WEBVTT - Inside the Gerber Statistic with Sander Gerber of Hudson Bay Capital 0:00:02.520 --> 0:00:11.879 Bloomberg Audio Studios, podcasts, radio news. This is Masters in 0:00:11.960 --> 0:00:15.480 Business with Barry Ritholts on Bloomberg Radio. 0:00:16.360 --> 0:00:20.280 Strap yourself in for another good one. Sander Gerber, CEO 0:00:20.400 --> 0:00:25.680 CIO of Hudson Bay Capital. What a fascinating background he has, 0:00:26.720 --> 0:00:30.680 starting in philosophy and ending up on the floor of 0:00:30.760 --> 0:00:36.640 the American Stock Exchange as an equity options trader. That experience, 0:00:36.720 --> 0:00:40.960 those two things combined to really create a kind of 0:00:41.080 --> 0:00:44.840 unique perspective on the world of markets, on the world 0:00:44.880 --> 0:00:48.760 of risk, and on the world of models. You know, 0:00:48.880 --> 0:00:52.480 I've used the George Box quote a million times. All 0:00:52.560 --> 0:00:56.120 models are wrong, but some are useful. And the way 0:00:56.320 --> 0:01:01.680 Gerber goes about using models is very much along the 0:01:01.720 --> 0:01:05.280 George Box lines, which is, not only are we going 0:01:05.319 --> 0:01:08.000 to assume that models are wrong, but we want to 0:01:08.040 --> 0:01:11.840 create our own models to be able to identify when 0:01:11.920 --> 0:01:14.280 they're going to be at a great variance to what's 0:01:14.360 --> 0:01:17.280 going on in reality, and then how to position ourselves 0:01:17.760 --> 0:01:21.959 to take advantage of it. They're less directional traders than 0:01:21.959 --> 0:01:28.040 they are arbitreasures. Hudson Big Capital runs a dozen different 0:01:28.080 --> 0:01:32.880 strategies and they're all quite fascinating. Everything from risk, arb 0:01:33.000 --> 0:01:37.959 to private credit and real estate in the first quarter 0:01:38.000 --> 0:01:41.560 of twenty twenty five, where volatility spikes and a lot 0:01:41.560 --> 0:01:46.319 of people's expectations are dashed. Their models do really well. 0:01:46.760 --> 0:01:50.919 I find his depth of knowledge and his technical expertise 0:01:50.960 --> 0:01:54.360 to be absolutely fascinating. I think you'll find him to 0:01:54.400 --> 0:01:58.000 be fascinating also, with no further ado, my conversation with 0:01:58.080 --> 0:02:04.840 Hudson Bay Capitals Xander Gerbert. So let's start a little 0:02:04.840 --> 0:02:09.560 bit with your background bachelors and humanistic philosophy and an 0:02:09.639 --> 0:02:12.680 MBA from Wharton Finance. What was the career plan? 0:02:13.000 --> 0:02:15.280 Well, actually, I was good at math, so I first 0:02:15.400 --> 0:02:18.720 entered the Wharton School undergrad. I don't have an MBA 0:02:18.840 --> 0:02:21.960 from Wharton. And then when I was at Wharton, I 0:02:21.960 --> 0:02:26.400 didn't think I was getting an education, so I decided 0:02:26.480 --> 0:02:30.080 to transfer into the College of Arts and Sciences, so 0:02:30.080 --> 0:02:32.720 I got two degrees. Concurrently, I picked up a degree 0:02:32.760 --> 0:02:37.320 in philosophy. Humanistic philosophy. I wanted to understand the development 0:02:37.360 --> 0:02:39.520 of thought, how we got to where we are in. 0:02:39.480 --> 0:02:43.640 Society, epistemology or something more specific. 0:02:43.880 --> 0:02:47.200 It was moral philosophy, generally, starting with the ancient Greeks 0:02:47.200 --> 0:02:51.440 through the existentialists. I think that I used my philosophy 0:02:51.680 --> 0:02:54.880 background much more than my finance background, because it really 0:02:54.880 --> 0:02:57.120 gives you a different view on the world. When I 0:02:57.160 --> 0:03:03.200 was at Wharton colleg Andrew Krieger came in nineteen eighty 0:03:03.520 --> 0:03:10.000 seven to speak. He had majored in Sanskrit Eastern philosophy 0:03:10.160 --> 0:03:12.960 and then he got his MBA at Wharton and he 0:03:13.000 --> 0:03:16.200 was the leading FX trader at Banker's Trust. And he 0:03:16.240 --> 0:03:20.480 spoke about how his philosophy Eastern philosophy helped him understand 0:03:20.480 --> 0:03:24.360 the markets. That you might feel very convicted the markets 0:03:24.360 --> 0:03:26.120 should go a certain way, but the markets have their 0:03:26.120 --> 0:03:29.880 own mindset and you have to accept what the markets have. 0:03:30.680 --> 0:03:33.720 And it helped him emotionally to trade better because he 0:03:33.800 --> 0:03:36.000 realized that mother market was going to be right, and 0:03:36.040 --> 0:03:39.160 so it was from his philosophy background that he was 0:03:39.200 --> 0:03:44.400 able to reconcile that with him with his beliefs in 0:03:44.480 --> 0:03:46.200 terms of where markets should go, and it helped him 0:03:46.200 --> 0:03:47.080 to be a better trader. 0:03:47.320 --> 0:03:50.320 That I definitely can see that. You know the concept. 0:03:50.600 --> 0:03:53.320 I don't know if I'm stealing this from Zen Buddhism, 0:03:53.360 --> 0:03:57.040 but it's the water flows, but the rigid tree breaks 0:03:57.080 --> 0:04:01.160 in the storm, and it's very similar to, hey, that's 0:04:01.240 --> 0:04:03.440 an Eastern way of saying, why are you finding the 0:04:03.440 --> 0:04:04.440 trend exactly? 0:04:04.520 --> 0:04:06.600 And so, you know, when I was in college, I 0:04:06.600 --> 0:04:09.000 really didn't know much about the markets. And as I 0:04:09.040 --> 0:04:12.120 told you, I still I had entered first the Wharton School, 0:04:12.120 --> 0:04:13.920 so I was still getting my degree there, but I 0:04:13.960 --> 0:04:17.040 was really focused on the philosophy. And you know, people 0:04:17.080 --> 0:04:19.200 think the philosophy is not so practical, what are you 0:04:19.240 --> 0:04:21.240 going to do with it? And here the top FX 0:04:21.279 --> 0:04:23.880 trader in the world came and said, this is what 0:04:23.920 --> 0:04:26.039 you should be doing. So it was it was sort of, 0:04:26.480 --> 0:04:30.000 you know, ratification of what I was studying. 0:04:30.200 --> 0:04:33.040 Huh. I think you're the first person who I've ever 0:04:33.120 --> 0:04:37.360 spoken to who said, yeah, the Wharton School of Finance 0:04:37.400 --> 0:04:42.160 at University of Pennsylvania not a great education. Isn't it 0:04:42.240 --> 0:04:45.320 really true that most of our education, or at least 0:04:45.640 --> 0:04:48.280 for a lot of people, you're just self taught. Schools 0:04:48.279 --> 0:04:51.480 will give you a curriculum and here's the reading list, 0:04:51.520 --> 0:04:54.159 but it's up to you to kind of learn whatever 0:04:54.200 --> 0:04:54.960 there is to learn. 0:04:56.040 --> 0:04:58.680 I think it's a good point. You know, the Wharton 0:04:58.760 --> 0:05:03.160 School is arguable the finest finance school, but finance is 0:05:03.200 --> 0:05:06.320 a technical discipline, and I wanted to understand the world. 0:05:07.000 --> 0:05:09.800 And I think that you can only go a certain 0:05:10.279 --> 0:05:14.400 degree using that background. And it's true. Then in order 0:05:14.440 --> 0:05:19.520 to I think, upgrade yourself, you've got to be able 0:05:19.520 --> 0:05:23.840 to develop the capacity to self learn, to take in 0:05:24.080 --> 0:05:28.040 from the environment around you, to enable yourself to grow 0:05:28.120 --> 0:05:32.719 your skill set to your experiences through working with others. 0:05:32.960 --> 0:05:35.800 And that's something we try to incorporate within Hudson Bay 0:05:36.720 --> 0:05:40.720 is the ability for people's careers to develop, and it 0:05:40.800 --> 0:05:43.839 is something that you have to rely on self learning 0:05:43.839 --> 0:05:48.080 and within college in certain disciplines. In college, like in philosophy, 0:05:48.160 --> 0:05:52.240 a lot of it is you know, discovery, self discovery, 0:05:52.360 --> 0:05:55.719 and other disciplines there is no self discovery. So I 0:05:55.760 --> 0:05:58.400 think it is important to the humanistic background. 0:05:58.880 --> 0:06:02.920 So you come out of of Wharton and University of Pennsylvania, 0:06:03.080 --> 0:06:05.720 you start your career on the floor of the American 0:06:05.960 --> 0:06:10.760 Stock Exchange as an equity options market maker. That had 0:06:10.760 --> 0:06:16.840 to be a fascinating experience, especially nineteen nineties and two thousands, 0:06:16.880 --> 0:06:19.640 that was a hot period and option trading. Tell us 0:06:19.680 --> 0:06:21.160 a little bit about that experience. 0:06:21.760 --> 0:06:25.040 Well, actually, when I graduated Penn I had been I'd 0:06:25.040 --> 0:06:29.719 clerked on the floor of the Philadelphia Options Exchange in 0:06:29.920 --> 0:06:33.280 nineteen eighty seven, and I liked it. But my parents 0:06:33.320 --> 0:06:35.320 had spent all this money to send me to a 0:06:35.360 --> 0:06:38.440 fancy school. They had taken out a home equity loan 0:06:38.560 --> 0:06:41.240 to pay for my college tuition. So I thought to 0:06:41.279 --> 0:06:43.720 be a muslely floor trader would be disrespectful. So I 0:06:43.760 --> 0:06:46.120 went to Banning Company for two years, and I was 0:06:46.120 --> 0:06:50.120 in management consulting for two years. It was boring, but 0:06:50.200 --> 0:06:52.000 I did learn something from it, and then I came 0:06:52.080 --> 0:06:54.320 to the floor of the AMEX. 0:06:54.360 --> 0:06:59.200 Wait before you jump to the AMEX. Aside from learning 0:06:59.240 --> 0:07:01.600 that being was boring, what else did you learn? 0:07:02.440 --> 0:07:07.040 I learned how people can work together in good conscious 0:07:08.120 --> 0:07:12.680 with dedication and still muck things up. Because what we 0:07:12.720 --> 0:07:16.520 would do is we would parachute into places like British Airways, 0:07:16.560 --> 0:07:21.760 Montreal Trusts, uh CIA Industries, and we were like the 0:07:21.880 --> 0:07:25.280 external strategic planning and we would They would put young 0:07:25.360 --> 0:07:28.000 people like me, and we'd sit next to people and 0:07:28.040 --> 0:07:30.960 interview them and figure out why projects went to muck. 0:07:31.680 --> 0:07:35.440 And I understood from that that well meaning people can 0:07:35.440 --> 0:07:38.040 still muck things up because they don't have an appropriate 0:07:38.960 --> 0:07:43.880 guide frame or appropriate leadership. Or they're not so like 0:07:43.960 --> 0:07:47.040 little things can take projects astray. 0:07:47.360 --> 0:07:49.360 So what was it that drew you to the floor 0:07:49.400 --> 0:07:50.440 of the well? 0:07:50.440 --> 0:07:54.720 I enjoyed the Philadelphia floor, and also I was I 0:07:54.800 --> 0:08:00.440 always liked games, and so I and I had a 0:08:00.440 --> 0:08:04.920 talent I thought for trading, and so I went to 0:08:05.160 --> 0:08:09.400 the the AMEX. Someone gave me it was like eleven 0:08:09.440 --> 0:08:12.280 hundred dollars a month as a stipend, and I kept 0:08:12.360 --> 0:08:15.240 roughly half the profits. And there was no training. They 0:08:15.320 --> 0:08:17.480 just threw me there very in the deep. 0:08:17.360 --> 0:08:20.400 End of the pool. Whoever doesn't drown. Hey, you can grab. 0:08:20.320 --> 0:08:25.880 Exactly right, exactly right. And it took me from July 0:08:26.080 --> 0:08:28.600 of ninety one till December of ninety one. I made 0:08:28.640 --> 0:08:33.800 five hundred dollars profit. Not for me, five hundred dollars. 0:08:33.840 --> 0:08:37.160 Trading had a split which I had to split. Yes, well, 0:08:37.200 --> 0:08:39.360 actually because I had a draw, I didn't get anything. 0:08:39.760 --> 0:08:41.840 But then the next year I took off and it 0:08:41.920 --> 0:08:44.600 turned out that I did have a knack fort I 0:08:44.640 --> 0:08:48.040 was able to understand the volatility of the market. Is 0:08:48.200 --> 0:08:52.920 usually we're vol traders, and I did something that was 0:08:53.000 --> 0:08:57.000 two things that were novel on the floor. The first 0:08:57.160 --> 0:08:59.560 is I understood that you have to break down your 0:08:59.600 --> 0:09:04.560 volatile exposure month by month, which back then was unusual. 0:09:04.640 --> 0:09:06.719 In other words, people had these models that would give 0:09:06.760 --> 0:09:10.280 you one volatility exposure across the entire portfolio. And I 0:09:10.360 --> 0:09:13.280 realized that julys and earnings month, and August is a 0:09:13.280 --> 0:09:16.480 beach month, so you can't use those two months to 0:09:16.559 --> 0:09:18.920 offset each other. And so I was able to jerry 0:09:18.960 --> 0:09:21.400 rig the models that were early then to be able 0:09:21.440 --> 0:09:24.040 to look at my VEGA exposure month by month. That was, 0:09:24.920 --> 0:09:27.960 believe it or not unusual. And the second thing that 0:09:27.960 --> 0:09:31.320 that's early nineties is yes, that was ninety one, ninety two. 0:09:31.679 --> 0:09:34.440 Okay, all these things we kind of take for granted. 0:09:34.480 --> 0:09:37.160 I know, right at one point in time, you wonder 0:09:37.160 --> 0:09:40.800 why it's become so increasingly difficult to beat the broad index. 0:09:41.120 --> 0:09:43.520 It was a ton of inefficiencies, that's right, that's right. 0:09:43.559 --> 0:09:45.480 And it was a great edge for me to come 0:09:45.520 --> 0:09:48.200 to that realization. And maybe it was because I had 0:09:48.520 --> 0:09:51.120 studied the models at the Wharton School. We had broken 0:09:51.160 --> 0:09:53.640 them down, and I understood that the models are only 0:09:53.679 --> 0:09:55.960 as good as the inputs. And a lot of people 0:09:56.000 --> 0:09:58.960 back then were doing spreads in their head and the 0:09:59.000 --> 0:10:02.559 other group were using these canned models that would give 0:10:02.600 --> 0:10:07.040 you one volatility exposure across you know, the entire model. 0:10:07.280 --> 0:10:11.120 And the second thing that I realized was that you 0:10:11.240 --> 0:10:16.720 need to combine fundamentals with the technicals of the models. 0:10:16.760 --> 0:10:20.080 In other words, the models assumer normal distribution of returns, 0:10:21.559 --> 0:10:26.160 but when you get into some kind of event, it's 0:10:26.240 --> 0:10:29.280 no longer a normal distribution returns. It's you know, the 0:10:29.320 --> 0:10:31.120 stock's either going to go up a lot or down 0:10:31.160 --> 0:10:35.320 a lot. That's a barbell distribution, right as opposed to 0:10:35.360 --> 0:10:39.439 normal distribution. And so by looking at events and when 0:10:39.480 --> 0:10:43.040 they're going to happen and breaking down the VEGA exposure 0:10:43.160 --> 0:10:45.640 month by month, that gave me an edge that I 0:10:45.679 --> 0:10:48.360 was able to exploit. Do you find vega for listeners 0:10:48.360 --> 0:10:53.440 who are Vega is the volatility So of the an 0:10:53.440 --> 0:10:57.360 option has premium, and that premium is the extra amount 0:10:57.360 --> 0:11:00.439 you pay for the right to have limited loss and 0:11:00.520 --> 0:11:07.120 unlimited gain. And so that premium, that value of that 0:11:07.240 --> 0:11:12.760 option to exercise or not exercise with limited loss, goes 0:11:12.840 --> 0:11:16.520 up and down in value based upon the degree of movements. 0:11:16.559 --> 0:11:18.559 So when something's moving around a lot, that has a 0:11:18.600 --> 0:11:21.720 lot more value. So premium value goes up when things 0:11:21.720 --> 0:11:24.880 are not moving a lot, premium value goes down, and 0:11:24.920 --> 0:11:28.640 so by trading this range of volatility up and down, 0:11:29.040 --> 0:11:32.160 which is in part dependent on what's happening with the 0:11:32.160 --> 0:11:37.160 fundamentals of the stock, you were able to grab edge. 0:11:37.280 --> 0:11:40.320 So these are really second or third level derivatives. It's 0:11:40.400 --> 0:11:44.680 not the underlying value. It's the increase in value of 0:11:44.720 --> 0:11:48.959 the option and then within that the range and the 0:11:49.040 --> 0:11:52.880 variability of that increase in option value. That's what you 0:11:52.920 --> 0:11:53.440 were trading. 0:11:53.679 --> 0:11:58.439 Yes, and you know it's really not complicated. I mean 0:11:58.480 --> 0:12:00.840 Wall Street tries to make things much more more complicated 0:12:00.880 --> 0:12:05.880 than they are, but the simple, elegant solution is always better. 0:12:06.960 --> 0:12:09.680 So it might sound complicated, but it's really not right. 0:12:09.880 --> 0:12:13.080 And that complexity is a feature, not a bug. You 0:12:13.120 --> 0:12:16.440 can sell stuff if it's complicated and hard to understand. 0:12:16.800 --> 0:12:19.120 If it's simple, well I think I could do that. 0:12:19.120 --> 0:12:21.720 That's right. Wall Street tries to make things more complicated 0:12:21.760 --> 0:12:26.360 because it has to justify the sales commission and if 0:12:26.600 --> 0:12:28.960 but things really are not so complicated. 0:12:29.160 --> 0:12:33.440 So what was your biggest takeaway from your experiences as 0:12:33.480 --> 0:12:36.520 a trader? How did it shape how you look at 0:12:36.679 --> 0:12:40.120 the world of investing, How did it affect what you're 0:12:40.120 --> 0:12:41.360 doing in Hudson Bay today. 0:12:41.880 --> 0:12:44.000 Well, I really was grounded by that three and a 0:12:44.040 --> 0:12:47.440 half years of watching every tick on the stock. You know, 0:12:47.520 --> 0:12:52.040 and you're you're geographically limited on the floor. You can 0:12:52.080 --> 0:12:54.679 only trade at the post that you're standing by. 0:12:54.720 --> 0:12:59.000 Like physically in space, your physically heether to that trading 0:12:59.040 --> 0:12:59.640 thing exactly. 0:13:00.240 --> 0:13:02.520 And there are even rules that you had to do 0:13:02.600 --> 0:13:05.360 most of your trading in that geography, so you couldn't 0:13:05.360 --> 0:13:08.439 move around a lot. And what it taught me is that, 0:13:09.320 --> 0:13:13.160 you know, like a trading post, a strategy goes in 0:13:13.200 --> 0:13:15.880 and out of favor, and if you want to be 0:13:15.880 --> 0:13:18.000 able to make money in all markets all the time, 0:13:18.080 --> 0:13:22.240 you have to develop a toolkit that can go beyond 0:13:22.320 --> 0:13:26.040 one particular strategy. So you need to have multiple strategies 0:13:26.080 --> 0:13:30.800 to develop persistent profitability. The other thing that I learned 0:13:31.000 --> 0:13:33.000 was that you can make the right decisions and still 0:13:33.040 --> 0:13:37.480 lose money. I had plenty of time where looking back, 0:13:37.559 --> 0:13:40.320 it was the right decision, but the markets thought differently, 0:13:40.480 --> 0:13:43.560 and so you always have to be worried about what 0:13:43.679 --> 0:13:48.160 can go wrong. And risk is not about not losing money. 0:13:48.520 --> 0:13:51.360 Risk management is not about not losing money. Risk management 0:13:51.520 --> 0:13:56.440 is about unexpectedly losing money. In other words, when you're 0:13:56.600 --> 0:14:00.800 evaluating a situation, you should know what is your reason 0:14:00.840 --> 0:14:04.600 worst case downside. Now there's always the black swan that 0:14:04.800 --> 0:14:08.280 maybe you can't figure on, but you should. But risk 0:14:08.360 --> 0:14:12.680 management is always about understanding what could go wrong and 0:14:12.800 --> 0:14:14.520 quantifying what could go wrong. 0:14:14.800 --> 0:14:16.880 So I want to unpack what you just said, because 0:14:16.920 --> 0:14:23.680 it's filled with goodness. First, you're referring to your approach 0:14:23.760 --> 0:14:27.400 is Hey, we're really more process focused than outcome focused, 0:14:27.400 --> 0:14:30.720 because if you have a good process, even if you 0:14:30.760 --> 0:14:34.480 get a bad outcome, it doesn't matter. Probabilities will eventually 0:14:34.680 --> 0:14:35.520 work in your fay. 0:14:35.600 --> 0:14:36.200 Exactly right. 0:14:36.520 --> 0:14:39.240 That's number one. But then the part two, which I 0:14:39.280 --> 0:14:44.600 think a lot of investors overlook, is and a risk 0:14:44.760 --> 0:14:48.600 management component that if the worst case happens, we still 0:14:48.640 --> 0:14:50.080 survive and lift to trade another. 0:14:50.080 --> 0:14:53.640 That's right, exactly right. And so at Hudson Bay, I 0:14:53.720 --> 0:14:56.760 created the deal code system, uh. 0:14:56.880 --> 0:14:58.360 Deal code system. 0:14:58.640 --> 0:15:02.120 Yes, so at the time, well, I left the floor 0:15:02.400 --> 0:15:05.040 beginning of ninety five and started deploying just the money 0:15:05.040 --> 0:15:08.640 I'd earned on the floor in an off floor trading account. 0:15:09.600 --> 0:15:13.000 And I would develop a strategy and hire someone else 0:15:13.040 --> 0:15:15.720 to run it and develop another strategy and hire someone 0:15:15.720 --> 0:15:18.240 else to run it. And as I was having other 0:15:18.280 --> 0:15:24.200 people manage basically my trading account, I realized I had 0:15:24.200 --> 0:15:26.720 to scale my risk profile that I developed on the 0:15:26.720 --> 0:15:31.240 floor over multiple risk takers, and I needed to do 0:15:31.320 --> 0:15:35.000 it in a manner that would produce persistent profitability. So 0:15:35.080 --> 0:15:36.880 at the time, we were trading a lot of risk 0:15:36.920 --> 0:15:40.360 garbitrage deals, so we called it a deal code, and 0:15:40.400 --> 0:15:43.680 a deal code is just a numerical moniker that we 0:15:43.720 --> 0:15:47.560 put on each trading idea within the book, and that 0:15:47.760 --> 0:15:51.720 enables us to focus in on how is that trade hedged, 0:15:51.960 --> 0:15:55.280 what's the risk riskiness? How much could that trade lose 0:15:55.360 --> 0:15:58.640 in a reasonable worst case scenario, and it gives us 0:15:58.640 --> 0:16:02.840 a batting average, so we can under stand is a 0:16:03.200 --> 0:16:06.000 portfolio manager winning more ideas than they lose so to 0:16:06.040 --> 0:16:08.640 be persistently profitable. I think it's not just about winning 0:16:08.680 --> 0:16:11.840 more dollars than you lose. It's about winning more ideas 0:16:11.880 --> 0:16:12.440 than you lose. 0:16:13.040 --> 0:16:16.000 So let's talk a little bit about Hudson Bay's strategy. 0:16:17.400 --> 0:16:22.600 You've been managing outside capital across a variety of asset 0:16:22.680 --> 0:16:27.160 classes and strategies. Tell us talk about some of the 0:16:27.280 --> 0:16:31.720 key strategies and what has been the drivers of making 0:16:31.800 --> 0:16:33.720 those strategies successful. Well. 0:16:33.760 --> 0:16:35.400 As I mentioned, I wanted to be able to make 0:16:35.440 --> 0:16:37.880 money in all market environments, so you need a tool 0:16:37.960 --> 0:16:41.000 set to do that. So our strategies are equity long 0:16:41.040 --> 0:16:47.400 short converts, credit, event merger, volatility trading. 0:16:48.120 --> 0:16:50.360 This isn't just I'm going to buy the S and 0:16:50.360 --> 0:16:53.240 P five hundred and put it away for a decade. 0:16:53.600 --> 0:16:57.920 You're active traders, and you're really looking to take advantage 0:16:57.960 --> 0:17:01.440 of situations where you have a fairly good idea of 0:17:01.480 --> 0:17:04.119 what the outcome is going to look like. It's not hey, 0:17:04.160 --> 0:17:08.320 this is open ended. Usually you're pretty confident in here's 0:17:08.320 --> 0:17:10.119 what our range of potential outcomes are. 0:17:10.240 --> 0:17:13.800 I think that, especially in today's world, you have to 0:17:13.880 --> 0:17:17.560 understand what your edge is versus the machines. And a 0:17:17.600 --> 0:17:22.960 machine can calculate risk based on historical precedent, but a 0:17:23.000 --> 0:17:26.639 machine cannot calculate risk based upon some kind of uncertainty 0:17:26.720 --> 0:17:29.160 due to some kind of event, callous or change that's 0:17:29.160 --> 0:17:32.080 coming up because it's new. So the machine doesn't have 0:17:32.119 --> 0:17:35.320 the ability to calibrate for something that's new. And so 0:17:35.440 --> 0:17:38.199 generally across all our strategies, that's what we're focused on, 0:17:38.400 --> 0:17:41.880 is we're focused on event callous change. How can we 0:17:42.040 --> 0:17:45.320 profit off of that in a way that machines cannot. 0:17:45.600 --> 0:17:50.399 So that's the fundamental criticism of models. All models assume 0:17:50.520 --> 0:17:52.200 that the world in the future is going to look 0:17:52.280 --> 0:17:55.560 like the world in the past. Risk management is what 0:17:55.640 --> 0:17:57.600 happens if the world doesn't look like out at. 0:17:57.640 --> 0:18:00.520 Us precisely, And that's why we don't use the standard 0:18:00.680 --> 0:18:05.440 risk management models. I actually created a statistic, the Gerber statistic, 0:18:05.560 --> 0:18:10.119 that helps to understand diversification between our deal codes, between 0:18:10.160 --> 0:18:13.639 our investment positions. A lot of our competitors are tied 0:18:13.680 --> 0:18:19.879 to factor based modeling, which ultimately, underneath it is reliant 0:18:19.960 --> 0:18:24.639 on regression analysis. Regressions. Our straight line fits through normalized 0:18:24.680 --> 0:18:28.640 sets of data, and human relationships don't file straight lines, 0:18:28.680 --> 0:18:32.800 and certainly market relationships don't file straight lines. So using 0:18:32.840 --> 0:18:37.640 that as the underpinning of a risk management system is 0:18:38.600 --> 0:18:42.600 just incorrect. And so we've created a whole different structure. 0:18:42.880 --> 0:18:44.879 As I said, we've used since nineteen ninety eight, and 0:18:44.880 --> 0:18:49.520 I think that's given us the ability to weather storms 0:18:49.560 --> 0:18:51.840 and profit from it in ways that our competitors can. 0:18:52.560 --> 0:18:55.440 So let's talk a little bit about the Gerber statistic. 0:18:56.240 --> 0:19:02.199 You had this validated by Harry Markowitz, the creator of 0:19:02.560 --> 0:19:07.840 modern portfolio folio theory. Tell us about that collaboration and 0:19:09.320 --> 0:19:11.879 break down the Garberg statistic a little bit. How do 0:19:11.920 --> 0:19:13.280 you guys actually use it? 0:19:14.080 --> 0:19:16.879 So, because of my distrust of models, based upon my 0:19:16.920 --> 0:19:20.400 experience on the floor, in particularly the guts of the models, 0:19:20.520 --> 0:19:26.040 I never believed in the correlation statistic, that correlation is predictive, 0:19:27.280 --> 0:19:30.000 and this was I thought one of the underpinnings of 0:19:30.040 --> 0:19:33.679 modern portfolio theory that you look at the expected return 0:19:33.680 --> 0:19:37.800 of the stock, the expected variants of the stock, and 0:19:37.880 --> 0:19:42.240 the covariance of correlation between the different components of a portfolio. 0:19:43.160 --> 0:19:46.640 And at the time, you know, we used the deal 0:19:46.640 --> 0:19:49.960 code system and on Wall Street the banks were telling 0:19:50.000 --> 0:19:52.280 me this is nonsense, but don't even talk about it 0:19:52.280 --> 0:19:55.520 with investors. And then in eight when everyone lost money 0:19:55.560 --> 0:19:58.719 and we made money, I realized we were doing something different. 0:19:59.080 --> 0:20:00.760 And then I had the idea. Because of course I'd 0:20:00.800 --> 0:20:05.800 studied about Harry in modern portfolio theory. Everyone in finance has. 0:20:05.920 --> 0:20:08.240 He won the Nobel Prize. I decided, you know what, 0:20:08.280 --> 0:20:10.080 I'm going to go out to see him to see 0:20:10.080 --> 0:20:13.800 what he thinks about the Gerber statistic, and at the 0:20:13.840 --> 0:20:15.800 time it wasn't called the Gerber statistic. But a friend 0:20:15.800 --> 0:20:17.679 of mine said, gee, you really should file a patent 0:20:17.720 --> 0:20:20.320 on this before you see Harry, and so I did, 0:20:20.560 --> 0:20:22.200 and I had to name it something, so I called 0:20:22.200 --> 0:20:24.400 it the Gerber statistic. And we now have I think 0:20:24.440 --> 0:20:28.520 we just got our sixth patent on our process for diversification. 0:20:28.920 --> 0:20:32.120 So I got to see Harry in San Diego. Lovely guy. 0:20:32.960 --> 0:20:36.200 He welcomed me, and we're walking. He liked to walk 0:20:36.200 --> 0:20:39.080 along the beach and I said, Harry, you know, I 0:20:39.119 --> 0:20:43.120 don't think that correlation's predictive, and Harry said, you're right. 0:20:43.320 --> 0:20:45.960 I said, no, no, Harry, you don't understand it. I don't 0:20:46.000 --> 0:20:48.919 think that because it's one of the base foundational bases 0:20:49.800 --> 0:20:52.200 for what She won the Nobel Prize in Modern portfolio theory. 0:20:52.280 --> 0:20:56.720 Said Harry, I don't think that historical correlation has relevance 0:20:56.760 --> 0:20:58.960 to the future. And he said, you're right. And it 0:20:59.040 --> 0:21:02.600 turns out that in his nineteen fifty two paper that 0:21:02.720 --> 0:21:06.480 sets forth modern portfolio theory, he said that correlation should 0:21:06.520 --> 0:21:10.000 be determined by the judgment of practical men. In other words, 0:21:10.080 --> 0:21:13.720 the stock analysts should think what will be the relationship 0:21:13.800 --> 0:21:17.480 going forward, not to mind the past, but be forward looking. 0:21:17.880 --> 0:21:21.760 But in the nineteen sixties, as computing power increase, people said, oh, 0:21:22.000 --> 0:21:25.960 we can mind the statistic, this row statistic correlation, and 0:21:26.000 --> 0:21:28.960 then we can plug it into the model as correlation. 0:21:29.160 --> 0:21:33.080 He meant correlation in a semantic sense, not in a 0:21:33.119 --> 0:21:36.800 mathematical sense in terms of using in his model. So 0:21:37.280 --> 0:21:41.200 he actually said that the deal code system uses his system, 0:21:41.240 --> 0:21:45.640 the modern portfolio theory system. He said that there's three 0:21:45.720 --> 0:21:49.359 legs to his system. And so because we use limited loss, 0:21:49.480 --> 0:21:53.320 because we seek to diversification through hesing on the own, 0:21:53.400 --> 0:21:56.000 because we seek to win more than we lose in 0:21:56.040 --> 0:22:01.119 each investment idea, he said that is accordance with his system. 0:22:01.320 --> 0:22:04.639 But in any way, we we've written several papers together 0:22:05.440 --> 0:22:08.720 on the Gerber statistic within modern portfolio theory and have 0:22:08.800 --> 0:22:12.360 demonstrated that you get better performance with less risk by 0:22:12.400 --> 0:22:17.320 replacing historical covariance with the Gerber statistic. And Harry and 0:22:17.359 --> 0:22:20.560 I actually we only had really one disagreement, and the 0:22:20.600 --> 0:22:23.439 one disagreement was on factors. There's all these you know, 0:22:23.520 --> 0:22:27.440 factor methodologies, and Harry believed that only one factor matters 0:22:27.960 --> 0:22:31.679 for portfolios, and I think two factors matter, so and 0:22:31.760 --> 0:22:34.880 so that, but the other twenty three factors we both 0:22:34.880 --> 0:22:36.200 agree are complete nonsets. 0:22:36.720 --> 0:22:41.000 So if you look at the fomb of French model, 0:22:41.040 --> 0:22:43.280 which started out as two or three factors and then 0:22:43.320 --> 0:22:44.320 became five fact. 0:22:44.720 --> 0:22:47.280 And then grow and grow. If you speak to the 0:22:47.280 --> 0:22:51.959 research departments of bar Axioma, they'll tell you that thirty 0:22:52.000 --> 0:22:55.320 four to forty percent of a stock price movement can 0:22:55.400 --> 0:22:57.040 be explained by factors. 0:22:57.480 --> 0:22:59.720 Okay, so that's third, let's. 0:22:59.600 --> 0:23:03.240 Roll it a and of that third, eighty five percent 0:23:03.520 --> 0:23:07.520 of that third can be explained by the first five factors, okay, 0:23:07.600 --> 0:23:11.719 which means giving credit to five, which that's bar Naxioma 0:23:11.880 --> 0:23:16.399 tells you eighty five percent of the forty percent can 0:23:16.440 --> 0:23:18.959 be explained by five factors, which means the other twenty 0:23:19.000 --> 0:23:22.800 factors explain the fifteen percent of forty percent of the words. 0:23:22.880 --> 0:23:25.680 Six percent of a stock price movement can be explained 0:23:25.680 --> 0:23:30.240 by twenty one factors, right, meaning which is complete. You know, nonsense, 0:23:30.280 --> 0:23:33.959 but no, if you lever a portfolio up, you know 0:23:34.080 --> 0:23:37.040 ten times, all of a sudden, that six percent looks 0:23:37.119 --> 0:23:40.040 like it's sixty percent, but it's all complete nonsense. It's 0:23:40.119 --> 0:23:43.400 numerical mumbo jumbo. It's part of the whole Wall Street 0:23:44.440 --> 0:23:48.399