WEBVTT - Morgan Stanley’s Rogers on Consistent Growth 0:00:14.400 --> 0:00:17.320 Welcome to Inside Active, a podcast about active managers that 0:00:17.400 --> 0:00:19.840 goes beyond sound bites and headlines and looks deeper into 0:00:19.880 --> 0:00:24.560 the processes, challenges, and philosophies and security selection. I'm David cone, I, 0:00:24.600 --> 0:00:27.840 lead mutual fund and active Research at Bloomberg Intelligence. Over 0:00:27.880 --> 0:00:31.280 the past decade, growth investing has gone through several very 0:00:31.320 --> 0:00:34.400 key different market environments. We've seen periods where a handful 0:00:34.440 --> 0:00:39.000 of megacap companies have dominated returns, dramatic shifts and interest rates, 0:00:39.080 --> 0:00:42.440 the rise of passive investing, and more recently, the emergence 0:00:42.479 --> 0:00:46.440 of artificial intelligence as a major investment theme. In an 0:00:46.560 --> 0:00:49.479 environment like this, generating returns as an active growth manager 0:00:49.520 --> 0:00:53.400 requires more than simply identifying growth companies. Requires a repeatable 0:00:53.440 --> 0:00:58.480 process for evaluating business quality, assessing valuation, managing risk, and 0:00:58.560 --> 0:01:02.080 maintaining conviction through changing market conditions. So today I wanted 0:01:02.120 --> 0:01:05.559 to explore how a discipline growth investor translates research into 0:01:05.600 --> 0:01:10.199 portfolio decisions. From sourcing ideas and building conviction to managing risk, 0:01:10.520 --> 0:01:14.200 testing assumptions I'm determining when to buy, hold or sell. 0:01:14.640 --> 0:01:17.480 Join me to discuss that is. Doug Rogers, Managing director 0:01:17.480 --> 0:01:20.160 of Morgan Stanley and a portfolio manager of the EAT 0:01:20.160 --> 0:01:23.440 Advanced Core Growth Team, including the EAT Advanced Growth Fund 0:01:23.520 --> 0:01:27.520 ticker el ci X and the Advanced Focus Growth Opportunities 0:01:27.520 --> 0:01:31.120 Fund ticker eif g X. Doug, thanks for joining me today. 0:01:31.840 --> 0:01:33.679 Thank you, David. It's excited to be here. 0:01:34.360 --> 0:01:37.480 So to start, how about at a high level, how 0:01:37.480 --> 0:01:40.399 would you describe your investment philosophy today? And you know 0:01:40.400 --> 0:01:43.040 what beliefs about the markets of businesses are most central 0:01:43.040 --> 0:01:43.959 to the way you invest. 0:01:44.920 --> 0:01:48.400 Sure At eaton Vance, we define growth maybe a little 0:01:48.440 --> 0:01:51.840 bit differently than a lot of other firms or other 0:01:51.920 --> 0:01:54.640 mutual funds may do. So one way that we look 0:01:54.680 --> 0:01:57.560 at growth is just the consistency of growth. So we're 0:01:57.640 --> 0:02:01.760 less concerned about the appst growth rate. There's plenty of 0:02:01.760 --> 0:02:05.200 companies out there that might do, you know, twenty thirty 0:02:05.200 --> 0:02:07.720 percent growth one year, negative five the next year, and 0:02:08.480 --> 0:02:12.280 you know over time average compound growth rate of five 0:02:12.360 --> 0:02:15.959 or ten percent. We're really looking for those growth companies 0:02:16.000 --> 0:02:19.680 that can deliver growth consistently year in year out, a 0:02:19.680 --> 0:02:23.840 little less concerned about the the overall growth rate. Although 0:02:23.880 --> 0:02:26.519 we do tend to focus on companies that can deliver 0:02:27.480 --> 0:02:31.720 you know, revenue growth in excess of five to ten percent. 0:02:32.360 --> 0:02:35.960 In fact, if you look at you if you look 0:02:36.080 --> 0:02:38.880 back historically at companies that have been able to do so, 0:02:38.919 --> 0:02:41.680 they tend to outperform the market. We looked at Russell 0:02:41.760 --> 0:02:46.880 one thousand index constituents that survived a decade in the index, 0:02:47.600 --> 0:02:50.560 and we looked at companies that I divide into three groups, 0:02:50.919 --> 0:02:54.000 the first being companies that failed to deliver a five 0:02:54.000 --> 0:02:57.480 percent cager over that decade, the second being companies that 0:02:57.880 --> 0:03:01.840 delivered a five percent cager, and then the third companies 0:03:01.840 --> 0:03:05.720 that delivered a five percent growth rate each and every 0:03:05.760 --> 0:03:08.560 year of those ten years, So ten consistent years of 0:03:08.600 --> 0:03:11.079 five percent growth. It turns out that forty five to 0:03:11.080 --> 0:03:15.040 fifty percent fall in each of the first two categories, 0:03:15.080 --> 0:03:17.800 only about five percent fall in that third category of 0:03:17.880 --> 0:03:21.400 five percent each and every year. And those those stocks 0:03:21.440 --> 0:03:24.400 on an annualized return basis have tended to outperform the 0:03:24.400 --> 0:03:28.799 others my seven, eight nine percent, depending on the year, 0:03:28.919 --> 0:03:32.200 fairly consistently. So that's really what we target is those 0:03:32.280 --> 0:03:36.920 sustainable compound growers, and I think it makes our job 0:03:36.960 --> 0:03:40.440 a little bit easier just you know, targeting that's there's 0:03:40.640 --> 0:03:43.880 less volatility in some of their returns. But also makes 0:03:43.880 --> 0:03:46.160 it a little bit more difficult. And it's really key 0:03:46.200 --> 0:03:50.360 to find those companies early on those in those growth rates, 0:03:50.360 --> 0:03:52.800 and there's key attributes that we look at to determine that. 0:03:53.600 --> 0:03:56.040 Look, can you walk us through what your investment process 0:03:56.080 --> 0:03:58.560 looks like, you know, the life cycle of an investment 0:03:58.640 --> 0:04:01.680 idea on your team, how ideas get sourced research and 0:04:01.840 --> 0:04:03.280 ultimately added to the portfolio. 0:04:04.040 --> 0:04:07.720 Sure, there's there's some great academic research on some of 0:04:07.760 --> 0:04:11.320 the things that I just just described. Others i'd encourage 0:04:11.360 --> 0:04:15.720 your listeners to look up Professor Rita McGrath. She's a 0:04:15.760 --> 0:04:19.640 former Columbia Business School professor. There's Professor Amy Eminson who 0:04:19.680 --> 0:04:22.000 I had the honor of studying under at Harvard Business 0:04:22.000 --> 0:04:24.520 School as well. They've done a lot of research in 0:04:24.640 --> 0:04:27.160 terms of, you know, what makes these companies good and 0:04:27.400 --> 0:04:32.239 and grow and find inflection points and organize themselves for growth. 0:04:32.560 --> 0:04:38.640 So two recommendations there, and we have done our own 0:04:38.680 --> 0:04:41.120 research too in terms of, you know, looking at the 0:04:41.200 --> 0:04:44.120 attributes of those those companies. So we're looking for companies 0:04:44.160 --> 0:04:46.440 the keyword that I draw out is innovation, and so 0:04:46.560 --> 0:04:49.640 that's really what our investment process centers around. We're looking 0:04:49.640 --> 0:04:52.520 for companies that continue to evolve over time, they catch 0:04:52.560 --> 0:04:57.679 those inflection points, they continue to develop their business model, 0:04:57.839 --> 0:05:01.520 change their business model and grow into into that next 0:05:01.680 --> 0:05:04.480 level of the of the curve, just additive curve after 0:05:04.560 --> 0:05:08.800 additive curve UH to to find their growth. We certainly 0:05:08.880 --> 0:05:11.480 do what I would consider table stakes investing, where we 0:05:11.920 --> 0:05:16.279 are table stakes research, where we look at the financial 0:05:16.520 --> 0:05:20.560 UH financials of the companies. We develop our own internal models, 0:05:20.600 --> 0:05:23.680 financial forecast. You know, I think that's the basics of 0:05:23.720 --> 0:05:25.720 investing needs to be done and you need to get 0:05:25.760 --> 0:05:29.720 that directionally accurate for sure. We also spend a lot 0:05:29.760 --> 0:05:35.120 of time just discussing the strategy of of the company 0:05:35.200 --> 0:05:37.880 and and the overall end market and the growth of 0:05:37.920 --> 0:05:41.839 that mark and how that company can can participate. But 0:05:41.920 --> 0:05:45.520 I think the real UH success of our of our 0:05:45.560 --> 0:05:47.960 team comes down to the debate that we have around 0:05:47.960 --> 0:05:51.640 different securities. So we've been able to construct our team 0:05:51.640 --> 0:05:54.760 where we have some very different personalities in our in 0:05:54.839 --> 0:05:58.480 our analysts team, which really work well together to generate 0:05:58.640 --> 0:06:02.520 a strong debate OFT from a lot of different backgrounds 0:06:02.960 --> 0:06:06.480 in the industry and outside of the industry as well. 0:06:06.920 --> 0:06:09.000 And really when it comes down to it, we we 0:06:09.040 --> 0:06:12.200 do all that background research, We interview company teams, we 0:06:12.200 --> 0:06:14.480 get a sense for the strength of the management team, 0:06:14.520 --> 0:06:17.120 the strength of the strategy, and then we UH we 0:06:17.440 --> 0:06:22.159 debate those ideas vigorously UH to include or exclude them 0:06:22.520 --> 0:06:27.360 from our portfolio. We have a system we use we 0:06:27.400 --> 0:06:30.640 call them portfolio exercises, that we use to combat inherent 0:06:30.680 --> 0:06:33.839 biases in the in the investment process. So sometimes you 0:06:33.920 --> 0:06:37.080 just get a little too comfortable owning as owning a stock, 0:06:37.160 --> 0:06:39.960 or you get complacent in owning a stock. So we'll 0:06:40.040 --> 0:06:43.200 generate ideas through these portfolio exercises. One might be a 0:06:43.279 --> 0:06:47.320 designated bull or bear, so we'll designate sometimes the individual 0:06:47.400 --> 0:06:50.520 it's most bullish on a company will will make him 0:06:50.640 --> 0:06:54.320 or her the bear and the opposite and h and 0:06:54.360 --> 0:06:57.880 then we'll just engage in debate over over the investment 0:06:57.920 --> 0:07:01.480 thesis and and explore and robe where we could be 0:07:01.560 --> 0:07:04.960 stronger or weaker on on either side. And so it's 0:07:05.000 --> 0:07:08.960 really that debate that leads to to inclusion or or 0:07:09.120 --> 0:07:14.400 removal of a stock from from our portfolio. And that's 0:07:14.440 --> 0:07:17.880 with every company, With every company that that we put 0:07:17.920 --> 0:07:20.760 in or out of the portfolio, we really we really debate, 0:07:20.840 --> 0:07:23.600 We try not to you know, just make make bets 0:07:23.640 --> 0:07:26.960 on on physicians for so called exposure to to an 0:07:27.000 --> 0:07:30.600 area or or or not. Really, you know, you only 0:07:30.640 --> 0:07:34.200 have limiteds base. Our our focus fund typically has twenty 0:07:34.240 --> 0:07:37.200 five to thirty names or diversified fund, we like to 0:07:37.240 --> 0:07:40.600 have around sixty names in that. So each and every uh, 0:07:40.760 --> 0:07:43.360 you know, basis point of capital that we deploy is 0:07:43.400 --> 0:07:47.160 precious in our eyes, and so we really like to 0:07:47.200 --> 0:07:51.280 make sure that each basis point is is really tested 0:07:51.880 --> 0:07:56.240 and and and put to its best use. So that 0:07:56.320 --> 0:07:56.920 kind of brings me in. 0:07:56.960 --> 0:07:59.760 My next question is, you know your background is unusually analytical, 0:08:00.080 --> 0:08:03.600 some engineering, the Navy, CFA, c MT. How has that 0:08:03.720 --> 0:08:06.520 kind of shaped your process in even your risk framework. 0:08:07.480 --> 0:08:10.920 Yes, so much of what I used today is rooted 0:08:10.960 --> 0:08:13.559 in those early years of my career. As you mentioned, 0:08:13.560 --> 0:08:16.760 I was an engineering major. Actually it's what we called 0:08:16.880 --> 0:08:19.080 robotics back in the day, So perhaps they should have 0:08:19.840 --> 0:08:22.000 stuck with that as a I was. I was early 0:08:22.080 --> 0:08:25.400 in that career. And then perhaps most impactful was my 0:08:25.440 --> 0:08:28.320 time in the Navy. I was graduated from the Naval Academy, 0:08:28.920 --> 0:08:32.880 went directly into the nuclear pipeline and then ended up 0:08:32.920 --> 0:08:35.080 on a on a submarine where I spent just over 0:08:35.120 --> 0:08:38.280 four years on that submarine, and so many things that 0:08:38.320 --> 0:08:42.480 I use today and investing, although it seems like it's unrelated, 0:08:42.520 --> 0:08:44.480 a lot of the behaviors, a lot of the UH, 0:08:44.520 --> 0:08:47.400 the analytical approach that I use or rooted in that 0:08:48.440 --> 0:08:50.079 in the in the in the Navy, there was I 0:08:50.080 --> 0:08:52.400 guess there's two big lessons that I that I would 0:08:52.400 --> 0:08:55.720 take away. One was I had a great cat and 0:08:55.760 --> 0:09:01.199 Catain Nustyed still a mentor to this day who really 0:09:01.240 --> 0:09:04.160 taught us don't take unnecessary risk, right, you need to 0:09:04.160 --> 0:09:08.720 take risks in this business, in in the Navy to 0:09:08.400 --> 0:09:12.040 h to be successful, to generate alpha, to generate a 0:09:12.080 --> 0:09:15.080 good outcome in your in your naval mission. But you 0:09:15.160 --> 0:09:17.120 just want to understand those risks. You want to understand 0:09:17.120 --> 0:09:20.480 what risks that you are that you're taking. And the 0:09:20.520 --> 0:09:24.040 other is you're never going to have complete information, especially 0:09:24.080 --> 0:09:27.080 on the submarine we were UH, we were limited to 0:09:27.160 --> 0:09:30.400 our sonar. It would been great sometimes to use active 0:09:30.440 --> 0:09:33.280 sonar to find out exactly what was ahead or exactly 0:09:33.320 --> 0:09:35.600 the range to to something that we're trying to find, 0:09:35.640 --> 0:09:37.559 but in order to do that we would have to 0:09:37.600 --> 0:09:40.079 sacrifice our position which of course we didn't want to 0:09:40.480 --> 0:09:45.760 let up, so so you always had incomplete information. And 0:09:45.840 --> 0:09:48.920 so the skill is knowing when you have enough to 0:09:49.000 --> 0:09:52.960 take action and and that's uh, there's no magic number. 0:09:53.000 --> 0:09:55.040 I can't say over eighty percent of the way there, 0:09:55.120 --> 0:09:58.240 let's uh, let's move. But but it's just a skill 0:09:58.280 --> 0:10:00.760 that you develop over time to understand. And Okay, I 0:10:00.800 --> 0:10:03.400 think we have enough here to have confidence to make 0:10:03.440 --> 0:10:07.280 this a position. Sometimes more information becomes available and its 0:10:07.280 --> 0:10:10.680 strengthens your conviction. Sometimes the opposite happens. You find out 0:10:10.720 --> 0:10:12.800 more and and it pokes a hole in your thesis 0:10:12.840 --> 0:10:16.240 and you may want to reevaluate your your your choices there. 0:10:16.559 --> 0:10:19.000 So you know, I think that background has really shaped 0:10:19.080 --> 0:10:21.560 a lot of the processes that we use today on 0:10:21.600 --> 0:10:26.160 our team. Uh and and really help over the long 0:10:26.320 --> 0:10:27.800 term as an investor. 0:10:28.720 --> 0:10:31.120 Okay, you know, if we go back to your process 0:10:31.120 --> 0:10:33.280 a little bit, how much would you say is fundamentally 0:10:33.360 --> 0:10:36.040 qualitative versus you know, quantitatively driven. 0:10:36.679 --> 0:10:41.720 Sure, we're definitely a fundamentally driven team. That's where where 0:10:41.880 --> 0:10:45.160 we're rooted. You know, I'd say the quantitative aspect comes 0:10:45.200 --> 0:10:47.080 in a little bit on risk management, and we can 0:10:47.080 --> 0:10:50.319 certainly discuss that you know, if you'd like. But we're 0:10:50.400 --> 0:10:54.280 really rooted in in in bottom up fundamental research. I 0:10:54.320 --> 0:10:57.040 think that's what we all enjoy doing. I think you know, 0:10:57.080 --> 0:10:59.640 when you talk to many so called stock pickers, I 0:10:59.640 --> 0:11:02.120 think that that's what they enjoy doing too. Learning about 0:11:02.240 --> 0:11:05.360 an industry, learning about a stock, learning about the company's 0:11:05.400 --> 0:11:10.160 position within that industry, the drivers, you know, things like that. 0:11:10.559 --> 0:11:15.200 So we really rely on on fundamentally. We do use 0:11:15.440 --> 0:11:19.160 risk management as it comes down to our position sizing. 0:11:19.280 --> 0:11:22.440 I as the portfolio manager, you ultimately make the call 0:11:22.920 --> 0:11:25.000 on the on the position size, with a lot of 0:11:25.000 --> 0:11:29.760 input from our analysts as well. You can you get 0:11:29.960 --> 0:11:31.959 a good sense from the analysts in terms of their 0:11:32.000 --> 0:11:35.920 conviction on ideas and as the team you know, debates it, 0:11:36.320 --> 0:11:38.800 you know the risk and reward that we're taking. We 0:11:38.880 --> 0:11:41.560 use something called weighted price potential where we look at 0:11:41.640 --> 0:11:44.400 the bowl, the bear and the base case on stocks. 0:11:44.520 --> 0:11:48.320 So that helps us to to measure our upside, our downside, 0:11:48.320 --> 0:11:52.600 our risk reward potential and h and and help judge 0:11:52.679 --> 0:11:56.320 just you know, how convicted we are in that in 0:11:56.400 --> 0:12:00.000 that idea. And then where the quantitative does come in. 0:12:00.080 --> 0:12:02.720 It's a bit more on the risk management side. We 0:12:02.800 --> 0:12:05.240 have an entire risk management team that we that we 0:12:05.320 --> 0:12:08.080 work with to help us judge where we're taking those risks. 0:12:08.080 --> 0:12:11.120 I mentioned earlier that you know, we need to take 0:12:11.200 --> 0:12:13.079 risks in the portfolio. We just want to make sure 0:12:13.160 --> 0:12:15.360 that we understand what risk we're taking. You know, are 0:12:15.360 --> 0:12:19.320 we are too tied to a factor, too untied to 0:12:19.760 --> 0:12:25.680 a factor? I know in prior podcast you've interviewed a colleague, 0:12:25.679 --> 0:12:28.680 guy Andrew Slimmon as well, who does a lot with 0:12:28.679 --> 0:12:31.640 with with factor work. We don't get as involved as 0:12:31.679 --> 0:12:35.760 Andrew does, but we uh uh we we we you know, 0:12:35.800 --> 0:12:38.480 definitely pay attention to those to make sure that we're 0:12:38.480 --> 0:12:43.800 not taking unnecessary risk by not having exposure to certain 0:12:43.840 --> 0:12:46.800 factors that we you know, believe may may have an input. 0:12:46.920 --> 0:12:49.480 And we really use that to help us determine position 0:12:49.640 --> 0:12:52.280 sizing more than more than anything. 0:12:51.920 --> 0:12:55.000 Else, you know, when you're making a new investment, what 0:12:55.040 --> 0:12:58.280 are the key assumptions you absolutely have to be right about. 0:12:59.240 --> 0:13:03.080 It's always always a great question, and it's really like 0:13:03.360 --> 0:13:06.040 we really try to stick to our knitting on this 0:13:06.200 --> 0:13:08.560 on this framework and trying to find you know, good 0:13:08.640 --> 0:13:11.880 companies that continue to grow and so we test those 0:13:12.000 --> 0:13:14.760 those assumptions sometimes a lot of people and you know, 0:13:14.760 --> 0:13:17.360 i'd say this is something I did certainly in my 0:13:17.440 --> 0:13:21.120 younger years. In the career, you really get involved in 0:13:21.160 --> 0:13:23.240 your model, in your financial model, and you have to 0:13:23.240 --> 0:13:26.800 do that because your model helps you to test different assumptions. 0:13:26.800 --> 0:13:28.320 You can go through, well, what if they add one 0:13:28.400 --> 0:13:31.199 hundred basis points to to to margins or one hundred 0:13:31.960 --> 0:13:35.400 one percent of margins. What if what if the tax 0:13:35.440 --> 0:13:37.959 rate goes up, or this revenue growth of this lower 0:13:38.000 --> 0:13:41.800 margin segment increases or decreases, mix shift. It really helps 0:13:41.840 --> 0:13:44.800 you to understand that. But at the same time, you 0:13:44.840 --> 0:13:47.400 know you have to be directionally right on a lot 0:13:47.400 --> 0:13:50.440 of different factors. Sometimes you're just in a good market. 0:13:50.880 --> 0:13:54.280 You know, look at look at the megacap stocks and 0:13:54.320 --> 0:13:57.679 the AI influence on a lot of different names in 0:13:57.720 --> 0:14:01.559 that space. There there is a such thing, I guess 0:14:01.559 --> 0:14:05.440 maybe my navy analogy, the rising tide. You know, analogy 0:14:05.559 --> 0:14:08.160 certainly can lift all boats there. And so you know, 0:14:08.200 --> 0:14:10.000 if you've done the work not just on the company, 0:14:10.040 --> 0:14:13.600 but on the industry and sector, then hopefully it can 0:14:13.640 --> 0:14:18.280 help you to identify certain key points. I'd say, one 0:14:18.400 --> 0:14:21.800 common thing that we really look for is potential inflection points. 0:14:22.360 --> 0:14:25.840 You know, the the impact of AI would certainly be 0:14:25.960 --> 0:14:28.160 one of one of those. I think it's something we 0:14:28.160 --> 0:14:33.120 were fortunate enough to identify early, the impact that could 0:14:33.120 --> 0:14:37.160 have not only on spending that it was going to take, 0:14:37.240 --> 0:14:40.600 but who would be the beneficiaries of that spending and 0:14:40.640 --> 0:14:43.240 also on the cost side, you know, where where companies 0:14:43.280 --> 0:14:46.280 could take out costs, you know from AI. So we're 0:14:46.280 --> 0:14:49.960 looking at it from a revenue driver, from a cost saver, 0:14:50.440 --> 0:14:53.960 and just from capital expenses and one firm's cap x 0:14:54.040 --> 0:14:57.280 is another firm's revenues, so you know, trying to identify 0:14:57.360 --> 0:15:00.560 the linkages there. So we're really looking for those I 0:15:00.600 --> 0:15:03.720 mentioned inflection points earlier. So are there are there any 0:15:03.760 --> 0:15:07.240 sort of wholesale shifts where where an entire industry or 0:15:07.680 --> 0:15:12.280 sector could really shift based on on a bigger picture 0:15:12.520 --> 0:15:17.040 or market driving theme. So we're keen to identify those. 0:15:17.920 --> 0:15:20.320 Are there any assumptions you can afford to be wrong about? 0:15:22.440 --> 0:15:27.640 We try to minimize those for I'm sorry question just kiddus. 0:15:27.680 --> 0:15:30.080 Yeah, no, you know, I think some of those as 0:15:30.120 --> 0:15:32.800 long as you get them, you know directionally right there 0:15:32.840 --> 0:15:36.280 there are some things that that you can be off 0:15:36.360 --> 0:15:39.560 by by a little bit, just because those errors are 0:15:39.600 --> 0:15:45.120 overwhelmed by the by the the broader strength. Right, So 0:15:45.360 --> 0:15:48.320 you might have somebody that's you know, very strong and 0:15:48.560 --> 0:15:51.600 nine out of ten events and the catalon and and 0:15:51.600 --> 0:15:54.920 and you hope that that the strength there overshadows maybe 0:15:54.920 --> 0:15:58.440 they're inability to uh uh, you know, to do the 0:15:58.480 --> 0:16:00.840 high jump, you know, in the into the caf on. 0:16:01.200 --> 0:16:04.920 So you know, we're we're we're hopeful that that focusing 0:16:04.960 --> 0:16:08.080 on the on the bigger drivers allows you to to 0:16:08.240 --> 0:16:10.600 maybe have a little bit of flexibility. I think some 0:16:10.640 --> 0:16:12.920 of the things that you can test with the and 0:16:13.080 --> 0:16:16.120 the our approach on those factors is just to do 0:16:16.240 --> 0:16:19.360 some sensitivity analysis around things that we're less certain about. 0:16:19.760 --> 0:16:22.200 So if you look at you know, if you if 0:16:22.200 --> 0:16:24.920 you look at something where you have the least amount 0:16:24.960 --> 0:16:27.440 of certainty, the least amount of conviction, maybe it's that 0:16:27.520 --> 0:16:29.840 data point that you just can't find, uh, you know, 0:16:29.880 --> 0:16:32.520 the answer to or you know you have you have 0:16:34.240 --> 0:16:37.960 three unknowns and and two two equations you know to 0:16:37.960 --> 0:16:39.400 to figure it out, so you just can't get the 0:16:39.480 --> 0:16:42.880 right answer. Uh, then what we'll do is we'll just 0:16:42.880 --> 0:16:46.600 do some sensitivity testing around that. So what if what 0:16:46.640 --> 0:16:49.520 if this bullish scenario comes to fruition, what if this 0:16:49.640 --> 0:16:53.000 barrier bearish scenario comes to fruition, and really test how 0:16:53.040 --> 0:16:56.480 impactful that can be. If it's something that that even 0:16:56.560 --> 0:16:59.920 in the most bearish case, it really doesn't add considered 0:17:00.240 --> 0:17:02.200 to the risk that you're taking in the stock, then 0:17:02.240 --> 0:17:04.680 we can approach that with higher conviction. If it's something 0:17:04.720 --> 0:17:08.680 where it's a bigger driver than perhaps we anticipated, then 0:17:08.920 --> 0:17:12.239 you know, I think that'll result in lower conviction. Uh 0:17:12.720 --> 0:17:16.200 you know, maybe that influences the position size, or maybe 0:17:16.200 --> 0:17:19.520 we just start looking for a different opportunity altogether. 0:17:20.240 --> 0:17:22.159 And you mentioned testing, I mean, what does that actually 0:17:22.200 --> 0:17:24.719 look like? You know, what exactly are you doing when 0:17:24.760 --> 0:17:27.320 you're testing something portfolio testing. 0:17:27.760 --> 0:17:30.040 Core just I mean on the on the stock level, 0:17:30.119 --> 0:17:33.920 we're taking that down to you're just looking at it 0:17:33.960 --> 0:17:35.880 at a certain thing. Maybe it's a revenue growth rate, 0:17:35.920 --> 0:17:38.520 maybe it's a new product, and how successful it can 0:17:38.640 --> 0:17:41.600 it can be, how much it can contribute to revenues. 0:17:41.600 --> 0:17:44.399 It might be a mix shift, so if a certain 0:17:44.440 --> 0:17:48.359 high margin product is growing faster than the lower margin product, 0:17:48.440 --> 0:17:50.760 you know what, we'll test that to see how high 0:17:50.800 --> 0:17:52.879 it can go, how successful does it have to be 0:17:53.359 --> 0:17:56.000 maybe it's a newly acquired product through M and A. 0:17:56.359 --> 0:17:58.520 You know, we'll look and we'll do sensitivity in terms 0:17:58.520 --> 0:18:02.639 of the cost savings that they might get through synergies 0:18:02.760 --> 0:18:06.800 or or you know, through just revenue enhancement from that 0:18:06.880 --> 0:18:10.560 new product, maybe running it through a more developed salesforce 0:18:11.359 --> 0:18:14.040 as well. So we'll look at a lot of different sensitivities. 0:18:14.040 --> 0:18:18.240 There's a lot of just financial modeling, scenario analysis to 0:18:18.800 --> 0:18:22.800 determine you know, the potential upside and downside on the 0:18:22.840 --> 0:18:26.359 portfolio level. You know, we'll we'll we'll look evill test. 0:18:26.400 --> 0:18:29.280 I mentioned risk management earlier, so we'll look just to 0:18:29.280 --> 0:18:33.879 see where we have different uh intended or unintended exposures. 0:18:33.920 --> 0:18:37.200 Maybe it's something it relates to the interest rates or 0:18:37.320 --> 0:18:40.520 the price of oil, or you know, something you know 0:18:40.560 --> 0:18:43.720 related to AI spend or things like that. We can 0:18:44.000 --> 0:18:47.119 we can do testing. We use a program called Bara 0:18:47.240 --> 0:18:49.520 to do to do a lot of testing, and we 0:18:49.640 --> 0:18:52.919 have our own our risk management software as well that 0:18:52.960 --> 0:18:56.440 we look and measure to see if one company owning 0:18:56.480 --> 0:19:00.640 it or not owning it, is contributing an outside an 0:19:00.680 --> 0:19:04.720 outsized level of risk to the portfolio. And so you know, 0:19:04.800 --> 0:19:08.880 if If that's the case, then we'll try to minimize 0:19:09.480 --> 0:19:11.800 that risk and we can test to see, Okay, well, 0:19:11.800 --> 0:19:14.480 what if we take that position size of fifty bits, 0:19:14.520 --> 0:19:17.159 what does that do to a certain risk factor or 0:19:17.160 --> 0:19:19.480 what does it do to you know, our exposure to 0:19:19.520 --> 0:19:22.040 interest rates things like that. So you're we're able to 0:19:22.440 --> 0:19:25.959 run different scenarios without actually trading the portfolio, generating gains, 0:19:26.200 --> 0:19:29.919 trading costs, etc. We're able to simulate that, of course, 0:19:30.280 --> 0:19:32.760 to see what the best move in the portfolio might be. 0:19:33.359 --> 0:19:36.399 Okay, you know, if you look back at your best 0:19:36.480 --> 0:19:40.160 long term investments, you know, I know you're obviously looking 0:19:40.200 --> 0:19:43.000 for consistent growth, but is there any patterns or characteristics 0:19:43.040 --> 0:19:44.679 that kind of show up again and again when you 0:19:44.680 --> 0:19:46.920 think of your best long term investments. 0:19:47.440 --> 0:19:50.800 Yes, so you know, we are long term investors. Our 0:19:50.880 --> 0:19:54.040 portfolio turnover is generally maybe a little bit on the 0:19:54.080 --> 0:19:56.879 lower side for a typical growth portfolio. We tend to 0:19:56.880 --> 0:19:59.239 be in the twenty to thirty percent growth range, so 0:19:59.400 --> 0:20:02.399 or turnover, so we're really looking you know, for that 0:20:02.400 --> 0:20:06.119 that that longer three to five year holding would would 0:20:06.119 --> 0:20:08.280 be great. I think it was Warren Buffett that said 0:20:08.280 --> 0:20:10.200 something along the lines of you know, the best stock 0:20:10.320 --> 0:20:12.480 is the one that you never have to sell something 0:20:12.520 --> 0:20:14.360 like that. So you know, we're looking for those long 0:20:14.480 --> 0:20:16.840 term things. And so one of the things that helps 0:20:16.920 --> 0:20:20.000 us identify is is something that I've alluded to before. 0:20:20.040 --> 0:20:24.040 It's just something where we're looking for inflection points and 0:20:24.040 --> 0:20:27.800 and there's minor inflection points and there's there's major inflection points, 0:20:27.840 --> 0:20:30.960 and so you know, maybe it's something I think back, boy, 0:20:30.960 --> 0:20:33.600 it must be ten plus years ago where you went 0:20:33.680 --> 0:20:39.560 with with social advertising, you know, on on that. And 0:20:39.880 --> 0:20:42.960 one of the big things when we initially bought bought 0:20:43.000 --> 0:20:49.359 Meta was they experienced a big transition from from not 0:20:49.480 --> 0:20:52.520 really being able to measure your advertise. Remember it was 0:20:52.560 --> 0:20:54.680 all in just likes. How many likes did you get 0:20:54.680 --> 0:20:57.240 for that ad budget? So it was a dollars per like, 0:20:57.280 --> 0:21:00.120 which is a great measure for for you know, some 0:21:00.119 --> 0:21:03.400 some consumer products, just to kind of get a sense 0:21:03.400 --> 0:21:05.159 for that. But you really couldn't get a return on 0:21:05.200 --> 0:21:09.720 that advertising spend, as the old one to maker quote 0:21:09.720 --> 0:21:12.280 where I know I waste half of my ad budget, 0:21:12.320 --> 0:21:17.000 I just don't know which half. So advertisers really didn't 0:21:17.119 --> 0:21:19.399 didn't understand what they were getting as a return for 0:21:19.440 --> 0:21:21.679 that platform. And then there was this big shift that 0:21:21.720 --> 0:21:24.520 happened about a decade ago where Meta was able to 0:21:25.040 --> 0:21:31.040 really more accurately measure that that advertising spend. And so 0:21:31.080 --> 0:21:33.240 you had this big inflection where you had a lot 0:21:33.240 --> 0:21:37.400 of big advertisers, big consumer products companies, etc. That were 0:21:37.440 --> 0:21:39.800 hesitant to put too much money on the platform, When 0:21:39.800 --> 0:21:42.000 all of a sudden they could measure their return on 0:21:42.040 --> 0:21:47.359 their advertising spend and as a result, we're getting incredible 0:21:47.400 --> 0:21:52.040 returns and you were able to allocate more of their 0:21:52.080 --> 0:21:56.720 budget to the then Facebook platform. So I think we're 0:21:56.800 --> 0:22:02.360 really happy to look for those those big inflection points 0:22:02.800 --> 0:22:06.000 and and and if you can identify those and identify 0:22:06.119 --> 0:22:07.960 not just where they might you know, help one or 0:22:07.960 --> 0:22:12.360 two specific companies, but entire industries, then I think that 0:22:12.440 --> 0:22:17.680 it really opens up the the available investment opportunities for you. 0:22:18.080 --> 0:22:20.240 And you know, these are companies that you can be 0:22:20.280 --> 0:22:24.360 a little less worried about quarterly fluctuations in their growth rate, 0:22:24.840 --> 0:22:30.320 get good confidence in management ability to identify opportunities and 0:22:30.359 --> 0:22:33.720 continue to exploit those opportunities, and and grow over a 0:22:33.760 --> 0:22:35.440 long period of time. 0:22:36.080 --> 0:22:38.760 Okay, and you know, I also want to talk about valuations. 0:22:38.760 --> 0:22:41.000 It's a little bit you know, especially in today's market, 0:22:41.200 --> 0:22:43.879