02.640 --> 0:15:06.960 time frame you're measuring. So we like to think about 0:15:07.000 --> 0:15:11.480 three different timeframes. So in the long term, let's say 0:15:11.560 --> 0:15:15.840 we're measuring over a year or more. In terms of 0:15:15.880 --> 0:15:23.680 those long term drivers, it's company's valuation, their profitability, and 0:15:23.760 --> 0:15:27.720 their size. Then you start to get into some of 0:15:27.720 --> 0:15:31.800 the more intermediate or shorter term drivers. Let's say we're 0:15:31.840 --> 0:15:36.800 measuring those over months or weeks. They're things like momentum 0:15:37.760 --> 0:15:44.320 or asset growth, or interestingly, stocks that are expensive to borrow. 0:15:44.400 --> 0:15:48.160 In the securities lending market, that's actually, to me a 0:15:48.240 --> 0:15:54.560 really cool factor. We often say that we extract information 0:15:54.680 --> 0:15:57.000 from market prices. So earlier you asked me about our 0:15:57.000 --> 0:15:59.400 investment philosophy, and I said, we take the prices for 0:15:59.440 --> 0:16:01.880 what they are and we see what information we can 0:16:01.960 --> 0:16:05.680 extract from that. Well, here's an example where the securities 0:16:05.760 --> 0:16:09.560 lending market that is another market just like the stock 0:16:09.600 --> 0:16:11.920 markets a market, the stock lending markets market, and it's 0:16:11.920 --> 0:16:15.480 got prices, and if people are willing to pay very 0:16:15.560 --> 0:16:20.160 high fees to borrow stocks, often to shorten them, that's 0:16:20.160 --> 0:16:24.440 actually a really negative sign that explains under performance. Of 0:16:24.480 --> 0:16:26.880 stocks over the next few weeks after they become expensive 0:16:26.920 --> 0:16:31.720 to borrow. And then the last very sort of short 0:16:31.800 --> 0:16:38.160 term factors are things related to liquidity. So one of 0:16:38.160 --> 0:16:42.920 them that's in the academic research is price reversals, and 0:16:42.960 --> 0:16:46.640 then the other are things related to implicit trade and costs, 0:16:46.760 --> 0:16:52.080 so spreads, price impact. So I think, really zooming back out, 0:16:52.680 --> 0:16:56.600 you want to think about which factors are reliable, but 0:16:56.680 --> 0:16:59.920 then which ones apply over different timeframes, and how you 0:17:00.080 --> 0:17:03.360 implement will depend on the timeframe that they apply over. 0:17:04.240 --> 0:17:06.720 And so I think maybe the last thing to add 0:17:07.960 --> 0:17:10.800 before I'm sure you have questions on that is some 0:17:11.320 --> 0:17:14.320 listeners may be wondering why I didn't mention some of 0:17:14.320 --> 0:17:19.440 the commonly cided factors that they've heard of. And unfortunately, 0:17:20.240 --> 0:17:22.359 you guys have probably heard the term the factor zoo. 0:17:23.040 --> 0:17:26.080 So there's so many people publishing papers about different factors. 0:17:26.440 --> 0:17:28.439 You know, some people say three hundred or four hundred 0:17:28.440 --> 0:17:31.960 factors have been identified. Well, those are mainly filled with 0:17:32.080 --> 0:17:37.520 either deplicative or unreliable factors. And so when I say deplicative, 0:17:37.600 --> 0:17:40.959 I just mean that once you control for the factors 0:17:41.000 --> 0:17:44.640 I already mentioned that the other ones don't add any 0:17:44.680 --> 0:17:47.240 new explanatory power. It's not to say there's anything wrong 0:17:47.280 --> 0:17:50.600 with those, it's just it could be you know that 0:17:51.000 --> 0:17:54.960 you're going to approach that factor using some other definition. 0:17:55.119 --> 0:17:57.280 That's fine as long as you know and you're not 0:17:57.359 --> 0:18:00.800 being redundant and applying basically sort of the same factor twice. 0:18:01.320 --> 0:18:04.560 And then the other reason why I didn't mention some 0:18:04.720 --> 0:18:08.080 is some of them just don't pass the high standards 0:18:08.119 --> 0:18:11.280 of the scientific method which I talked about earlier, and 0:18:11.320 --> 0:18:14.040 that is you need to have a strong economic theory 0:18:14.080 --> 0:18:16.639 for why a factor should exist. You need to be 0:18:16.680 --> 0:18:20.679 able to reproduce those results, and they need to be 0:18:20.680 --> 0:18:23.639 able to hold up an out of sample testing. Otherwise 0:18:23.680 --> 0:18:26.439 it's hard to be confident that those will occur in 0:18:26.440 --> 0:18:26.879 the future. 0:18:27.200 --> 0:18:30.200 So interesting, I you know, it's a jewel. I reserve 0:18:30.280 --> 0:18:34.040 the right to steal your buying roses on Valentine's Day analogy. 0:18:34.160 --> 0:18:39.200 I love that. So my questions around combining multiple factors, 0:18:39.240 --> 0:18:41.639 I mean, you know, thank you for walking through that. 0:18:41.640 --> 0:18:44.080 That was really interesting. With the different timeframes, you know, 0:18:44.119 --> 0:18:47.760 I don't see many people frame it that way, So 0:18:48.160 --> 0:18:51.200 you know, can you talk us through how those different 0:18:51.240 --> 0:18:55.760 timeframes you know, apply to a multi factor process. How 0:18:55.800 --> 0:18:59.360 do you combine factors, especially if they have different time frames? 0:18:59.560 --> 0:19:02.840 It is any element, and I guess, I guess I 0:19:02.880 --> 0:19:06.359 can ask do you believe in factor timing, Like, do 0:19:06.400 --> 0:19:08.800 you think there's a way to time factors or do 0:19:08.840 --> 0:19:11.639 you think it's a better approach to just have a 0:19:12.560 --> 0:19:17.600 relatively constant exposure to factors that you believe, you know 0:19:17.760 --> 0:19:21.320 are are advantages for the long term. 0:19:21.359 --> 0:19:23.359 Sure, well, it's a two part question, So let me 0:19:23.400 --> 0:19:25.439 take the second part of your question first, which is 0:19:26.640 --> 0:19:30.920 we have looked for every way that we could possibly 0:19:30.920 --> 0:19:35.359 think of time factors, and we really wish that you 0:19:35.400 --> 0:19:40.840 could just Unfortunately there's no evidence that you can, and 0:19:40.880 --> 0:19:44.560 that oftentimes the cost of getting it wrong is really significant. 0:19:44.680 --> 0:19:44.800 Right. 0:19:44.800 --> 0:19:47.199 One of the things I learned in engineering is you 0:19:47.200 --> 0:19:50.040 always have to think about if a certain part or 0:19:50.080 --> 0:19:54.320 system fails, how bad is the outcome when it fails? 0:19:54.760 --> 0:19:59.280 And getting factor timing wrong can be a really expensive 0:20:01.000 --> 0:20:06.600 and so generally it's better to take multiple factors that 0:20:06.680 --> 0:20:10.960 are reliable but that oftentimes are not highly correlated with 0:20:11.040 --> 0:20:14.119 each other and include them into a multi factor portfolio. 0:20:14.440 --> 0:20:17.439 This is going to give you a little bit more 0:20:18.400 --> 0:20:22.320 risk control and the ability to sort of ride out 0:20:22.440 --> 0:20:25.119 or survive different periods in the market when certain factors 0:20:25.160 --> 0:20:28.080 are in or out of favor. So I think, Chris, 0:20:28.160 --> 0:20:30.120 that gets to your second question, which is, then how 0:20:30.160 --> 0:20:33.040 do you start to combine multiple factors into a portfolio? 0:20:34.200 --> 0:20:37.200 And I think there's a few lessons to keep in mind. 0:20:38.080 --> 0:20:42.360 The first one that I said earlier is, you know, 0:20:42.520 --> 0:20:46.600 more factors are not necessarily better. There's a quote that's 0:20:46.640 --> 0:20:51.800 often attributed to Einstein that I really like that you know, 0:20:51.960 --> 0:20:55.520 supposedly pretty much every quote is either attributed nowadays to 0:20:55.520 --> 0:20:59.239 either Einstein or Mark Twain, so you never really know 0:20:59.320 --> 0:21:01.560 if they're said, but anyway, it's a good quote which 0:21:01.640 --> 0:21:04.919 says everything should be as simple as it can be, 0:21:05.920 --> 0:21:10.240 but not simpler, right, So there is room for things 0:21:10.240 --> 0:21:14.760 that are complicated in this world. But just throwing additional 0:21:14.800 --> 0:21:18.320 factors into something, even though it may seem sophisticated, sometimes 0:21:18.359 --> 0:21:22.480 actually is detrimental. And so I would say you want 0:21:22.520 --> 0:21:25.439 to start with factors that are rigorously tested or not 0:21:25.560 --> 0:21:31.120 duplicative with one another, and then, like you said, understand 0:21:31.160 --> 0:21:33.760 the timeframes. And so the way that we approach it 0:21:33.840 --> 0:21:37.080 is those long term factors that help explain returns over 0:21:37.200 --> 0:21:41.320 years those are good things to actually build a strategy's 0:21:41.359 --> 0:21:45.879 construction around, right, because you can do that in a 0:21:45.920 --> 0:21:49.840 pretty stable way without a lot of turnover, and so 0:21:50.080 --> 0:21:52.399 things like you mentioned earlier you were talking about that 0:21:52.480 --> 0:21:57.600 small cap strategy, So things like valuation, profitability, size, those 0:21:57.640 --> 0:22:01.560 are great to include in a long term strategy. And 0:22:01.600 --> 0:22:05.760 the way that we do it is we will start 0:22:05.760 --> 0:22:08.240 with market cap weights of securities, and then to the 0:22:08.320 --> 0:22:12.080 extent that securities look good across multiple factors are bad, 0:22:12.200 --> 0:22:17.520 we'll overweight and underweight relative to market cap weights. Now, 0:22:17.600 --> 0:22:20.480 then this brings in some of those shorter time period factors, 0:22:21.119 --> 0:22:25.239 and so with those, I think it's important to not 0:22:25.480 --> 0:22:29.359 apply them in the construction because if a factor is 0:22:30.200 --> 0:22:33.920 changing its signal or it's information is providing you every 0:22:33.920 --> 0:22:36.520 couple of weeks, then it's going to cause a lot 0:22:36.560 --> 0:22:39.640 of turnover in the portfolio. That could cause very high 0:22:39.640 --> 0:22:42.720 trading cost or if you have taxbile investors, that could 0:22:42.800 --> 0:22:47.119 cause them a huge capital gains tax bill. So there, 0:22:47.400 --> 0:22:50.520 I think the best thing to do is to use 0:22:50.600 --> 0:22:55.159 them as delays. So let's say that you would have 0:22:55.320 --> 0:22:58.600 purchased or sold some security based on the long term factors, 0:22:59.000 --> 0:23:01.640 but then you screen them for the short term factors, 0:23:01.680 --> 0:23:04.280 and then you may decide to either delay that buy 0:23:04.359 --> 0:23:08.040 or sell and then substitute in another name that isn't 0:23:08.080 --> 0:23:12.879 having that maybe negative short run expected return. And so 0:23:13.680 --> 0:23:16.160 I think that tends to be the way that we 0:23:16.200 --> 0:23:18.200 think about it. And then the last thing that I 0:23:18.240 --> 0:23:21.640 would say is you really want to understand how those 0:23:21.680 --> 0:23:26.080 factors interrelate with one another. And so for example, value 0:23:26.520 --> 0:23:30.600 and profitability, they tend to be complements. So more often 0:23:30.640 --> 0:23:33.800 than not, when the value premium is negative, the profitability 0:23:33.800 --> 0:23:36.600 premium is positive, or vice versa. So therefore those are 0:23:36.640 --> 0:23:42.400 great to combine in a portfolio, whereas profitability and let's 0:23:42.440 --> 0:23:46.439 say growth, those tend to be positively correlated. So if 0:23:46.480 --> 0:23:48.919 you aren't careful, you could just be doubling down and 0:23:49.000 --> 0:23:52.520 increasing your risk without really increasing your expected return. So 0:23:52.800 --> 0:23:55.320 I think that's the main way that we think about 0:23:55.359 --> 0:23:56.960 including multiple factors. 0:23:57.560 --> 0:23:59.640 That's so interesting. Thank you. I mean, I think it's 0:23:59.640 --> 0:24:02.600 relative unique that you guys do like the you know, 0:24:02.640 --> 0:24:04.600 the long term and in the short term, and I 0:24:04.720 --> 0:24:07.159 thank you for explaining that. I mean, that's really a 0:24:07.200 --> 0:24:11.280 really cool perspective. Who knows if Leonardo da Vinci actually 0:24:11.359 --> 0:24:14.880