1 00:00:00,120 --> 00:00:02,720 Speaker 1: For most of the last entry, investing was a lot 2 00:00:02,759 --> 00:00:06,360 Speaker 1: more art than science. People did in whatever was working 3 00:00:06,480 --> 00:00:11,040 Speaker 1: based more on gut feelings than data. Portfolio management was 4 00:00:11,080 --> 00:00:14,480 Speaker 1: a lot less evidence based than it is today, she. 5 00:00:18,160 --> 00:00:20,160 Speaker 2: Noted with silence. 6 00:00:21,040 --> 00:00:23,759 Speaker 1: As it turns out there are ways you can use 7 00:00:23,840 --> 00:00:27,640 Speaker 1: data to your advantage even if you're not a math wizard. 8 00:00:28,080 --> 00:00:31,440 Speaker 1: I'm Barry Ridults, and on today's edition of At the Money, 9 00:00:31,800 --> 00:00:34,440 Speaker 1: we're going to discuss how to use what we've learned 10 00:00:34,960 --> 00:00:38,800 Speaker 1: about quantitative investing to help us unpack all of this 11 00:00:38,880 --> 00:00:41,959 Speaker 1: and what it means for your portfolio. Let's bring in 12 00:00:42,080 --> 00:00:46,440 Speaker 1: Jim O'Shaughnessy. Jim is the former chairman and founder of 13 00:00:46,479 --> 00:00:50,360 Speaker 1: O'Shaughnessy Asset Management, which was sold to Franklin Templeton a 14 00:00:50,360 --> 00:00:53,800 Speaker 1: couple of years ago. He is also the author of 15 00:00:53,840 --> 00:00:57,160 Speaker 1: the New York Times best selling book What Works on 16 00:00:57,240 --> 00:01:00,880 Speaker 1: Wall Street, now in its fourth edition. What Works on 17 00:01:00,880 --> 00:01:05,600 Speaker 1: Wall Street was the first quantitative equity investing work, more 18 00:01:05,680 --> 00:01:08,759 Speaker 1: or less for the late person. Jim, welcome to add 19 00:01:08,760 --> 00:01:14,679 Speaker 1: the money. Let's start very basically define quantitative investing. 20 00:01:15,200 --> 00:01:21,200 Speaker 2: Quantitative investing, Barry is using empirical evidence that you gather 21 00:01:21,440 --> 00:01:25,559 Speaker 2: over looking at how various factors like things like price 22 00:01:25,600 --> 00:01:30,240 Speaker 2: to earnings ratio or earning's growth rate, and testing them 23 00:01:30,360 --> 00:01:33,840 Speaker 2: over as many market cycles as you can. That gives 24 00:01:33,880 --> 00:01:37,759 Speaker 2: you information that you simply couldn't have without such a test. 25 00:01:37,800 --> 00:01:41,120 Speaker 2: For example, you can see what's the biggest draw down, 26 00:01:41,440 --> 00:01:45,240 Speaker 2: how long did it last? How long and how often 27 00:01:45,319 --> 00:01:49,400 Speaker 2: did a strategy beat its benchmark and by what magnitude. 28 00:01:49,560 --> 00:01:54,200 Speaker 2: It's essentially like a very long term study just looking 29 00:01:54,280 --> 00:01:57,000 Speaker 2: at the evidence as opposed to stories. 30 00:01:57,600 --> 00:02:01,840 Speaker 1: So let's compare evidence versus the stories. When we look 31 00:02:01,880 --> 00:02:08,800 Speaker 1: at history, quantitative models outperform professional investors and experts who 32 00:02:08,840 --> 00:02:14,120 Speaker 1: rely on much squishier qualitative judgments. Why is that? 33 00:02:14,639 --> 00:02:18,280 Speaker 2: Primarily the old Pogo cartoon We've met the enemy and 34 00:02:18,320 --> 00:02:23,519 Speaker 2: it's us succinctly points out the reasoning here. Essentially, when 35 00:02:23,560 --> 00:02:27,880 Speaker 2: we model great investors and look at the underlying factors 36 00:02:27,960 --> 00:02:32,480 Speaker 2: of their portfolio, they do do extraordinarily well over time. 37 00:02:33,000 --> 00:02:38,280 Speaker 2: The challenge is that the expert themselves often makes emotional choices, 38 00:02:38,800 --> 00:02:44,079 Speaker 2: especially during times of intense market volatility. For example, during 39 00:02:44,200 --> 00:02:50,480 Speaker 2: the Great Financial Crisis, many even quantitative investors emotionally overrode 40 00:02:50,480 --> 00:02:56,519 Speaker 2: their models, so making decisions consistently according to a process 41 00:02:56,880 --> 00:02:59,760 Speaker 2: that you've tested, sort of saves you from your own 42 00:03:00,000 --> 00:03:01,560 Speaker 2: emotional problems. 43 00:03:01,919 --> 00:03:04,720 Speaker 1: So you've looked at a lot of these strategies and 44 00:03:04,760 --> 00:03:09,080 Speaker 1: strategists going back a century to the nineteen twenties. What 45 00:03:09,200 --> 00:03:13,640 Speaker 1: kinds of approaches have consistently performed the best. 46 00:03:14,120 --> 00:03:18,920 Speaker 2: No big surprise, Barry over long periods of time. Buying 47 00:03:18,960 --> 00:03:23,480 Speaker 2: stocks more cheaply priced than those that are priced into 48 00:03:23,520 --> 00:03:28,040 Speaker 2: the stratosphere generally works over long periods of time. But 49 00:03:28,120 --> 00:03:30,920 Speaker 2: one of the models that we've found that actually performed 50 00:03:31,080 --> 00:03:34,720 Speaker 2: really well over a variety of market cycles was essentially 51 00:03:34,760 --> 00:03:38,720 Speaker 2: buying cheap stocks as measured by things like price to 52 00:03:38,800 --> 00:03:42,480 Speaker 2: cash flow, even to enterprise value, etc. That are on 53 00:03:42,600 --> 00:03:45,760 Speaker 2: the men that have turned a corner and are showing 54 00:03:45,880 --> 00:03:50,480 Speaker 2: some good price momentum. Cheap stocks on the mend is 55 00:03:50,520 --> 00:03:53,400 Speaker 2: a really interesting way to look at the market, because 56 00:03:53,520 --> 00:03:57,280 Speaker 2: essentially the market is saying, yeah, that stock is very, 57 00:03:57,400 --> 00:04:00,880 Speaker 2: very cheap, but we think it's probably too cheap. They're 58 00:04:00,880 --> 00:04:03,720 Speaker 2: putting their money where their mouth is and buying it. 59 00:04:03,840 --> 00:04:06,040 Speaker 2: That's a great strategy overall. 60 00:04:06,160 --> 00:04:09,400 Speaker 1: So let's break that into two half, starting with valuation. 61 00:04:10,040 --> 00:04:12,280 Speaker 1: One of the things that struck me the first time 62 00:04:12,280 --> 00:04:15,600 Speaker 1: I read what works on Wall Street was the price 63 00:04:15,640 --> 00:04:19,960 Speaker 1: to earnings ratio, the PE ratio which everybody seems to 64 00:04:20,000 --> 00:04:24,000 Speaker 1: focus on. It doesn't really produce great results for investors. 65 00:04:24,440 --> 00:04:27,800 Speaker 1: Explain why PE isn't the best way to measure valuation. 66 00:04:28,400 --> 00:04:32,040 Speaker 2: Well, you know, when a measurement becomes a target, it 67 00:04:32,120 --> 00:04:36,000 Speaker 2: often loses its efficacy. And you know, there's the old 68 00:04:36,080 --> 00:04:39,800 Speaker 2: joke about the company hiring a new CFO and they 69 00:04:39,800 --> 00:04:43,160 Speaker 2: only ask them one question, what's two plus two? And 70 00:04:43,240 --> 00:04:46,640 Speaker 2: everyone answers four except for the person they hire, whose 71 00:04:46,680 --> 00:04:50,159 Speaker 2: answer was what number did you have? In mind? Earnings 72 00:04:50,160 --> 00:04:54,800 Speaker 2: are much easier to manipulate than things like revenue and 73 00:04:55,320 --> 00:04:59,360 Speaker 2: other measurements of value, and I think that's one of 74 00:04:59,400 --> 00:05:03,480 Speaker 2: the reasons why. Well, it worked very very well before 75 00:05:03,800 --> 00:05:08,480 Speaker 2: all of our innovations and computer databases, etc. Once it 76 00:05:08,520 --> 00:05:13,000 Speaker 2: became a target for people to pick things on, it 77 00:05:13,120 --> 00:05:16,039 Speaker 2: started getting manipulated at the corporate level. 78 00:05:16,760 --> 00:05:20,640 Speaker 1: So let's talk about some other measures. You talked about, 79 00:05:20,680 --> 00:05:26,080 Speaker 1: price to sales ratio, you talked about EBADA to enterprise value. 80 00:05:26,640 --> 00:05:30,240 Speaker 1: Tell us what actually works as a way of measuring 81 00:05:30,720 --> 00:05:31,799 Speaker 1: corporate value. 82 00:05:32,600 --> 00:05:36,320 Speaker 2: Specifically, we like to look at a composite of various 83 00:05:36,400 --> 00:05:40,640 Speaker 2: value factors, several of which you mentioned. One of my 84 00:05:40,960 --> 00:05:43,600 Speaker 2: rookie mistakes in the first version of the book was 85 00:05:43,640 --> 00:05:46,760 Speaker 2: simply looking at the data and saying, well, price to 86 00:05:46,839 --> 00:05:50,599 Speaker 2: sales has done the best of any single measurement. Well, 87 00:05:51,040 --> 00:05:55,000 Speaker 2: it was a rookie mistake because I was measuring it 88 00:05:55,040 --> 00:05:58,720 Speaker 2: over a specific period of time. As we improved our 89 00:05:58,800 --> 00:06:03,520 Speaker 2: process of testing, we found that using rolling rebalances and 90 00:06:03,680 --> 00:06:09,760 Speaker 2: multiple value factors, it alone was outperformed by a value composite. 91 00:06:10,080 --> 00:06:12,839 Speaker 1: And let's talk a bit about price momentum. That has 92 00:06:12,880 --> 00:06:17,880 Speaker 1: been a robust factor for strong performance, especially as you mentioned, 93 00:06:17,880 --> 00:06:22,520 Speaker 1: when you combine momentum with value metrics give us an 94 00:06:22,520 --> 00:06:26,280 Speaker 1: explanation for how we should be looking at momentum. 95 00:06:26,640 --> 00:06:31,000 Speaker 2: So momentum is really interesting because academics hate it because 96 00:06:31,040 --> 00:06:35,440 Speaker 2: there is no reason underlying economic reason why it should 97 00:06:35,480 --> 00:06:37,960 Speaker 2: make sense. But it does when you test it all 98 00:06:38,000 --> 00:06:41,560 Speaker 2: the way back to the twenties. The rolling batting averages 99 00:06:41,680 --> 00:06:45,000 Speaker 2: i e. The number of periods over one, three, five, 100 00:06:45,040 --> 00:06:49,000 Speaker 2: and ten years where it beats its benchmark is extremely high. 101 00:06:49,520 --> 00:06:52,719 Speaker 2: And that's sort of the wisdom of crowds working there. 102 00:06:52,760 --> 00:06:57,840 Speaker 2: I believe when people have very differing opinions on a stock. 103 00:06:58,160 --> 00:07:02,440 Speaker 2: They have heterogeneous opinions, right, as long as those opinions 104 00:07:02,480 --> 00:07:07,479 Speaker 2: remain heterogeneous, the price movement is an excellent indicator of 105 00:07:07,600 --> 00:07:11,880 Speaker 2: the net net net sentiment of investors. When it's going 106 00:07:12,000 --> 00:07:15,680 Speaker 2: much much higher, obviously, that's positive. When it's going negative, 107 00:07:16,120 --> 00:07:19,760 Speaker 2: that's very negative. If you invert momentum and look at 108 00:07:19,800 --> 00:07:22,840 Speaker 2: buying the stocks with the worst six month or twelve 109 00:07:22,880 --> 00:07:29,120 Speaker 2: month price momentum, the results are a true disaster. So essentially, it's, 110 00:07:29,560 --> 00:07:32,920 Speaker 2: as Ben Graham would call it, it's listening to mister market, 111 00:07:33,000 --> 00:07:35,520 Speaker 2: and they're putting their money where their mouth is. And 112 00:07:35,520 --> 00:07:38,920 Speaker 2: that's why I think it's such a strong and robust 113 00:07:39,040 --> 00:07:42,960 Speaker 2: indicator over a huge number of market cycles. 114 00:07:43,400 --> 00:07:45,840 Speaker 1: You know, it's interesting you say that. I always just 115 00:07:45,960 --> 00:07:49,800 Speaker 1: assumed that if you're a big fund manager and you're 116 00:07:49,840 --> 00:07:53,200 Speaker 1: buying fill in the blank, Microsoft and Vidia, Apple, it 117 00:07:53,240 --> 00:07:59,080 Speaker 1: doesn't matter. You're not saying, hey, Tuesday, March nineteenth, I'm 118 00:07:59,080 --> 00:08:04,000 Speaker 1: buying my five year allowance of Nvidia. You're buying that 119 00:08:04,240 --> 00:08:08,920 Speaker 1: as cash flows into your funds, you're consistently buying your 120 00:08:08,960 --> 00:08:13,400 Speaker 1: favorite names kind of relentlessly over time. Is that to 121 00:08:13,720 --> 00:08:18,040 Speaker 1: pop psychology? Of an explanation for momentum or is there 122 00:08:18,080 --> 00:08:22,960 Speaker 1: something too names that institutions like they tend to buy 123 00:08:23,160 --> 00:08:24,800 Speaker 1: and continue to buy over time. 124 00:08:25,920 --> 00:08:29,920 Speaker 2: Yeah, that's the persistent underlying bid theory, and I'm sure 125 00:08:29,960 --> 00:08:34,240 Speaker 2: that there is an effect when institutions continue to pour 126 00:08:34,320 --> 00:08:37,120 Speaker 2: money into their favorites on a buy list. But I 127 00:08:37,200 --> 00:08:43,080 Speaker 2: think that the reason momentum really works is those names 128 00:08:43,080 --> 00:08:46,840 Speaker 2: that you just mentioned. They do have positive momentum most 129 00:08:46,840 --> 00:08:50,439 Speaker 2: of the time, but the fact is they probably aren't 130 00:08:50,520 --> 00:08:53,599 Speaker 2: qualifying for the list of the stocks with the biggest 131 00:08:53,720 --> 00:08:57,559 Speaker 2: change in prices. Those names tend to be very, very 132 00:08:57,600 --> 00:09:02,679 Speaker 2: different than institutional favorites. So having an underlying persistent bid 133 00:09:02,679 --> 00:09:06,640 Speaker 2: from institutions yeah helpful. But a lot of those names 134 00:09:06,760 --> 00:09:09,839 Speaker 2: don't actually make the cut when you're sorting on your 135 00:09:09,840 --> 00:09:11,520 Speaker 2: final factor being momentum. 136 00:09:12,040 --> 00:09:16,720 Speaker 1: So let's talk about a fascinating piece of research you did. 137 00:09:16,720 --> 00:09:20,840 Speaker 1: I believe is also referenced in the book. People like 138 00:09:20,920 --> 00:09:24,000 Speaker 1: things like private equity and venture capital, but they're not 139 00:09:24,520 --> 00:09:28,160 Speaker 1: thrilled with being locked up for five years or seven years, 140 00:09:28,200 --> 00:09:34,199 Speaker 1: or sometimes even ten years. You identified that the microcaps 141 00:09:34,440 --> 00:09:39,760 Speaker 1: screened for quality seem to reproduce venture capital and private 142 00:09:39,800 --> 00:09:42,800 Speaker 1: equity returns but without the lock up period. Tell us 143 00:09:42,800 --> 00:09:43,280 Speaker 1: about that. 144 00:09:44,880 --> 00:09:48,920 Speaker 2: Yeah, we have several papers at Shawn c Asset Management 145 00:09:49,000 --> 00:09:54,240 Speaker 2: on that effect. It's really fascinating because the microcap universe 146 00:09:54,400 --> 00:09:57,680 Speaker 2: is kind of this undiscovered country. Half of the names 147 00:09:57,800 --> 00:10:01,280 Speaker 2: in it aren't even covered by a single analysts and 148 00:10:01,360 --> 00:10:05,760 Speaker 2: when you use quality, momentum, etc. To sort it out, 149 00:10:05,840 --> 00:10:12,120 Speaker 2: because warning, the universe itself is pretty not a great, 150 00:10:12,720 --> 00:10:13,560 Speaker 2: not a great universe. 151 00:10:13,679 --> 00:10:15,960 Speaker 1: You can call it garbage, Jim, It's okay. 152 00:10:15,720 --> 00:10:19,679 Speaker 2: Yeah, okay, all right, So the universe itself is garbage, 153 00:10:20,040 --> 00:10:23,800 Speaker 2: but there are a lot of hidden gems there and 154 00:10:23,960 --> 00:10:27,280 Speaker 2: the ability to sort out those hidden gems that are 155 00:10:27,440 --> 00:10:31,560 Speaker 2: little covered or not covered at all. Basically, what we 156 00:10:31,640 --> 00:10:35,000 Speaker 2: found in a paper that we published several years ago 157 00:10:35,360 --> 00:10:39,160 Speaker 2: was the returns sort of are great proxy for private 158 00:10:39,200 --> 00:10:43,360 Speaker 2: equity in particular. And so if you're looking for a 159 00:10:43,640 --> 00:10:47,960 Speaker 2: far less expensive way to get private equity, like returns 160 00:10:48,320 --> 00:10:51,280 Speaker 2: at lower fees with no lock up, you'll want to 161 00:10:51,320 --> 00:10:55,800 Speaker 2: take a look at the microcap universe sort it by 162 00:10:56,080 --> 00:10:57,319 Speaker 2: these various metrics. 163 00:10:57,960 --> 00:11:00,439 Speaker 1: So in the book What Works on Wall Street you 164 00:11:00,640 --> 00:11:08,160 Speaker 1: emphasize the importance of having a systematic, disciplined approach. Explain 165 00:11:08,280 --> 00:11:13,959 Speaker 1: to listeners what goes into taking what is kind of 166 00:11:15,200 --> 00:11:19,040 Speaker 1: used to be sort of a loose, an undisciplined approach 167 00:11:19,120 --> 00:11:23,319 Speaker 1: to stock selection and turning it into something much more disciplined. 168 00:11:25,040 --> 00:11:29,440 Speaker 2: Well, I think that essentially, I'd say, would you go 169 00:11:29,520 --> 00:11:32,280 Speaker 2: to a doctor who looked at you and said, hey, Barry, 170 00:11:32,640 --> 00:11:35,040 Speaker 2: I just got these little yellow pills and they look 171 00:11:35,080 --> 00:11:37,720 Speaker 2: appealing to me, and I think they might work for 172 00:11:37,800 --> 00:11:40,600 Speaker 2: what's wrong with you? I don't think you would, right, 173 00:11:40,679 --> 00:11:44,080 Speaker 2: I think you'd say, well, where are the studies, where's 174 00:11:44,120 --> 00:11:49,120 Speaker 2: the evidence? Where is the long longitudinal studies to prove 175 00:11:49,160 --> 00:11:52,600 Speaker 2: the efficacy of this little yellow pill? Right? That's really 176 00:11:52,679 --> 00:11:56,520 Speaker 2: what we're doing with factor or quantitative investing. We are 177 00:11:56,679 --> 00:12:01,679 Speaker 2: looking historically at ideas that make economic sense, right, don't 178 00:12:01,679 --> 00:12:05,720 Speaker 2: pay the moon by momentum, et cetera. But then this 179 00:12:05,880 --> 00:12:09,400 Speaker 2: is the key important part. We're turning it into a 180 00:12:09,520 --> 00:12:13,880 Speaker 2: process that we run time and again and don't override. 181 00:12:14,400 --> 00:12:19,920 Speaker 2: You know, the in basketball to investing, the process is 182 00:12:20,080 --> 00:12:24,160 Speaker 2: much more important than the either intuitive ooh I should 183 00:12:24,200 --> 00:12:27,319 Speaker 2: jump on this name or the terror Oh my god, 184 00:12:27,720 --> 00:12:28,720 Speaker 2: the name is collapsing. 185 00:12:28,760 --> 00:12:29,200 Speaker 1: I've got to. 186 00:12:29,240 --> 00:12:32,760 Speaker 2: Jump out of it. It really brings a rigor and 187 00:12:33,080 --> 00:12:37,559 Speaker 2: a discipline to approaching the market that is really hard 188 00:12:37,600 --> 00:12:43,559 Speaker 2: to duplicate without that process underlying the quantitative methodology not impossible, 189 00:12:44,080 --> 00:12:50,120 Speaker 2: but willpower dissipates very very quickly, especially in times of 190 00:12:50,240 --> 00:12:55,160 Speaker 2: either exuberance right during a bubble or despair during a 191 00:12:55,160 --> 00:12:59,640 Speaker 2: bear market. Following the process through thick and thin, which 192 00:12:59,679 --> 00:13:02,680 Speaker 2: you're all always trying to improve, by the way, but 193 00:13:02,960 --> 00:13:08,319 Speaker 2: following that process without making any additional emotional overrides, has 194 00:13:08,320 --> 00:13:12,640 Speaker 2: proven itself to be quite effective at getting rid of, 195 00:13:13,280 --> 00:13:17,280 Speaker 2: or at least neutralizing some of the very famous behavioral 196 00:13:17,320 --> 00:13:20,360 Speaker 2: biases that we all have as humans. Right, we're all 197 00:13:20,679 --> 00:13:26,400 Speaker 2: running human operating system and helping us avoid the pitfalls 198 00:13:26,559 --> 00:13:30,160 Speaker 2: is really what the underlying process does, and does very 199 00:13:30,280 --> 00:13:30,840 Speaker 2: very well. 200 00:13:30,920 --> 00:13:35,079 Speaker 1: So let's address that for a final question. One of 201 00:13:35,120 --> 00:13:39,040 Speaker 1: the things you have discussed previously is some of the 202 00:13:39,040 --> 00:13:45,440 Speaker 1: biggest challenges investors face is avoiding emotional decision making. What 203 00:13:45,640 --> 00:13:50,520 Speaker 1: are the tools you recommend for making sure that the 204 00:13:50,559 --> 00:13:55,960 Speaker 1: average mom and pop investor doesn't succumb to their own 205 00:13:55,960 --> 00:14:02,480 Speaker 1: emotional limbic system and making choice from the wrong place, 206 00:14:02,559 --> 00:14:06,280 Speaker 1: making choices from emotional panic or greed. 207 00:14:07,320 --> 00:14:09,800 Speaker 2: Well, you know, I've often said that the four horsemen 208 00:14:09,840 --> 00:14:13,400 Speaker 2: of the investment of apocalypse are fear, greed, hope, and ignorance, 209 00:14:13,720 --> 00:14:16,680 Speaker 2: and ignorance is the only one that is really correctable 210 00:14:16,800 --> 00:14:22,800 Speaker 2: by studying. It's very, very difficult, especially as you note, 211 00:14:22,920 --> 00:14:26,880 Speaker 2: for retail investors who look they have other interests, they 212 00:14:26,920 --> 00:14:29,960 Speaker 2: have other things that they're going to spend their time on. 213 00:14:30,440 --> 00:14:34,560 Speaker 2: So what I concluded was probably the best thing that 214 00:14:34,600 --> 00:14:38,640 Speaker 2: you can do is find yourself a good financial advisor 215 00:14:39,040 --> 00:14:42,720 Speaker 2: who could sort of serve as your wingman. The thing 216 00:14:42,760 --> 00:14:45,320 Speaker 2: that advisors are able to do because of a lot 217 00:14:45,320 --> 00:14:47,400 Speaker 2: of reasons, right it's not their money. They can be 218 00:14:47,520 --> 00:14:50,360 Speaker 2: much more dispassionate about it, they can be much more 219 00:14:50,400 --> 00:14:53,880 Speaker 2: professional about it, and then they can help their client 220 00:14:54,840 --> 00:14:57,520 Speaker 2: during those tough times. It's like the old joke about 221 00:14:57,560 --> 00:15:02,120 Speaker 2: anesthesiologists ninety five percent of the time they're board silly. 222 00:15:02,440 --> 00:15:05,240 Speaker 2: Five percent of the time that is where they earn 223 00:15:05,360 --> 00:15:06,720 Speaker 2: all their money. 224 00:15:07,400 --> 00:15:11,280 Speaker 1: Really interesting. Thanks Jim for all these insights. So to 225 00:15:11,360 --> 00:15:17,680 Speaker 1: wrap up, quantitative investing provides an enormous advantage to investors. 226 00:15:18,480 --> 00:15:23,080 Speaker 1: It's specific, it's evidence based, it uses data, and it 227 00:15:23,160 --> 00:15:28,000 Speaker 1: avoids the emotional decision making that leads investors to stray. 228 00:15:28,800 --> 00:15:33,320 Speaker 1: If you want to apply some quantitative strategies to your portfolio, 229 00:15:33,880 --> 00:15:38,280 Speaker 1: consider looking at the combination of momentum and low price 230 00:15:38,360 --> 00:15:44,400 Speaker 1: stocks or microcaps that have been screened for quality and value. 231 00:15:44,760 --> 00:16:00,960 Speaker 1: I'm Barry Ridoults. You're listening to Bloomberg's At the Money.