1 00:00:12,240 --> 00:00:15,360 Speaker 1: Hello, and welcome to What Goes Up a Bloomberg Weekening 2 00:00:15,400 --> 00:00:19,520 Speaker 1: Markets podcast. I'm Sara Plante, reporter on the Cross Asset team, 3 00:00:19,680 --> 00:00:23,160 Speaker 1: and I'm Mike Reagan, a senior editor on the Markets team. 4 00:00:23,200 --> 00:00:25,640 Speaker 1: This week on the show, there's no denying it. We're 5 00:00:25,680 --> 00:00:28,800 Speaker 1: in a healthcare crisis, as disheartening as it may be, 6 00:00:29,080 --> 00:00:31,280 Speaker 1: and you could also say that we're in an economic 7 00:00:31,320 --> 00:00:34,800 Speaker 1: and a market crisis. Well, our guests actually coined the 8 00:00:34,920 --> 00:00:38,239 Speaker 1: term crisis alpha, and the strategy she runs is up 9 00:00:38,240 --> 00:00:42,120 Speaker 1: seven percent this year. She'll explain what crisis alpha actually 10 00:00:42,320 --> 00:00:44,839 Speaker 1: is and how to capture it in times like these, 11 00:00:45,479 --> 00:00:48,000 Speaker 1: and as always, we will close out the episode with 12 00:00:48,040 --> 00:00:52,680 Speaker 1: our tradition the craziest thing I saw in markets this week? Uh, 13 00:00:52,720 --> 00:00:55,240 Speaker 1: And please do if you see something crazy and markets, 14 00:00:55,240 --> 00:00:58,560 Speaker 1: give us a call on the podcast hotline at six 15 00:00:58,600 --> 00:01:03,920 Speaker 1: four six four three four nine oh or tweet to 16 00:01:04,040 --> 00:01:07,160 Speaker 1: us at Podcasts and let us know the craziest thing 17 00:01:07,160 --> 00:01:09,920 Speaker 1: you saw and maybe we'll play your voicemail or mention 18 00:01:10,000 --> 00:01:13,840 Speaker 1: your tweet on the air. Well, let's introduce a new 19 00:01:13,959 --> 00:01:16,760 Speaker 1: voice here, first time on the show. Very excited to 20 00:01:17,040 --> 00:01:20,080 Speaker 1: have her. As sorry, as you pointed out, she is 21 00:01:20,240 --> 00:01:24,800 Speaker 1: an expert in trend following UH using managed futures, in fact, 22 00:01:24,880 --> 00:01:26,800 Speaker 1: wrote the book on it, or at least co wrote 23 00:01:27,040 --> 00:01:30,520 Speaker 1: the book Trend Following with Managed Futures, The Search for 24 00:01:30,680 --> 00:01:35,160 Speaker 1: Crisis Alpha. She is the chief research strategist at Alpha 25 00:01:35,240 --> 00:01:38,880 Speaker 1: Simplex Group. UH, teaches at m I T in her 26 00:01:38,920 --> 00:01:42,640 Speaker 1: spare time, and very excited to get her take on 27 00:01:42,680 --> 00:01:46,240 Speaker 1: these markets. Her name is Katie Kaminsky. Katie, Welcome to 28 00:01:46,240 --> 00:01:50,600 Speaker 1: the show. Hi, nice to be here today. I wanted 29 00:01:50,640 --> 00:01:54,920 Speaker 1: to ask about sort of how the trend following, especially UH. 30 00:01:55,160 --> 00:01:58,680 Speaker 1: I believe it's the Alpha Simplex Managed Future strategy that 31 00:01:58,800 --> 00:02:01,520 Speaker 1: Sarah was referring to. It's up like about seven or 32 00:02:01,600 --> 00:02:04,720 Speaker 1: eight percent this year. UM. I was reading a note 33 00:02:04,840 --> 00:02:08,200 Speaker 1: you wrote about sort of the process of trend following 34 00:02:08,800 --> 00:02:12,800 Speaker 1: during this bear market in stocks that we've seen this year, 35 00:02:13,639 --> 00:02:15,920 Speaker 1: and I guess you wrote a little bit about how 36 00:02:15,960 --> 00:02:18,960 Speaker 1: the signals, the cross assets signals from say the bond 37 00:02:19,040 --> 00:02:23,680 Speaker 1: market and the and the commodities market copper and oil especially, UM, 38 00:02:23,760 --> 00:02:28,000 Speaker 1: we're sort of signaling a risk off environment a lot 39 00:02:28,040 --> 00:02:31,040 Speaker 1: earlier than stocks, at least before stocks peaked towards the 40 00:02:31,160 --> 00:02:33,680 Speaker 1: end of February there. But I'm just curious how it 41 00:02:33,720 --> 00:02:35,640 Speaker 1: all sort of fits together, if you could kind of 42 00:02:35,720 --> 00:02:38,799 Speaker 1: dissect for us the returns and that fund how it's 43 00:02:38,840 --> 00:02:41,520 Speaker 1: able to do so well in this type of environment. 44 00:02:42,520 --> 00:02:46,440 Speaker 1: So the concept of crisis alpha opportunities are opportunities game 45 00:02:46,520 --> 00:02:51,360 Speaker 1: during periods of market stress or crisis. Um Strategies like 46 00:02:51,400 --> 00:02:57,960 Speaker 1: trend following are specifically designed to constantly measure where markets 47 00:02:57,960 --> 00:03:00,840 Speaker 1: are going and how things are changing across a wide 48 00:03:00,919 --> 00:03:04,600 Speaker 1: range of methodologies. And what we find is that we 49 00:03:04,680 --> 00:03:08,200 Speaker 1: move as the markets move, So as markets move in 50 00:03:08,280 --> 00:03:13,400 Speaker 1: different directions, we're constantly adjusting and following where markets go. 51 00:03:14,040 --> 00:03:16,320 Speaker 1: And so in the moments when there's a lot of 52 00:03:16,400 --> 00:03:19,679 Speaker 1: uncertainty or there's a lot of stress in the markets, 53 00:03:20,040 --> 00:03:22,239 Speaker 1: it turns out that people tend to be much more 54 00:03:22,320 --> 00:03:27,080 Speaker 1: polarized in their actions, for both either behavioral reasons or 55 00:03:27,280 --> 00:03:30,480 Speaker 1: for the fact that they may be driven into action 56 00:03:30,560 --> 00:03:36,080 Speaker 1: based on risk management and other typical institutional protocols. So 57 00:03:36,680 --> 00:03:39,480 Speaker 1: the key thing that we are following, and what's different 58 00:03:39,520 --> 00:03:42,760 Speaker 1: about us is that we're much more technical in nature, 59 00:03:42,960 --> 00:03:45,520 Speaker 1: and that we're actually looking at where the market's going 60 00:03:45,560 --> 00:03:49,400 Speaker 1: as opposed to why it's going somewhere, And that means 61 00:03:49,480 --> 00:03:53,600 Speaker 1: that we're listening to the markets and seeing where they 62 00:03:53,640 --> 00:03:57,560 Speaker 1: are pointing. So if I think about what happened earlier 63 00:03:57,640 --> 00:04:01,520 Speaker 1: this year, especially January, what was very ominous to me 64 00:04:01,920 --> 00:04:06,119 Speaker 1: and was giving a little pause was just how are 65 00:04:06,280 --> 00:04:09,840 Speaker 1: trend fling signals and how trend fling in general started 66 00:04:09,880 --> 00:04:14,320 Speaker 1: to see a growing apprehension, not in the equity markets, 67 00:04:14,360 --> 00:04:17,800 Speaker 1: but more so in the other periphery markets, which were 68 00:04:17,800 --> 00:04:21,359 Speaker 1: starting to price in some of the uncertainty and some 69 00:04:21,520 --> 00:04:26,599 Speaker 1: of the potential UH impacts of a potential pandemic. So, 70 00:04:26,760 --> 00:04:29,200 Speaker 1: speaking of this apprehension, Katie, the last time I saw 71 00:04:29,240 --> 00:04:31,920 Speaker 1: you was early March. It seems like a lifetime ago 72 00:04:32,000 --> 00:04:35,839 Speaker 1: because we were actually face to face in person. Doesn't 73 00:04:35,839 --> 00:04:39,400 Speaker 1: happen anymore. I believe it was on on March six. Then. 74 00:04:39,440 --> 00:04:42,520 Speaker 1: At the time, the SMP had fallen twelve percent, and 75 00:04:42,600 --> 00:04:44,800 Speaker 1: little did anyone know that from that point we still 76 00:04:44,800 --> 00:04:48,839 Speaker 1: had roughly or more to go. We would also all 77 00:04:48,880 --> 00:04:52,960 Speaker 1: be entering stay at home orders. Businesses would be shutting. 78 00:04:52,960 --> 00:04:55,920 Speaker 1: And at the time you expressed that apprehension, and around 79 00:04:55,920 --> 00:04:59,280 Speaker 1: the same period you also authored a report and within 80 00:04:59,360 --> 00:05:02,200 Speaker 1: it you said the market smells as skunk, precisely for 81 00:05:02,240 --> 00:05:07,080 Speaker 1: those reasons that other asset classes were signaling caution and 82 00:05:07,080 --> 00:05:09,120 Speaker 1: and it makes me think, I mean, if the market 83 00:05:09,440 --> 00:05:12,120 Speaker 1: quote unquote smelled the skunk, then well then what does 84 00:05:12,160 --> 00:05:14,400 Speaker 1: it smell now, because I mean, you look at oil 85 00:05:14,440 --> 00:05:17,839 Speaker 1: prices this past week, which dropped below twenty a barrel 86 00:05:17,880 --> 00:05:19,840 Speaker 1: for w t I again, and at the same time, 87 00:05:19,839 --> 00:05:23,080 Speaker 1: we haven't really seen bond prices react all that much. 88 00:05:23,120 --> 00:05:26,560 Speaker 1: But meanwhile, we've just seen equity markets turn around to 89 00:05:26,640 --> 00:05:30,880 Speaker 1: the upside pretty forcefully, exactly. And what's interesting for us 90 00:05:31,000 --> 00:05:35,400 Speaker 1: is that we saw tremendous trends in the cross asset space. 91 00:05:36,000 --> 00:05:41,799 Speaker 1: So there were tremendous opportunities in fixed income UM, short energies, 92 00:05:42,200 --> 00:05:47,520 Speaker 1: short industrial metals, long precious metals. UH. The currency market 93 00:05:47,600 --> 00:05:49,320 Speaker 1: has been a little bit more of it back and 94 00:05:49,400 --> 00:05:52,880 Speaker 1: forth in all of this situation, but in general, the 95 00:05:52,920 --> 00:05:56,719 Speaker 1: trends that we were seeing were relatively strong, much stronger 96 00:05:56,760 --> 00:05:59,280 Speaker 1: than the typical amount of trend that you would see 97 00:05:59,760 --> 00:06:02,360 Speaker 1: UM in a time where people are not concerned. And 98 00:06:02,400 --> 00:06:05,599 Speaker 1: this is why these strategies actually do very well in 99 00:06:05,640 --> 00:06:09,839 Speaker 1: these environments is that during periods of fear or distress, 100 00:06:10,000 --> 00:06:13,320 Speaker 1: people are much more coordinated and how they behave and 101 00:06:13,400 --> 00:06:15,960 Speaker 1: prices as a result, can also move in a much 102 00:06:16,000 --> 00:06:20,440 Speaker 1: more coordinated way, which means that a particular strategy that's 103 00:06:20,440 --> 00:06:24,919 Speaker 1: actually measuring and monitoring these trends can actually capture them. 104 00:06:24,960 --> 00:06:28,920 Speaker 1: So I often think about our positioning as an aggregate 105 00:06:29,240 --> 00:06:32,960 Speaker 1: estimate or view of what the market thinks, where the 106 00:06:33,000 --> 00:06:35,680 Speaker 1: market's going. So if I take a look back in 107 00:06:35,800 --> 00:06:38,919 Speaker 1: January at the beginning of this what was concerning to 108 00:06:39,000 --> 00:06:42,480 Speaker 1: me is I saw a lot of strength in terms 109 00:06:42,480 --> 00:06:46,960 Speaker 1: of a lot of bullish signals for fixed income, you know, 110 00:06:47,080 --> 00:06:50,839 Speaker 1: kind of in some sense hesitation about the equity markets. 111 00:06:51,240 --> 00:06:53,640 Speaker 1: I also saw a lot of strength in terms of 112 00:06:53,720 --> 00:06:58,000 Speaker 1: short positions in things like energies, and as you know, 113 00:06:58,200 --> 00:07:01,920 Speaker 1: oftentimes energies fall with equities but don't recover as much 114 00:07:02,680 --> 00:07:05,120 Speaker 1: um And so we saw all of these type of 115 00:07:05,160 --> 00:07:08,599 Speaker 1: signs and strengthening, especially in flight to safety trades in 116 00:07:08,760 --> 00:07:12,080 Speaker 1: terms of the cross assets that we monitor, which was 117 00:07:12,120 --> 00:07:15,440 Speaker 1: indicative that half of the things we were looking at 118 00:07:15,480 --> 00:07:18,840 Speaker 1: we're looking a little ominous. And the equity markets were 119 00:07:18,880 --> 00:07:22,520 Speaker 1: yet to fall Asian markets were a little bit weaker. 120 00:07:22,920 --> 00:07:26,960 Speaker 1: But as we saw markets fall out in February into March, 121 00:07:27,520 --> 00:07:30,920 Speaker 1: then the theme became coordinated and it was very much 122 00:07:30,960 --> 00:07:35,320 Speaker 1: a a theme of crisis. And since that point we 123 00:07:35,360 --> 00:07:41,000 Speaker 1: saw that continue throughout March. Um our signals have gone 124 00:07:41,040 --> 00:07:45,520 Speaker 1: from being very cautiously optimistic about equities to cautiously pessimistic. 125 00:07:46,240 --> 00:07:50,480 Speaker 1: Um not in size, but definitely right now the way 126 00:07:50,520 --> 00:07:54,200 Speaker 1: we're thinking about things, because you asked about positioning, UM, 127 00:07:54,240 --> 00:07:56,760 Speaker 1: if I take a look at how trends signals are 128 00:07:56,760 --> 00:08:01,120 Speaker 1: looking right now, there's definitely a very cautious view on equities, 129 00:08:01,480 --> 00:08:05,160 Speaker 1: cautious and slightly negative. Yeah. I'm sure everyone right now 130 00:08:05,200 --> 00:08:09,520 Speaker 1: is having to make very difficult decisions. And when you 131 00:08:09,600 --> 00:08:13,720 Speaker 1: say that the stands currently, at least regarding equities is 132 00:08:13,760 --> 00:08:17,720 Speaker 1: cautiously pessimistic, can you maybe walk us through the evolution 133 00:08:18,400 --> 00:08:21,920 Speaker 1: of the strategy maybe from the end of January to 134 00:08:21,960 --> 00:08:24,160 Speaker 1: the point at which we get to this point now 135 00:08:24,160 --> 00:08:27,280 Speaker 1: where we've had a nice rebound off of the lows 136 00:08:27,360 --> 00:08:31,200 Speaker 1: and the strategy is pessimistic. I know it changes quite often, 137 00:08:31,640 --> 00:08:33,640 Speaker 1: but can you maybe give us a sense of how 138 00:08:33,679 --> 00:08:37,080 Speaker 1: the strategy did change throughout time as markets were moving 139 00:08:37,400 --> 00:08:40,440 Speaker 1: up until this point. Yeah, I will run through how 140 00:08:40,480 --> 00:08:43,040 Speaker 1: the strategy had moved, But then at the end I'll 141 00:08:43,040 --> 00:08:47,240 Speaker 1: maybe give some um overall view in terms of what 142 00:08:47,360 --> 00:08:50,320 Speaker 1: could be driving this UM. So we'll start with at 143 00:08:50,360 --> 00:08:53,720 Speaker 1: the beginning of the year. UM. It was quite interesting 144 00:08:53,760 --> 00:08:56,600 Speaker 1: because after a year that was so phenomenally good for 145 00:08:56,640 --> 00:09:01,160 Speaker 1: the equity markets last year, things were looking good. Bond 146 00:09:01,240 --> 00:09:05,400 Speaker 1: markets had been more range bound and reverted somewhat in December, 147 00:09:05,880 --> 00:09:09,400 Speaker 1: so it was really looking like a very pro equity 148 00:09:09,440 --> 00:09:13,040 Speaker 1: market environment. UM. I know, growth estimates were a little 149 00:09:13,040 --> 00:09:16,720 Speaker 1: bit more muted than the priory prior year, but in general, 150 00:09:16,960 --> 00:09:19,839 Speaker 1: the risk on theme had grown a lot, and we've 151 00:09:19,880 --> 00:09:22,920 Speaker 1: seen that in em currencies, we've seen that in equities. 152 00:09:23,320 --> 00:09:26,480 Speaker 1: But then later in the month and around mid month 153 00:09:27,360 --> 00:09:31,360 Speaker 1: in January, as people started to notice some of the 154 00:09:31,400 --> 00:09:35,000 Speaker 1: things that we're going on in Asia, we noticed that 155 00:09:35,120 --> 00:09:39,760 Speaker 1: our potential signals in fixed income started actually to tick up, 156 00:09:40,080 --> 00:09:44,480 Speaker 1: our short view on energy started to grow. And then 157 00:09:44,520 --> 00:09:47,480 Speaker 1: as we had sort of an initial hiccup at the 158 00:09:47,600 --> 00:09:51,480 Speaker 1: end of January, we started to pick up some potential 159 00:09:51,559 --> 00:09:55,560 Speaker 1: concern um, not in US equity markets, but in some 160 00:09:55,679 --> 00:09:58,920 Speaker 1: of the cross asset markets. And what was interesting is 161 00:09:58,960 --> 00:10:02,439 Speaker 1: that you start to get to a position which looked 162 00:10:02,559 --> 00:10:07,080 Speaker 1: very hedged, so it was long equities, long fixed income, 163 00:10:07,200 --> 00:10:10,760 Speaker 1: short energy. Now, if you think about that, that's really 164 00:10:10,840 --> 00:10:14,280 Speaker 1: a hedged position. It's almost like a no position in 165 00:10:14,320 --> 00:10:17,880 Speaker 1: the sense that you're kind of if equities go down, 166 00:10:17,920 --> 00:10:20,320 Speaker 1: you have things that might go up UM in terms 167 00:10:20,360 --> 00:10:24,000 Speaker 1: of your positioning. So that continued in through the month 168 00:10:24,000 --> 00:10:29,320 Speaker 1: of February. So February nineteen was the peak before the 169 00:10:29,360 --> 00:10:33,040 Speaker 1: great fall. And what's been interesting about that is that 170 00:10:33,400 --> 00:10:35,800 Speaker 1: all of the other signals that we were seeing and 171 00:10:35,920 --> 00:10:39,920 Speaker 1: other asset classes just extended during these periods of time. 172 00:10:40,000 --> 00:10:43,640 Speaker 1: So the short energy trade grew strength. We also saw 173 00:10:43,640 --> 00:10:48,200 Speaker 1: a fixed income positively responding to that. So for us, 174 00:10:48,280 --> 00:10:51,920 Speaker 1: it was really about UM, a somewhat hedged position. So 175 00:10:52,280 --> 00:10:55,360 Speaker 1: Trent following an average was roughly flat for the month 176 00:10:55,360 --> 00:10:59,480 Speaker 1: of February, which I think is relatively spectacular given the 177 00:10:59,559 --> 00:11:03,680 Speaker 1: type of moves that we saw. Then in March, as 178 00:11:03,760 --> 00:11:07,800 Speaker 1: we were seeing this move continue, we we're getting out 179 00:11:07,800 --> 00:11:12,400 Speaker 1: of equity markets and trend failing signals were reducing exposure 180 00:11:12,440 --> 00:11:16,760 Speaker 1: to equities down to an almost neutral to very low position, 181 00:11:17,440 --> 00:11:22,959 Speaker 1: and we saw continued gains in fixed income and as 182 00:11:23,000 --> 00:11:27,200 Speaker 1: well as commodity markets. Okayny I love if you could 183 00:11:27,600 --> 00:11:30,440 Speaker 1: sort of explain for us some of the signals that 184 00:11:30,480 --> 00:11:34,640 Speaker 1: define a trend uh in your strategies. Um, you know, 185 00:11:34,720 --> 00:11:37,520 Speaker 1: is it as simple as something like a moving average? Uh? 186 00:11:37,640 --> 00:11:41,320 Speaker 1: You know, I imagine there's a lot of complex math involved. 187 00:11:41,360 --> 00:11:44,480 Speaker 1: But what are some of the sort of cornerstones of 188 00:11:44,559 --> 00:11:49,559 Speaker 1: identifying a trend that the strategy uses. So the key 189 00:11:49,760 --> 00:11:53,959 Speaker 1: approach to trend falling is about taking many different technical 190 00:11:54,000 --> 00:11:58,559 Speaker 1: methodologies and using those to create some sort of score 191 00:11:58,760 --> 00:12:02,880 Speaker 1: or vote in terms of the direction of an individual market. 192 00:12:03,400 --> 00:12:08,320 Speaker 1: So this requires you to parameterize how much data you're 193 00:12:08,360 --> 00:12:11,559 Speaker 1: going to use and what methodology you're going to use 194 00:12:11,600 --> 00:12:14,640 Speaker 1: in terms of measuring the strength of that particular trend. 195 00:12:15,600 --> 00:12:17,880 Speaker 1: What we tend to do, and what many in the 196 00:12:17,960 --> 00:12:20,920 Speaker 1: space tend to do, is we use a wide range 197 00:12:21,000 --> 00:12:26,360 Speaker 1: of different methodologies, some using more technical simple terms like 198 00:12:26,440 --> 00:12:30,800 Speaker 1: moving averages and breakout signals, and others too as complicated 199 00:12:30,840 --> 00:12:34,920 Speaker 1: as drawing from the machine learning literature and trying to 200 00:12:34,960 --> 00:12:39,200 Speaker 1: do things a little bit more nonlinearly. So overall, I 201 00:12:39,280 --> 00:12:42,760 Speaker 1: tend to explain a trend filling system is really similar 202 00:12:42,800 --> 00:12:45,880 Speaker 1: to a voting system. You have many different models with 203 00:12:46,000 --> 00:12:49,400 Speaker 1: different time horizons in terms of how much data they're using, 204 00:12:49,880 --> 00:12:52,400 Speaker 1: and they all come together an aggregate to vote on 205 00:12:52,480 --> 00:12:55,080 Speaker 1: where the market is going. So if you think about 206 00:12:55,080 --> 00:12:57,760 Speaker 1: what we're really trying to do, we're taking in all 207 00:12:57,800 --> 00:13:01,000 Speaker 1: this data from the markets would as you know, if 208 00:13:01,000 --> 00:13:02,720 Speaker 1: you look at a week, and you look at a month, 209 00:13:02,760 --> 00:13:04,800 Speaker 1: and you look at a year, they can look very different. 210 00:13:05,440 --> 00:13:09,040 Speaker 1: Try to use mathematical techniques to measure those and then 211 00:13:09,200 --> 00:13:13,839 Speaker 1: aggregate them together. Let those approaches vote to create an 212 00:13:13,840 --> 00:13:18,240 Speaker 1: overall signal. What this means is that in aggregate we 213 00:13:18,320 --> 00:13:21,920 Speaker 1: are trying to measure all the information and bring it 214 00:13:22,000 --> 00:13:24,960 Speaker 1: together to give ourselves an overall view of where the 215 00:13:25,040 --> 00:13:28,720 Speaker 1: market's going. Because trend falling is really just momentum trading 216 00:13:29,200 --> 00:13:33,480 Speaker 1: across different assets. You're following where things are moving, and 217 00:13:33,520 --> 00:13:53,080 Speaker 1: you're adjusting as the world changes. Whenever there is a 218 00:13:53,160 --> 00:13:57,040 Speaker 1: heightened state of volatility in the market, UM, there's this 219 00:13:57,120 --> 00:14:02,400 Speaker 1: tendency for analysts or or market pundits who can't really 220 00:14:02,400 --> 00:14:05,080 Speaker 1: explain what's going on, to sort of point the finger 221 00:14:05,120 --> 00:14:08,920 Speaker 1: at the machines running quant strategies. Uh. You know, if 222 00:14:08,960 --> 00:14:13,320 Speaker 1: if not trend following, then uh, volatility targeting and UM 223 00:14:13,400 --> 00:14:15,960 Speaker 1: even risk parity that sort of thing, And you know 224 00:14:16,000 --> 00:14:19,080 Speaker 1: that it's kind of an easy scapegoat. I guess for 225 00:14:19,080 --> 00:14:22,160 Speaker 1: for some people to say, you know, this market doesn't 226 00:14:22,200 --> 00:14:25,800 Speaker 1: make any sense to anyone but a machine running the 227 00:14:25,920 --> 00:14:28,680 Speaker 1: strategy and the application. A lot of times is that 228 00:14:28,920 --> 00:14:32,680 Speaker 1: UM uh quant strategies tend to do the same type 229 00:14:32,680 --> 00:14:35,560 Speaker 1: of thing you're talking about, UH, all sort of reacting 230 00:14:35,640 --> 00:14:38,720 Speaker 1: maybe racking to different signals, but the end result being 231 00:14:38,760 --> 00:14:41,560 Speaker 1: to sell or buy all at the same time and 232 00:14:41,640 --> 00:14:46,760 Speaker 1: possibly exaggerate the moves in the market. UM. Does do 233 00:14:46,800 --> 00:14:52,200 Speaker 1: you think that really happens in general? Uh? And specifically? 234 00:14:52,440 --> 00:14:55,080 Speaker 1: And and say the volatility we've seen the last couple 235 00:14:55,080 --> 00:14:57,760 Speaker 1: of months, UM or is it just impossible to know 236 00:14:57,880 --> 00:15:02,240 Speaker 1: and sort of impossible to dice sacked what is causing 237 00:15:02,320 --> 00:15:05,880 Speaker 1: massive swings like that? I always see and and I 238 00:15:05,920 --> 00:15:08,680 Speaker 1: think it's an easy narrative to say that, because it's 239 00:15:08,720 --> 00:15:12,080 Speaker 1: easier to blame a machine than a person. UM. But 240 00:15:12,840 --> 00:15:15,080 Speaker 1: one other thing is is that I always go back 241 00:15:15,120 --> 00:15:21,280 Speaker 1: to the basic tenants of volatility. Volatility represents uncertainty. When 242 00:15:21,320 --> 00:15:24,200 Speaker 1: things go up and down a lot, it's because people, 243 00:15:24,480 --> 00:15:29,000 Speaker 1: whether or not it's algorithm or a person, I don't 244 00:15:29,000 --> 00:15:32,760 Speaker 1: know what's going on, and they're unsure about where the 245 00:15:32,840 --> 00:15:36,480 Speaker 1: markets are going, and I would say that across the 246 00:15:36,560 --> 00:15:40,840 Speaker 1: quant space it's actually been very mixed. Trend Falling strategies 247 00:15:40,840 --> 00:15:44,160 Speaker 1: are one of the only strategies that have really tend 248 00:15:44,200 --> 00:15:47,000 Speaker 1: to do very well in this environment. It actually turns 249 00:15:47,000 --> 00:15:49,320 Speaker 1: out that a lot of the other quant strategies have 250 00:15:49,560 --> 00:15:52,920 Speaker 1: struggled UM. The reason being is that they may have 251 00:15:53,080 --> 00:15:58,240 Speaker 1: very specific hedges or offsets and in strategies that when 252 00:15:58,280 --> 00:16:02,200 Speaker 1: things get volatile, things get complicated for them. UM. And 253 00:16:02,240 --> 00:16:04,240 Speaker 1: so I would say that I tend to think about 254 00:16:04,320 --> 00:16:08,640 Speaker 1: volatility is really our perception or it's a measurement of 255 00:16:08,760 --> 00:16:12,560 Speaker 1: our view of uncertainty. So the environment that we just 256 00:16:12,640 --> 00:16:15,920 Speaker 1: went into, and you can probably you probably agree with 257 00:16:15,960 --> 00:16:19,640 Speaker 1: me yourself, is that the idea of a pandemic, the 258 00:16:19,720 --> 00:16:22,600 Speaker 1: idea of staying at home, the idea of a lockdown 259 00:16:23,440 --> 00:16:27,560 Speaker 1: UM is something so uncertain that it is not at 260 00:16:27,600 --> 00:16:30,600 Speaker 1: all surprising to me that markets would be up and 261 00:16:30,680 --> 00:16:34,880 Speaker 1: down every other day. Because volatility is a measure of 262 00:16:35,000 --> 00:16:39,640 Speaker 1: uncertainty things going around UM A lot is much more 263 00:16:39,680 --> 00:16:44,760 Speaker 1: about how we feel about what things, what things are worth. UM. 264 00:16:44,840 --> 00:16:49,400 Speaker 1: Now could UH systematic managers or quad managers when people 265 00:16:49,840 --> 00:16:53,240 Speaker 1: do the same thing move these things more, it's possible. 266 00:16:53,560 --> 00:16:56,360 Speaker 1: I'd have to do a much more extensive research and 267 00:16:56,440 --> 00:16:59,360 Speaker 1: really get into the data. I know that even when 268 00:16:59,360 --> 00:17:01,800 Speaker 1: we looked at the flash crash, I know the CFTC 269 00:17:02,160 --> 00:17:05,600 Speaker 1: did some extensive analysis of that and found actually that 270 00:17:06,080 --> 00:17:09,600 Speaker 1: it was a fundamental trade that was just too large 271 00:17:09,680 --> 00:17:13,040 Speaker 1: that created a dislocation. So I think I think that's 272 00:17:13,040 --> 00:17:16,159 Speaker 1: a great question. It's definitely a good narrative. People like 273 00:17:16,280 --> 00:17:20,200 Speaker 1: it blame the machine, um, But for me, it's really 274 00:17:20,960 --> 00:17:25,240 Speaker 1: this volatility isn't someone's fault. It's more that we don't know. 275 00:17:26,240 --> 00:17:31,520 Speaker 1: It's really representative of how unsure the markets are about 276 00:17:31,560 --> 00:17:35,800 Speaker 1: what's going on. No, there's no doubt that headlines news 277 00:17:35,800 --> 00:17:39,640 Speaker 1: flow has been on hyper drive. It scenes and Mike, 278 00:17:39,760 --> 00:17:42,840 Speaker 1: you know that that has given us plenty of opportunities 279 00:17:42,880 --> 00:17:46,479 Speaker 1: at least to uh think of crazy things for our 280 00:17:46,840 --> 00:17:51,840 Speaker 1: crazy things and markets for sure, So what did what's 281 00:17:51,880 --> 00:17:54,920 Speaker 1: your best? What has been shocking to me has been 282 00:17:54,960 --> 00:17:58,720 Speaker 1: the contango in oil that we have seen the fact 283 00:17:58,760 --> 00:18:03,840 Speaker 1: that may oil pray says we're nineteen and September thirty something, 284 00:18:03,960 --> 00:18:07,720 Speaker 1: and I saw a report from Bloomberg today that people, um, 285 00:18:07,800 --> 00:18:10,280 Speaker 1: so going back to what we saw bonds in the 286 00:18:10,320 --> 00:18:13,640 Speaker 1: summer where people are willing to pay to own German debt. 287 00:18:13,720 --> 00:18:15,919 Speaker 1: Now we have a situation where you get paid to 288 00:18:16,000 --> 00:18:20,560 Speaker 1: sell gasoline, So maybe that's the next thing. We all 289 00:18:20,560 --> 00:18:23,920 Speaker 1: go around and find gasoline and sell it, because, um, 290 00:18:24,520 --> 00:18:26,800 Speaker 1: that's a weird world that you could get paid to 291 00:18:26,840 --> 00:18:31,560 Speaker 1: actually sell gasoline. There must be just oil tigers crowded 292 00:18:31,600 --> 00:18:33,640 Speaker 1: off the shores right now full of oil. It's it's 293 00:18:33,640 --> 00:18:37,439 Speaker 1: an amazing Uh, that is an amazing situation. Apparently they 294 00:18:37,480 --> 00:18:40,400 Speaker 1: said it was twelve cents a gallon in in North 295 00:18:40,480 --> 00:18:43,919 Speaker 1: Dakota for oil. Well that's a good one, Katie, and 296 00:18:43,920 --> 00:18:49,240 Speaker 1: you get you get props for sticking close to the markets, Sara, 297 00:18:49,320 --> 00:18:53,119 Speaker 1: can you top Katie's oil can tango? So I brought 298 00:18:53,200 --> 00:18:56,560 Speaker 1: to one that's markets related and one that's less so so, 299 00:18:57,600 --> 00:19:01,600 Speaker 1: but I'll start with the market related one and that's that. 300 00:19:02,160 --> 00:19:06,600 Speaker 1: Now the five largest companies make up which is a 301 00:19:06,600 --> 00:19:09,600 Speaker 1: new record. And I think it's just been pretty amazing 302 00:19:09,600 --> 00:19:11,960 Speaker 1: that we continue to see a lot of these mega 303 00:19:12,040 --> 00:19:16,240 Speaker 1: cap technology and internet companies just continue to perform so 304 00:19:16,280 --> 00:19:19,480 Speaker 1: well in this type of environment. I think like a 305 00:19:19,560 --> 00:19:22,160 Speaker 1: couple of years ago, people would have said that when 306 00:19:22,160 --> 00:19:24,280 Speaker 1: the bull market came to an end. The companies that 307 00:19:24,359 --> 00:19:26,560 Speaker 1: let on the way up, we're going to lead on 308 00:19:26,600 --> 00:19:29,600 Speaker 1: the way down and that and that certainly hasn't happened. Um. 309 00:19:29,640 --> 00:19:31,080 Speaker 1: So I think the fact that we have a new 310 00:19:31,119 --> 00:19:34,280 Speaker 1: record related to top heaviness in the market is pretty crazy. 311 00:19:34,440 --> 00:19:39,480 Speaker 1: For one, Yeah, absolutely absolutely, and then uh, the less 312 00:19:39,520 --> 00:19:41,960 Speaker 1: markets related one really not related to the markets at all. 313 00:19:42,520 --> 00:19:45,320 Speaker 1: There was just a great story in the New York Times. 314 00:19:45,359 --> 00:19:50,000 Speaker 1: It was a bit uh, someone would say humorous. Um, 315 00:19:50,119 --> 00:19:52,719 Speaker 1: but the headline reads Trump wanted a radio show, but 316 00:19:52,840 --> 00:19:55,520 Speaker 1: he didn't want to compete with them, and it's it's 317 00:19:55,560 --> 00:19:58,080 Speaker 1: a great read if you have some downtime. Essentially, it's 318 00:19:58,080 --> 00:20:01,040 Speaker 1: just details President Trump going to one of the Coronavirus 319 00:20:01,160 --> 00:20:03,280 Speaker 1: Task Force meetings and laying out this plan that he 320 00:20:03,320 --> 00:20:06,879 Speaker 1: wanted to have a two hour radio show each day. Um. 321 00:20:06,960 --> 00:20:08,560 Speaker 1: And the only reason he didn't want to do it 322 00:20:08,600 --> 00:20:11,680 Speaker 1: is because he didn't want to knock Rush Limbaugh's ratings. Um. 323 00:20:11,720 --> 00:20:15,080 Speaker 1: It's it's an interesting rate. Uh, it's just a bit 324 00:20:15,200 --> 00:20:17,239 Speaker 1: humorous in these In these times, he has a two 325 00:20:17,280 --> 00:20:19,400 Speaker 1: hour TV show every night at the at the press 326 00:20:19,480 --> 00:20:21,960 Speaker 1: count right now, he has a TV show instead with 327 00:20:21,960 --> 00:20:26,680 Speaker 1: with great ratings so crazy times. I'm not sure how 328 00:20:26,720 --> 00:20:29,080 Speaker 1: two hours on the radio helps him fight the virus, 329 00:20:29,160 --> 00:20:32,840 Speaker 1: but he does like to talk, so UM, I have 330 00:20:32,880 --> 00:20:36,000 Speaker 1: no no doubt he could fill two hours or radio 331 00:20:36,080 --> 00:20:38,520 Speaker 1: time a day. All right, these are all pretty good. 332 00:20:38,520 --> 00:20:42,800 Speaker 1: I will I'll give you mine, um mine. As you know, 333 00:20:42,880 --> 00:20:45,400 Speaker 1: I like to push the boundaries of what is considered 334 00:20:45,440 --> 00:20:49,160 Speaker 1: a market story. Uh, but this is certainly crazy now. 335 00:20:50,520 --> 00:20:54,080 Speaker 1: One of the most depressing things about this virus, uh 336 00:20:54,680 --> 00:20:57,040 Speaker 1: for the average person who hasn't really had to deal 337 00:20:57,080 --> 00:21:00,640 Speaker 1: with with a sick or dying relative, but the lack 338 00:21:00,680 --> 00:21:05,160 Speaker 1: of sports on TV uh throughout this has been traumatic 339 00:21:05,240 --> 00:21:09,400 Speaker 1: for a lot of people, um, especially gamblers. And here's 340 00:21:09,400 --> 00:21:12,040 Speaker 1: where we get into the markets. Now that online gambling 341 00:21:12,200 --> 00:21:15,680 Speaker 1: is legal in some states, I I think it's okay 342 00:21:15,680 --> 00:21:18,520 Speaker 1: to consider that an official market, at least for the 343 00:21:18,520 --> 00:21:21,399 Speaker 1: purposes of this crea before. Yeah, at least for the 344 00:21:21,400 --> 00:21:26,480 Speaker 1: purposes of this this crazy observation. So the first major 345 00:21:26,600 --> 00:21:29,760 Speaker 1: league sport to get back in business, do you know 346 00:21:29,800 --> 00:21:33,439 Speaker 1: what it is? Well, not counting world wide wrestling. Uh, 347 00:21:33,560 --> 00:21:35,680 Speaker 1: that's what I was gonna say. W w Okay, I 348 00:21:35,720 --> 00:21:38,480 Speaker 1: guess that might be there might be a tie between that, 349 00:21:38,840 --> 00:21:41,439 Speaker 1: but you can't. You can't gamble on that. I mean, 350 00:21:41,480 --> 00:21:43,000 Speaker 1: I guess you could. But if you're gonna gamble on 351 00:21:43,080 --> 00:21:49,120 Speaker 1: professional professional wrestling, then you've got goods of major problems. 352 00:21:49,960 --> 00:21:53,480 Speaker 1: But I believe if you have inside information, right, yeah, 353 00:21:53,520 --> 00:21:56,840 Speaker 1: but those are all plans anyways, right, they're all chograph's 354 00:21:56,880 --> 00:22:00,200 Speaker 1: bet on the good guy. I guess um. They're is 355 00:22:00,240 --> 00:22:04,360 Speaker 1: a league called the Major League Eating League, and it's 356 00:22:04,400 --> 00:22:06,440 Speaker 1: these guys you know, like at the hot dog eating 357 00:22:06,440 --> 00:22:09,600 Speaker 1: contests on Conan Island. It's all those guys. Uh. It's 358 00:22:09,600 --> 00:22:12,919 Speaker 1: been officially turned into a league called Major League Eating 359 00:22:13,800 --> 00:22:16,159 Speaker 1: and they believe they are the first professional sport to 360 00:22:16,240 --> 00:22:21,800 Speaker 1: get back in business. They're having eating tournament. Everyone's gonna 361 00:22:21,800 --> 00:22:25,679 Speaker 1: be at their home zooming in or or skyping in. 362 00:22:25,760 --> 00:22:28,199 Speaker 1: I guess uh. And you'll be able to gamble on it. 363 00:22:28,240 --> 00:22:30,840 Speaker 1: They've already set some of the over unders and stuff 364 00:22:30,880 --> 00:22:34,800 Speaker 1: like that on it. Let me just tell you what 365 00:22:34,880 --> 00:22:37,400 Speaker 1: you have to do to to participate in this tournament. 366 00:22:37,520 --> 00:22:41,320 Speaker 1: So the qualifying round will consist of two pounds of 367 00:22:41,359 --> 00:22:45,040 Speaker 1: slice bologney. So you have the two pounds of slice bologney, 368 00:22:45,600 --> 00:22:48,119 Speaker 1: and it's a race. So who can eat that two 369 00:22:48,160 --> 00:22:51,560 Speaker 1: pounds of blowney. The fastest I've read somewhere the overunder 370 00:22:51,720 --> 00:22:56,800 Speaker 1: was like sixty nine seconds three to eat two pounds 371 00:22:56,800 --> 00:23:00,320 Speaker 1: of blaney. So um, So, Mike, you're not you're not 372 00:23:00,359 --> 00:23:03,960 Speaker 1: going to try to take part of Maybe if it 373 00:23:04,080 --> 00:23:09,159 Speaker 1: was I don't know about bolony the quarter finals hot dogs, 374 00:23:09,200 --> 00:23:11,439 Speaker 1: I could I don't know, I could kind of see that. 375 00:23:11,480 --> 00:23:15,240 Speaker 1: If it was chicken wings, maybe I I could get 376 00:23:15,240 --> 00:23:17,960 Speaker 1: into that. I'm from Philly, where the the big competition 377 00:23:18,000 --> 00:23:21,439 Speaker 1: is the chicken chicken wing eating competitions. But so then 378 00:23:21,480 --> 00:23:24,560 Speaker 1: from the quarterfinals, uh, you'll have to eat a family 379 00:23:24,600 --> 00:23:27,879 Speaker 1: sized pack of oreos and a half a gallon of milk. 380 00:23:28,080 --> 00:23:31,520 Speaker 1: That doesn't seem that tough actually, but here's where, yeah, 381 00:23:31,760 --> 00:23:36,800 Speaker 1: here's where they really will separate the pros from the amateurs. Though. Uh. 382 00:23:36,920 --> 00:23:39,400 Speaker 1: To make it to the finals, you'll have to eat 383 00:23:39,480 --> 00:23:45,399 Speaker 1: over a gallon of baked beans. Oh and if you 384 00:23:45,440 --> 00:23:50,919 Speaker 1: win that, the the finals consists of ten individual cups 385 00:23:51,040 --> 00:23:53,680 Speaker 1: of ramen noodles. Um. But I think that gun. I 386 00:23:53,680 --> 00:23:56,320 Speaker 1: wonder who comes up with this stuff beans and ramen? 387 00:23:56,359 --> 00:23:58,360 Speaker 1: What are they assuming more people have these things at 388 00:23:58,359 --> 00:24:03,080 Speaker 1: their home. I wonder if that's it. Yeah. Yeah, Oreos 389 00:24:03,400 --> 00:24:05,520 Speaker 1: the gaunt of baked beans, I think is the deal 390 00:24:05,560 --> 00:24:08,600 Speaker 1: breaker there. I don't, I don't know, I I I 391 00:24:08,960 --> 00:24:12,600 Speaker 1: pity the person who gets that far. It's a hard one. 392 00:24:12,720 --> 00:24:15,400 Speaker 1: I must say. I haven't been dragged into eating a 393 00:24:15,440 --> 00:24:18,800 Speaker 1: food watching it. But I've been watching um the horse 394 00:24:18,880 --> 00:24:21,560 Speaker 1: tournaments for the NBA and the w n b A 395 00:24:21,760 --> 00:24:26,040 Speaker 1: and also i've been watching some NBA players playing two 396 00:24:26,119 --> 00:24:31,240 Speaker 1: K on Xbox, which has been a pretty entertaining and 397 00:24:31,320 --> 00:24:35,000 Speaker 1: this time. Yeah, yeah, that's that's not bad. Let's say, Hey, 398 00:24:35,000 --> 00:24:38,760 Speaker 1: it beats beats watching a rerun of a game. Anyway, Katie, 399 00:24:38,800 --> 00:24:40,320 Speaker 1: maybe you could get your pals and m I t 400 00:24:40,480 --> 00:24:44,560 Speaker 1: you could have like a New England clam chowder eating competition. 401 00:24:47,720 --> 00:24:50,280 Speaker 1: Why not? I think I think it's probably hard to 402 00:24:50,320 --> 00:24:54,119 Speaker 1: get ahold of some fresh clam chowder around here. I 403 00:24:54,160 --> 00:25:01,439 Speaker 1: don't know. Maybe there's a delivery service to check if legal, right, Uh, 404 00:25:02,359 --> 00:25:04,560 Speaker 1: all right, well do what you gotta do in these times. 405 00:25:06,160 --> 00:25:08,920 Speaker 1: But on that note, anyways, Katie Kaminski, thank you so 406 00:25:09,040 --> 00:25:11,439 Speaker 1: much for joining the show this week. Thank you so 407 00:25:11,560 --> 00:25:21,119 Speaker 1: much for having me. What goes up? We'll be back 408 00:25:21,200 --> 00:25:23,520 Speaker 1: next week. Until then, you can find us on the 409 00:25:23,560 --> 00:25:27,520 Speaker 1: Bloomberg Terminal, website and app, or wherever you get your podcasts. 410 00:25:27,880 --> 00:25:29,520 Speaker 1: We'd love it if you took the time to rate 411 00:25:29,560 --> 00:25:32,480 Speaker 1: interview the show on Apple podcast so more listeners can 412 00:25:32,480 --> 00:25:35,480 Speaker 1: find us, and you can find us on Twitter, follow 413 00:25:35,560 --> 00:25:39,480 Speaker 1: me at at Sarah Panzac, Mike is that Reaganonymous, and 414 00:25:39,600 --> 00:25:43,960 Speaker 1: you can also follow Bloomberg Podcasts at podcasts. What Goes 415 00:25:44,080 --> 00:25:47,000 Speaker 1: Up is produced by Toper Foreheads. The head of Bloomberg 416 00:25:47,040 --> 00:25:50,560 Speaker 1: Podcast is Francesca Levie. Thanks for listening, See you next time. 417 00:26:04,880 --> 00:26:05,760 Speaker 1: Before