WEBVTT - Astoria’s Davi on Mitigating Concentration Risk 0:00:15.040 --> 0:00:18.239 Welcome to Inside Active, a podcast about active managers that 0:00:18.280 --> 0:00:21.239 goes beyond sound bites and headlines and looks deeper into 0:00:21.280 --> 0:00:26.080 their processes, challenges and philosophies and security selection. I'm David Cohne, 0:00:26.079 --> 0:00:29.080 I lead mutual fund and active research at Bloomberg Intelligence. 0:00:29.440 --> 0:00:33.080 Today my co host is Christopher kine, Us, quantitative strategist 0:00:33.080 --> 0:00:36.040 at Bloomberg Intelligence. Chris, thank you for joining me today. 0:00:36.320 --> 0:00:37.720 Thank you so much for having me. David. 0:00:38.560 --> 0:00:42.400 So, you wrote a recent note about adding profitability to 0:00:42.640 --> 0:00:46.760 value stocks or the profitability factor. Since our conversation today 0:00:46.800 --> 0:00:49.519 will be focused on quality, I wonder if you could 0:00:49.560 --> 0:00:52.640 give us a sense of how adding that profitability factor 0:00:52.680 --> 0:00:55.600 to a standalone value strategy performs. 0:00:56.200 --> 0:00:59.240 Yeah. I'm a big fan of adding profitability to value. 0:00:59.280 --> 0:01:01.520 I mean just in empirically, you know, it seems to 0:01:01.520 --> 0:01:04.200 work better and it's very logical. So you know, just 0:01:04.240 --> 0:01:08.120 as a as a review, you know, value was the 0:01:08.120 --> 0:01:11.440 only factor that underperformed in twenty twenty four by our measurement. 0:01:11.720 --> 0:01:13.520 If you look at the long short factor, it was 0:01:13.560 --> 0:01:16.920 the only one that's down on the year, And if 0:01:16.959 --> 0:01:18.840 you only look at the long only legs, it was 0:01:18.840 --> 0:01:21.720 the only one that underperform the market. So it so 0:01:22.000 --> 0:01:24.640 just Q one value. Just cheap stocks returned about ten 0:01:24.680 --> 0:01:27.040 percent last year in the Russell one thousand as compared 0:01:27.040 --> 0:01:30.800 to about thirteen or so percent return for the equal 0:01:30.800 --> 0:01:33.760 weighted a Russell one thousand. If you added some profitability 0:01:33.800 --> 0:01:37.399 to that, that increased the returns to about fifteen to 0:01:37.440 --> 0:01:40.120 sixteen percent. So you know it, I'll perform a market 0:01:40.120 --> 0:01:43.880 if you just had that profitability component. To me, you know, 0:01:43.920 --> 0:01:48.080 it's very logical because you know, sometimes value stocks are 0:01:48.160 --> 0:01:50.600 valued for a reason. You know they have, you know, 0:01:50.760 --> 0:01:53.600 not good prospects and little chance for a turnaround. If 0:01:53.600 --> 0:01:56.680 you add a profitability filter to your value factor, you 0:01:56.760 --> 0:01:59.680 kind of filter out those value traps or you know, 0:02:00.160 --> 0:02:02.240 cheap companies that are cheap for a good reason. And 0:02:02.240 --> 0:02:05.120 that seems to work good both in the short term 0:02:05.120 --> 0:02:05.880 and the long term. 0:02:06.680 --> 0:02:09.519 That makes sense. So I think we'd like to introduce 0:02:09.840 --> 0:02:13.760 someone who's actually no stranger to quality, John Davey. John 0:02:13.880 --> 0:02:18.760 is founder, CEO, and CIO of Astoria Portfolio Advisors. John, 0:02:18.800 --> 0:02:20.240 thank you so much for joining us today. 0:02:20.280 --> 0:02:22.000 Great great to be here, guys, thank you for having 0:02:22.000 --> 0:02:22.240 me on. 0:02:23.200 --> 0:02:26.120 So before we get into talking about your investment process, 0:02:26.520 --> 0:02:28.840 Can you tell us more about your start in the 0:02:28.880 --> 0:02:32.560 investment industry and what led you to start Astoria. 0:02:32.720 --> 0:02:37.920 Sure. So I began as a quantitative derivative analyst and 0:02:38.000 --> 0:02:42.200 Merrill Lynch's derivative research group in the late nineties. So 0:02:42.240 --> 0:02:45.560 it was an intern you know, basically spent my first 0:02:45.600 --> 0:02:49.960 ten years kind of doing index level research. Quant research, 0:02:51.080 --> 0:02:54.680 always at the index level, so that included like index 0:02:54.760 --> 0:02:59.080 futures and next options ETFs. You know, got popular in 0:02:59.080 --> 0:03:03.200 the late nineties and so ets were underneath our research group. 0:03:04.480 --> 0:03:07.080 So then did that for ten years, and then I 0:03:07.160 --> 0:03:11.639 became head of Morgan Stanley's ETF content for institutional clients. 0:03:12.280 --> 0:03:16.280 And you know, I had always liked macro research, asset allocation, 0:03:17.120 --> 0:03:19.600 and you know, always wanted to join the buy side 0:03:19.600 --> 0:03:22.000 and be an entrepreneur. So I felt, you know, here 0:03:22.040 --> 0:03:24.040 is a way to kind of do both kill two 0:03:24.040 --> 0:03:27.560 birds one stone, kind of joined the buyside and also 0:03:27.680 --> 0:03:29.200 to you know, be an entrepreneur. 0:03:29.720 --> 0:03:32.280 So let's talk a little more about Astoria. How would 0:03:32.320 --> 0:03:34.880 you describe the Astoria investment philosophy. 0:03:35.320 --> 0:03:39.400 Yeah, so we I would say it's it's a combination 0:03:39.560 --> 0:03:43.720 of there's kind of two verticals, like two business lines. 0:03:43.760 --> 0:03:48.960 One is like quantitative research, and the expression could be 0:03:49.000 --> 0:03:51.600 like an SMA, a quant SMA could be an ETF. 0:03:52.240 --> 0:03:54.880 And then the other business line is kind of multi 0:03:54.920 --> 0:04:01.640 asset ETF investing kind of asset allocation. So really I 0:04:01.640 --> 0:04:05.760 would say it's it's combining active and passive. That's kind 0:04:05.760 --> 0:04:09.360 of what we do, you know, at our firm. I 0:04:09.360 --> 0:04:16.000 would say our ETFs are systematically active. It's very rules based. 0:04:16.440 --> 0:04:20.800 Implementation is active like when we actually rebalance and how 0:04:20.800 --> 0:04:22.960 we trade, and I can spend a lot of time 0:04:23.000 --> 0:04:26.640 talking about that, but it's very kind of rules based, 0:04:27.000 --> 0:04:32.039 quantitative in nature. Our asset allocation is you know, I 0:04:32.040 --> 0:04:35.560 would say the idea there is that we want to 0:04:35.640 --> 0:04:40.240 use the business cycle, use earning valuations, use sentiment in 0:04:40.360 --> 0:04:42.200 order to kind of dictate whether or not we want 0:04:42.240 --> 0:04:44.839 to be ovoid on the way in NASA class, and 0:04:44.880 --> 0:04:46.960 then we use a tiny bit of liquid olts in 0:04:47.040 --> 0:04:49.720 order to kind of hedge our left tail risk. Once 0:04:49.760 --> 0:04:53.080 you hedge your left tail risk, which I know we're 0:04:53.080 --> 0:04:56.479 in a bull market, but we've had many crisises the 0:04:56.560 --> 0:04:59.680 last you know, seven eight years, so that ability to 0:04:59.760 --> 0:05:02.840 kind of of hedge left tail risk, I think is 0:05:02.960 --> 0:05:05.760 quite important and you know, just use like a little 0:05:05.760 --> 0:05:07.760 bit of liquid alts in order to kind of hedge that. 0:05:08.320 --> 0:05:10.839 So that's kind of like our two business lines. One 0:05:10.920 --> 0:05:14.839 is quant sma's ETFs, the other is multi ASCID ETF 0:05:14.880 --> 0:05:16.440 model portfolios. 0:05:16.800 --> 0:05:19.400 Great. So if we want to, you know, focus in 0:05:19.440 --> 0:05:23.680 on the ETF specifically OROE the astoria US equal Weight 0:05:23.800 --> 0:05:27.400 Quality Kings ETF, is there a process you follow to 0:05:27.560 --> 0:05:30.320 narrow down a universe and then select the stocks for 0:05:30.360 --> 0:05:31.080 the portfolio. 0:05:31.920 --> 0:05:35.080 Absolutely, so you know the idea there is that, you know, 0:05:35.160 --> 0:05:37.880 and for background, you know, we all worried about the 0:05:37.880 --> 0:05:40.920 concentration risk and the ND the CES. You know, ten 0:05:40.960 --> 0:05:43.440 stocks make up forty percent of the S and P 0:05:43.560 --> 0:05:48.719 five hundred and we launched are we back in August 0:05:48.880 --> 0:05:51.880 first of twenty twenty three, So and you know it 0:05:51.880 --> 0:05:53.840 takes like, you know, three six months to let's say, 0:05:53.880 --> 0:05:56.440 launch an ETF. So we were worried about concentration risk 0:05:57.000 --> 0:05:59.480 for a while, you know, and we looked at the 0:06:00.080 --> 0:06:03.040 available options out there and we just weren't quite comfortable. 0:06:03.080 --> 0:06:06.000 And I can spend some time talking about what makes 0:06:06.160 --> 0:06:10.479 our equo weight approach different, but essentially it's like a funnel, right, 0:06:10.560 --> 0:06:14.320 we start with like ten thousand stocks, we filter out, 0:06:14.360 --> 0:06:18.560 set out, we picked you know, large liquid you know, 0:06:18.680 --> 0:06:23.080 minimum free float, minimum market cap weights. Then we come 0:06:23.160 --> 0:06:26.480 up with like eight hundred investible stocks. And the idea 0:06:27.080 --> 0:06:28.760 with those eight hundred stocks is if we want to 0:06:28.760 --> 0:06:32.200 pick the hundred of you know, let's say the best 0:06:32.279 --> 0:06:36.000 in kind of that eight hundred, And what we do is, 0:06:36.160 --> 0:06:40.120 you know, we look at five different factors, so things 0:06:40.240 --> 0:06:46.400 like quality, valuation, growth, momentum, and dividend. And we want 0:06:46.440 --> 0:06:51.159 to so we'll weight our etf So fifty percent of 0:06:51.160 --> 0:06:55.080 the quant code is allocated to the quality factor, twenty 0:06:55.080 --> 0:06:58.640 percent to the dividend factor, twenty percent to the valuation factor, 0:06:59.200 --> 0:07:02.240 five percent to growth factor, and five percent to the 0:07:02.279 --> 0:07:06.159 momentum factor. And essentially these winds up being like high 0:07:06.279 --> 0:07:11.280 quality companies that are reasonably priced. You know, within each 0:07:11.320 --> 0:07:14.000 one of those five factors, there's like three, four or 0:07:14.120 --> 0:07:19.760 five fundamental ratios that express the factor of view. So 0:07:19.800 --> 0:07:22.840 in the case of like quality, like we're looking at 0:07:22.880 --> 0:07:25.480 companies with ro OE r O A, r O I C, 0:07:27.240 --> 0:07:30.880 dividing could be you know, the sustainability the dividend, the 0:07:30.880 --> 0:07:34.720 dispersion of the dividend. Valuations could be like, you know, 0:07:34.720 --> 0:07:38.040 things like PE price, the sales. The growth factor could 0:07:38.080 --> 0:07:42.440 be things like PEG ratios. The momentum factor could be 0:07:42.440 --> 0:07:45.960 like relative strength indicators and our premise. And you asked 0:07:46.000 --> 0:07:48.720 me before, David, like, what do we fundamentally believe in? 0:07:49.360 --> 0:07:51.760 You know, we definitely think that the more factors you 0:07:51.800 --> 0:07:54.560 can harvest in a portfolio, as long as you harvest 0:07:54.600 --> 0:07:58.280 in a low cost manner and as long as you 0:07:58.320 --> 0:08:02.680 stick with the factors like that historically has been able 0:08:02.720 --> 0:08:05.400 to give you higher risk adjuster returns and kind of 0:08:05.400 --> 0:08:09.800 put you higher up on the fishing frontier. So to summarize, 0:08:09.800 --> 0:08:12.679 you know, start with like ten thousand investable stocks, filter 0:08:12.800 --> 0:08:15.680 down to eight hundred of the ones that are the largest, 0:08:15.720 --> 0:08:19.120 most liquid, you know, good free float, and then pick 0:08:19.160 --> 0:08:22.520 a hundred of that eight hundred that have you know, 0:08:22.640 --> 0:08:26.560 strong roe, strong row, you know, strong quality metrics, that 0:08:26.640 --> 0:08:29.640 paid dividends, that are reasonably priced, that have a little 0:08:29.640 --> 0:08:33.199 bit of growth and momentum characteristics. It's great. 0:08:33.600 --> 0:08:36.640 So let's focus in on quality for a second. What 0:08:36.800 --> 0:08:39.040 is your research shown about the long term value of 0:08:39.160 --> 0:08:40.000 quality stocks. 0:08:40.720 --> 0:08:43.080 Well, I liked what Chris said before. I mean, you know, 0:08:43.640 --> 0:08:48.200 valuing in beta or valuant quality you know definitely have 0:08:48.400 --> 0:08:51.679 very very low negative you know, very low correlations, if 0:08:51.679 --> 0:08:53.960 not negative. Right. So if again, if you believe in 0:08:53.960 --> 0:08:56.760 this concept of like how do I get higher? But 0:08:57.080 --> 0:09:00.640 on the fish frontier, how do I mix factors? You know, 0:09:00.679 --> 0:09:04.160 you're picking a factor quality that you know has pretty 0:09:04.240 --> 0:09:09.720 robust long term characteristics, and especially if you pair that 0:09:09.800 --> 0:09:14.040 with like value or you know, you know small cap 0:09:14.040 --> 0:09:17.080 stocks that that looks very very attractive to us for 0:09:17.240 --> 0:09:19.240 us at the end of the day, Like you know, 0:09:19.360 --> 0:09:23.200 quality are companies that you know are robust, they pay dividends, 0:09:23.240 --> 0:09:26.640 they have good earnings, good ROI. You know ro O, 0:09:26.760 --> 0:09:30.880 I c roa Roe. And you know it's it's this 0:09:31.000 --> 0:09:36.560 concept of like it's persistent, pervasive, robust. It works across sectors, 0:09:36.600 --> 0:09:41.040 across countries, across economic cycles, and you know there is 0:09:41.240 --> 0:09:42.360 historical out performance. 0:09:42.440 --> 0:09:42.560 Right. 0:09:42.600 --> 0:09:46.760 So if you do some farm of French you know analytics, 0:09:46.800 --> 0:09:49.880 you'll see that high quality stocks have beaten low quality 0:09:49.920 --> 0:09:52.480 stocks and being the market you know, over the last 0:09:52.559 --> 0:09:54.880 you know, half a century, if not longer. I think 0:09:54.920 --> 0:09:57.600 their data set goes back to like nineteen sixty three. 0:09:58.520 --> 0:10:01.480 So that's what we're looking for. I mean, these could 0:10:01.480 --> 0:10:06.400 be you know companies that Microsoft, Google, you know Facebook, 0:10:06.440 --> 0:10:08.360 I mean a lot of them tend to be growth now, 0:10:09.480 --> 0:10:13.720 but you know it's brand hold names essentially. So that's 0:10:13.840 --> 0:10:18.000 that's how we think about it, you. 0:10:17.960 --> 0:10:20.000 Know, John, I I talked to a lot of clients 0:10:20.000 --> 0:10:22.480 in my role, and you know, when it comes to 0:10:22.559 --> 0:10:25.920 factor investing, you know, I feel like the standard factors, 0:10:26.000 --> 0:10:28.480 and you know, most people have a very good definition. 0:10:28.800 --> 0:10:32.439 While it might vary somewhat of these factors, right, things 0:10:32.440 --> 0:10:35.679 like value, things like momentum, things like low risk. Right, 0:10:35.720 --> 0:10:37.480 you might have a different look back for your for 0:10:37.520 --> 0:10:40.120 your momentum factor per se, but we all understand what 0:10:40.160 --> 0:10:43.360 momentum is. Quality seems to be the one where people 0:10:43.640 --> 0:10:48.480 have different differing definitions. It typically is a profitability metric. 0:10:48.840 --> 0:10:51.280 And then I've seen other things and you just mentioned 0:10:51.320 --> 0:10:53.360 some of them. But like when you think about a 0:10:53.440 --> 0:10:56.600 quality company, obviously you use profitability metrics like r O 0:10:56.640 --> 0:10:59.920 E r O. I see other than other factors saying 0:11:00.040 --> 0:11:02.360 within the quality bucket, like what other thing like do 0:11:02.440 --> 0:11:05.080 you look at like things like stability of earnings or 0:11:05.360 --> 0:11:08.840 cruels or anything like that when you're when you're kind 0:11:08.840 --> 0:11:10.400 of defining your quality factor. 0:11:11.600 --> 0:11:13.559 Yeah, we do. I mean there's you know, there's about 0:11:13.640 --> 0:11:16.760 five that go within the quality bucket. But you know, 0:11:16.800 --> 0:11:21.520 as I try to emphasize, like our ro O E Tiff, 0:11:21.760 --> 0:11:24.600 not just high quality stocks, like we're picking high quality 0:11:24.600 --> 0:11:29.600 stocks that have you know, attractive valuations, that have good 0:11:29.640 --> 0:11:33.800 dividend pain ability and that all over and then have 0:11:33.840 --> 0:11:36.520 a little bit of growth the momentum too. But yeah, 0:11:36.559 --> 0:11:38.960 I mean in the end though, within the quality bucket 0:11:39.080 --> 0:11:41.440 it is skew towards ro O E, r O I, 0:11:41.520 --> 0:11:44.760 C ro O A. But I think the point that 0:11:44.960 --> 0:11:47.800 I'm trying to articulate and maybe I am, you know, 0:11:47.840 --> 0:11:50.000 I need to do better job. But you know, if 0:11:50.040 --> 0:11:53.120 you have a good return on equity of a good 0:11:53.240 --> 0:11:56.640 return on asset, you know you are doing other things 0:11:56.640 --> 0:11:59.880 well in the company, Like you're issuing dividends, you have 0:12:00.160 --> 0:12:03.640 good free cash flow, you don't use a lot of 0:12:03.679 --> 0:12:09.480 debt to equity. Your leverage ratios are you know, well 0:12:09.720 --> 0:12:14.040 or well allocated. Let's say. So it does at times, 0:12:14.160 --> 0:12:17.600 Chris like feel a little bit fuzzy because I think, 0:12:17.640 --> 0:12:20.520 like values just okay, you're a stock that has a 0:12:20.520 --> 0:12:23.960 broken story and you need to have something to come corrected. 0:12:24.360 --> 0:12:26.760 The sis factor. You know, small cap stock you're just 0:12:26.840 --> 0:12:29.680 you know, very small. You know, momentum is just you know, 0:12:29.760 --> 0:12:33.719 relative strength, you know, very technical factor. So quality kind 0:12:33.760 --> 0:12:39.440 of encapsulates a few other metrics beyond just you know, 0:12:39.840 --> 0:12:42.640 the return on equity, return on assets. You know, some 0:12:43.040 --> 0:12:47.080 index providers and some metail fishers will say, you know, 0:12:47.160 --> 0:12:49.760 debt to equity is a big component of it. Within 0:12:50.520 --> 0:12:53.800 you know, the quality definition. For us, it's not. We 0:12:53.880 --> 0:12:56.800 tend to use more kind of traditional metrics like r 0:12:56.840 --> 0:12:58.719 O A ro OE and r O C. 0:12:59.640 --> 0:13:01.640 Yeah, I totally agree with that. I mean, just based 0:13:01.640 --> 0:13:04.360 on my research. You know, like you said, it's quality 0:13:04.440 --> 0:13:07.240 is sometimes a fuzzy definition. But it seems very clear 0:13:07.280 --> 0:13:10.559 to me that profitability is the most important part of quality. 0:13:10.880 --> 0:13:12.720 And when you when you look at back tests of 0:13:12.760 --> 0:13:16.359 all these different things or crurals or stability of earnings 0:13:16.440 --> 0:13:18.520 or whatever, you know, the r O E, r O 0:13:18.679 --> 0:13:21.200 I C r O A back tests just perform much better. 0:13:21.240 --> 0:13:23.560 And I and you know, I think profitability is really 0:13:24.760 --> 0:13:28.760 the backbone equality in many respects. So another question I 0:13:28.800 --> 0:13:30.480 give from clients all the time, kind of leading you 0:13:30.520 --> 0:13:34.160 to water here. But you know, some some clients that 0:13:34.240 --> 0:13:36.559 might not be a sophisticated in fact or investing. They'll 0:13:36.600 --> 0:13:39.319 say things to me like, well, isn't quality just growth? 0:13:39.640 --> 0:13:41.800 Why don't you just use growth? Why don't why do 0:13:41.880 --> 0:13:46.360 you use quality in addition to growth or quality, you know, 0:13:47.559 --> 0:13:51.240 instead of growth? You know, what would you say that? Like, 0:13:51.280 --> 0:13:53.800 would you say, and you know, would you say, quality 0:13:53.880 --> 0:13:58.000 is like growth? How would you differentiate it? What would 0:13:58.040 --> 0:13:58.840 you say to that question? 0:13:59.320 --> 0:14:04.440 So they're different. We happen to like combining both of them. 0:14:04.880 --> 0:14:07.800 We have an ETF G Triple Q that's kind of 0:14:07.880 --> 0:14:11.240 quality growth stocks. It's like fifty percent, you know, it's 0:14:11.240 --> 0:14:15.120 like half quality half growth. Let's say I would say, 0:14:15.280 --> 0:14:18.040 right now, we're in this kind of unusual period, Chris, 0:14:18.080 --> 0:14:21.760 where a lot of growth companies tend to also be 0:14:21.840 --> 0:14:24.400 in the quality bucket. It wasn't O is the case, 0:14:25.960 --> 0:14:29.600 you know, but because tech stocks have produced such strong 0:14:29.720 --> 0:14:33.520 returns and they have good you know, earnings revisions, they 0:14:33.560 --> 0:14:36.760 have good growth estimates, good PEG ratios, they also happen 0:14:36.840 --> 0:14:39.920 to have like strong ROE strong ro I C strong 0:14:40.000 --> 0:14:44.520 ro A, So they're in both buckets. But like you know, 0:14:44.560 --> 0:14:46.440 we use like these zis. We have like a white 0:14:46.440 --> 0:14:48.800 paper we wrote for our ro O E TF and 0:14:48.840 --> 0:14:52.040 we show them in the paper, like, Okay, what's historically 0:14:52.080 --> 0:14:57.360 the sharp ratio the standard deviation for quality momentum involve 0:14:57.480 --> 0:15:01.080 those size growth market divine il VALU and you see 0:15:01.200 --> 0:15:05.240 quality as the highest sharp ratio and it's got a 0:15:05.280 --> 0:15:09.120 pretty low standing deviation. So the standardiation and this has 0:15:09.160 --> 0:15:11.440 gone back you know, thirty years in MSA and the 0:15:11.520 --> 0:15:14.920 SEAS is about fourteen and a half. The growth factor 0:15:15.080 --> 0:15:18.440 has about seventeen and a half stand deviation, so much 0:15:18.560 --> 0:15:22.440 like almost like three standard deviation points higher. And they 0:15:22.440 --> 0:15:26.320 both have similar kegers. So growth stocks just happen to 0:15:26.440 --> 0:15:30.240 have a lower sharp ratio. But this is like thirty 0:15:30.280 --> 0:15:33.480 years worth of data, right, But I would say technically 0:15:33.560 --> 0:15:37.760 the answer is like they are different. You know, one 0:15:37.880 --> 0:15:42.920 has traditionally like strong roa ROI. You know that's equality, 0:15:42.960 --> 0:15:45.040 and the growth have you know, more like higher peg 0:15:45.160 --> 0:15:48.800 ratios earnings momentum. It's just the only recently in the 0:15:48.880 --> 0:15:51.960 last cycle where I would say there's a lot of 0:15:52.040 --> 0:15:56.400 like mix. You know, stocks are in both quality ETFs 0:15:56.440 --> 0:15:57.800 and the growth ETFs. 0:15:58.120 --> 0:16:01.680 Yeah, I found that same thing, and you know I've 0:16:01.680 --> 0:16:04.120 also found that you know, quality is much better, sharp 0:16:04.200 --> 0:16:07.000 ratio is much better risk adjuster returns, and like you know, 0:16:07.040 --> 0:16:09.720 I've seen that quality slaze profitability. It's definitely not the 0:16:09.800 --> 0:16:12.760 same as something like low risk, but it does overlap 0:16:12.800 --> 0:16:16.040 with like low risk, low beta lovall, you know, you 0:16:16.080 --> 0:16:18.880 typically get similar stocks in there, and that also has 0:16:19.000 --> 0:16:22.240 very strong risk adjuster returns. So the next question I 0:16:22.240 --> 0:16:24.520 wanted to ask you was something that's very interesting and 0:16:24.600 --> 0:16:27.200 something that I again talk to clients all the time about, 0:16:27.280 --> 0:16:31.280 and that is weighting your stocks right like right now. 0:16:31.480 --> 0:16:35.040 Just because of recency bias, it seems like any non 0:16:35.160 --> 0:16:40.160 market cap weight you know, it's it's lagging. You know, 0:16:40.760 --> 0:16:42.760 customers come to me and say, why would you eagually 0:16:42.800 --> 0:16:46.120 wait the stocks? Why would you have any other waiting 0:16:46.120 --> 0:16:48.440 scheme other than market cap waiting, because market cap waiting 0:16:48.480 --> 0:16:51.480 has worked so well very recently, and you know, I 0:16:51.560 --> 0:16:53.400 know that when you go back far in time, that's 0:16:53.480 --> 0:16:55.000 not the case. So I would love to know your 0:16:55.040 --> 0:16:57.560 thought process behind why you weight your stocks how you do, 0:16:58.040 --> 0:17:00.960 and maybe you know, you could dub to into maybe 0:17:00.960 --> 0:17:04.520 some you know, concerns you could potentially have with the 0:17:04.600 --> 0:17:07.320 market cap weighted indices how they're currently constructed. 0:17:07.480 --> 0:17:09.760 I saw my career in two thousand and it was 0:17:09.840 --> 0:17:14.000 basically the Internet bubble erupted, and that was kind of 0:17:14.040 --> 0:17:18.399 like the the you know, the impetus for like Wisden 0:17:18.440 --> 0:17:23.439 Try got popular, Rob Barnett got popular, you know, AQR launch, 0:17:23.520 --> 0:17:25.920 And it was because Marke cap weight indities were flawed 0:17:26.480 --> 0:17:28.760 because you know, they had a lot of these tech companies. 0:17:29.200 --> 0:17:31.879 Some of them were profitable, some of them were not profitable, 0:17:32.280 --> 0:17:35.760 and really smart bait investment, I think became popular because 0:17:35.800 --> 0:17:38.439 the tech bubble and you know, unwinding in two thousand 0:17:38.440 --> 0:17:40.600 and one, two thousand and two, I feel like it's 0:17:40.600 --> 0:17:44.240 the same movie again, although the difference is now is 0:17:44.240 --> 0:17:46.480 that a lot of these companies are actually pretty profitable. 0:17:46.480 --> 0:17:50.760 It's just that they're just gargantuan size. I would say 0:17:51.280 --> 0:17:55.679 we whenever I've done quantitative like stock selection, you know 0:17:56.000 --> 0:17:59.520 here at Astoria or my prior companies, like we always 0:17:59.560 --> 0:18:02.720 generally equally weighted, and it's like a risk mitigation tool. 0:18:03.440 --> 0:18:05.440 You know, the more way you give one stock, the 0:18:05.440 --> 0:18:08.359 more you know risk you take in that one stock. 0:18:09.080 --> 0:18:13.400 You know, obviously now that there's a big passive bubble, 0:18:13.560 --> 0:18:17.080 a ETF bubble, and money keeps pouring into like spy, 0:18:17.359 --> 0:18:22.159 vu IVV and it's like this massive self fulfilling prophecy 0:18:22.240 --> 0:18:25.439 because you know, the cost sore low. It's you know, 0:18:25.480 --> 0:18:28.720 two basis points, three basis points. Whatever it is, it works, 0:18:29.119 --> 0:18:32.199 people buy it, more money comes in, they buy the 0:18:32.240 --> 0:18:35.159 same stocks. So I would say now more than ever. 0:18:36.640 --> 0:18:39.639 You know, it's important to tilt away. And we have 0:18:39.720 --> 0:18:42.080 like these decision trees, like when we run our multi 0:18:42.160 --> 0:18:45.200 asset ETF strategies, like what do you want to tilt 0:18:45.200 --> 0:18:49.680 the way towards? So I'll go that real quick. So basically, okay, 0:18:49.720 --> 0:18:51.320 like you tilted away from our cap. You can choose 0:18:51.320 --> 0:18:55.159 eco weight. That's one you know decision tree. But you 0:18:55.200 --> 0:18:56.879 have to be careful with equal weight because how are 0:18:56.880 --> 0:18:59.000 you equally waiting it? And we could spend like five 0:18:59.000 --> 0:19:02.760 minutes talking about that. Do you want to tell towards value? Okay? 0:19:02.880 --> 0:19:06.440 Value is a factor. That's very tough. It's very fickle. 0:19:06.640 --> 0:19:09.879 It works you know every ten years, maybe two three 0:19:09.960 --> 0:19:13.240 of the ten years work. So that's tough. Small caps, 0:19:13.400 --> 0:19:15.960 that's tough. You need a certain credit cycle, interest rate 0:19:16.000 --> 0:19:18.960 cycle for small caps to work. Then you have international. 0:19:19.359 --> 0:19:21.720 So the point is like, if you have concerns about 0:19:21.720 --> 0:19:25.120 market weighted ind ses, people tend to lean on equal weight. 0:19:25.160 --> 0:19:27.440 You have to be careful with equal weight. I think 0:19:27.520 --> 0:19:30.240 eqal weight you know now has been tough, but like 0:19:30.359 --> 0:19:33.080 over like twenty thirty years, Like you see the equal 0:19:33.080 --> 0:19:36.800 weight tensaple form mark cap it works better out of 0:19:36.840 --> 0:19:39.640 like a recession, so when you cut it up, you'll 0:19:39.640 --> 0:19:42.679 see that. Like when when you're like in this like 0:19:42.880 --> 0:19:46.280 economic slowdown, people buy more market cap weight, which I 0:19:46.320 --> 0:19:49.080 think is kind of this current period that we're in now. 0:19:50.080 --> 0:19:53.359 I sometimes hear people say, wow, small cap EQO weight's 0:19:53.440 --> 0:19:56.040 no longer going to work because companies stay in private. 0:19:56.680 --> 0:19:59.679 But I just think we're in this like really unusual 0:20:00.080 --> 0:20:05.399 bubble of passive indexation ETF flows and mark cap is 0:20:05.440 --> 0:20:08.440 just bid because just money keeps plowing into those products. 0:20:08.880 --> 0:20:12.199 Yep, yep. I found the exact same thing. So what 0:20:12.359 --> 0:20:15.560 about like you know, and I typically stick to equal 0:20:15.560 --> 0:20:17.119 weight as well. I feel like it gets you like 0:20:17.200 --> 0:20:20.040 ninety five percent of the way there. But like sometimes 0:20:20.040 --> 0:20:22.840 customers ask me, well, what about a more complicated scheme, 0:20:22.920 --> 0:20:25.679 Like what about some kind of inverse polatility waiting like 0:20:25.800 --> 0:20:29.320 Ray Dalio style, or like risk parity or maybe even 0:20:29.480 --> 0:20:33.800 more like me invariance optimization type waiting scheme, Like do 0:20:33.840 --> 0:20:37.280 you find any value in those overly complicated ones or 0:20:37.280 --> 0:20:39.840 do you think that's kind of adding more degrees of 0:20:39.880 --> 0:20:43.119 freedom to a model which is you know, generally bad. 0:20:44.280 --> 0:20:46.439 I mean to be honest, Like it gets such a 0:20:46.480 --> 0:20:49.760 bad name, you know, smart beta. But this idea of 0:20:49.800 --> 0:20:53.119 like weighting based on like quant metrics, like the higher 0:20:53.160 --> 0:20:55.760 the quant rank in, the more way you give, Like 0:20:55.800 --> 0:20:58.439 we have some strategies where we do that. That to 0:20:58.480 --> 0:21:02.359 me makes sense and as like easier to explain if 0:21:02.359 --> 0:21:05.239 you deal with institutional investors, totally get it, you know, 0:21:05.400 --> 0:21:09.320 mean variance optimization inverse volatility, Like I think you can 0:21:09.359 --> 0:21:11.600 do that and get away with it. But in the 0:21:11.720 --> 0:21:14.639 financial advisor world that I live in, our world, like 0:21:15.119 --> 0:21:18.959 equal weight is enough tracking error versus the benchmark that 0:21:19.440 --> 0:21:21.399 and it's easy to explain. I think you just have 0:21:21.440 --> 0:21:24.879 to be careful with equally weight and like when you 0:21:24.960 --> 0:21:27.480 equally wait, you know, let's say the Russell one thousand 0:21:27.640 --> 0:21:30.800 index now you're talking about each stock is like thirteen 0:21:30.880 --> 0:21:35.280 bip weight. Let's say twelve bip weight. That's tough. If 0:21:35.280 --> 0:21:37.240 you equal wait s and P five hundred each stock 0:21:37.320 --> 0:21:40.080 is twenty BIPs. Wait, we just like the reason why 0:21:40.119 --> 0:21:42.439 we launched o OEI was because we weren't comfortable with 0:21:42.600 --> 0:21:47.199 SMP equal way to DTF because a, you know, there 0:21:47.240 --> 0:21:50.679 was only fifteen percent technology exposure, so we wanted to 0:21:50.720 --> 0:21:54.160 kind of optimize our ro oe E TF to match 0:21:54.200 --> 0:21:56.720 the S and P sector weight. So and then we 0:21:56.800 --> 0:21:59.960 pick only one hundred stocks. So now your marginal contribution 0:22:00.040 --> 0:22:02.880 and to risk and return is a lot higher when 0:22:02.880 --> 0:22:05.639 you once you equally weight one hundred stocks compared to 0:22:05.720 --> 0:22:08.479 like five hundred or thousand. And the other real extreme 0:22:08.520 --> 0:22:11.400 example is I put out a report called ten ETFs 0:22:11.520 --> 0:22:14.720 for twenty twenty five, and I put in there this 0:22:15.080 --> 0:22:18.119 xn tk ETF. It's an equal weighted tech ETF from 0:22:18.160 --> 0:22:22.120 Spiders and it's actually been the cues over the last 0:22:22.160 --> 0:22:24.640 three years. When we launched a report, and some people 0:22:24.680 --> 0:22:27.880 were surprised, but you know, it's got thirty five stocks. 0:22:27.920 --> 0:22:30.480 Each stock is three percent weight. And then it's not 0:22:30.560 --> 0:22:34.560