1 00:00:06,000 --> 00:00:08,280 Speaker 1: Welcome to Fear and Greed Q and A, where we 2 00:00:08,360 --> 00:00:12,600 Speaker 1: ask and answer questions about business, investing, economics, politics and more. 3 00:00:12,960 --> 00:00:17,240 Speaker 1: I'm Adam Langan. Today we're asking can algorithms beat humans 4 00:00:17,280 --> 00:00:21,239 Speaker 1: at investing? Or like artificial intelligence, is it the combination 5 00:00:21,560 --> 00:00:24,600 Speaker 1: of humans and machines that wins. Please note that this 6 00:00:24,680 --> 00:00:27,680 Speaker 1: is general information only and you should seek professional advice 7 00:00:27,720 --> 00:00:31,760 Speaker 1: before making any investment decisions. My guest today I'm delighted 8 00:00:31,800 --> 00:00:35,040 Speaker 1: to say is Ivan Sherman, chief investment officer at Siye 9 00:00:35,080 --> 00:00:38,600 Speaker 1: Tech Investments and the portfolio manager of the osbi's capital 10 00:00:38,960 --> 00:00:42,360 Speaker 1: sie Tech grow Wise Fund, a supporter of this podcast. 11 00:00:42,720 --> 00:00:47,640 Speaker 1: Originally from Argentina, Ivan holds a PhD and advanced certifications 12 00:00:47,680 --> 00:00:51,720 Speaker 1: from get This, London Business School, New York University's stern 13 00:00:52,080 --> 00:00:56,880 Speaker 1: ARPM Lab and University dad Polytechnica de Madrid. He's visiting 14 00:00:56,920 --> 00:00:59,920 Speaker 1: Australia now as the grow Wise Fund opens its door 15 00:01:00,160 --> 00:01:03,320 Speaker 1: was to retail investors for the first time. Ivan, Welcome 16 00:01:03,360 --> 00:01:04,240 Speaker 1: to Fear and Great. 17 00:01:04,160 --> 00:01:05,800 Speaker 2: Thank you so much, Thank you for having me. 18 00:01:06,600 --> 00:01:10,880 Speaker 1: You've made global news in twenty twenty three by winning 19 00:01:10,920 --> 00:01:14,080 Speaker 1: the World Cup of Trading with a nearly five hundred 20 00:01:14,120 --> 00:01:17,800 Speaker 1: percent return in one year. How did you do it. 21 00:01:20,360 --> 00:01:24,880 Speaker 2: By trading the same trading systems I trade for my company, 22 00:01:25,120 --> 00:01:31,360 Speaker 2: but perhaps with a different tactical approach. What I wanted 23 00:01:31,400 --> 00:01:36,880 Speaker 2: to do is to combine different trading assets, different assets, 24 00:01:36,920 --> 00:01:42,960 Speaker 2: asset classes, with different trading strategies and different time frames 25 00:01:43,560 --> 00:01:48,760 Speaker 2: in order to create an equity curve as steady as 26 00:01:48,760 --> 00:01:53,600 Speaker 2: I can get. And that's what I did. The contribution 27 00:01:53,840 --> 00:01:56,880 Speaker 2: of each of the systems into the performance of a 28 00:01:57,000 --> 00:02:00,560 Speaker 2: portfolio took me to win the championship. 29 00:02:00,240 --> 00:02:03,000 Speaker 1: As you're talking about it, and almost see that competitive 30 00:02:03,040 --> 00:02:04,000 Speaker 1: spirit come alive. 31 00:02:05,040 --> 00:02:05,960 Speaker 2: Was it like a game? 32 00:02:06,240 --> 00:02:07,800 Speaker 1: Was it like a full contact sport? 33 00:02:08,919 --> 00:02:11,320 Speaker 2: Yes? And no. I mean I tried to stick to 34 00:02:11,360 --> 00:02:14,840 Speaker 2: my plan, tried to not be influenced by what was 35 00:02:14,880 --> 00:02:17,359 Speaker 2: happening around me, because there were a lot of competitors 36 00:02:17,400 --> 00:02:20,200 Speaker 2: who went up very fast and went down very fast 37 00:02:20,200 --> 00:02:20,720 Speaker 2: as well. 38 00:02:20,800 --> 00:02:22,600 Speaker 1: It does sound, as you talk about it, like an 39 00:02:22,600 --> 00:02:27,400 Speaker 1: incredibly disciplined approach. So I looked at your resume of education, 40 00:02:27,560 --> 00:02:29,440 Speaker 1: and you've got that disciplined approach in the way you 41 00:02:29,520 --> 00:02:34,280 Speaker 1: approach things. You're also someone who embraces meditation, fitness, martial arts, 42 00:02:34,440 --> 00:02:38,600 Speaker 1: and horse riding. How do all these different disciplines shape 43 00:02:38,600 --> 00:02:39,760 Speaker 1: your investment philosophy. 44 00:02:41,560 --> 00:02:46,480 Speaker 2: Martial arts. It gave me the insurance I would say 45 00:02:46,520 --> 00:02:50,920 Speaker 2: that nothing is impossible. You always have to find a 46 00:02:50,960 --> 00:02:53,840 Speaker 2: way to get to that point where you're going to 47 00:02:53,840 --> 00:02:57,800 Speaker 2: achieve what you want. There's always a way to achieve 48 00:02:57,840 --> 00:03:01,640 Speaker 2: what you want, but you need to keep working on 49 00:03:01,680 --> 00:03:04,040 Speaker 2: that in one way or another. But you can't. You 50 00:03:04,560 --> 00:03:06,400 Speaker 2: can't give up. There's a way and you have to 51 00:03:06,440 --> 00:03:08,560 Speaker 2: find it. You have to fight until you find it. 52 00:03:09,280 --> 00:03:13,120 Speaker 2: That's something I learned from from martial arts. Meditation helps 53 00:03:13,160 --> 00:03:18,040 Speaker 2: me to center my mind before I work, after I work, 54 00:03:18,160 --> 00:03:22,000 Speaker 2: and in my life too. I need it like I 55 00:03:22,080 --> 00:03:26,399 Speaker 2: need the air, especially in this kind of business, which 56 00:03:26,440 --> 00:03:30,720 Speaker 2: is very stress in business, and and I practice meditation 57 00:03:31,000 --> 00:03:36,520 Speaker 2: in order to stay focused, to connect with myself, to 58 00:03:36,880 --> 00:03:39,320 Speaker 2: in a way to connect with God because I'm a believer, 59 00:03:40,200 --> 00:03:44,080 Speaker 2: and it prepares me to start a day and to 60 00:03:44,080 --> 00:03:45,000 Speaker 2: finish the day as well. 61 00:03:45,120 --> 00:03:48,840 Speaker 1: Yeah, wonderful markets in some ways are the sum of 62 00:03:48,880 --> 00:03:52,400 Speaker 1: many people's risk capitalized and their investment decisions, so they 63 00:03:52,480 --> 00:03:56,800 Speaker 1: therefore reflect to set a whole of human behaviors. How 64 00:03:56,800 --> 00:03:59,880 Speaker 1: do you design your systems so you can spot meaning 65 00:04:00,200 --> 00:04:02,520 Speaker 1: patterns they are getting lost in all of that noise. 66 00:04:05,600 --> 00:04:10,480 Speaker 2: It's kind of a fear a great thing. The name 67 00:04:10,560 --> 00:04:15,600 Speaker 2: is perfect for this. Markets are driven by humans. We 68 00:04:16,040 --> 00:04:20,840 Speaker 2: all have the same behaviors, no matter whether we are 69 00:04:21,200 --> 00:04:24,480 Speaker 2: in the twenty oneth century, in the twenty first century, 70 00:04:24,480 --> 00:04:28,000 Speaker 2: in the nineteenth century, it doesn't matter. We all have 71 00:04:28,120 --> 00:04:34,800 Speaker 2: the same reactions, emotional reactions, and those common behaviors are 72 00:04:34,839 --> 00:04:39,080 Speaker 2: the ones that we try to detect with the metologies 73 00:04:39,120 --> 00:04:43,720 Speaker 2: we used to look for patterns. In a way, we 74 00:04:43,839 --> 00:04:49,880 Speaker 2: are using mathematics in order to get those patterns and 75 00:04:50,680 --> 00:04:53,560 Speaker 2: try to see where they take us, what kind of 76 00:04:53,640 --> 00:04:56,919 Speaker 2: outcome we can get from those patterns. And if we 77 00:04:57,000 --> 00:05:02,320 Speaker 2: can establish what outcome we can get in certain racial probabilities, 78 00:05:02,839 --> 00:05:04,440 Speaker 2: we know that we have a button that can be 79 00:05:04,520 --> 00:05:08,800 Speaker 2: exploited in the market. So sentiments from the people fed 80 00:05:08,880 --> 00:05:09,400 Speaker 2: on grid. 81 00:05:09,839 --> 00:05:12,640 Speaker 1: Yeah, and turning really human behaviors into numbers and patterns 82 00:05:12,640 --> 00:05:16,120 Speaker 1: that you can recognize exactly. So early in your investment career, 83 00:05:16,160 --> 00:05:19,000 Speaker 1: before going global as you have, you managed money for 84 00:05:19,000 --> 00:05:22,839 Speaker 1: a family office in Argentina, growing your Latin American footprint. 85 00:05:23,400 --> 00:05:25,480 Speaker 1: What did that experience you know, if you think back 86 00:05:25,520 --> 00:05:28,040 Speaker 1: to that in those formative years and times, what did 87 00:05:28,040 --> 00:05:31,080 Speaker 1: that experience teach you about managing other people's capital? 88 00:05:32,400 --> 00:05:37,240 Speaker 2: First of all, that you have to be extra responsible. 89 00:05:37,320 --> 00:05:41,520 Speaker 2: You're gonna be dealing not only with their money, but 90 00:05:41,680 --> 00:05:47,320 Speaker 2: with their psychology. Okay, there will be times when they're 91 00:05:47,320 --> 00:05:52,320 Speaker 2: gonna feel afraid because what's happening in the markets, because 92 00:05:52,360 --> 00:05:55,200 Speaker 2: what's happening with the portfolio, and you will have to 93 00:05:55,960 --> 00:05:59,360 Speaker 2: deal with that too and prepare protocols to deal with 94 00:05:59,400 --> 00:06:04,200 Speaker 2: that tool I mean risk management protocols to give them 95 00:06:04,200 --> 00:06:07,640 Speaker 2: an objective way to measure what you're doing so they 96 00:06:07,680 --> 00:06:10,719 Speaker 2: can see how you can You're going to deal with 97 00:06:11,320 --> 00:06:14,560 Speaker 2: the market with the noise in the in the portfolio. 98 00:06:15,720 --> 00:06:18,360 Speaker 2: So the first thing I learned is that you're not 99 00:06:18,400 --> 00:06:21,000 Speaker 2: only dealing with the money, you're dealing with the psychology 100 00:06:21,040 --> 00:06:24,360 Speaker 2: of the people. That takes you to the point where 101 00:06:25,040 --> 00:06:28,880 Speaker 2: when they say that they can stand at a certain 102 00:06:28,960 --> 00:06:30,600 Speaker 2: kind of bridgs, you have to consider that they can 103 00:06:30,640 --> 00:06:33,600 Speaker 2: stand a half of that risk. So I think those 104 00:06:33,640 --> 00:06:37,320 Speaker 2: are the most important things I have learned from my 105 00:06:38,000 --> 00:06:40,480 Speaker 2: job as a family office manager. 106 00:06:41,480 --> 00:06:45,680 Speaker 1: Let's move to what is called quantitative investing. As you've described, 107 00:06:45,800 --> 00:06:48,640 Speaker 1: how does the ausb's capital side tect grow wise fund 108 00:06:49,160 --> 00:06:52,560 Speaker 1: differ from what investors typically expect from other fund managers. 109 00:06:53,880 --> 00:06:57,599 Speaker 2: OSWEE is going to replicate what we have been doing 110 00:06:58,080 --> 00:07:02,560 Speaker 2: for the last eighteen years. So the Auspice grow as 111 00:07:02,600 --> 00:07:08,240 Speaker 2: Capital fund is going to be a multi asset, multi strategy, 112 00:07:08,800 --> 00:07:13,640 Speaker 2: multidirection and multi time frame fun That means that we're 113 00:07:13,680 --> 00:07:17,960 Speaker 2: going to use all kinds of asset classes in order 114 00:07:18,080 --> 00:07:24,520 Speaker 2: to try to look for patterns and as we trade, 115 00:07:24,560 --> 00:07:28,640 Speaker 2: patterns and patterns are a short definition of the data 116 00:07:28,680 --> 00:07:31,480 Speaker 2: series in time. So that means that we get in 117 00:07:31,800 --> 00:07:34,560 Speaker 2: from the into the data and were out and get 118 00:07:34,560 --> 00:07:37,760 Speaker 2: out out of the data when when the conditions are met. 119 00:07:38,480 --> 00:07:40,400 Speaker 2: That means that we're not in the markets all the time. 120 00:07:41,080 --> 00:07:43,200 Speaker 2: So if we are not in the market all the time, 121 00:07:43,560 --> 00:07:49,440 Speaker 2: we need multiple opportunities in order to avoid the under 122 00:07:49,640 --> 00:07:54,360 Speaker 2: use of our capital. Okay, so to do that, we 123 00:07:54,400 --> 00:07:58,200 Speaker 2: need to get as many as many opportunities as we can. 124 00:07:58,400 --> 00:08:02,600 Speaker 2: And that's something that it can be found if you 125 00:08:02,720 --> 00:08:07,760 Speaker 2: train multiple assets and multiple directions. That means long, short, 126 00:08:08,200 --> 00:08:12,920 Speaker 2: neutral strategies and multiple time frames, because you're going to have, 127 00:08:13,320 --> 00:08:17,559 Speaker 2: for example, different different behaviors, whether it's on a daily 128 00:08:17,600 --> 00:08:20,360 Speaker 2: time frame, when it's sixty minutes time frame where is 129 00:08:20,760 --> 00:08:23,440 Speaker 2: so you will see that in a certain time frame, 130 00:08:23,880 --> 00:08:27,480 Speaker 2: the prices of certain asset is going to have a 131 00:08:27,560 --> 00:08:30,520 Speaker 2: mean reverting profile, but in a lower time frame it 132 00:08:30,600 --> 00:08:34,800 Speaker 2: might have a trend follow wing profile. And that gives 133 00:08:34,800 --> 00:08:38,360 Speaker 2: you different opportunities, even in the same assets, to go 134 00:08:38,440 --> 00:08:41,880 Speaker 2: along to short and to take advantage of those assets 135 00:08:42,120 --> 00:08:47,040 Speaker 2: as independent p and ls, as independent performance providers. 136 00:08:47,679 --> 00:08:51,200 Speaker 1: It's a fascinating matrix because in my head, I'm trying 137 00:08:51,240 --> 00:08:53,760 Speaker 1: to work a hell I possibly do that, as you know, 138 00:08:53,920 --> 00:08:55,120 Speaker 1: just align in my own mind. 139 00:08:55,240 --> 00:08:56,520 Speaker 2: Now it can be done. 140 00:08:56,559 --> 00:08:59,200 Speaker 1: You know, it's in practical So one thing that stands 141 00:08:59,200 --> 00:09:02,520 Speaker 1: out about to your business is the frame model. There's 142 00:09:02,520 --> 00:09:06,760 Speaker 1: no management phase, only a performance fee above high watermark. 143 00:09:07,559 --> 00:09:09,600 Speaker 1: Why did you go with that structure and how does 144 00:09:09,640 --> 00:09:11,640 Speaker 1: that align with your investors? 145 00:09:12,320 --> 00:09:14,880 Speaker 2: I think I say that we don't charge the client. 146 00:09:14,920 --> 00:09:19,360 Speaker 2: We charge the market because we don't touch the client's capital. 147 00:09:20,280 --> 00:09:25,600 Speaker 2: But it reflects the philosophy of my of my fund 148 00:09:25,640 --> 00:09:28,520 Speaker 2: and of my life. I think that if I'm going 149 00:09:28,559 --> 00:09:33,280 Speaker 2: to offer you something and I don't provide you with 150 00:09:33,440 --> 00:09:37,079 Speaker 2: what I had offered, I couldn't charge you. It's it's 151 00:09:38,320 --> 00:09:41,400 Speaker 2: it's not moral in my opinion. So I have to 152 00:09:41,480 --> 00:09:43,480 Speaker 2: give you a performance and I will charge you. But 153 00:09:43,520 --> 00:09:46,840 Speaker 2: if I don't give you a performance, why would I 154 00:09:46,920 --> 00:09:51,559 Speaker 2: charge you? That's that's what I think. I don't criticize 155 00:09:51,720 --> 00:09:55,800 Speaker 2: the ones who does it differently, but I prefer to 156 00:09:55,840 --> 00:10:01,240 Speaker 2: do it that way. And secondly, that demonstrate that I 157 00:10:01,440 --> 00:10:05,640 Speaker 2: truly believe in what we do, because if I wouldn't, 158 00:10:07,160 --> 00:10:10,800 Speaker 2: it would it would have to be in another business. 159 00:10:11,559 --> 00:10:15,240 Speaker 1: So let's talk about risk in everyone's mind, especially with 160 00:10:15,280 --> 00:10:19,640 Speaker 1: someone trailing across equities, commodities, currencies, digital assets. What you've 161 00:10:19,679 --> 00:10:23,040 Speaker 1: talked about there. We haven't specifically mentioned diversification, but it's 162 00:10:23,080 --> 00:10:26,040 Speaker 1: implicit in what you've already said in about multiple models 163 00:10:26,080 --> 00:10:27,000 Speaker 1: at the same time. 164 00:10:29,160 --> 00:10:30,199 Speaker 2: How do you do that? 165 00:10:30,440 --> 00:10:33,559 Speaker 1: How do you make that approach work to protect investments 166 00:10:33,640 --> 00:10:35,120 Speaker 1: during market downturns. 167 00:10:36,360 --> 00:10:43,800 Speaker 2: The versification for me is the ancorrelation of different strategies, 168 00:10:43,840 --> 00:10:47,760 Speaker 2: are play tool, different assets classes, or different time friends, 169 00:10:47,880 --> 00:10:52,720 Speaker 2: or different directions. That means I don't I don't see assets, 170 00:10:53,200 --> 00:10:57,240 Speaker 2: I don't I don't see Google. That's good. It's not 171 00:10:57,280 --> 00:11:00,160 Speaker 2: a management no, no, it's there all data series. So 172 00:11:01,679 --> 00:11:04,760 Speaker 2: what I get from those data series are the patterns 173 00:11:04,920 --> 00:11:08,720 Speaker 2: and the p and l the performance of those patterns 174 00:11:09,840 --> 00:11:14,319 Speaker 2: mustn't be correlated. When they are not correlated, they are 175 00:11:14,440 --> 00:11:18,880 Speaker 2: diversifying because they're gonna be compensating the other system draw 176 00:11:18,960 --> 00:11:23,040 Speaker 2: down if they if it occurs, and they're gonna be 177 00:11:23,520 --> 00:11:26,080 Speaker 2: smoothing the equity curve in the in the long run, 178 00:11:26,800 --> 00:11:31,040 Speaker 2: and bye by trading different time frames. Perhaps you might 179 00:11:31,080 --> 00:11:34,080 Speaker 2: have a crisis in a daily time frame, but the 180 00:11:34,120 --> 00:11:37,520 Speaker 2: cricy doesn't exist in in the in a smaller timeframe, 181 00:11:38,080 --> 00:11:41,679 Speaker 2: for example. Or perhaps you have a very fast movement 182 00:11:42,040 --> 00:11:45,680 Speaker 2: in a in a lower time frame, but that correction 183 00:11:45,800 --> 00:11:49,360 Speaker 2: doesn't exist in a higher time frame. So by by 184 00:11:49,760 --> 00:11:55,840 Speaker 2: by trading different time frames in different directions and taking 185 00:11:55,920 --> 00:12:01,520 Speaker 2: care being sure mathematically, of course, the those strategies are 186 00:12:01,559 --> 00:12:06,240 Speaker 2: not correlated at all. You're adding diversification to a portfolio, 187 00:12:06,240 --> 00:12:10,319 Speaker 2: and you're protecting your portfolio against these kind of events. 188 00:12:10,880 --> 00:12:14,000 Speaker 1: Let's talk about digital assets. There's not really the decades 189 00:12:14,040 --> 00:12:18,040 Speaker 1: of history available perhaps in other asset classes. How did 190 00:12:18,080 --> 00:12:20,280 Speaker 1: you adapt your strategy or did you even have to 191 00:12:20,760 --> 00:12:23,320 Speaker 1: model and try it effectively in markets that have a 192 00:12:23,360 --> 00:12:24,319 Speaker 1: short track record. 193 00:12:25,240 --> 00:12:30,000 Speaker 2: First of all, to trade an asset asset or another asset, 194 00:12:30,400 --> 00:12:34,800 Speaker 2: we need the most important raw material. We have to 195 00:12:34,880 --> 00:12:39,840 Speaker 2: use the data. It should be quality data, and a 196 00:12:39,920 --> 00:12:44,520 Speaker 2: problem with crypto is that we don't have quality data 197 00:12:44,600 --> 00:12:49,439 Speaker 2: and the quality data is very new. So we can 198 00:12:49,600 --> 00:12:52,880 Speaker 2: take the history that we have in crypto right now. 199 00:12:52,920 --> 00:12:59,959 Speaker 2: In order to make statistical significant conclusions, we would need 200 00:13:00,120 --> 00:13:05,040 Speaker 2: more history. But that doesn't mean that crypto doesn't reflect 201 00:13:05,480 --> 00:13:09,959 Speaker 2: behaviors human behaviors as the rest of the assets do. 202 00:13:11,280 --> 00:13:15,360 Speaker 2: We have different systems. Systems that are good for just 203 00:13:15,400 --> 00:13:18,600 Speaker 2: one asset, systems are are good for a basket of assets, 204 00:13:18,640 --> 00:13:22,360 Speaker 2: and we have systems are are good for almost all 205 00:13:22,440 --> 00:13:27,680 Speaker 2: kinds of assets. As we trade cryptos, regulated cryptos through 206 00:13:27,960 --> 00:13:32,520 Speaker 2: regulated edfs, we apply a different system that we use 207 00:13:32,559 --> 00:13:35,800 Speaker 2: for interest rates, and we and some others that we 208 00:13:35,920 --> 00:13:40,280 Speaker 2: use for training universities of stocks. They have been tested 209 00:13:40,360 --> 00:13:44,880 Speaker 2: through thousands and thousands of patterns in different stocks and 210 00:13:44,960 --> 00:13:50,120 Speaker 2: they have survived, so when applying them to crypto, they 211 00:13:50,160 --> 00:13:51,319 Speaker 2: work very well as well. 212 00:13:52,160 --> 00:13:54,840 Speaker 1: Now let's just wrap this up with every die investors 213 00:13:54,920 --> 00:13:57,640 Speaker 1: you might be listening in because this is fascinating material. 214 00:13:57,800 --> 00:13:58,120 Speaker 2: Thank you. 215 00:13:58,600 --> 00:14:03,600 Speaker 1: What is the biggest conception that you say about systematic investing. 216 00:14:05,240 --> 00:14:08,320 Speaker 2: Most of the people think that by knowing how to 217 00:14:08,400 --> 00:14:13,320 Speaker 2: design a system. You just design a boat, an algorithm, 218 00:14:14,160 --> 00:14:16,800 Speaker 2: your robot, and you're gonna get into jump into the 219 00:14:16,840 --> 00:14:19,880 Speaker 2: market and start trading. And it doesn't work that way. 220 00:14:20,520 --> 00:14:24,920 Speaker 2: You're gonna end up adjusting your training conclusion to the 221 00:14:25,000 --> 00:14:28,400 Speaker 2: data in a point where you are going to overfeit 222 00:14:28,600 --> 00:14:32,600 Speaker 2: your model and you won't be able to transporlate your 223 00:14:32,640 --> 00:14:35,400 Speaker 2: model into the future. It's not going to produce good 224 00:14:35,440 --> 00:14:40,280 Speaker 2: performance into the future because human behaviors don't reput use 225 00:14:40,360 --> 00:14:45,080 Speaker 2: into the future in a very precise way. For example, 226 00:14:45,560 --> 00:14:48,920 Speaker 2: if we stand in front of the lion, your reaction 227 00:14:49,520 --> 00:14:52,840 Speaker 2: would be pretty similar to my reaction, but you would 228 00:14:53,360 --> 00:14:57,040 Speaker 2: end up running away after ten seconds. I would be 229 00:14:57,400 --> 00:15:02,320 Speaker 2: running away after fifteen seconds. So that gives us a 230 00:15:02,400 --> 00:15:08,440 Speaker 2: room for certain baby and there are different statistical techniques 231 00:15:08,480 --> 00:15:11,120 Speaker 2: to lead with that to look for robblesness in the 232 00:15:11,200 --> 00:15:14,960 Speaker 2: development of the of the models. And that's something that 233 00:15:15,480 --> 00:15:21,720 Speaker 2: is not understood in the new systematic traders. They need 234 00:15:21,760 --> 00:15:27,560 Speaker 2: to use different different tools in order tool deal with 235 00:15:27,840 --> 00:15:32,720 Speaker 2: over feeding Oberfiit is our first enemy as systematic traders. 236 00:15:32,920 --> 00:15:36,440 Speaker 1: Okay, yes, that is fascinating. Ivan, Thank you so much 237 00:15:36,480 --> 00:15:38,360 Speaker 1: for joining us today on fear and greed Q and A. 238 00:15:38,480 --> 00:15:40,040 Speaker 2: It's a pleasure, Thank you for having me. 239 00:15:40,520 --> 00:15:43,240 Speaker 1: That was Ivan Sherman, chief investment officer at Sciente Tech 240 00:15:43,280 --> 00:15:46,920 Speaker 1: Investments and portfolio manager of the Osby's capital side Tech 241 00:15:47,000 --> 00:15:50,320 Speaker 1: grow Wise Fund, a proud support of this podcast. If 242 00:15:50,320 --> 00:15:51,840 Speaker 1: you've got something you'd like to know, send you a 243 00:15:51,960 --> 00:15:55,560 Speaker 1: question via LinkedIn, Instagram, Facebook, or head over to fearangreed 244 00:15:55,600 --> 00:15:58,160 Speaker 1: dot com dot au. I'm Adam Lang and this has 245 00:15:58,160 --> 00:15:59,280 Speaker 1: been Fearing great Q and A.