1 00:00:02,240 --> 00:00:06,800 Speaker 1: This is Master's in Business with Barry Ridholts on Bloomberg Radio. 2 00:00:07,360 --> 00:00:10,080 Speaker 1: This weekend. On the podcast, I have an extra special 3 00:00:10,119 --> 00:00:14,960 Speaker 1: guest and it is filled. Our conversation is filled with 4 00:00:15,160 --> 00:00:19,640 Speaker 1: geeky goodness. Uh Andrew Ang, head of Factor Investing at 5 00:00:19,680 --> 00:00:22,600 Speaker 1: black Rock name run I don't know six points something 6 00:00:22,680 --> 00:00:27,480 Speaker 1: trillion dollars um. Ang is really a born and bread 7 00:00:28,080 --> 00:00:31,000 Speaker 1: uh factor investor. Not only does he have a background 8 00:00:31,400 --> 00:00:35,640 Speaker 1: in stats and finance from from UM Stanford, but he 9 00:00:35,720 --> 00:00:41,280 Speaker 1: taught finance at Columbia and the opportunity to put his 10 00:00:41,440 --> 00:00:46,600 Speaker 1: theories into actual practice at black Rock just proved to 11 00:00:46,640 --> 00:00:51,840 Speaker 1: be too tempting. He had to leave UM the theoretical 12 00:00:51,880 --> 00:00:55,280 Speaker 1: practice of teaching and working at Columbia that he really 13 00:00:55,360 --> 00:00:57,680 Speaker 1: enjoyed to give it a shot at black Rock, and 14 00:00:57,720 --> 00:01:01,280 Speaker 1: it's worked out extremely well. If you are at all 15 00:01:01,360 --> 00:01:09,000 Speaker 1: interested in quantitative investing, modeling, factor investing, anything remotely involved 16 00:01:09,080 --> 00:01:14,600 Speaker 1: in the wonky goodness of mathematical theory and investing, you're 17 00:01:14,600 --> 00:01:18,920 Speaker 1: gonna love this conversation. So, with no further ado, my 18 00:01:19,080 --> 00:01:24,039 Speaker 1: conversation with Black Rocks Andrew Ang. My extra special guest 19 00:01:24,120 --> 00:01:28,000 Speaker 1: this week is Andrew Ang. He is the head of 20 00:01:28,120 --> 00:01:32,360 Speaker 1: Factor investing at black Rock, the firm manages over six 21 00:01:32,400 --> 00:01:35,440 Speaker 1: trillion dollars. He comes to us with a PhD in 22 00:01:35,520 --> 00:01:39,520 Speaker 1: finance and a master's degree in statistics from Stanford and 23 00:01:39,600 --> 00:01:43,640 Speaker 1: he is the author of a book called Asset Management, 24 00:01:44,080 --> 00:01:49,840 Speaker 1: A Systemic Approach to Factor Investing. Andrew Ang, Welcome to Bloomberg. 25 00:01:49,880 --> 00:01:52,120 Speaker 1: Thank you. Barrett's a real pleasure to be here. Thanks 26 00:01:52,160 --> 00:01:55,320 Speaker 1: for coming in. You have You have a really fascinating background. 27 00:01:55,360 --> 00:01:59,200 Speaker 1: You spend the first half of your career in academia, 28 00:02:00,160 --> 00:02:04,160 Speaker 1: made you decide to transition from theory to practice. Indeed, 29 00:02:04,200 --> 00:02:08,600 Speaker 1: I was a professor for fifteen years at Columbia University 30 00:02:08,720 --> 00:02:12,320 Speaker 1: and ended as chair of the Finance and Economics Division 31 00:02:12,639 --> 00:02:16,720 Speaker 1: and was the Anne F. Kaplan Professor of Business. What's 32 00:02:16,760 --> 00:02:20,520 Speaker 1: interesting is that my wife, she was born in China. 33 00:02:21,120 --> 00:02:25,680 Speaker 1: Her parents have this long, very scholarly Confucian style tradition 34 00:02:25,800 --> 00:02:29,320 Speaker 1: and the highest life form for them is a tenured 35 00:02:29,360 --> 00:02:32,240 Speaker 1: professor at an Ivy League institution. And I thought I 36 00:02:32,320 --> 00:02:36,720 Speaker 1: was absolutely crazy and leaving that and coming to industry. 37 00:02:36,960 --> 00:02:39,440 Speaker 1: My parents, on the other hand, they didn't go to university. 38 00:02:39,520 --> 00:02:43,880 Speaker 1: They actually I really don't know still today what a 39 00:02:43,919 --> 00:02:46,600 Speaker 1: professor does well what do you mean you're not teaching. 40 00:02:46,760 --> 00:02:50,120 Speaker 1: You mean you're on vacation. And they were really proud 41 00:02:50,120 --> 00:02:53,239 Speaker 1: of me for getting a real job. So the disparity 42 00:02:53,280 --> 00:02:56,720 Speaker 1: in the attitudes, well, one thing that was very interesting 43 00:02:56,800 --> 00:03:00,160 Speaker 1: is my wife said to me, Andrew, you're a hypocrite, 44 00:03:00,720 --> 00:03:03,000 Speaker 1: because I used to feel that a lot of academics, 45 00:03:03,000 --> 00:03:06,160 Speaker 1: and I was myself one. They're very theoretical, but they 46 00:03:06,240 --> 00:03:09,440 Speaker 1: believe that the world should operate in a particular way, 47 00:03:09,800 --> 00:03:12,840 Speaker 1: of course, the way that they study the world, but 48 00:03:13,480 --> 00:03:17,080 Speaker 1: they he she called me a hypocrite because actually I 49 00:03:17,120 --> 00:03:21,679 Speaker 1: believed so much that I accepted a job offer to 50 00:03:21,720 --> 00:03:25,040 Speaker 1: come to Black Crop because I wanted to change the 51 00:03:25,080 --> 00:03:29,639 Speaker 1: way that finance was practiced in accordance to the research 52 00:03:29,720 --> 00:03:32,160 Speaker 1: and factors that I was doing. So let's talk about 53 00:03:32,160 --> 00:03:35,360 Speaker 1: that research a little bit. You have a background and statistics, 54 00:03:35,440 --> 00:03:39,080 Speaker 1: You get a PhD in finance that really lends itself 55 00:03:39,160 --> 00:03:43,280 Speaker 1: to factor investing. That sort of quantitative approach is practically 56 00:03:43,880 --> 00:03:47,600 Speaker 1: made for this. But I have to ask from your research, 57 00:03:47,680 --> 00:03:50,080 Speaker 1: how did you find your way to a factor investing. 58 00:03:50,840 --> 00:03:52,600 Speaker 1: I was a professor, and I did a lot of 59 00:03:52,640 --> 00:03:55,280 Speaker 1: consulting while I was a professor, and I had the 60 00:03:55,280 --> 00:04:00,200 Speaker 1: privilege of working for some very large institutions, including the 61 00:04:00,280 --> 00:04:03,120 Speaker 1: Norwegian Sovereign Wealth Fund, and this is a very special fund. 62 00:04:03,160 --> 00:04:07,440 Speaker 1: It's a trillion dollars today, it's multiple multiples times the 63 00:04:07,440 --> 00:04:11,160 Speaker 1: country's GDP, and they went through some tough times in 64 00:04:11,400 --> 00:04:15,680 Speaker 1: two thousand and eight, like many institutions, and I was 65 00:04:15,760 --> 00:04:19,279 Speaker 1: tasked by the Ministry of Finance representing Parliament, together with 66 00:04:19,360 --> 00:04:23,839 Speaker 1: two other academics to take a deep look at the fund, 67 00:04:24,360 --> 00:04:27,560 Speaker 1: to analyze it, to see where the losses were coming from, 68 00:04:27,600 --> 00:04:30,599 Speaker 1: and to make recommendations. And what we found was that 69 00:04:30,760 --> 00:04:36,040 Speaker 1: despite this fund owning tens of thousands of securities dozens 70 00:04:36,080 --> 00:04:38,839 Speaker 1: of active managers, what mattered at the end of the 71 00:04:38,920 --> 00:04:43,440 Speaker 1: day were these factors broad and persistent sources of returns. 72 00:04:43,480 --> 00:04:47,760 Speaker 1: Macro factors like economic growth, real rates and inflation which 73 00:04:47,800 --> 00:04:52,080 Speaker 1: comes through market cap indices, and then relative to those 74 00:04:52,120 --> 00:04:56,440 Speaker 1: market cap benchmarks, style factors like value and momentum quality, 75 00:04:56,480 --> 00:05:00,880 Speaker 1: minimum volatility explain two thirds of the variation of these 76 00:05:00,920 --> 00:05:04,719 Speaker 1: active returns, and so factors really mattered, and it was 77 00:05:04,880 --> 00:05:08,400 Speaker 1: entirely appropriate for Norway to have these exposures to these 78 00:05:08,440 --> 00:05:13,280 Speaker 1: factors that resulted in long term superior returns. So, so 79 00:05:13,360 --> 00:05:15,280 Speaker 1: let me jump in right here and ask this. You're 80 00:05:15,360 --> 00:05:19,400 Speaker 1: you're viewing a trillion dollar portfolio. You're really separating the 81 00:05:19,400 --> 00:05:22,880 Speaker 1: wheat from the chaff. You're identifying what the source of 82 00:05:23,000 --> 00:05:28,400 Speaker 1: returns within that trillion dollar portfolio is. Do do the 83 00:05:28,440 --> 00:05:31,320 Speaker 1: managers of the Norwegian Sovereign Wealth Fund then turn around 84 00:05:31,320 --> 00:05:35,559 Speaker 1: and say, we're going to move away from the parts 85 00:05:35,560 --> 00:05:39,480 Speaker 1: of our portfolio that aren't performing and towards where our 86 00:05:39,720 --> 00:05:44,760 Speaker 1: out performances coming from. Or did they consider that diversification 87 00:05:44,839 --> 00:05:49,279 Speaker 1: and they leave it as it was. Norway has always 88 00:05:49,360 --> 00:05:54,160 Speaker 1: used different sources of return, including fundamental analysis, and they 89 00:05:54,200 --> 00:05:58,320 Speaker 1: continue to do that. But what we recommended and they 90 00:05:58,320 --> 00:06:02,120 Speaker 1: did adopt, was to make a very top down, deliberate 91 00:06:02,120 --> 00:06:06,479 Speaker 1: decision on these factors. And as a result, Norway started 92 00:06:06,520 --> 00:06:11,039 Speaker 1: directly allocating to these factors to manage, better understand their risks, 93 00:06:11,080 --> 00:06:14,200 Speaker 1: to enhance their returns, and as you say, Barry too, 94 00:06:14,880 --> 00:06:18,520 Speaker 1: improve the diversification. So so they seem to be pretty 95 00:06:18,560 --> 00:06:22,600 Speaker 1: well versed in understanding the academic literature. But out in 96 00:06:22,640 --> 00:06:25,680 Speaker 1: the real world, which is a fair statement to say, 97 00:06:25,680 --> 00:06:28,320 Speaker 1: out in the rest of the real world, how does 98 00:06:29,160 --> 00:06:33,680 Speaker 1: the way most people invest differ from from what's in 99 00:06:33,839 --> 00:06:38,880 Speaker 1: the textbook. What what are the big disparities between people 100 00:06:38,920 --> 00:06:41,800 Speaker 1: who aren't the Norway sovereign wealth funds and and the 101 00:06:41,839 --> 00:06:45,320 Speaker 1: average investor? What what's the difference in their process and 102 00:06:45,360 --> 00:06:48,360 Speaker 1: in their results? Great question bear because I really think 103 00:06:48,360 --> 00:06:50,839 Speaker 1: they are more similarities than differences. But if you have 104 00:06:50,920 --> 00:06:53,080 Speaker 1: to think about you know, I used to be a 105 00:06:53,120 --> 00:06:56,360 Speaker 1: professor and now you're a practitioner. What what are these differences? 106 00:06:56,800 --> 00:06:59,400 Speaker 1: A lot of people talk about implementation short for and 107 00:06:59,400 --> 00:07:02,200 Speaker 1: a lot of a jargon, the difference with transaction costs 108 00:07:02,240 --> 00:07:05,720 Speaker 1: and stale prices or stale data. But actually the real 109 00:07:05,839 --> 00:07:09,880 Speaker 1: difference between academic and practice is you've got to work 110 00:07:09,880 --> 00:07:12,920 Speaker 1: with a lot of people to get these things to fruition. 111 00:07:12,960 --> 00:07:14,679 Speaker 1: And as a professor, you're sitting there in your office, 112 00:07:14,760 --> 00:07:17,800 Speaker 1: you're sitting there by yourself often and you just do 113 00:07:17,840 --> 00:07:21,040 Speaker 1: your own thing. But to make a difference, you have 114 00:07:21,560 --> 00:07:24,880 Speaker 1: dozens of people and teams that you've got to partner 115 00:07:24,960 --> 00:07:28,400 Speaker 1: with in order to make a product come until an 116 00:07:28,400 --> 00:07:32,400 Speaker 1: advisor shelf. Let's talk a little bit about the best 117 00:07:32,440 --> 00:07:36,320 Speaker 1: way to use factors. Are they designed to manage risk 118 00:07:36,760 --> 00:07:43,200 Speaker 1: or are they designed to deliver market out performance. Well, yes, actually, 119 00:07:44,160 --> 00:07:48,120 Speaker 1: I think factors should be used in all facets of 120 00:07:48,160 --> 00:07:52,360 Speaker 1: the investment process. We definitely need factors to look at 121 00:07:52,560 --> 00:07:54,880 Speaker 1: really what drives our returned So there is an angle 122 00:07:54,920 --> 00:07:58,240 Speaker 1: for risk management, and I think your firm has exemplified 123 00:07:58,280 --> 00:08:00,800 Speaker 1: that very But we also would like to use factors 124 00:08:00,840 --> 00:08:03,520 Speaker 1: to enhance our returns as well, and we can do 125 00:08:03,600 --> 00:08:08,240 Speaker 1: that with value, quality, momentum size, and combinations of these 126 00:08:08,240 --> 00:08:11,560 Speaker 1: return enhancing factors. We can also use factors to target 127 00:08:11,640 --> 00:08:17,120 Speaker 1: specific outcomes like minimizing our downside risk exposure through minimum 128 00:08:17,160 --> 00:08:20,480 Speaker 1: volatility strategies. Factors can be used for all of these, 129 00:08:20,560 --> 00:08:23,800 Speaker 1: And what's really exciting is that we can ask, what's 130 00:08:23,880 --> 00:08:26,040 Speaker 1: the outcome you want to achieve. Perhaps it has created 131 00:08:26,040 --> 00:08:29,600 Speaker 1: a versification or put full of resilience, and we will 132 00:08:29,680 --> 00:08:33,679 Speaker 1: have some combination of factors that's right for you. So 133 00:08:34,360 --> 00:08:37,600 Speaker 1: here's the question that always comes up when I discuss 134 00:08:37,640 --> 00:08:41,560 Speaker 1: factors with other people. It seems once everybody discovers a 135 00:08:41,559 --> 00:08:45,680 Speaker 1: new idea, it's power has a tendency to sort of 136 00:08:45,720 --> 00:08:49,400 Speaker 1: fade away. Now that we know so much about factors, 137 00:08:49,400 --> 00:08:51,480 Speaker 1: we know about value, we know about small cap, we 138 00:08:51,520 --> 00:08:54,920 Speaker 1: know about quality, why hasn't that been arbitraged away. How 139 00:08:55,040 --> 00:08:59,600 Speaker 1: is it that long term factors still deliver some degree 140 00:08:59,640 --> 00:09:04,280 Speaker 1: about formants. Ultimately, that's a question of who's on the 141 00:09:04,320 --> 00:09:07,560 Speaker 1: other side, because not everyone can buy cheap. For every 142 00:09:07,760 --> 00:09:10,240 Speaker 1: value stock that's cheap, there's got to be a stock 143 00:09:10,320 --> 00:09:15,600 Speaker 1: that's relatively expensive. The economic rationales behind all these factors 144 00:09:16,320 --> 00:09:19,959 Speaker 1: are the same reasons why we think that these sources 145 00:09:20,000 --> 00:09:22,160 Speaker 1: of returns are going to persevere for a long time. 146 00:09:22,320 --> 00:09:25,320 Speaker 1: And there are three. There's a reward for bearing risk, 147 00:09:25,720 --> 00:09:30,040 Speaker 1: a structural impediment, and investors behavioral biases. So wait before 148 00:09:30,040 --> 00:09:32,160 Speaker 1: we get to the first and the third one, which 149 00:09:32,200 --> 00:09:34,160 Speaker 1: I have a feeling, I know what you're gonna say, 150 00:09:34,320 --> 00:09:36,800 Speaker 1: tell me about the second one. What is the structural 151 00:09:36,840 --> 00:09:42,120 Speaker 1: impediment to buying cheap or buying quality? Well, for value, 152 00:09:42,240 --> 00:09:45,079 Speaker 1: there is no structural impediment because you can buy cheap. 153 00:09:45,480 --> 00:09:49,640 Speaker 1: But for minimum volatility though, this is where structural impediments 154 00:09:49,679 --> 00:09:51,760 Speaker 1: come in. And if we look at the United States, 155 00:09:51,840 --> 00:09:54,439 Speaker 1: there are a large number of very large funds, a 156 00:09:54,480 --> 00:09:58,760 Speaker 1: lot of public pension plans, but also other large institutions 157 00:09:58,800 --> 00:10:01,320 Speaker 1: that have high to to return targets but a lot 158 00:10:01,400 --> 00:10:04,880 Speaker 1: of restrictions on what they can do with their investment policies. 159 00:10:05,360 --> 00:10:10,160 Speaker 1: Some of those institutions will gravitate to higher risk stocks 160 00:10:10,240 --> 00:10:13,280 Speaker 1: in an attempt to meet those high told to return targets, 161 00:10:13,600 --> 00:10:18,360 Speaker 1: and then underweight the low volatility or low risk stocks, 162 00:10:18,440 --> 00:10:21,920 Speaker 1: and that gives rise to minimum volatility strategies. Now, if 163 00:10:22,000 --> 00:10:26,320 Speaker 1: that structural impediment disappeared and suddenly all of those institutions 164 00:10:26,360 --> 00:10:29,640 Speaker 1: had much more flexible investment policies than perhaps we might 165 00:10:29,640 --> 00:10:33,120 Speaker 1: see minimum volatility go away. But let's go to the 166 00:10:33,160 --> 00:10:36,840 Speaker 1: first and third of those right, Well, well, what about 167 00:10:36,880 --> 00:10:39,080 Speaker 1: the reward for bearing risk? And here I'll give value 168 00:10:39,120 --> 00:10:42,920 Speaker 1: as an example, since you raised this before, or small cap, 169 00:10:42,960 --> 00:10:47,040 Speaker 1: because I keep having discussions with people who insist that 170 00:10:47,200 --> 00:10:50,080 Speaker 1: the small cap premium is all risk, and I'm not 171 00:10:50,120 --> 00:10:53,400 Speaker 1: sure how true that is. And if it is largely 172 00:10:53,520 --> 00:10:56,559 Speaker 1: risk that we're shown, but that's a risk that you 173 00:10:56,600 --> 00:10:59,920 Speaker 1: should be comfortable bearing and will result in the long 174 00:11:00,120 --> 00:11:04,440 Speaker 1: term with compensated higher returns. Now, Value a lot of 175 00:11:04,559 --> 00:11:08,319 Speaker 1: value companies a little bit old fashioned. They often manufacture 176 00:11:08,360 --> 00:11:11,079 Speaker 1: things or produce services. They're very good at that, often 177 00:11:11,120 --> 00:11:14,360 Speaker 1: with a lot of fixed or physical capital. And when 178 00:11:14,440 --> 00:11:17,960 Speaker 1: you get into a lite economic cycle or an economic recession. 179 00:11:18,080 --> 00:11:22,480 Speaker 1: It's very hard to change what your factory is currently manufactured, 180 00:11:23,080 --> 00:11:27,280 Speaker 1: and so not surprisingly, those value firms tend to underperform 181 00:11:27,400 --> 00:11:31,760 Speaker 1: those fixed costs. All of that physical capital give those 182 00:11:32,000 --> 00:11:34,920 Speaker 1: value companies economies of scale, so they tend to perform 183 00:11:34,960 --> 00:11:38,200 Speaker 1: the best coming out from the recessions in the recovery. Now, 184 00:11:38,360 --> 00:11:42,880 Speaker 1: you can't stomach these cyclical losses, and value absolutely no doubt, 185 00:11:42,920 --> 00:11:45,480 Speaker 1: has had a pretty rough ride of it over the 186 00:11:45,520 --> 00:11:48,680 Speaker 1: past couple of quarters, consistent where where we are in 187 00:11:48,679 --> 00:11:52,320 Speaker 1: the late economic cycle. If you can't stomach that under performance, 188 00:11:52,720 --> 00:11:56,080 Speaker 1: then well values not for you, but for those who 189 00:11:56,280 --> 00:12:00,960 Speaker 1: can bear those risks of short term to performance, you 190 00:12:01,000 --> 00:12:04,240 Speaker 1: will be compensated with a long term value premium. That's 191 00:12:04,240 --> 00:12:07,040 Speaker 1: the reward for barons. So how long is long term? 192 00:12:07,120 --> 00:12:10,280 Speaker 1: Because since the OH nine crisis ended, value is under 193 00:12:10,520 --> 00:12:14,000 Speaker 1: underperformed growth. That's a solid decade. We've been having an 194 00:12:14,080 --> 00:12:17,559 Speaker 1: argument in my office. Is it one decade, two decades? 195 00:12:17,600 --> 00:12:22,720 Speaker 1: It goes quite a while. Since value has consistently outperformed growth, 196 00:12:23,200 --> 00:12:27,560 Speaker 1: What is the long term for for a factor manifesting 197 00:12:27,559 --> 00:12:30,120 Speaker 1: itself as alpha. Yeah, these cycles can be three to 198 00:12:30,200 --> 00:12:33,800 Speaker 1: five years, but over the last ten years value has outperformed. 199 00:12:33,840 --> 00:12:36,160 Speaker 1: But we give a little bit of a story coming 200 00:12:36,360 --> 00:12:39,640 Speaker 1: into twenty six and that was a really great year 201 00:12:39,760 --> 00:12:43,160 Speaker 1: for value. In fact, particularly in the last part of 202 00:12:43,160 --> 00:12:48,960 Speaker 1: the year. Started before Trump's election in November, value was 203 00:12:49,040 --> 00:12:53,520 Speaker 1: pretty much flat, and then there was tremendous under performance. 204 00:12:53,960 --> 00:12:56,080 Speaker 1: It was until the fourth quarter of the fourth quarter 205 00:12:58,240 --> 00:13:01,520 Speaker 1: Uarter four, and then through twenty eighteen we saw those losses. 206 00:13:01,559 --> 00:13:06,920 Speaker 1: Ex sorry, we find that twenty eighteen to now where 207 00:13:07,040 --> 00:13:12,720 Speaker 1: in May is the fourth worst value draw down, fourth 208 00:13:12,720 --> 00:13:14,920 Speaker 1: worst value draw down in almost a hundred years of 209 00:13:15,000 --> 00:13:19,079 Speaker 1: data using the data set that starts in five constructed 210 00:13:19,080 --> 00:13:21,839 Speaker 1: by Nobel Prize winning Gene Farmer and his longtime co 211 00:13:21,960 --> 00:13:26,240 Speaker 1: author Kenneth French. Isn't that amazing fourth worth through century? 212 00:13:26,520 --> 00:13:30,120 Speaker 1: That that's quite fascinating. Well again, fourth quarter of eighteen, 213 00:13:30,240 --> 00:13:35,439 Speaker 1: when the market SMP fell about we saw value indexes 214 00:13:35,520 --> 00:13:38,080 Speaker 1: do much better. They fell a little bit, but not 215 00:13:38,280 --> 00:13:40,480 Speaker 1: nearly as much as the growth in this disease. The 216 00:13:40,520 --> 00:13:43,160 Speaker 1: fang stocks got she lacked in the fourth quarter, But 217 00:13:43,240 --> 00:13:46,600 Speaker 1: here we are pretty close to near all time highs 218 00:13:46,640 --> 00:13:49,079 Speaker 1: and it looks like growth has kind of caught up again. 219 00:13:49,520 --> 00:13:53,640 Speaker 1: So is the expectation we're going to see some serious 220 00:13:53,679 --> 00:13:55,800 Speaker 1: mean reversion and at some point in the not to 221 00:13:55,960 --> 00:13:59,880 Speaker 1: distant future. Well, I believe in value, I'm a value investor. 222 00:14:00,080 --> 00:14:03,760 Speaker 1: M H. We do need to stay the course. Let's 223 00:14:03,760 --> 00:14:07,000 Speaker 1: put that fourth worst draw down in context, so it's 224 00:14:07,840 --> 00:14:10,960 Speaker 1: not unprecedented. There are some worst times, and if we 225 00:14:11,000 --> 00:14:13,840 Speaker 1: look at the top six to eight episodes of really 226 00:14:13,920 --> 00:14:17,520 Speaker 1: bad value performance, they're characterized by an environment like what 227 00:14:17,559 --> 00:14:21,600 Speaker 1: we've had late economic cycle, except our cycle today has 228 00:14:21,960 --> 00:14:25,280 Speaker 1: perhaps been very prolonged to be in this late stage, 229 00:14:25,280 --> 00:14:27,480 Speaker 1: and I mean I think that's a separate macro post 230 00:14:27,520 --> 00:14:33,920 Speaker 1: financial credit crisis, FED intervention, etcetera, monetary policy and all 231 00:14:34,000 --> 00:14:37,280 Speaker 1: the rest of that. We also see some very severe 232 00:14:37,320 --> 00:14:39,840 Speaker 1: accessions that There are two episodes in the nineteen thirties 233 00:14:39,880 --> 00:14:42,960 Speaker 1: as well that are but the worst one is the 234 00:14:43,040 --> 00:14:47,360 Speaker 1: late nineteen nineties in fact, and we're about half as 235 00:14:47,400 --> 00:14:52,120 Speaker 1: bad as So let's talk a little bit about fixed 236 00:14:52,120 --> 00:14:56,080 Speaker 1: income investors. Are they actually beginning to use factors now? 237 00:14:56,680 --> 00:15:00,360 Speaker 1: They are, and we've just introduced a few fixed income 238 00:15:01,000 --> 00:15:03,280 Speaker 1: factor e t f s. That's part of the next 239 00:15:03,320 --> 00:15:07,440 Speaker 1: evolutionists pushing these time tested concepts of like buying cheap 240 00:15:07,560 --> 00:15:11,360 Speaker 1: and finding higher quality names, finding trends, but pushing that 241 00:15:11,480 --> 00:15:15,280 Speaker 1: from where it's being mostly equities to fixed income and 242 00:15:15,320 --> 00:15:21,200 Speaker 1: then to other multi assets applications like currencies and commodities, 243 00:15:21,720 --> 00:15:24,680 Speaker 1: and then also to go invest in a long short 244 00:15:24,680 --> 00:15:27,280 Speaker 1: manner as well, and fixed income. It's right there at 245 00:15:27,280 --> 00:15:30,080 Speaker 1: the frontier. So when I think of factor investing, I 246 00:15:30,120 --> 00:15:32,960 Speaker 1: think of capsize, and I think of quality, and I 247 00:15:33,000 --> 00:15:38,600 Speaker 1: think of price, namely value. Are you creating parallel versions 248 00:15:38,680 --> 00:15:44,400 Speaker 1: of this for UM bonds? I mean our bonds cheaper 249 00:15:44,440 --> 00:15:49,320 Speaker 1: expensive as a function relative to UM the combination of 250 00:15:49,320 --> 00:15:53,560 Speaker 1: their credit quality and their forward expected cash flow based 251 00:15:53,600 --> 00:15:56,080 Speaker 1: on will this default or not? How do you determine 252 00:15:56,520 --> 00:15:59,880 Speaker 1: value or is it yield relative to to what the 253 00:16:00,040 --> 00:16:02,880 Speaker 1: ten your treasury is doing. All of these factors are 254 00:16:03,000 --> 00:16:06,560 Speaker 1: broad and persistent, so they are seen in many different areas, 255 00:16:06,600 --> 00:16:09,800 Speaker 1: but you do need some research to apply it in 256 00:16:09,840 --> 00:16:13,400 Speaker 1: these different asset classes. So value it's all about buying 257 00:16:13,480 --> 00:16:17,960 Speaker 1: cheap relative to intrinsic right, what's intrinsic or fundamental value 258 00:16:17,960 --> 00:16:20,800 Speaker 1: for a bond? And so we can measure or apply 259 00:16:20,960 --> 00:16:23,160 Speaker 1: value by looking at the yield of a bond. Well, 260 00:16:23,160 --> 00:16:26,360 Speaker 1: that's equivalent to price. But we might now have intrinsic 261 00:16:26,680 --> 00:16:30,600 Speaker 1: value versus a forward rate curve or versus an option 262 00:16:30,640 --> 00:16:34,440 Speaker 1: adjusted spread, for example. But we can apply the same 263 00:16:34,480 --> 00:16:39,000 Speaker 1: concepts price or yield relative to a measure of intrinsic value. 264 00:16:39,040 --> 00:16:42,520 Speaker 1: How does how does the risk free um treasury fit 265 00:16:42,600 --> 00:16:46,600 Speaker 1: into figuring out what value is for a bond? The 266 00:16:46,720 --> 00:16:51,080 Speaker 1: risk free rate operates across these different asset classes, and 267 00:16:51,120 --> 00:16:54,280 Speaker 1: it's a base rate. It's sort of like the opportunity cost. 268 00:16:54,480 --> 00:16:57,520 Speaker 1: Instead of parking your money in the bank, well, we're 269 00:16:57,520 --> 00:16:59,440 Speaker 1: now going to take risk and were going to be 270 00:16:59,480 --> 00:17:03,080 Speaker 1: rewarded for it. So it's coming across asset classes now. 271 00:17:03,520 --> 00:17:07,080 Speaker 1: The risk free rate, though in fixed income, gives you 272 00:17:07,160 --> 00:17:11,640 Speaker 1: a term structure, and that term structure will translate into 273 00:17:11,800 --> 00:17:15,439 Speaker 1: different factor strategies. So some people will talk about curve 274 00:17:15,720 --> 00:17:20,600 Speaker 1: or row down. That's certainly a part of income investing 275 00:17:20,680 --> 00:17:24,000 Speaker 1: or carry. We can also talk about risk free rates 276 00:17:24,040 --> 00:17:26,639 Speaker 1: affecting different countries, and so now we think of an 277 00:17:26,920 --> 00:17:31,119 Speaker 1: uh an international version of fixed income factor investing as well. 278 00:17:31,400 --> 00:17:35,120 Speaker 1: Since we're talking about fixed income investing, there's now about 279 00:17:35,280 --> 00:17:40,119 Speaker 1: twelve trillion dollars of bonds that carry in negative yield. Here, 280 00:17:40,480 --> 00:17:42,679 Speaker 1: I'm gonna lend you money, and I'm gonna pay you 281 00:17:42,760 --> 00:17:46,160 Speaker 1: to hold my cash for me. How does that figure 282 00:17:46,480 --> 00:17:50,480 Speaker 1: into factor investing for for bonds? And what does this 283 00:17:50,560 --> 00:17:56,040 Speaker 1: say about the world of the cost of capital? I 284 00:17:56,040 --> 00:18:00,920 Speaker 1: and almost guilty, really, because a lot of academics spent 285 00:18:01,200 --> 00:18:04,920 Speaker 1: an enormous amount of time writing down very complicated models 286 00:18:04,960 --> 00:18:08,119 Speaker 1: to ensure that interest rates remain positive. And what are 287 00:18:08,119 --> 00:18:11,200 Speaker 1: they now? They're they're not positive. It's almost like all 288 00:18:11,320 --> 00:18:15,639 Speaker 1: that literature could have been thrown out more seriously, More seriously, 289 00:18:16,240 --> 00:18:20,200 Speaker 1: what's really relevant here is the real rate rather than 290 00:18:20,280 --> 00:18:24,120 Speaker 1: the nominal relative to inflation, relative to inflation, and there 291 00:18:24,200 --> 00:18:27,520 Speaker 1: we've seen many episodes of negative real rates, and some 292 00:18:27,600 --> 00:18:30,439 Speaker 1: of them I've I've worked with some co authors in 293 00:18:30,520 --> 00:18:33,320 Speaker 1: papers about. The second is that if we think about 294 00:18:33,720 --> 00:18:36,280 Speaker 1: the negative yielders, that you invest in bonds and you're 295 00:18:36,280 --> 00:18:41,280 Speaker 1: going to lose money. But we've had debt consolidations, we've 296 00:18:41,320 --> 00:18:46,000 Speaker 1: had demonetizations, confiscations in the past. In the United States, 297 00:18:46,000 --> 00:18:49,680 Speaker 1: we've actually seen some wealth destruction. In the nine thirties, 298 00:18:50,080 --> 00:18:53,520 Speaker 1: we had a ban on individuals holding gold right, and 299 00:18:53,560 --> 00:18:55,560 Speaker 1: that's a near money substitute, or at least it was 300 00:18:55,600 --> 00:18:57,560 Speaker 1: at the time, because we were on the gold standard, 301 00:18:57,880 --> 00:19:01,320 Speaker 1: So these negative yielding in a much order context. It's 302 00:19:01,960 --> 00:19:06,879 Speaker 1: actually we've had these episodes before. Factors will continue to 303 00:19:06,920 --> 00:19:09,440 Speaker 1: have a place in this period. I think you still 304 00:19:09,480 --> 00:19:12,080 Speaker 1: want to buy cheap, you still want to find these trends, 305 00:19:12,400 --> 00:19:15,960 Speaker 1: you want higher quality names probably that's more important than ever. 306 00:19:16,160 --> 00:19:18,439 Speaker 1: And you want to have portfolio resilience. And we can 307 00:19:18,480 --> 00:19:21,639 Speaker 1: hold a combination of factors to help these investors. So 308 00:19:22,320 --> 00:19:25,480 Speaker 1: you mentioned the evolution of factors and the evolution of 309 00:19:25,560 --> 00:19:29,000 Speaker 1: new products. What what do you see coming down the pike? 310 00:19:29,080 --> 00:19:31,520 Speaker 1: What sort of stuff we've been hearing for a long 311 00:19:31,560 --> 00:19:35,520 Speaker 1: time about these one thirty thirty portfolios, these long short 312 00:19:35,600 --> 00:19:38,720 Speaker 1: et f s. What are the next things that factor 313 00:19:38,800 --> 00:19:42,320 Speaker 1: investing is going to drive From the product side, we 314 00:19:42,400 --> 00:19:45,280 Speaker 1: talked about some of these already pushing out these concepts 315 00:19:45,280 --> 00:19:48,440 Speaker 1: from equities to fix income and other multi asset classes. 316 00:19:48,800 --> 00:19:51,760 Speaker 1: But I think the real gains will come from applying 317 00:19:51,840 --> 00:19:55,919 Speaker 1: data and technology. Two. The mom and dad sitting across 318 00:19:55,960 --> 00:20:01,080 Speaker 1: the table from a financial advisor. And my vision is 319 00:20:01,080 --> 00:20:04,800 Speaker 1: that if you're having that conversation with an individual and 320 00:20:04,800 --> 00:20:07,600 Speaker 1: that individual says I'm really worried about losing my job, 321 00:20:08,280 --> 00:20:11,640 Speaker 1: they're making a statement about economic growth, and we can 322 00:20:11,760 --> 00:20:14,960 Speaker 1: have some factors to help hedge that bad outcome. What's 323 00:20:14,960 --> 00:20:18,480 Speaker 1: a day in the life of Andrew Ang, Like, yeah, 324 00:20:18,520 --> 00:20:21,000 Speaker 1: what does that mean? Leading factor investing at black Rock 325 00:20:21,160 --> 00:20:23,440 Speaker 1: means like talk with a lot of people. I have 326 00:20:23,520 --> 00:20:26,359 Speaker 1: the privilege of working with some really talented people, and 327 00:20:26,400 --> 00:20:28,680 Speaker 1: I feel like a little kid in a candy store 328 00:20:28,880 --> 00:20:31,840 Speaker 1: because there's all this great data and technology at Black 329 00:20:31,840 --> 00:20:34,600 Speaker 1: Crock and we can put things to work and introduce 330 00:20:34,640 --> 00:20:38,200 Speaker 1: new products and make it happen and have some factor analytics, 331 00:20:38,280 --> 00:20:40,879 Speaker 1: data and technology all based on factors as well. So 332 00:20:40,960 --> 00:20:42,960 Speaker 1: let's talk a little bit about your book. This is 333 00:20:43,000 --> 00:20:48,080 Speaker 1: a serious um quantitative work. Tell us how the book 334 00:20:48,119 --> 00:20:52,760 Speaker 1: came about, and uh, who's it for. I wrote the 335 00:20:52,800 --> 00:20:59,800 Speaker 1: book after working for several large sovereign institutions, sovereign wealth fronts, 336 00:21:00,160 --> 00:21:03,480 Speaker 1: sovereign pension plans, and I talked all about factors, and 337 00:21:03,520 --> 00:21:08,800 Speaker 1: I wanted to bring all of that knowledge that just 338 00:21:08,920 --> 00:21:11,840 Speaker 1: even a decade two decades ago, were only available to 339 00:21:12,680 --> 00:21:18,040 Speaker 1: really large sophisticated institutions, and I wanted to democratize access. 340 00:21:18,040 --> 00:21:21,159 Speaker 1: In fact, that's our mission statement. It's to democratize the 341 00:21:21,200 --> 00:21:25,119 Speaker 1: broad and persistent democratize access to factors. And this book 342 00:21:26,000 --> 00:21:29,960 Speaker 1: really put into context with case studies based on some 343 00:21:30,119 --> 00:21:33,480 Speaker 1: of those, Uh, some of those institutions how to use 344 00:21:33,520 --> 00:21:39,439 Speaker 1: factors in portfolios. So you said factors plural um and 345 00:21:39,480 --> 00:21:42,760 Speaker 1: you mentioned Gene Farmer before, So the original Farmer French 346 00:21:42,840 --> 00:21:47,520 Speaker 1: model was right. Then we got the five factor model, 347 00:21:47,560 --> 00:21:50,840 Speaker 1: then the seven factor model. And some people have made 348 00:21:50,840 --> 00:21:55,359 Speaker 1: the claim that and I'm a little skeptical that most 349 00:21:55,400 --> 00:21:59,359 Speaker 1: of these are of of really significant value, that there 350 00:21:59,359 --> 00:22:01,760 Speaker 1: are four hun drew to a five factors. Some people 351 00:22:01,800 --> 00:22:04,920 Speaker 1: have said a thousand factors. How many factors are there 352 00:22:04,960 --> 00:22:12,359 Speaker 1: and how many really can be implemented? There are half 353 00:22:12,359 --> 00:22:16,360 Speaker 1: a dozen macro factors and half a dozen style factors. 354 00:22:16,960 --> 00:22:20,400 Speaker 1: Macro factors drive returns across asset classes. The big three 355 00:22:20,400 --> 00:22:24,480 Speaker 1: are economic growth, real rates, and inflation, and they explain 356 00:22:24,960 --> 00:22:29,159 Speaker 1: about eight of the variation of returns across these different 357 00:22:29,160 --> 00:22:32,159 Speaker 1: asset classes. Give us private markets. Give us those three again, 358 00:22:32,480 --> 00:22:38,240 Speaker 1: economic growth, real rates, and inflation. Those are the big three, 359 00:22:39,280 --> 00:22:44,000 Speaker 1: and within each different asset class, within equities, we can 360 00:22:44,080 --> 00:22:47,960 Speaker 1: find pockets of securities that over the long run have 361 00:22:48,080 --> 00:22:51,280 Speaker 1: resulted in higher risk adjusted returns. Those securities that are 362 00:22:51,400 --> 00:22:54,000 Speaker 1: cheap or high quality that we talked about earlier, and 363 00:22:54,040 --> 00:22:58,919 Speaker 1: we can find those same patents in bonds and the commodities. 364 00:22:58,920 --> 00:23:02,119 Speaker 1: We can even find them in private markets like private 365 00:23:02,160 --> 00:23:05,679 Speaker 1: equity and real estate. Those are style factors and they 366 00:23:05,720 --> 00:23:09,520 Speaker 1: operate within an asset class, and in equities we think 367 00:23:09,560 --> 00:23:15,320 Speaker 1: of value, quality, momentum, size, a minimum volatility. Now the 368 00:23:15,440 --> 00:23:19,639 Speaker 1: criteria for these and why there's only like half a 369 00:23:19,680 --> 00:23:23,040 Speaker 1: dozen macro half a dozen style, there's four criteria that 370 00:23:23,080 --> 00:23:28,040 Speaker 1: whittles down the potential hundreds or thousands to just these narrows, 371 00:23:28,040 --> 00:23:31,280 Speaker 1: just this narrow set. The first is that economic rationale 372 00:23:31,280 --> 00:23:34,240 Speaker 1: that we talked about earlier, reward for bearing risks, structural 373 00:23:34,240 --> 00:23:39,520 Speaker 1: and pediment or behavioral bias. We want very long histories 374 00:23:39,600 --> 00:23:43,080 Speaker 1: and that removes basically most of that. A lot of these, 375 00:23:43,119 --> 00:23:46,280 Speaker 1: a lot of these don't don't have decades worth of history, 376 00:23:46,720 --> 00:23:49,760 Speaker 1: and we would like that so that it informs how 377 00:23:49,800 --> 00:23:52,480 Speaker 1: we can build those strategies and offer them. We want 378 00:23:52,600 --> 00:23:57,800 Speaker 1: differentiated returns, particularly with respect to market cap benchmarks, right, 379 00:23:57,880 --> 00:23:59,920 Speaker 1: what is it giving us that that that is different 380 00:24:00,000 --> 00:24:03,000 Speaker 1: And then finally we want and this is a choice 381 00:24:03,040 --> 00:24:05,320 Speaker 1: for black Rock, we want to be able to offer 382 00:24:05,359 --> 00:24:08,359 Speaker 1: these in scale, so that means we can pass on 383 00:24:08,440 --> 00:24:12,720 Speaker 1: low costs to our clients. After him imposing all those 384 00:24:12,760 --> 00:24:16,160 Speaker 1: full criteria, we're only left with that half a dozen 385 00:24:16,200 --> 00:24:19,520 Speaker 1: macro half a dozen stuff quite interesting. So so what 386 00:24:19,720 --> 00:24:24,280 Speaker 1: is next in factor land? Are there any yet undiscovered 387 00:24:24,320 --> 00:24:28,359 Speaker 1: factors out there that might fall into either of these 388 00:24:28,960 --> 00:24:32,480 Speaker 1: um two half dozen groups or have we pretty much 389 00:24:32,520 --> 00:24:34,919 Speaker 1: squeezed all the juice out of the orange at this point. 390 00:24:35,640 --> 00:24:39,240 Speaker 1: There's always continued development, but I think it's a little 391 00:24:39,280 --> 00:24:42,920 Speaker 1: bit like Shakespeare. You know, he wrote some great plays 392 00:24:42,920 --> 00:24:46,160 Speaker 1: and sonnets back in Elizabeth E. Times, did that with 393 00:24:46,400 --> 00:24:49,160 Speaker 1: quill and inc. Right, we still have well, he will 394 00:24:49,200 --> 00:24:52,160 Speaker 1: be writing screenplays today. Right, Perhaps we have some streaming 395 00:24:52,160 --> 00:24:54,359 Speaker 1: TV and other things like that, but there's still character 396 00:24:54,480 --> 00:24:56,919 Speaker 1: and plot. But it's done in different forms. And we 397 00:24:56,960 --> 00:25:01,560 Speaker 1: want to evolve buying cheap finding train, so the implementations 398 00:25:01,560 --> 00:25:03,640 Speaker 1: of cost will change. We can do this better with 399 00:25:03,880 --> 00:25:08,560 Speaker 1: more efficient data and technology to lower transaction costs. We 400 00:25:08,600 --> 00:25:12,320 Speaker 1: would also like to see how we can use them 401 00:25:12,320 --> 00:25:17,040 Speaker 1: in portfolios. Factor analytics, factor allocation that I talked about earlier, Right, 402 00:25:17,119 --> 00:25:19,719 Speaker 1: that's really what's new. But we're always going to have 403 00:25:19,960 --> 00:25:23,199 Speaker 1: these half dozen macro and half dozen style. So you 404 00:25:23,240 --> 00:25:27,400 Speaker 1: wrote a white paper that UM, I want to want 405 00:25:27,520 --> 00:25:30,840 Speaker 1: out about a bit. The title was what does the 406 00:25:30,920 --> 00:25:34,760 Speaker 1: yield curve tell us about GDP growth? And there's a 407 00:25:34,760 --> 00:25:39,240 Speaker 1: professor at UM the University at Duke University who has 408 00:25:39,320 --> 00:25:43,440 Speaker 1: a recession forecasting model which has a perfect track record, 409 00:25:43,520 --> 00:25:46,680 Speaker 1: at least in the limited time it's existed, it's been perfect. 410 00:25:46,760 --> 00:25:50,879 Speaker 1: The fourth factor in his model is the inverted yield 411 00:25:50,880 --> 00:25:54,400 Speaker 1: curve uses the five year in the three months UM 412 00:25:54,560 --> 00:25:57,720 Speaker 1: and only when it's inverted for a substantial period of time, 413 00:25:58,160 --> 00:26:01,879 Speaker 1: which in his measurement is ninety days a full quarter. 414 00:26:02,520 --> 00:26:05,080 Speaker 1: Last week we passed that we've already been inverted for 415 00:26:05,240 --> 00:26:09,080 Speaker 1: that period of time. So I'm curious about what you found. 416 00:26:09,119 --> 00:26:12,720 Speaker 1: What the yield curve means for future GDP growth? He 417 00:26:12,920 --> 00:26:17,320 Speaker 1: suggests it's an indicator of recession twelve to eighteen months later. 418 00:26:17,440 --> 00:26:21,479 Speaker 1: What what did you find? The YU curve has a 419 00:26:21,520 --> 00:26:27,000 Speaker 1: lot of information about future economic activity, and there's always 420 00:26:27,080 --> 00:26:34,640 Speaker 1: been a slowdown after a negative UM. There's always been 421 00:26:34,680 --> 00:26:40,639 Speaker 1: a slowdown following a negative yelk of six quarters afterwards, 422 00:26:40,640 --> 00:26:44,159 Speaker 1: meaning an inversion. There's been actually one false positive, and 423 00:26:44,200 --> 00:26:46,160 Speaker 1: that's in the late nineteen sixties, but there was still 424 00:26:46,200 --> 00:26:48,840 Speaker 1: a slowdown in that period. Now that's an ode paper 425 00:26:48,880 --> 00:26:52,440 Speaker 1: baron that you brought up, and we actually showed that 426 00:26:52,680 --> 00:26:57,320 Speaker 1: in addition to the term spread negative term spread forecasting 427 00:26:57,720 --> 00:27:00,800 Speaker 1: poor economic activity, the level of the interest rate was 428 00:27:00,840 --> 00:27:04,080 Speaker 1: also pretty important too. And interest rates are fairly low 429 00:27:04,160 --> 00:27:07,760 Speaker 1: now and they've actually decreased over the last couple of 430 00:27:07,800 --> 00:27:11,240 Speaker 1: months around the world. The level of that you curve 431 00:27:11,440 --> 00:27:17,399 Speaker 1: also forecasts slowdowns. So it's not just the inversion, but 432 00:27:17,760 --> 00:27:22,280 Speaker 1: inversion from a relatively low level also has a negative 433 00:27:22,280 --> 00:27:27,080 Speaker 1: conta both the level. Low levels predict slowdowns and spreads. 434 00:27:27,320 --> 00:27:30,919 Speaker 1: Negative spreads also predicts So why would low levels predict 435 00:27:30,920 --> 00:27:33,720 Speaker 1: the slowdown? Is it a function of demand for capital 436 00:27:34,200 --> 00:27:37,680 Speaker 1: that's used by an expanding economy or something else? This 437 00:27:38,119 --> 00:27:41,600 Speaker 1: several explanations. See I'll just give one by John Taylor. 438 00:27:41,920 --> 00:27:44,919 Speaker 1: All Right, the Taylor rule? When is that? Is that 439 00:27:45,000 --> 00:27:48,280 Speaker 1: still in effect? I thought we sort of didn't. Didn't 440 00:27:48,280 --> 00:27:51,040 Speaker 1: we repeal the tailor rule. We've used it as the 441 00:27:51,080 --> 00:27:55,280 Speaker 1: basis for many different policy and macro models, just perhaps 442 00:27:55,280 --> 00:27:59,440 Speaker 1: not in its purest form to John Taylor, But it's 443 00:27:59,440 --> 00:28:02,080 Speaker 1: gone through very iterations, and I think the intuition is 444 00:28:02,119 --> 00:28:07,480 Speaker 1: still sound. Policymakers generally will raise interest rates when we're 445 00:28:07,520 --> 00:28:11,119 Speaker 1: in very good times, right Inflation tends to pick up 446 00:28:11,160 --> 00:28:14,240 Speaker 1: there and we want to take the punch bowl away. 447 00:28:14,680 --> 00:28:18,679 Speaker 1: During bad times, policymakers tend to lower interest rates to 448 00:28:18,720 --> 00:28:23,280 Speaker 1: simulate economic activity. And all these types of policy interactions 449 00:28:23,280 --> 00:28:27,480 Speaker 1: will give rise to when bad times come, interest rates 450 00:28:27,480 --> 00:28:30,640 Speaker 1: tend to be low. So that sounds a little bit 451 00:28:30,720 --> 00:28:34,919 Speaker 1: like policymakers are engaging a little bit of market timing themselves. 452 00:28:35,520 --> 00:28:38,480 Speaker 1: Let's talk about another paper of yours where you look 453 00:28:38,600 --> 00:28:44,520 Speaker 1: at factor timing and time series. Can an investor use 454 00:28:44,640 --> 00:28:48,200 Speaker 1: factors as part of a market timing approach? Are there 455 00:28:48,280 --> 00:28:51,960 Speaker 1: better or worse times for some factors? Or should it 456 00:28:52,040 --> 00:28:57,000 Speaker 1: just be full factor diversification across the board. That's a 457 00:28:57,120 --> 00:28:59,840 Speaker 1: paper we just published in the General Portfolio Management not 458 00:29:00,040 --> 00:29:04,400 Speaker 1: so long ago. Investors should start with a long term 459 00:29:04,440 --> 00:29:08,600 Speaker 1: strategic combination too. Lots of factors, don't hold just one. 460 00:29:08,600 --> 00:29:11,160 Speaker 1: If you hold just value, well, I felt it, you 461 00:29:11,320 --> 00:29:14,280 Speaker 1: felt it over the last couple of quarters, it's being painful. 462 00:29:15,080 --> 00:29:19,640 Speaker 1: We want lots of factors for diversification, but around that 463 00:29:19,840 --> 00:29:24,400 Speaker 1: long term strategic multi factor combination. We might think about tilting, 464 00:29:25,200 --> 00:29:27,640 Speaker 1: and I like the word tilting rather than the word timing, 465 00:29:27,640 --> 00:29:31,120 Speaker 1: because sometimes timing has these connotations are really short term 466 00:29:31,160 --> 00:29:35,360 Speaker 1: global macro that's not what we're about. But around those 467 00:29:35,400 --> 00:29:38,640 Speaker 1: strategic benchmarks you might tilt, and the paper gives a 468 00:29:38,680 --> 00:29:41,400 Speaker 1: framework to think about how to do that. So first, 469 00:29:41,760 --> 00:29:45,840 Speaker 1: factors become rich or cheap, just like every asset. So wait, 470 00:29:45,880 --> 00:29:49,440 Speaker 1: so we then within let's say the value factor, which 471 00:29:49,480 --> 00:29:52,480 Speaker 1: is looking at stocks that might be expensive or cheap, 472 00:29:52,880 --> 00:29:56,360 Speaker 1: there are times when that factor itself is expensive or chieved. 473 00:29:56,480 --> 00:30:00,560 Speaker 1: That's correct, So it's a second derivative removed once for um, 474 00:30:00,640 --> 00:30:03,479 Speaker 1: the underlying cheapness of it's. Now I'm gonna blow your 475 00:30:03,480 --> 00:30:06,560 Speaker 1: mind because that's truthful. Momentum momentum also helps. The pilsum 476 00:30:06,600 --> 00:30:11,160 Speaker 1: too has momentum. They are valuam momentum of valid momentum, 477 00:30:11,200 --> 00:30:14,880 Speaker 1: in fact, value momentum of each factor. But that's, by 478 00:30:14,880 --> 00:30:17,040 Speaker 1: the way, that's the most interesting thing I've heard today. 479 00:30:17,040 --> 00:30:19,160 Speaker 1: I just have to share that with you. Now that 480 00:30:19,160 --> 00:30:22,960 Speaker 1: that each of these have a derivative that is reflective, 481 00:30:23,240 --> 00:30:28,240 Speaker 1: it's almost like a mental brought reflexivity um or higher level, 482 00:30:29,040 --> 00:30:32,800 Speaker 1: meta factor, meta factor. Okay, yeah, but so there are 483 00:30:32,880 --> 00:30:37,240 Speaker 1: value and momentum effects. Will call that second one relative strength, 484 00:30:37,440 --> 00:30:40,000 Speaker 1: because we want to measure this trends of these factors 485 00:30:40,360 --> 00:30:43,440 Speaker 1: to each other. I know that stocks can be cheaper 486 00:30:43,520 --> 00:30:46,800 Speaker 1: or more expensive at different times, but I always assumed, Hey, 487 00:30:46,840 --> 00:30:51,000 Speaker 1: the bottom least expensive let's call a third of stocks, 488 00:30:51,720 --> 00:30:54,400 Speaker 1: is always going to be cheaper than everything else. I 489 00:30:54,480 --> 00:30:59,040 Speaker 1: never stopped to think that, sure they're they're relatively inexpensive, 490 00:30:59,080 --> 00:31:02,719 Speaker 1: but on an absolute basis, cheap stocks can be expensive. 491 00:31:03,160 --> 00:31:07,440 Speaker 1: That's that meta value is really quite fascinating. How do 492 00:31:07,480 --> 00:31:10,720 Speaker 1: you incorporate that into what you do? Very that's such 493 00:31:10,760 --> 00:31:15,400 Speaker 1: a really deep comment that you've just made. Because value 494 00:31:15,440 --> 00:31:17,600 Speaker 1: is always cheap, So what do you mean about using 495 00:31:17,680 --> 00:31:21,400 Speaker 1: value for value? So what we really mean here is 496 00:31:21,880 --> 00:31:25,160 Speaker 1: if we take the value factor, how cheap is value 497 00:31:25,480 --> 00:31:29,320 Speaker 1: currently relative to how cheap it's been in the past, 498 00:31:29,400 --> 00:31:32,040 Speaker 1: its own its own history, right, And then we can 499 00:31:32,080 --> 00:31:35,320 Speaker 1: also compare how cheap value is to other factors. And 500 00:31:35,760 --> 00:31:37,480 Speaker 1: if you're a quort, you would call this a time 501 00:31:37,480 --> 00:31:41,320 Speaker 1: series and cross sectional score. And that also applies to 502 00:31:42,120 --> 00:31:45,800 Speaker 1: relative strength or momentum, because momentum, by definition, the momentum 503 00:31:45,800 --> 00:31:48,760 Speaker 1: factor always has the most momentum. So what you really 504 00:31:48,800 --> 00:31:53,000 Speaker 1: mean here is what's the current trend of momentum relative 505 00:31:53,080 --> 00:31:56,800 Speaker 1: to the past trends that momentum has had. And then 506 00:31:57,240 --> 00:32:01,520 Speaker 1: once the relative strength of my even factor relative to 507 00:32:02,120 --> 00:32:04,880 Speaker 1: the trends of other factors. Again, it's this time series 508 00:32:04,920 --> 00:32:07,000 Speaker 1: and cross sectional. So in other words, it's which factor 509 00:32:07,160 --> 00:32:10,800 Speaker 1: is doing the best relative to other factors. That's right, 510 00:32:10,840 --> 00:32:13,320 Speaker 1: And so we actually put all these and one of 511 00:32:13,320 --> 00:32:16,640 Speaker 1: the you talked about a bit before about the frontiers 512 00:32:16,680 --> 00:32:21,720 Speaker 1: of factor investing is factor investing is really about taking 513 00:32:21,800 --> 00:32:25,440 Speaker 1: active insights things like value and momentum, but we can 514 00:32:25,560 --> 00:32:29,600 Speaker 1: also apply them in other active ways. Factor tilting is 515 00:32:29,600 --> 00:32:31,800 Speaker 1: one of those ways. So so let's talk about that, 516 00:32:32,320 --> 00:32:35,600 Speaker 1: because years ago there were a number of models that 517 00:32:35,640 --> 00:32:38,920 Speaker 1: came out and they didn't do factor tilting. They tried 518 00:32:38,960 --> 00:32:42,760 Speaker 1: to do sector tilting. They would rotate within the SMP five, 519 00:32:43,560 --> 00:32:47,680 Speaker 1: within the different groups that would go from technology to healthcare, 520 00:32:48,360 --> 00:32:53,200 Speaker 1: um to to finance, and they always sounded great on paper, 521 00:32:53,560 --> 00:32:55,920 Speaker 1: and then in the real world they didn't do so well. 522 00:32:56,320 --> 00:33:01,760 Speaker 1: So on a on on this sort of factor tilting model, 523 00:33:01,880 --> 00:33:06,320 Speaker 1: how can you capture in real time those benefits. Aren't 524 00:33:06,320 --> 00:33:08,239 Speaker 1: you always going to be lagging? What do you use 525 00:33:08,280 --> 00:33:10,360 Speaker 1: as a signal to say, all right, now is the 526 00:33:10,480 --> 00:33:14,920 Speaker 1: time to over emphasize cap as opposed to quality or 527 00:33:16,560 --> 00:33:19,320 Speaker 1: is there too much of a lag to capture that? 528 00:33:19,720 --> 00:33:21,920 Speaker 1: Or do you get enough of the heads up? Hey, 529 00:33:22,000 --> 00:33:24,880 Speaker 1: here's the direction this is shifting. You can move some 530 00:33:24,920 --> 00:33:28,600 Speaker 1: of the portfolio quickly enough to take advantage of it. Well, 531 00:33:28,640 --> 00:33:32,000 Speaker 1: I believe all types of tilting it they're hot and 532 00:33:32,320 --> 00:33:36,720 Speaker 1: factor tilting. It's hard to but done in a discipline way. 533 00:33:36,720 --> 00:33:40,640 Speaker 1: There's a couple of differences to country or sector rotation, 534 00:33:40,880 --> 00:33:44,080 Speaker 1: so they're nice compliments. So often we like to apply 535 00:33:44,280 --> 00:33:48,600 Speaker 1: factors within a particular sector or within a particular region, 536 00:33:48,880 --> 00:33:52,120 Speaker 1: and so that gives room for factor rotation to sit 537 00:33:52,280 --> 00:33:56,960 Speaker 1: side by side with these others. Second, is that exposure 538 00:33:57,040 --> 00:34:00,360 Speaker 1: to sectors over the long run. In fact, actually the 539 00:34:00,440 --> 00:34:03,480 Speaker 1: capa and works fine. There are some academic papers on 540 00:34:03,560 --> 00:34:07,560 Speaker 1: that too. If we take a strategic portfolio that bias 541 00:34:07,680 --> 00:34:11,200 Speaker 1: cheap finds, trends finds, high quality names, right, all those 542 00:34:11,239 --> 00:34:16,719 Speaker 1: factors those are long term determinants or performance. Whereas static 543 00:34:17,400 --> 00:34:21,879 Speaker 1: sector exposure, well, actually the market has sectors might as well, 544 00:34:21,920 --> 00:34:26,239 Speaker 1: do that, but these factors, the strategic tilt gives you 545 00:34:26,280 --> 00:34:29,719 Speaker 1: an uplift over the long run innovat of itself, and 546 00:34:29,760 --> 00:34:33,120 Speaker 1: then around that you might incrementally add returns with the 547 00:34:33,160 --> 00:34:36,399 Speaker 1: factor rotation. And the third difference I think is that 548 00:34:36,760 --> 00:34:40,520 Speaker 1: with these factors we can employ them in different ways. 549 00:34:41,040 --> 00:34:44,160 Speaker 1: So we want to do this transparently. We have this paper, 550 00:34:44,480 --> 00:34:47,520 Speaker 1: we've introduced some some products. We want to be active 551 00:34:47,560 --> 00:34:50,200 Speaker 1: with factors. Let's not just use one signal. Let's look 552 00:34:50,239 --> 00:34:52,680 Speaker 1: at definitely and how cheap something is. We talked about 553 00:34:52,680 --> 00:34:55,760 Speaker 1: relative strength as well. We'll use the economic regime measures 554 00:34:55,800 --> 00:34:58,520 Speaker 1: of the opportunity set or dispersion. But we want to 555 00:34:58,600 --> 00:35:01,880 Speaker 1: use all of those insights to other m HM. So 556 00:35:01,880 --> 00:35:06,160 Speaker 1: so let's talk about something UM not market timing, but 557 00:35:06,520 --> 00:35:11,080 Speaker 1: factor tilts. If I had could have my way, I 558 00:35:11,160 --> 00:35:15,600 Speaker 1: would at the end of a recession lean as heavily 559 00:35:15,680 --> 00:35:18,520 Speaker 1: towards growth as I could. Not always easy to do. 560 00:35:18,560 --> 00:35:21,600 Speaker 1: Everybody is miserable. No one wants to hear you. In 561 00:35:21,719 --> 00:35:24,319 Speaker 1: March O nine say okay, now is the time to 562 00:35:24,360 --> 00:35:28,319 Speaker 1: buy the growth stocks UM that have done nothing but 563 00:35:28,440 --> 00:35:31,120 Speaker 1: get killed for the past two years and towards the 564 00:35:31,280 --> 00:35:34,520 Speaker 1: end of the cycle, and that assumes you know in 565 00:35:34,600 --> 00:35:37,160 Speaker 1: the end of the cycle is in advance. Typically we 566 00:35:37,200 --> 00:35:40,840 Speaker 1: don't know till after the fact. Gradually move that tilt 567 00:35:40,880 --> 00:35:45,200 Speaker 1: away from growth towards value, because if your charges, you 568 00:35:45,239 --> 00:35:47,960 Speaker 1: must be fully invested at all times. On the equity side, 569 00:35:48,440 --> 00:35:51,719 Speaker 1: the assumption is that in any sort of recession, be 570 00:35:51,840 --> 00:35:55,480 Speaker 1: it a mild recession or something like oh, eight oh 571 00:35:55,560 --> 00:36:00,320 Speaker 1: nine or two thousand oh two, you're gonna see growth 572 00:36:00,360 --> 00:36:03,319 Speaker 1: gets relaxed and value is going to hold up much better. 573 00:36:03,800 --> 00:36:10,600 Speaker 1: And I can't help but recall hearing this Warren Buffett 574 00:36:10,640 --> 00:36:13,000 Speaker 1: guy is washed up. That sort of value crap is 575 00:36:13,040 --> 00:36:15,960 Speaker 1: never gonna work again. And as people said, that was 576 00:36:16,040 --> 00:36:20,720 Speaker 1: really when he began another period of huge out performance. So, first, 577 00:36:21,120 --> 00:36:24,960 Speaker 1: is that something that you can accomplish with tilts? And second, 578 00:36:25,320 --> 00:36:28,080 Speaker 1: how do you get the timing right at the end 579 00:36:28,160 --> 00:36:33,239 Speaker 1: of a market crash. It's pretty clear, Um, when you're 580 00:36:33,280 --> 00:36:37,200 Speaker 1: closer let's let's say, closer to the end than the beginning. Um, 581 00:36:37,239 --> 00:36:40,160 Speaker 1: So whether it was January O nine or juneo nine, 582 00:36:41,120 --> 00:36:44,399 Speaker 1: anywhere in that range, you're you're pretty close. You're you're 583 00:36:44,480 --> 00:36:46,400 Speaker 1: much closer to the end of that than the beginning. 584 00:36:47,000 --> 00:36:50,200 Speaker 1: How how does one make that determination that we want 585 00:36:50,200 --> 00:36:52,680 Speaker 1: to tilt towards growth here and here's how to do it. 586 00:36:53,040 --> 00:36:55,480 Speaker 1: And then at the other end of the cycle, Hey, 587 00:36:55,560 --> 00:36:58,279 Speaker 1: we want to tilt more towards value here and here 588 00:36:58,280 --> 00:37:01,000 Speaker 1: are the signals that send us. How would one do that. 589 00:37:01,840 --> 00:37:07,680 Speaker 1: Let's remember first, diversification, diversification, diversification, that's the key, so 590 00:37:07,719 --> 00:37:10,760 Speaker 1: you have it's really hard too, I think, to to 591 00:37:10,760 --> 00:37:14,040 Speaker 1: to call anything with precision or make decisions about individual 592 00:37:14,160 --> 00:37:17,560 Speaker 1: factors or any type of investment. Diversification is that key, 593 00:37:17,560 --> 00:37:21,719 Speaker 1: and that provides that long term strategic benchmark. But around that, 594 00:37:21,880 --> 00:37:25,080 Speaker 1: if you have the rest tolerance and the capability and 595 00:37:25,160 --> 00:37:30,240 Speaker 1: be active with factors, then would like to use information 596 00:37:30,239 --> 00:37:33,000 Speaker 1: about how cheap a given factor is. We'll see if 597 00:37:33,040 --> 00:37:36,319 Speaker 1: the factor is trending up right versus trending down. In fact, 598 00:37:36,400 --> 00:37:39,040 Speaker 1: value has been trending down over the past couple of 599 00:37:39,040 --> 00:37:43,120 Speaker 1: of quarters, but value is cheap today. Would also like 600 00:37:43,200 --> 00:37:44,800 Speaker 1: to see where we are in the economic cycle. The 601 00:37:44,840 --> 00:37:47,080 Speaker 1: fact that we're in that late stage where we said 602 00:37:47,120 --> 00:37:51,040 Speaker 1: that value firms tend to underperform. That's not very favorable 603 00:37:51,160 --> 00:37:55,760 Speaker 1: to value. We also look at dispersion. Dispersion for value, 604 00:37:56,360 --> 00:37:59,480 Speaker 1: it's okay, but it doesn't scream like it's a it's 605 00:37:59,480 --> 00:38:02,640 Speaker 1: a big I. We use all of those together and 606 00:38:02,680 --> 00:38:06,560 Speaker 1: then we'll have an aggregate view on these different factors. 607 00:38:07,680 --> 00:38:10,560 Speaker 1: Quite quite interesting. There were a few other questions I 608 00:38:10,640 --> 00:38:13,759 Speaker 1: want to get to before we get to our standard 609 00:38:14,400 --> 00:38:19,759 Speaker 1: um question. We we mentioned value stocks underperforming. I saw 610 00:38:19,840 --> 00:38:23,760 Speaker 1: something recently that said they've underperformed for thirty five years? 611 00:38:24,000 --> 00:38:27,560 Speaker 1: Is that remote? Well, that seems wrong, doesn't it? Even? 612 00:38:27,560 --> 00:38:29,680 Speaker 1: In fact, if I'll performed in the last ten years, 613 00:38:29,800 --> 00:38:33,200 Speaker 1: but they've been difficult periods under the past past decade, 614 00:38:33,360 --> 00:38:36,320 Speaker 1: growth is outperformed in the past. I had actually values 615 00:38:36,360 --> 00:38:41,080 Speaker 1: done quite well. Value since oh not? But value, yes, 616 00:38:41,440 --> 00:38:46,600 Speaker 1: value over the past uh two years has suffered. Okay, 617 00:38:46,680 --> 00:38:50,360 Speaker 1: that's interesting though. I I have looked at value as 618 00:38:51,000 --> 00:38:54,560 Speaker 1: let me rephrase that. I've looked at growth as doing 619 00:38:54,640 --> 00:38:58,520 Speaker 1: exceedingly well since the end of the financial crisis. Think 620 00:38:58,560 --> 00:39:02,080 Speaker 1: about Amazon at dollars and Apple at twelve dollars or 621 00:39:02,080 --> 00:39:06,880 Speaker 1: whatever the prices were, and they've all exploded, and I 622 00:39:06,920 --> 00:39:11,200 Speaker 1: guess they're categorized as growth. Although with those prices you 623 00:39:11,239 --> 00:39:13,440 Speaker 1: can really call those value stacks. You know, that's a 624 00:39:13,480 --> 00:39:17,080 Speaker 1: great a great point. That comes one of the topics 625 00:39:17,080 --> 00:39:21,400 Speaker 1: that I wrote about recently in my blog Andrew's Angle, 626 00:39:21,480 --> 00:39:25,680 Speaker 1: and it's growth. That's not the opposite of value, all right, 627 00:39:25,760 --> 00:39:28,560 Speaker 1: And we kind of used the word well, it's certainly 628 00:39:28,640 --> 00:39:33,719 Speaker 1: value for cheap. We've used the word growth to denote expensive. 629 00:39:33,880 --> 00:39:38,080 Speaker 1: But actually there's two other connotations of growth which are 630 00:39:38,120 --> 00:39:41,080 Speaker 1: quite distinct from the opposite of value. I mean, the 631 00:39:41,120 --> 00:39:43,680 Speaker 1: first one is that a lot of growth managers will 632 00:39:44,080 --> 00:39:47,439 Speaker 1: search for trends, and you'd actually like to a trend 633 00:39:47,480 --> 00:39:51,360 Speaker 1: to be sustainable, and that's an aspect of momentum investing, 634 00:39:51,800 --> 00:39:54,880 Speaker 1: and that's rewarded over the long run. Another aspect of 635 00:39:55,040 --> 00:39:58,000 Speaker 1: growth is something that you alluded to, is like, what's 636 00:39:58,000 --> 00:40:01,759 Speaker 1: the quality actually behind that? And indeed, if you look 637 00:40:01,800 --> 00:40:06,400 Speaker 1: at many growth funds, certainly they will load many of 638 00:40:06,440 --> 00:40:11,640 Speaker 1: them on momentum and quality factors. Growth itself is not 639 00:40:11,680 --> 00:40:13,719 Speaker 1: the opposite of value. But I think you don't want 640 00:40:13,719 --> 00:40:19,080 Speaker 1: to buy expensive. If a stock does tend to be 641 00:40:19,560 --> 00:40:23,359 Speaker 1: more expensive, that is not value. It might be justifiable 642 00:40:23,400 --> 00:40:25,879 Speaker 1: because it might have aspects of quality or momentum in there. 643 00:40:26,040 --> 00:40:28,560 Speaker 1: So when you are defining something as a growth stock 644 00:40:28,640 --> 00:40:31,640 Speaker 1: or a value stock, you know my frame of references. 645 00:40:31,760 --> 00:40:34,839 Speaker 1: There's the SMP five growth group and the SMP five 646 00:40:34,920 --> 00:40:37,600 Speaker 1: hundred value group, and never the twins shall meet. But 647 00:40:37,719 --> 00:40:40,800 Speaker 1: I suspect you might take issue with some of the 648 00:40:40,800 --> 00:40:42,680 Speaker 1: stocks they call growth in something, and I think it's 649 00:40:42,680 --> 00:40:45,160 Speaker 1: a little bit more nuanced. I would call the first 650 00:40:45,160 --> 00:40:49,160 Speaker 1: generation exactly just splitting the thing into two, and today 651 00:40:49,200 --> 00:40:52,480 Speaker 1: we would think a little bit harder, and many stocks 652 00:40:52,480 --> 00:40:56,000 Speaker 1: will have aspects of multiple factors within that same stock. 653 00:40:56,640 --> 00:40:58,879 Speaker 1: So let's talk a little bit about back testing. We're 654 00:40:58,880 --> 00:41:01,719 Speaker 1: really gonna go deep into the weeds here. Um. It 655 00:41:01,840 --> 00:41:04,440 Speaker 1: seems that a lot of back tests show these great 656 00:41:04,520 --> 00:41:09,160 Speaker 1: returns for different combinations of factors, and then implementing them 657 00:41:09,160 --> 00:41:13,680 Speaker 1: in the real world becomes challenging. You mentioned the problems 658 00:41:13,719 --> 00:41:19,160 Speaker 1: with organizations and getting everybody pulling in the same direction. Um, 659 00:41:19,200 --> 00:41:23,320 Speaker 1: But there have been instances of small um hedge funds 660 00:41:23,400 --> 00:41:27,800 Speaker 1: quantitative hedge funds that try to implement these and momentum 661 00:41:27,840 --> 00:41:33,319 Speaker 1: is a perfect example. Momentum has some real application in 662 00:41:33,760 --> 00:41:37,240 Speaker 1: real portfolios, but it seems the back tests are always 663 00:41:37,320 --> 00:41:40,680 Speaker 1: much better than the actual implementation. What is it about 664 00:41:41,040 --> 00:41:44,600 Speaker 1: momentum and some of these other factors that makes it 665 00:41:44,680 --> 00:41:51,120 Speaker 1: so challenging to capture what theory says in practice, momentum 666 00:41:51,200 --> 00:41:55,920 Speaker 1: has pretty high turnover, So a momentum funds run at 667 00:41:55,920 --> 00:42:03,000 Speaker 1: turnover above significantly about Because of that, transaction costs are crucial. 668 00:42:03,680 --> 00:42:07,440 Speaker 1: So you see some research in the literature that says, actually, 669 00:42:07,560 --> 00:42:11,960 Speaker 1: we can't really do momentum and practice, and some others 670 00:42:11,960 --> 00:42:14,360 Speaker 1: that will say, well, if you're very good at transaction 671 00:42:14,480 --> 00:42:20,799 Speaker 1: costs optimization and you have access to transaction cost minimization 672 00:42:21,600 --> 00:42:26,080 Speaker 1: in your execution, then momentum will be a favorable and 673 00:42:26,440 --> 00:42:31,200 Speaker 1: profitable factor. So it's really key that you have to 674 00:42:31,239 --> 00:42:33,960 Speaker 1: really look at the details once you implement a factor. 675 00:42:34,080 --> 00:42:36,479 Speaker 1: The devil is always in the details. Let's let's let's 676 00:42:36,480 --> 00:42:40,440 Speaker 1: look at another one. Theoretically, high beta stocks should do 677 00:42:40,600 --> 00:42:45,600 Speaker 1: really well, but your research in as implemented in black 678 00:42:45,680 --> 00:42:50,600 Speaker 1: Rock has found low volatility stocks have done well. Why 679 00:42:50,760 --> 00:42:53,560 Speaker 1: is it that the high beta stocks aren't capturing those 680 00:42:53,560 --> 00:42:58,200 Speaker 1: gains once you have a portfolio implement implementation, it's the 681 00:42:58,239 --> 00:43:00,960 Speaker 1: low vall stocks that seem to be doing better. Yeah, 682 00:43:01,000 --> 00:43:03,319 Speaker 1: and this is a paper that I wrote in the 683 00:43:03,360 --> 00:43:08,000 Speaker 1: two thousands, and this paper, I'm lucky and very fortunate, 684 00:43:08,440 --> 00:43:11,400 Speaker 1: has played a really important role in building out the 685 00:43:11,440 --> 00:43:16,160 Speaker 1: minimum volatility and factor industry more broadly, and you've hit 686 00:43:16,280 --> 00:43:20,200 Speaker 1: on the key note here that in theory we should 687 00:43:20,239 --> 00:43:24,440 Speaker 1: have higher risk stocks should have higher returns, but actually 688 00:43:25,000 --> 00:43:28,680 Speaker 1: we found the opposite. And in the paper my co 689 00:43:28,760 --> 00:43:31,880 Speaker 1: authors and I said, the higher risk stocks have quote 690 00:43:31,920 --> 00:43:37,520 Speaker 1: abysmally low returns unquote abysmally low. And if we rank 691 00:43:37,680 --> 00:43:40,879 Speaker 1: stocks based on risk, and we did this by volatility 692 00:43:40,920 --> 00:43:43,520 Speaker 1: idios and critic and total volaty of the paper, subsequent 693 00:43:43,560 --> 00:43:46,600 Speaker 1: papers did this by beta or downside risk measures. The 694 00:43:46,680 --> 00:43:51,920 Speaker 1: general pattern is that stocks have the same expected return 695 00:43:53,320 --> 00:43:57,040 Speaker 1: and then as the volatility increases, there's a very steep 696 00:43:57,160 --> 00:44:01,160 Speaker 1: drop off in returns for the very high risk stocks. 697 00:44:02,000 --> 00:44:05,880 Speaker 1: And that's actually this low volatility effect. If you construct 698 00:44:05,880 --> 00:44:09,160 Speaker 1: a portfolio of minimum volatility, and you can do that 699 00:44:09,200 --> 00:44:12,480 Speaker 1: by holding low data stocks or stocks with low idiosyncratic risk, 700 00:44:12,600 --> 00:44:16,480 Speaker 1: or both, you form a portfolio of low volatility that 701 00:44:16,600 --> 00:44:19,440 Speaker 1: gives you the same return over the long run as 702 00:44:19,480 --> 00:44:22,640 Speaker 1: the market, but it does so with reduced risk. The 703 00:44:22,680 --> 00:44:25,680 Speaker 1: shop ratio is high not because of the numerator of 704 00:44:25,760 --> 00:44:29,080 Speaker 1: the higher expected return, but it's because of the decrease 705 00:44:29,120 --> 00:44:32,319 Speaker 1: in the denominator the reduced risk. So if someone were 706 00:44:32,360 --> 00:44:34,120 Speaker 1: to come to me and say, listen, I could give 707 00:44:34,160 --> 00:44:39,040 Speaker 1: you market returns, but much lower draw downs, much lower volatility. 708 00:44:39,080 --> 00:44:41,080 Speaker 1: Of course I want to say, I want some of that. 709 00:44:41,400 --> 00:44:43,640 Speaker 1: If you're not going to get out performance for the 710 00:44:43,719 --> 00:44:48,040 Speaker 1: same um volatility, well the same performance for less volatility. 711 00:44:48,560 --> 00:44:52,440 Speaker 1: That seems like it's much more livable for the average investor. 712 00:44:52,719 --> 00:44:54,680 Speaker 1: And I think that's one of the great benefits for 713 00:44:54,760 --> 00:44:58,440 Speaker 1: minimum volatility strategies is it just helps an investor stay 714 00:44:58,480 --> 00:45:01,920 Speaker 1: the course. So you're an subject to those tremendous swings, 715 00:45:01,960 --> 00:45:04,920 Speaker 1: particularly on the downside, and we can mitigate some of 716 00:45:04,960 --> 00:45:09,280 Speaker 1: that downside risk with these minimum volatility strategies. Upside downside 717 00:45:09,280 --> 00:45:12,440 Speaker 1: capture ratios for minimum volatility alright, you well, it's all 718 00:45:12,480 --> 00:45:16,360 Speaker 1: about trying to uh participate in as few as possible 719 00:45:16,400 --> 00:45:21,920 Speaker 1: of these drawdowns. It's around fifty downside and upside for 720 00:45:22,080 --> 00:45:26,320 Speaker 1: these downside upside risk capture issues. That that's really quite interesting. 721 00:45:27,000 --> 00:45:30,680 Speaker 1: Um So one of the questions I mentioned to somebody 722 00:45:30,680 --> 00:45:34,040 Speaker 1: I was speaking to you, and they asked a really 723 00:45:34,080 --> 00:45:39,640 Speaker 1: interesting question. Do you consider factor indexes to be closer 724 00:45:39,680 --> 00:45:43,560 Speaker 1: to the active spectrum or closer to the passive end 725 00:45:43,640 --> 00:45:46,719 Speaker 1: of the spectrum. Where where do you put factor investing 726 00:45:47,320 --> 00:45:50,200 Speaker 1: on that continuum from active to passive? Oh, this is 727 00:45:50,239 --> 00:45:54,640 Speaker 1: another one of these uh yes questions. That's right. You 728 00:45:54,680 --> 00:45:56,239 Speaker 1: know that this is a bugbear of mine. I have 729 00:45:56,280 --> 00:46:00,200 Speaker 1: to say barriers that everything is active and it's just 730 00:46:00,640 --> 00:46:03,280 Speaker 1: a question of greater or lescent degree. I totally agree. 731 00:46:03,320 --> 00:46:07,800 Speaker 1: I I've written and discussed that even the basic SMP 732 00:46:07,880 --> 00:46:10,360 Speaker 1: five hundreds somebody made. That's right. That's a bunch of 733 00:46:10,400 --> 00:46:13,160 Speaker 1: active decisions about one market cap rated and where do 734 00:46:13,200 --> 00:46:15,680 Speaker 1: you draw the what's the free float and what gets 735 00:46:15,680 --> 00:46:17,920 Speaker 1: in there? Right? And then while do you use the 736 00:46:18,000 --> 00:46:20,719 Speaker 1: SMP five founderversus some other index? Right? And then you 737 00:46:20,760 --> 00:46:23,320 Speaker 1: know when we go to other asset classes, you know 738 00:46:23,400 --> 00:46:26,640 Speaker 1: it's almost all active implementation. Right. So I think I 739 00:46:26,680 --> 00:46:29,200 Speaker 1: would like to rephrase that question, if I may, on 740 00:46:29,840 --> 00:46:35,000 Speaker 1: the difference between index or average and then taking um 741 00:46:35,280 --> 00:46:40,120 Speaker 1: deviations from there. And in this context, factors are absolutely active. 742 00:46:40,280 --> 00:46:43,719 Speaker 1: We're tilting towards broad and persistent sources of returns. We 743 00:46:43,760 --> 00:46:46,120 Speaker 1: don't want to hold a market cup. Folil would favor 744 00:46:46,600 --> 00:46:51,960 Speaker 1: overweighting stocks that have low prices relative to intrinsic value. 745 00:46:52,000 --> 00:46:53,800 Speaker 1: Those stocks that are trending up right, those stocks of 746 00:46:53,880 --> 00:46:57,919 Speaker 1: high quality earnings, and those are active decisions. What we're 747 00:46:57,960 --> 00:47:01,520 Speaker 1: doing it in a transparent way. It's low cost, we 748 00:47:01,560 --> 00:47:05,120 Speaker 1: can put it into an easy to access fund, right, 749 00:47:05,160 --> 00:47:08,600 Speaker 1: and we can put these insights into multiple asset classes too. 750 00:47:08,719 --> 00:47:11,120 Speaker 1: So you keep referencing this is being done in a 751 00:47:11,200 --> 00:47:16,600 Speaker 1: transparent way. Why is that important? Because I look at 752 00:47:16,680 --> 00:47:21,400 Speaker 1: places like the Shore or renaissance technologies that have generated 753 00:47:21,400 --> 00:47:25,919 Speaker 1: out performance for decades, they're not transparent. Those are their 754 00:47:26,040 --> 00:47:30,680 Speaker 1: secret sauce that goes into their alpha generation. Why does 755 00:47:30,719 --> 00:47:33,719 Speaker 1: black Rock feel we're creating something and we want to 756 00:47:33,760 --> 00:47:38,720 Speaker 1: be completely transparent in this product. I believe in active, 757 00:47:39,200 --> 00:47:43,120 Speaker 1: I believe in alpha, and I define these factors as 758 00:47:43,160 --> 00:47:47,000 Speaker 1: broad you see them in many places and persistently rewarded. 759 00:47:47,080 --> 00:47:50,000 Speaker 1: We've got decades of academic research, so is this a 760 00:47:50,160 --> 00:47:54,680 Speaker 1: peer reviewed approach to invest in now? Alpha is actually 761 00:47:54,719 --> 00:47:58,520 Speaker 1: not broad and persistent, right requires specialized skills like the 762 00:47:58,680 --> 00:48:02,240 Speaker 1: firms that you've talked about. Alpham two will use sophisticated 763 00:48:02,280 --> 00:48:04,680 Speaker 1: techniques with big data and machine learning. You could have 764 00:48:04,719 --> 00:48:09,799 Speaker 1: a fundamental approach that news a lot about just a 765 00:48:09,840 --> 00:48:13,919 Speaker 1: few stocks. The complete opposite of broad and those when 766 00:48:13,920 --> 00:48:16,400 Speaker 1: you find those skills, you should reward them. Sometimes you 767 00:48:16,480 --> 00:48:19,920 Speaker 1: might be able to generate alpha insights by taking advantage 768 00:48:19,960 --> 00:48:24,040 Speaker 1: of very short term high frequency market dislocations. When we 769 00:48:24,120 --> 00:48:26,200 Speaker 1: find that school, we should pay up for it. But 770 00:48:26,280 --> 00:48:29,120 Speaker 1: those things that have been in the literature for decades, 771 00:48:29,680 --> 00:48:32,759 Speaker 1: that have been well studied, that the game is all 772 00:48:32,800 --> 00:48:36,880 Speaker 1: about implementation and efficiency, well, I don't think we should 773 00:48:36,880 --> 00:48:39,640 Speaker 1: be paying very expensive fees for that. We should be 774 00:48:39,680 --> 00:48:44,080 Speaker 1: giving control to the client. We should be paying less 775 00:48:44,120 --> 00:48:46,960 Speaker 1: and getting more. And that's where factors come in. So 776 00:48:46,960 --> 00:48:49,799 Speaker 1: so where does the transparency on some of these new 777 00:48:49,880 --> 00:48:54,400 Speaker 1: models come in? Why share your findings as opposed to 778 00:48:54,520 --> 00:49:00,560 Speaker 1: keeping it secret. We believe in sharing, and we know 779 00:49:00,640 --> 00:49:03,200 Speaker 1: that these factors are going to endure because of that 780 00:49:03,280 --> 00:49:06,440 Speaker 1: economic rationale. Right, there's always going to be the reward 781 00:49:06,480 --> 00:49:09,239 Speaker 1: for bearing risk. Unless these structural impediments get removed, they're 782 00:49:09,280 --> 00:49:11,520 Speaker 1: going to be there. And investors, well, they're going to 783 00:49:11,600 --> 00:49:14,439 Speaker 1: be investors. There's going to be these behavioral biases as 784 00:49:14,520 --> 00:49:19,480 Speaker 1: long as these economic rationales endure, these factors are going 785 00:49:19,520 --> 00:49:22,160 Speaker 1: to be with us. They're going to be cyclical. Absolutely, 786 00:49:22,440 --> 00:49:24,800 Speaker 1: so sometimes there might be room for a factor tilting. 787 00:49:25,200 --> 00:49:27,040 Speaker 1: But these factors are going to be with us for 788 00:49:27,120 --> 00:49:30,640 Speaker 1: decades to come, and let's share this and democratize access 789 00:49:30,680 --> 00:49:33,520 Speaker 1: to all of this. That's our purpose, and we can 790 00:49:33,560 --> 00:49:37,080 Speaker 1: do that so that you understand what's inside, how we 791 00:49:37,239 --> 00:49:39,759 Speaker 1: exactly buy cheap and we want to make sure that 792 00:49:39,880 --> 00:49:42,000 Speaker 1: you see it. So sometimes you might want to have 793 00:49:42,480 --> 00:49:46,239 Speaker 1: position level information available. It helps you fit that with 794 00:49:46,280 --> 00:49:48,399 Speaker 1: the rest of your portfolio, or integrate it with data 795 00:49:48,440 --> 00:49:51,520 Speaker 1: and technology, and you might have better risk management. I 796 00:49:51,560 --> 00:49:55,040 Speaker 1: think that approach is unusual. Not a lot of firms 797 00:49:55,040 --> 00:49:58,800 Speaker 1: the size of black Rock are comfortable sharing their research. 798 00:49:59,200 --> 00:50:02,279 Speaker 1: Although I get us. Black Rock could say, hey, we're 799 00:50:02,280 --> 00:50:05,720 Speaker 1: so big, we're so efficient. Here here's the secret source. 800 00:50:06,040 --> 00:50:08,320 Speaker 1: You can never do this as cheaply as we could. Anyway, 801 00:50:09,000 --> 00:50:11,040 Speaker 1: I'm that's my words. I'm not under means, but word. 802 00:50:11,120 --> 00:50:14,000 Speaker 1: We always put the client first. So but you got 803 00:50:14,080 --> 00:50:17,200 Speaker 1: I mean, not to the clients, to competitors, to other 804 00:50:17,280 --> 00:50:19,480 Speaker 1: people who might say, oh, here's a new paper from 805 00:50:19,520 --> 00:50:21,719 Speaker 1: black Rock, let's see if we can find something to 806 00:50:21,840 --> 00:50:26,040 Speaker 1: implement from this. I find it to be a typical, 807 00:50:26,280 --> 00:50:29,560 Speaker 1: although I guess that's not Lots of firms published white 808 00:50:29,560 --> 00:50:32,160 Speaker 1: papers lots of firms do that, so maybe I'm over 809 00:50:32,239 --> 00:50:36,560 Speaker 1: emphasizing the transparency aspect of it. I just find that 810 00:50:36,640 --> 00:50:42,120 Speaker 1: intriguing that the secret source from a particular group of funds. 811 00:50:42,680 --> 00:50:45,279 Speaker 1: You guys are that open with and I guess I think, 812 00:50:45,320 --> 00:50:47,000 Speaker 1: I think maybe you would agree with my wife once 813 00:50:47,000 --> 00:50:49,240 Speaker 1: you called me a hypocrite because I'm I'm the ultimate 814 00:50:49,239 --> 00:50:51,440 Speaker 1: true believer. There you go. So so that makes a 815 00:50:51,440 --> 00:50:53,640 Speaker 1: lot of sense to me. So let me jump to 816 00:50:53,680 --> 00:50:56,920 Speaker 1: my favorite questions. This is our speed round, and we 817 00:50:57,000 --> 00:51:00,920 Speaker 1: asked this of all our guests. UM, let's start with 818 00:51:00,960 --> 00:51:04,160 Speaker 1: a simple question. What was the first car you've ever owned? 819 00:51:04,280 --> 00:51:09,400 Speaker 1: Year making model Toyota Corolla three one point six Leader, 820 00:51:09,920 --> 00:51:12,680 Speaker 1: kind of maroon color, which was really fortunate because the 821 00:51:12,719 --> 00:51:15,520 Speaker 1: amount of rust and there you kind of you couldn't see. 822 00:51:16,520 --> 00:51:19,040 Speaker 1: They always made good cars, but in the early days, 823 00:51:19,160 --> 00:51:22,080 Speaker 1: that was a very thin metal and it was a rustbucket. 824 00:51:22,560 --> 00:51:24,680 Speaker 1: It happens a lot. I remember that drove that car 825 00:51:24,719 --> 00:51:29,560 Speaker 1: across Australia. Really, Um, where you originally from? I was 826 00:51:30,000 --> 00:51:35,840 Speaker 1: born in Malaysia, and uh during the late nineteen sixties 827 00:51:35,880 --> 00:51:39,600 Speaker 1: and early nineteen seventies, Malaysia went through a series of 828 00:51:39,680 --> 00:51:43,200 Speaker 1: race rights and my parents wanted somewhere safe to raise 829 00:51:43,280 --> 00:51:47,560 Speaker 1: their family. And then White Australia Policy ended and that 830 00:51:47,640 --> 00:51:50,600 Speaker 1: was actually the official name of the policy Australia was 831 00:51:50,719 --> 00:51:53,799 Speaker 1: ended by Gulf Whitlam Australian Prime Minister in nineteen seventy three. 832 00:51:53,880 --> 00:51:56,839 Speaker 1: And we were one of the first Asian families after 833 00:51:56,880 --> 00:52:00,400 Speaker 1: the wide Australian policy to move to Perth. And I 834 00:52:00,440 --> 00:52:02,600 Speaker 1: remember growing up, I was the only non white kid 835 00:52:02,600 --> 00:52:05,800 Speaker 1: in class and I was really different, kind of marked 836 00:52:05,840 --> 00:52:09,799 Speaker 1: my whole worldview. UM factors really are all about walking 837 00:52:09,840 --> 00:52:14,080 Speaker 1: through and being different too. I did well in school, 838 00:52:14,120 --> 00:52:17,640 Speaker 1: was so thankful for UM, for the opportunities that were 839 00:52:17,680 --> 00:52:20,239 Speaker 1: given to me. And and then you know, I ended 840 00:52:20,320 --> 00:52:23,600 Speaker 1: up in the US for for graduate school. I got 841 00:52:23,600 --> 00:52:26,120 Speaker 1: to work on it Scotinamian who was a professor. And 842 00:52:26,200 --> 00:52:28,239 Speaker 1: you know, now I'm I'm like every other person who 843 00:52:28,320 --> 00:52:31,040 Speaker 1: lives in New York City. That's so, that's so interesting. 844 00:52:31,320 --> 00:52:33,439 Speaker 1: So I was going to ask you a question, what's 845 00:52:33,480 --> 00:52:36,400 Speaker 1: the most important thing we don't know about you? But 846 00:52:36,480 --> 00:52:38,960 Speaker 1: I suspect you maybe I don't know. I'm I'm a musician. 847 00:52:39,440 --> 00:52:44,000 Speaker 1: Oh really, so with the piano, I am a classical pianist. 848 00:52:44,400 --> 00:52:46,879 Speaker 1: I used to play the violin, but I've always loved 849 00:52:46,880 --> 00:52:50,120 Speaker 1: the piano more. I've played in a few black rock 850 00:52:50,160 --> 00:52:53,520 Speaker 1: corporate bands, so I'm trying to expand my musical genres 851 00:52:53,800 --> 00:52:57,799 Speaker 1: away from thelassical towards So have you ever done like 852 00:52:58,000 --> 00:53:03,759 Speaker 1: full classical m I've concertos. Have you played for audiences? 853 00:53:04,440 --> 00:53:07,120 Speaker 1: How far did your music career take? Yes, I can 854 00:53:07,120 --> 00:53:10,120 Speaker 1: play those. Really, that doesn't mean I'm very good at it, 855 00:53:10,480 --> 00:53:13,000 Speaker 1: but I love I love playing. So so tell us 856 00:53:13,040 --> 00:53:17,080 Speaker 1: about some of your mentors who helped develop the way 857 00:53:17,120 --> 00:53:20,200 Speaker 1: you think about markets. I would like to answer that 858 00:53:20,239 --> 00:53:22,319 Speaker 1: in two ways. So the first one is like, who 859 00:53:22,360 --> 00:53:26,640 Speaker 1: do I model myself on in black rock running a 860 00:53:26,680 --> 00:53:30,680 Speaker 1: business and trying to change the world with factors? And 861 00:53:30,719 --> 00:53:34,160 Speaker 1: that person is Walt Disney. Really it's not an investor. 862 00:53:34,680 --> 00:53:36,720 Speaker 1: But if we look at Walt Disney, he didn't invent 863 00:53:36,800 --> 00:53:41,000 Speaker 1: animated films. He didn't invent amusement parks right, or people 864 00:53:41,120 --> 00:53:45,080 Speaker 1: dressed up in uh in different characters. But what he 865 00:53:45,160 --> 00:53:48,399 Speaker 1: did he brought all of those together and he just 866 00:53:48,520 --> 00:53:52,320 Speaker 1: by integrating all that created something new. And that's actually 867 00:53:52,320 --> 00:53:55,799 Speaker 1: what factors are doing too. We didn't invent buying cheap right. 868 00:53:55,880 --> 00:53:59,400 Speaker 1: We didn't invent momentum, but bring of those together with 869 00:53:59,520 --> 00:54:02,480 Speaker 1: darn too technology, Yes, we can remake the world and 870 00:54:02,520 --> 00:54:08,600 Speaker 1: give people a better experience. Interesting. Just a footnote, I 871 00:54:08,680 --> 00:54:11,120 Speaker 1: was at Disneyland two weeks ago. Is the first time 872 00:54:11,160 --> 00:54:14,280 Speaker 1: I've ever gone to any Disney property, and it's quite 873 00:54:14,400 --> 00:54:18,719 Speaker 1: the experience too. In your fifties experience a Disney park 874 00:54:18,920 --> 00:54:20,920 Speaker 1: for for the first time all ages, it is the 875 00:54:20,920 --> 00:54:24,800 Speaker 1: happiest and I basically any ride, I don't care, fast, 876 00:54:24,880 --> 00:54:28,480 Speaker 1: upside down, doesn't matter. I'm I'm right there, and we 877 00:54:28,520 --> 00:54:31,160 Speaker 1: had a blast. It was absolutely you could see why. 878 00:54:31,200 --> 00:54:33,160 Speaker 1: Oh no, I kind of get Disney. This makes a 879 00:54:33,160 --> 00:54:36,520 Speaker 1: lot of sense. But but the other mentors, Yeah, you 880 00:54:36,560 --> 00:54:40,240 Speaker 1: know I I was pretty nerdy, as you can tell. Uh. 881 00:54:40,280 --> 00:54:43,920 Speaker 1: And one of the weight nerdy I have not noticed 882 00:54:44,640 --> 00:54:48,960 Speaker 1: in this book on quantitative factor investing, I did not 883 00:54:48,960 --> 00:54:53,560 Speaker 1: notice anything at all. Uh. And when I was in 884 00:54:53,640 --> 00:54:57,400 Speaker 1: school high school, I got to go to National Mathematics 885 00:54:57,400 --> 00:54:59,799 Speaker 1: summer school and that was just an eye open up 886 00:54:59,800 --> 00:55:03,160 Speaker 1: for that. There were people kind of like me that 887 00:55:04,000 --> 00:55:08,479 Speaker 1: liked math and it really changed my life. So let's 888 00:55:08,480 --> 00:55:12,440 Speaker 1: talk a little bit about investors who influenced your approach 889 00:55:12,600 --> 00:55:16,640 Speaker 1: to investing. Who were the folks that really shaped your 890 00:55:17,239 --> 00:55:21,640 Speaker 1: investing worldview? If any reader or listener out there hasn't 891 00:55:21,680 --> 00:55:27,080 Speaker 1: read Graham and Odd security analysis, but those were two 892 00:55:27,120 --> 00:55:29,919 Speaker 1: professors that the institution I taught up for many years 893 00:55:30,120 --> 00:55:33,040 Speaker 1: Columbia University. You've got to read that book. It's the 894 00:55:33,080 --> 00:55:36,959 Speaker 1: basis for value. Quality is in there because they teach 895 00:55:37,040 --> 00:55:39,319 Speaker 1: us that in order to estimate intrinsic value, you got 896 00:55:39,320 --> 00:55:41,640 Speaker 1: to use the more permanent components of anage, things that 897 00:55:41,719 --> 00:55:45,400 Speaker 1: we use in quality today. I have to mention Bogel. 898 00:55:46,320 --> 00:55:48,440 Speaker 1: When I met him for the first time, he he 899 00:55:49,040 --> 00:55:52,760 Speaker 1: actually was citing some things out of my book, particularly 900 00:55:52,800 --> 00:55:56,359 Speaker 1: that chapter on governance or agency theory. And one other 901 00:55:56,440 --> 00:55:59,600 Speaker 1: person is Joe Grin, but just to look at look 902 00:55:59,600 --> 00:56:03,279 Speaker 1: at us thematic approach to out to some capital. Yeah, 903 00:56:03,280 --> 00:56:06,320 Speaker 1: he's a very interesting guy. So let's talk about books. 904 00:56:06,440 --> 00:56:09,680 Speaker 1: What are some of your favorite books, be they market related, 905 00:56:09,760 --> 00:56:13,239 Speaker 1: not fiction, nonfiction. What have you enjoyed reading. I like 906 00:56:13,360 --> 00:56:16,920 Speaker 1: reading popular science books. My most recent one is by 907 00:56:16,920 --> 00:56:22,719 Speaker 1: Simontgomery and called The Soul of an Octopus. That amazing creatures, right, 908 00:56:22,760 --> 00:56:26,000 Speaker 1: and they just look so alien, but their emotional vally 909 00:56:26,080 --> 00:56:29,080 Speaker 1: in Teargent like them all like Custin we think. I'm 910 00:56:29,080 --> 00:56:31,520 Speaker 1: gonna tell you something. I read that book and I 911 00:56:31,560 --> 00:56:35,920 Speaker 1: stopped eating octopus afterwards. It basically and I eat pretty 912 00:56:36,000 --> 00:56:39,880 Speaker 1: much everything except cauliflower and brussels sprouts. That book is 913 00:56:39,920 --> 00:56:41,560 Speaker 1: the first thing I've ever read trying not to eat 914 00:56:41,600 --> 00:56:46,160 Speaker 1: brussel sprouts. I can't. I can't eat octopus anymore. They 915 00:56:46,200 --> 00:56:49,520 Speaker 1: They're just too intelligent and too soulful. One of the 916 00:56:49,520 --> 00:56:52,400 Speaker 1: things about popular science books that I like is even 917 00:56:52,480 --> 00:56:57,160 Speaker 1: for the areas that I'm familiar with and in some 918 00:56:57,239 --> 00:57:01,560 Speaker 1: cases you would say beat in the weeds with in 919 00:57:01,719 --> 00:57:05,680 Speaker 1: the research, you always learned something from them, because the 920 00:57:05,760 --> 00:57:08,560 Speaker 1: best ones just present information in a new way, or 921 00:57:08,600 --> 00:57:12,560 Speaker 1: they just open up your frontier, like like the Simon 922 00:57:12,600 --> 00:57:18,760 Speaker 1: Comery book. Give us another I think, UM like some 923 00:57:18,960 --> 00:57:22,920 Speaker 1: popular books on number theory and just physics and sciences 924 00:57:22,920 --> 00:57:25,120 Speaker 1: in general. Le let's hear some titles. Well. One of 925 00:57:25,160 --> 00:57:32,400 Speaker 1: them is Moonshot. It's about the American um policy. Yeah, 926 00:57:32,440 --> 00:57:35,800 Speaker 1: it's amazing book as well, moon Shot. That's um who 927 00:57:35,800 --> 00:57:38,520 Speaker 1: wrote that. I can't remember the full title right now. 928 00:57:39,400 --> 00:57:42,440 Speaker 1: Let's let's have Google rescue us while and then you 929 00:57:42,440 --> 00:57:48,479 Speaker 1: can mention it shot and we'll edit this out, uh, 930 00:57:48,520 --> 00:57:50,960 Speaker 1: and I have to. It's a pretty long title. In fact, 931 00:57:51,000 --> 00:57:53,880 Speaker 1: that Soul of an Octopus is a pretty long title too. So, 932 00:57:54,160 --> 00:57:56,160 Speaker 1: by the way, while I'm while I'm looking for this, 933 00:57:56,560 --> 00:58:00,720 Speaker 1: I recommended that book to my friends David Nodded, who 934 00:58:00,880 --> 00:58:04,120 Speaker 1: send set me that book and said thanks for the recommendation. 935 00:58:04,480 --> 00:58:07,640 Speaker 1: That book made me cry. There's another one by what 936 00:58:07,680 --> 00:58:11,080 Speaker 1: a Landing on the Moon Teaches? That's why I don't 937 00:58:11,360 --> 00:58:16,280 Speaker 1: Richard Wiseman. There's another one very very similar to Symontgomery's 938 00:58:16,280 --> 00:58:19,240 Speaker 1: book called by france To Rudin called uh, I Think 939 00:58:19,320 --> 00:58:23,240 Speaker 1: Mama's Hug, Mama's Last Hug. It's about Mama's last It's 940 00:58:23,280 --> 00:58:27,520 Speaker 1: about the great apes and their their intelligence in the capacity. 941 00:58:28,040 --> 00:58:30,840 Speaker 1: I'd enjoyed that one too. If if you I'm gonna 942 00:58:30,880 --> 00:58:32,760 Speaker 1: put that one, I put all these on my list. 943 00:58:32,840 --> 00:58:35,680 Speaker 1: But if if you like that, have you ever read 944 00:58:35,920 --> 00:58:41,160 Speaker 1: Last Ape Standing? So it's basically about the thirty or 945 00:58:41,240 --> 00:58:45,360 Speaker 1: so proto human species that had come out. You know, 946 00:58:45,440 --> 00:58:48,120 Speaker 1: you know chro Magnum, you know Neanderthal, but you don't 947 00:58:48,160 --> 00:58:52,520 Speaker 1: know there's thirty others and how close they all came 948 00:58:52,560 --> 00:58:55,280 Speaker 1: to being wiped out in the ice age, and how 949 00:58:55,920 --> 00:59:03,919 Speaker 1: this particular last ape standing UM, the Homo sapiens ended 950 00:59:03,960 --> 00:59:08,280 Speaker 1: up being the ones who who survived and eventually took over. 951 00:59:08,720 --> 00:59:12,160 Speaker 1: But if you're at all interested in nonfiction, I always 952 00:59:12,200 --> 00:59:15,680 Speaker 1: recommend that book. I've found that delightful. All right, so 953 00:59:15,720 --> 00:59:19,280 Speaker 1: we have three books. Let's jump to UM failure. Tell 954 00:59:19,360 --> 00:59:21,280 Speaker 1: us about a time you failed and what you learned 955 00:59:21,280 --> 00:59:25,720 Speaker 1: from the experience. I turn up at grad school, went 956 00:59:25,760 --> 00:59:29,360 Speaker 1: to Stanford, and I did pretty well. My undergrad one 957 00:59:29,400 --> 00:59:33,400 Speaker 1: a university medal, rote a dissertation, you know, Dunning Kruger 958 00:59:33,480 --> 00:59:38,360 Speaker 1: kind of effect, and you get to grad school n Kruger, 959 00:59:38,680 --> 00:59:42,280 Speaker 1: such a humbling experience. I did so badly. I thought 960 00:59:42,280 --> 00:59:46,760 Speaker 1: about withdrawing. I had to take all these classes in 961 00:59:46,800 --> 00:59:49,800 Speaker 1: the statistics department. That's actually why I have this Masters 962 00:59:49,800 --> 00:59:52,200 Speaker 1: of Science and Statistics was just because I was in 963 00:59:53,160 --> 00:59:55,600 Speaker 1: UM the remedial program. To take all these extra things 964 00:59:55,640 --> 00:59:57,720 Speaker 1: that I should have known before I entered my degree. 965 00:59:58,280 --> 01:00:01,200 Speaker 1: That was a really humbling experience. So that's very high 966 01:00:01,320 --> 01:00:06,480 Speaker 1: level Dunning Krueger meta cognition. I experienced that in college. 967 01:00:06,480 --> 01:00:08,960 Speaker 1: It's like high school was easy. You get to college 968 01:00:08,960 --> 01:00:11,360 Speaker 1: and suddenly it's like, Oh, these people are really smart 969 01:00:11,360 --> 01:00:13,720 Speaker 1: and they work really hard. I can't just you know, 970 01:00:13,800 --> 01:00:16,560 Speaker 1: phone it in. I don't know what your experience was 971 01:00:16,600 --> 01:00:19,840 Speaker 1: like in grad school, but it was in hindsight, pure 972 01:00:19,920 --> 01:00:24,800 Speaker 1: Dunning Krueger. What did I learn is, um, you can't 973 01:00:24,800 --> 01:00:28,040 Speaker 1: do it on your own. So I think everyone off 974 01:00:28,040 --> 01:00:32,480 Speaker 1: my class, June and June, Mark, Maria, Eric. Without you, 975 01:00:32,600 --> 01:00:36,160 Speaker 1: I could not have got through my homeworks and got 976 01:00:36,160 --> 01:00:39,280 Speaker 1: that gotten through. Wow, that's that's quite interesting. So what 977 01:00:39,320 --> 01:00:40,640 Speaker 1: do you do for fun? What do you do when 978 01:00:40,680 --> 01:00:45,439 Speaker 1: you're not crunching numbers? That's that's your that's your UM, 979 01:00:45,480 --> 01:00:48,960 Speaker 1: that's your stress release. That's my stress relase. Sitting at 980 01:00:48,960 --> 01:00:51,880 Speaker 1: a keyboard and just working your way through a Grand 981 01:00:52,120 --> 01:00:56,920 Speaker 1: Masters composition. Well, right now I'm also trying to do pilates. 982 01:00:57,040 --> 01:00:59,320 Speaker 1: I'm very very stiff. So my goal is to try 983 01:00:59,360 --> 01:01:04,360 Speaker 1: to touch my Okay, uh, tell us what your most 984 01:01:04,440 --> 01:01:09,640 Speaker 1: optimistic and pessimistic about today. It could be markets, investing, economy. 985 01:01:10,080 --> 01:01:13,800 Speaker 1: What what do you most optimistic and most pessimistic about? Oh? 986 01:01:13,960 --> 01:01:17,400 Speaker 1: I love all of the opportunities that are here today, 987 01:01:17,600 --> 01:01:20,160 Speaker 1: particularly for the fact is what we've been talking talking 988 01:01:20,200 --> 01:01:24,040 Speaker 1: about and the great advances that we will make to 989 01:01:24,120 --> 01:01:27,440 Speaker 1: put all those benefits in the hands of consumers and clients. 990 01:01:28,160 --> 01:01:32,000 Speaker 1: One of my pessimistic about well, my parents were migrants. 991 01:01:32,760 --> 01:01:36,280 Speaker 1: Really glad my parents migrated and gave me opportunities in 992 01:01:36,320 --> 01:01:39,880 Speaker 1: Australian then you know, living here in the US, and 993 01:01:40,480 --> 01:01:44,200 Speaker 1: there's this expression I got a fairgo and people a 994 01:01:44,320 --> 01:01:50,640 Speaker 1: fair go, And I'm a little pessimistic that there's increasing inequality, 995 01:01:51,200 --> 01:01:55,440 Speaker 1: lack of mobility, and bottom line is we should be 996 01:01:55,520 --> 01:01:59,680 Speaker 1: trying to give as many people a fair go, very 997 01:01:59,800 --> 01:02:02,880 Speaker 1: very reasonable. Let's uh, let me get to my two 998 01:02:02,880 --> 01:02:06,680 Speaker 1: favorite questions. Um, a millennial or someone just beginning their 999 01:02:06,720 --> 01:02:09,360 Speaker 1: career in finance comes up to you and ask for 1000 01:02:09,840 --> 01:02:13,280 Speaker 1: some advice. What sort of advice would you give them. 1001 01:02:13,320 --> 01:02:15,960 Speaker 1: It's actually advice I give myself. It was given to 1002 01:02:16,000 --> 01:02:20,280 Speaker 1: me by Bob Hodrick, a colleague and co author and friend, 1003 01:02:21,360 --> 01:02:25,200 Speaker 1: and he said, it's not your life. Don't presume to 1004 01:02:25,880 --> 01:02:30,680 Speaker 1: to suggest that it's it's your life either, but explain, 1005 01:02:30,960 --> 01:02:32,320 Speaker 1: give me, give me a little more. Do you make 1006 01:02:32,360 --> 01:02:36,640 Speaker 1: your choices. My preferences aren't yours, And you go and 1007 01:02:36,680 --> 01:02:39,800 Speaker 1: do what you think is best, and I'll go and 1008 01:02:39,840 --> 01:02:42,040 Speaker 1: support you the best that you can the best I can. 1009 01:02:42,120 --> 01:02:46,800 Speaker 1: That's quite intriguing. Um tell us for our final question, 1010 01:02:46,840 --> 01:02:49,160 Speaker 1: what do you know about the world of investing today? 1011 01:02:49,560 --> 01:02:51,720 Speaker 1: You wish you knew thirty years ago when you were 1012 01:02:51,760 --> 01:02:56,960 Speaker 1: first getting started. I think very often the most important 1013 01:02:57,440 --> 01:03:02,960 Speaker 1: problems in investments are actually not about investing really. For institutions, 1014 01:03:03,520 --> 01:03:09,720 Speaker 1: they're about management, structure, governance and incentives. And for individuals, well, 1015 01:03:09,720 --> 01:03:12,320 Speaker 1: you've had many guests on your show to all about 1016 01:03:13,040 --> 01:03:18,200 Speaker 1: tackling investors behavioral bodies, all right, and those sometimes are 1017 01:03:18,280 --> 01:03:21,440 Speaker 1: even more important than the actual investment problems. Sometimes the 1018 01:03:21,440 --> 01:03:23,840 Speaker 1: investment problem is the easy pot, all right, and then 1019 01:03:23,840 --> 01:03:26,520 Speaker 1: sitting the context of the investment problem in the wider 1020 01:03:26,560 --> 01:03:32,400 Speaker 1: portfolio or the wider structure in someone's family or an institution, 1021 01:03:32,720 --> 01:03:37,720 Speaker 1: that's actually the harder problem. Quite fascinating. We have been 1022 01:03:37,760 --> 01:03:40,520 Speaker 1: speaking with Andrew Ang. He is the head of factor 1023 01:03:40,560 --> 01:03:44,760 Speaker 1: investing at black Rock and the author of Asset Management, 1024 01:03:45,000 --> 01:03:50,400 Speaker 1: A Systematic Approach to Factor Investing. If you enjoy this conversation, well, 1025 01:03:50,400 --> 01:03:52,320 Speaker 1: look up an Inch or down an Inch on Apple 1026 01:03:52,360 --> 01:03:55,280 Speaker 1: iTunes and you could see any of the other two 1027 01:03:55,360 --> 01:03:58,680 Speaker 1: hundred and fifties such conversations we've had over the past 1028 01:03:58,720 --> 01:04:02,440 Speaker 1: five years and check that out. We love your comments, 1029 01:04:02,560 --> 01:04:07,280 Speaker 1: feedback and suggestions right to us at m IB podcast 1030 01:04:07,360 --> 01:04:10,360 Speaker 1: at Bloomberg dot net. I would be remiss if I 1031 01:04:10,400 --> 01:04:12,760 Speaker 1: did not thank the crack staff that helps put these 1032 01:04:12,760 --> 01:04:17,680 Speaker 1: conversations together. Attikavl Bron is our project manager. Michael Boyle 1033 01:04:17,920 --> 01:04:22,600 Speaker 1: is our head of booking slash producing. Michael Batnick is 1034 01:04:22,640 --> 01:04:26,200 Speaker 1: my head of research. I'm Barry Results. You've been listening 1035 01:04:26,280 --> 01:04:28,960 Speaker 1: to Master's Business on Bloomberg Radio