1 00:00:04,960 --> 00:00:08,200 Speaker 1: Single best idea, and today was an extraordinary day on 2 00:00:08,200 --> 00:00:10,920 Speaker 1: Bloomberg's surveillance. Our team just did a great job of 3 00:00:10,960 --> 00:00:14,560 Speaker 1: eclectic guess We finished strong with the elliot Ackerman in 4 00:00:14,680 --> 00:00:18,200 Speaker 1: celebration of his new book twenty fifty four with James Travetis. 5 00:00:18,600 --> 00:00:20,320 Speaker 1: I'll have a lot more to say about that. I'm 6 00:00:20,320 --> 00:00:22,279 Speaker 1: thinking in April or may I actually try to read 7 00:00:22,320 --> 00:00:25,240 Speaker 1: the books that I'm big on, and I'll have to 8 00:00:25,520 --> 00:00:28,760 Speaker 1: wait through twenty fifty four about the tensions that are 9 00:00:28,840 --> 00:00:34,160 Speaker 1: military faces. But today was wonderfully eclectic in equities. Tony 10 00:00:34,240 --> 00:00:36,199 Speaker 1: Dwyer was with us with a broad view of the 11 00:00:36,240 --> 00:00:41,000 Speaker 1: linkage of recession and those fears to tepid participation inequities. 12 00:00:41,040 --> 00:00:44,240 Speaker 1: Away from mag seven there were all sorts of others, 13 00:00:44,240 --> 00:00:47,560 Speaker 1: but what we really had was dueling quants. I can't 14 00:00:47,600 --> 00:00:49,400 Speaker 1: say enough. I'm not going to go into it here 15 00:00:49,479 --> 00:00:52,479 Speaker 1: because we're trying to keep this podcast tight, but I 16 00:00:52,520 --> 00:00:56,880 Speaker 1: can't say enough about the development of modern quantitative academics, 17 00:00:57,480 --> 00:01:01,360 Speaker 1: which came out of Imperial College and London with Paul Wilmot, 18 00:01:01,960 --> 00:01:05,560 Speaker 1: with all sorts of workout of other institutions, including foundational 19 00:01:05,600 --> 00:01:10,200 Speaker 1: work at Princeton and particularly Andrew Lowe l Andrew low 20 00:01:10,560 --> 00:01:14,679 Speaker 1: Up at Massachusetts Institute of Technology. We are thrilled to 21 00:01:14,720 --> 00:01:19,920 Speaker 1: bring you today Katherine Kaminski at Alpha Simplex out of 22 00:01:19,959 --> 00:01:24,200 Speaker 1: the MIT combine, but first Amy Wu Silverman of RBC, 23 00:01:24,480 --> 00:01:29,160 Speaker 1: out of the Princeton QUANDT combine. These people are wicked smart. 24 00:01:29,240 --> 00:01:31,640 Speaker 1: They're the ones that got the A in your math class. 25 00:01:32,120 --> 00:01:35,680 Speaker 1: And the answer is they really try to devolve the 26 00:01:35,720 --> 00:01:38,560 Speaker 1: complexities of the Greek letters and what are called cross 27 00:01:38,600 --> 00:01:43,080 Speaker 1: moments down to a mere mortal conversation like you can 28 00:01:43,280 --> 00:01:47,480 Speaker 1: digest on Bloomberg's surveillance. We digressed with Amy Wu Silverman, 29 00:01:47,920 --> 00:01:51,520 Speaker 1: and of course we looked at her cross moments and bitcoin. 30 00:01:52,000 --> 00:01:55,040 Speaker 2: The really interesting thing I would say about bitcoin, because 31 00:01:55,120 --> 00:01:57,800 Speaker 2: you know, you can't dabble in volatility without dabbling and 32 00:01:57,840 --> 00:02:01,760 Speaker 2: crypto a little is the This has historically been a 33 00:02:01,840 --> 00:02:04,680 Speaker 2: risk acid correlation that's actually been positive, even though it's 34 00:02:04,680 --> 00:02:07,240 Speaker 2: been made out not to be. However, we are actually 35 00:02:07,320 --> 00:02:10,919 Speaker 2: seeing that correlation decline. So if you look three years ago, 36 00:02:11,040 --> 00:02:14,040 Speaker 2: the correlation between just the simple equity market and bitcoin 37 00:02:14,400 --> 00:02:17,120 Speaker 2: was fairly positive and it is still positive, to be clear, 38 00:02:17,360 --> 00:02:19,520 Speaker 2: but it's actually come in a lot and so it 39 00:02:19,560 --> 00:02:24,160 Speaker 2: may actually begin to be behaving in the inflation hedge 40 00:02:24,240 --> 00:02:27,240 Speaker 2: slash equity hedge that it was purported to be in 41 00:02:27,280 --> 00:02:27,760 Speaker 2: the beginning. 42 00:02:28,080 --> 00:02:31,600 Speaker 1: Amy was Silverman there with RBC on bitcoin, and of 43 00:02:31,600 --> 00:02:33,680 Speaker 1: course we did talk to her about the broader equity 44 00:02:33,760 --> 00:02:36,560 Speaker 1: market and some of the oddities out there, particularly the 45 00:02:36,680 --> 00:02:41,320 Speaker 1: mass speculation and options in option day trading. I guess 46 00:02:41,320 --> 00:02:44,520 Speaker 1: it's speculation, or maybe it's almost like the roulette wheel 47 00:02:44,960 --> 00:02:48,600 Speaker 1: at a casino. Katie Kaminski is with Alpha Simplex, and 48 00:02:48,639 --> 00:02:50,280 Speaker 1: the heart and soul of what they do, which I'm 49 00:02:50,320 --> 00:02:54,519 Speaker 1: familiar with, is trend following. This is a cottage industry 50 00:02:54,919 --> 00:02:57,280 Speaker 1: which goes back a solid forty years, much of it 51 00:02:57,280 --> 00:03:00,600 Speaker 1: out of the greater New York City area. And the 52 00:03:00,639 --> 00:03:02,800 Speaker 1: idea here is not so much to catch the knife 53 00:03:02,840 --> 00:03:04,680 Speaker 1: in the dark. The idea here is not to get 54 00:03:04,760 --> 00:03:07,040 Speaker 1: right on the bottom of the trend going up or 55 00:03:07,120 --> 00:03:09,880 Speaker 1: the top of the trend going down, but rather just 56 00:03:09,919 --> 00:03:14,120 Speaker 1: to find the trend and monitor it as you invest, 57 00:03:14,600 --> 00:03:18,960 Speaker 1: and not day trading, but invest out weeks, quarters, in months. 58 00:03:19,320 --> 00:03:22,880 Speaker 1: Katie commencing, of course, looking at this extraordinary bull market 59 00:03:23,400 --> 00:03:26,840 Speaker 1: here she is on the quants, the cross moments of 60 00:03:26,880 --> 00:03:27,959 Speaker 1: our equity market. 61 00:03:28,440 --> 00:03:31,120 Speaker 3: When you look right now at where equities have moved, 62 00:03:31,600 --> 00:03:34,920 Speaker 3: the turning point was in October and it's been I mean, 63 00:03:34,960 --> 00:03:37,600 Speaker 3: look at S and P. It's up almost twenty five 64 00:03:37,600 --> 00:03:41,320 Speaker 3: percent since October, so pretty much over any window where 65 00:03:41,320 --> 00:03:43,680 Speaker 3: you measure the strength of the trend, you're seeing a 66 00:03:43,720 --> 00:03:46,560 Speaker 3: pretty strong signal that we're going straight to the moon. 67 00:03:47,400 --> 00:03:51,240 Speaker 3: And so I think that's where, you know, I'm surprised 68 00:03:51,280 --> 00:03:55,560 Speaker 3: at how incredibly resilient this market has been. If you 69 00:03:55,680 --> 00:03:58,000 Speaker 3: told me in January that February is going to be 70 00:03:58,040 --> 00:04:00,640 Speaker 3: as amazing as it was, I would have not believe you. 71 00:04:00,800 --> 00:04:03,840 Speaker 1: Katiekiminski there, and I really want to talk with Alpha Simplex, 72 00:04:03,840 --> 00:04:06,080 Speaker 1: and I really want to talk for a moment here 73 00:04:06,520 --> 00:04:10,400 Speaker 1: about the underlying here in the Bloomberg terminal. All of 74 00:04:10,440 --> 00:04:14,040 Speaker 1: this came out of really a bunch of really really 75 00:04:14,080 --> 00:04:19,080 Speaker 1: smart people working off Sun Microsystems Spark stations way in 76 00:04:19,080 --> 00:04:23,039 Speaker 1: the back. It wasn't PCs and decad Wang and you 77 00:04:23,040 --> 00:04:25,640 Speaker 1: know what Microsoft did with Intel and all that. It 78 00:04:25,680 --> 00:04:28,960 Speaker 1: was more sophisticated right from the get go. And it 79 00:04:29,000 --> 00:04:33,560 Speaker 1: involves Sun microsystem I can't remember the name midframe computers 80 00:04:33,600 --> 00:04:35,760 Speaker 1: I think is what they were called, but they did 81 00:04:35,800 --> 00:04:39,080 Speaker 1: it off Spark station. What Mike Bloomberg and Tom Sekunda 82 00:04:39,120 --> 00:04:42,960 Speaker 1: did to bring some of those mathematical dynamics over to 83 00:04:43,000 --> 00:04:46,400 Speaker 1: the Bloomberg terminal was at the time, and I remember 84 00:04:46,440 --> 00:04:49,560 Speaker 1: this clearly nothing short of an act of God. They 85 00:04:49,560 --> 00:04:54,440 Speaker 1: basically took high powered Sun Microsystem's work and brought over 86 00:04:54,520 --> 00:04:58,400 Speaker 1: those chart dynamics so you could establish a trend for 87 00:04:58,440 --> 00:05:00,760 Speaker 1: those of you that have a Bloomberg. For those of 88 00:05:00,760 --> 00:05:02,840 Speaker 1: you that want to get a Bloomberg, one of the 89 00:05:02,960 --> 00:05:08,520 Speaker 1: major major reasons is what's called stochastic analysis, but far 90 00:05:08,720 --> 00:05:11,080 Speaker 1: far more importantly, and you know I'm on this. I 91 00:05:11,080 --> 00:05:14,080 Speaker 1: think if Chris Verona's strateigue, it's the same way we 92 00:05:14,120 --> 00:05:17,520 Speaker 1: are into trend based following. And you do that with 93 00:05:17,839 --> 00:05:20,920 Speaker 1: moving averages. You do that with all sorts of other 94 00:05:21,000 --> 00:05:24,120 Speaker 1: technical studies, much of them founded by a guy named 95 00:05:24,120 --> 00:05:28,400 Speaker 1: Wells Wilder and brought forward in the quantitative finance space 96 00:05:29,240 --> 00:05:32,440 Speaker 1: of people at Princeton and people at MIT like Amy 97 00:05:32,440 --> 00:05:36,040 Speaker 1: wou Silverman and Katie Kaminski. You can do all that 98 00:05:36,279 --> 00:05:40,200 Speaker 1: on the Bloomberg. Check it out. This is single best idea, 99 00:05:40,240 --> 00:05:43,080 Speaker 1: And don't forget you can see us on Apple car Play. 100 00:05:43,279 --> 00:05:45,840 Speaker 1: It's really working out the Bloomberg Business app. It's free, 101 00:05:46,200 --> 00:05:49,720 Speaker 1: you go there. It's safer and better is Apple, says Apple, 102 00:05:49,800 --> 00:05:51,720 Speaker 1: and we were thrilled by the numbers. I actually got 103 00:05:51,720 --> 00:05:54,880 Speaker 1: brief done it this morning. I was like, really, sixty 104 00:05:55,360 --> 00:05:58,880 Speaker 1: nine nations are listening to us on Apple car Play 105 00:05:59,440 --> 00:06:02,200 Speaker 1: and on YouTube. We're thrilled by the international coverage and 106 00:06:02,240 --> 00:06:07,280 Speaker 1: of course across the nation on YouTube. Search Bloomberg Podcasts 107 00:06:07,279 --> 00:06:09,960 Speaker 1: and you'll find us there. Seven to ten for Wall 108 00:06:09,960 --> 00:06:14,720 Speaker 1: Street Time again, Bloomberg Surveillance, an Apple CarPlay, and on 109 00:06:14,760 --> 00:06:17,839 Speaker 1: YouTube