1 00:00:04,600 --> 00:00:07,680 Speaker 1: So the big question is this, how do investors like 2 00:00:07,880 --> 00:00:11,800 Speaker 1: us get access to the ideas, information, and most importantly, 3 00:00:12,039 --> 00:00:14,880 Speaker 1: the right people that give us the tools and information 4 00:00:14,960 --> 00:00:19,000 Speaker 1: we need to make conformed and educated decisions to have success. 5 00:00:19,600 --> 00:00:22,319 Speaker 1: That is the question, and this podcast will give us 6 00:00:22,400 --> 00:00:25,520 Speaker 1: the answers. This is Mark Moss, your host. Let's get 7 00:00:25,520 --> 00:00:28,400 Speaker 1: this started. Everyone, Welcome to another episode of the Market 8 00:00:28,440 --> 00:00:32,599 Speaker 1: Disruptors podcast. Today I am joined by Philip Swift and 9 00:00:32,640 --> 00:00:36,560 Speaker 1: we are going to be talking about bitcoin on chain analytics, 10 00:00:36,720 --> 00:00:38,720 Speaker 1: what they're looking like, how we can look at them, 11 00:00:38,720 --> 00:00:42,320 Speaker 1: and what they tell us. Uh, super super interesting conversations 12 00:00:42,320 --> 00:00:43,879 Speaker 1: that I've already had. I can't wait to jump in. 13 00:00:43,960 --> 00:00:48,599 Speaker 1: So Philip, welcome to the show. Hey man, thanks very 14 00:00:48,680 --> 00:00:49,960 Speaker 1: much for having me on the show. It's great to 15 00:00:50,000 --> 00:00:52,600 Speaker 1: be here. And yeah, things are looking good at the 16 00:00:52,640 --> 00:00:55,920 Speaker 1: market right now and it's great chatsy great right. So, 17 00:00:56,160 --> 00:00:57,760 Speaker 1: you know, I know we've had some conversations. I've been 18 00:00:57,760 --> 00:00:59,840 Speaker 1: watching some of the work that you've been doing UM 19 00:01:00,040 --> 00:01:02,400 Speaker 1: online and on your website. But for those that don't know, 20 00:01:02,440 --> 00:01:03,880 Speaker 1: why don't you just kind of fill us in on 21 00:01:04,360 --> 00:01:06,800 Speaker 1: UM you know who, what you've been doing, how you 22 00:01:06,840 --> 00:01:10,240 Speaker 1: got here, and what you're doing right now. Cool, thank you. 23 00:01:10,720 --> 00:01:14,560 Speaker 1: So I am a full time bitcoin trader and investor. 24 00:01:14,680 --> 00:01:16,640 Speaker 1: I have been for about two and a half years now, 25 00:01:17,880 --> 00:01:20,560 Speaker 1: very passionate about bitcoin for a number of reasons, so 26 00:01:21,360 --> 00:01:26,080 Speaker 1: not only from an investment opportunity, but also I believe 27 00:01:26,120 --> 00:01:28,400 Speaker 1: it's probably one of the most important tools for human 28 00:01:28,480 --> 00:01:30,360 Speaker 1: rights in the world right now in the coming years, 29 00:01:30,760 --> 00:01:33,120 Speaker 1: as we see governments have more and more issues with 30 00:01:33,160 --> 00:01:37,880 Speaker 1: their monetary and physical policies. Um. So yeah, full time trader, investor. 31 00:01:37,959 --> 00:01:42,200 Speaker 1: But in addition to that, I also build valuation models 32 00:01:42,319 --> 00:01:47,400 Speaker 1: for bitcoin, so indicators and tools that helped to identify 33 00:01:47,640 --> 00:01:52,320 Speaker 1: when bitcoin is under or values. That's a pretty new 34 00:01:53,040 --> 00:01:57,840 Speaker 1: and emerging space within bitcoin. It's probably been in existence 35 00:01:57,840 --> 00:02:00,400 Speaker 1: for a couple of years now because obviously bitcoin itself 36 00:02:00,480 --> 00:02:02,840 Speaker 1: is only ten coming up to eleven years old, so 37 00:02:04,280 --> 00:02:07,520 Speaker 1: we haven't really had enough data until recently to be 38 00:02:07,600 --> 00:02:12,160 Speaker 1: able to start to build valuation models for bitcoin. And 39 00:02:12,440 --> 00:02:16,320 Speaker 1: because it's a unique asset class, so it has characteristics 40 00:02:16,320 --> 00:02:21,680 Speaker 1: that are quite different to traditional finance instruments. Um, you 41 00:02:21,800 --> 00:02:26,480 Speaker 1: can't use tools from the transitional finance world and just 42 00:02:26,600 --> 00:02:29,160 Speaker 1: try and directly apply them to bitcoins, try and value 43 00:02:29,160 --> 00:02:32,000 Speaker 1: it so you can't. So in traditional finance, for stocks 44 00:02:32,040 --> 00:02:35,600 Speaker 1: and shares, you have things like price to earnings ratios 45 00:02:35,680 --> 00:02:39,600 Speaker 1: and discarded cash flows. You can't really apply those to bitcoin. 46 00:02:40,200 --> 00:02:41,840 Speaker 1: But what we can do is try and come up 47 00:02:41,840 --> 00:02:45,639 Speaker 1: with some new tools and metrics to understand when bitcoin 48 00:02:45,800 --> 00:02:49,120 Speaker 1: is under or overvalued. And that's what I do, and 49 00:02:49,520 --> 00:02:53,600 Speaker 1: I launched, as you mentioned, a website last month called 50 00:02:53,600 --> 00:02:56,440 Speaker 1: looking too bitcoin dot com and that has a hard 51 00:02:56,480 --> 00:02:59,600 Speaker 1: bunch of these different valuation models and tools all for 52 00:02:59,720 --> 00:03:03,760 Speaker 1: for uh choy to make them as user friendly and 53 00:03:04,160 --> 00:03:06,040 Speaker 1: nice to look at as possible and kind of live 54 00:03:06,200 --> 00:03:09,120 Speaker 1: chart data form. And yeah, it's all free and one 55 00:03:09,120 --> 00:03:12,320 Speaker 1: can go and check them out. Yeah. Now, as you said, right, 56 00:03:12,360 --> 00:03:16,000 Speaker 1: like typically when we're looking at trying to value financial 57 00:03:16,040 --> 00:03:19,600 Speaker 1: stocks and we look at fundamentals, and the fundamentals are 58 00:03:19,680 --> 00:03:21,880 Speaker 1: kind of like what you said, right, which are earnings 59 00:03:21,960 --> 00:03:25,160 Speaker 1: ratios and things like that. Um, and a lot of 60 00:03:25,160 --> 00:03:29,240 Speaker 1: people have always criticized cryptocurrencies because they don't have those fundamentals. 61 00:03:29,600 --> 00:03:33,320 Speaker 1: You're talking about looking at different metrics that can give 62 00:03:33,400 --> 00:03:36,920 Speaker 1: us the fundamentals because they're different, right, I get that, 63 00:03:36,960 --> 00:03:39,160 Speaker 1: But um, that's an interesting way to look at it 64 00:03:39,200 --> 00:03:41,320 Speaker 1: and I'm just curious. I I kind of know, but 65 00:03:41,320 --> 00:03:42,600 Speaker 1: why don't you fill us in a little bit on 66 00:03:42,640 --> 00:03:46,360 Speaker 1: your background and how maybe what shaped you? How did 67 00:03:46,360 --> 00:03:50,160 Speaker 1: you get to the point to start looking at like this. Yes, 68 00:03:50,240 --> 00:03:52,040 Speaker 1: so my book is probably a little bit different to 69 00:03:52,120 --> 00:03:54,600 Speaker 1: a lot of other traders and investors in the space. 70 00:03:55,080 --> 00:04:01,360 Speaker 1: Um So, I studied economics university, uh which was great 71 00:04:01,400 --> 00:04:03,560 Speaker 1: in terms of giving me a good grounding in terms 72 00:04:03,560 --> 00:04:09,360 Speaker 1: of how markets work. Um some macro principles around economics 73 00:04:09,440 --> 00:04:13,120 Speaker 1: and maths. But like I think many of the people 74 00:04:13,120 --> 00:04:15,600 Speaker 1: who studied economics, you kind of get to the end 75 00:04:15,600 --> 00:04:17,719 Speaker 1: of it and think, man, this is so theoretical you 76 00:04:17,760 --> 00:04:19,720 Speaker 1: kind of want to throw all your textbooks out of the 77 00:04:19,680 --> 00:04:24,320 Speaker 1: the window because it's quite hard to apply a lot 78 00:04:24,400 --> 00:04:26,800 Speaker 1: of it to the real world. So I kind of 79 00:04:26,880 --> 00:04:30,640 Speaker 1: left university feeling a little bit jaded, but I was 80 00:04:30,680 --> 00:04:34,280 Speaker 1: still very interested in the behavior economic side of things, 81 00:04:34,279 --> 00:04:40,640 Speaker 1: so understanding what makes markets work. And so I then 82 00:04:40,680 --> 00:04:45,400 Speaker 1: got a career actually working for major global dricks brands, 83 00:04:46,200 --> 00:04:51,919 Speaker 1: uh so, companies that own brands like Jack Daniels, Gray, 84 00:04:51,960 --> 00:04:56,200 Speaker 1: Goose Bug, Hendrix, gen Ster, Artoire. So if you like 85 00:04:56,279 --> 00:04:59,520 Speaker 1: a drink, you've probably had one of those brands, Um, 86 00:04:59,560 --> 00:05:03,120 Speaker 1: and I. She works in a unit within these companies 87 00:05:04,400 --> 00:05:09,200 Speaker 1: which was really a strategic marketing function of thoughts. And 88 00:05:09,600 --> 00:05:12,520 Speaker 1: unless you work for one of these big companies, you 89 00:05:12,520 --> 00:05:15,880 Speaker 1: probably don't realize that these functions even exist. It's called 90 00:05:15,960 --> 00:05:20,200 Speaker 1: Consumer Insight team and the role of these guys is 91 00:05:20,240 --> 00:05:27,480 Speaker 1: to understand the psychology of your potential consumers and your consumers, right, 92 00:05:27,880 --> 00:05:31,720 Speaker 1: so you're you're trying to segment them, understand their reasons 93 00:05:31,920 --> 00:05:34,480 Speaker 1: for choosing your brand or for not choosing your brand. 94 00:05:35,000 --> 00:05:37,920 Speaker 1: And that goes beyond just why they think about the sector. 95 00:05:37,960 --> 00:05:40,440 Speaker 1: It's around their hopes and dreams and their fears and 96 00:05:40,480 --> 00:05:44,120 Speaker 1: all that sort of stuff. So it deep goes quite 97 00:05:44,120 --> 00:05:49,320 Speaker 1: deep in terms of market psychology. And really that's how 98 00:05:49,360 --> 00:05:51,080 Speaker 1: these brands get so big is because they have a 99 00:05:51,240 --> 00:05:56,520 Speaker 1: very sophisticated understanding of market psychology. Now, if I can 100 00:05:56,560 --> 00:05:59,080 Speaker 1: just jump in at the rate there real quick. So, Um, 101 00:05:59,240 --> 00:06:03,320 Speaker 1: you studied market psychology working for the big brands, and 102 00:06:03,360 --> 00:06:07,200 Speaker 1: the economics was also um, trying to understand what markets 103 00:06:07,240 --> 00:06:11,760 Speaker 1: are market psychology, you said, what makes markets work? Right? Yeah, 104 00:06:11,920 --> 00:06:14,680 Speaker 1: I'm curious. Um, you said that a lot of is theoretical, 105 00:06:14,720 --> 00:06:17,120 Speaker 1: which I think that theoretical part probably helps you today 106 00:06:17,120 --> 00:06:20,919 Speaker 1: because trying to new ways to capture analytics, you have 107 00:06:21,000 --> 00:06:25,159 Speaker 1: to be theoretical. I'm curious though, Uh, you know, from 108 00:06:25,200 --> 00:06:27,479 Speaker 1: everyone that I've talked to, I didn't major in economics, 109 00:06:27,480 --> 00:06:29,039 Speaker 1: but I I know a lot of people who did, 110 00:06:29,520 --> 00:06:33,960 Speaker 1: and uh, you know they do not teach Austrian economics, 111 00:06:34,000 --> 00:06:37,679 Speaker 1: which everybody basically ends up at after they've been studying bitcoin. 112 00:06:37,720 --> 00:06:41,480 Speaker 1: It seems like yea, and sometimes the university training you 113 00:06:41,600 --> 00:06:45,679 Speaker 1: had can can keep you from really understanding bitcoin because 114 00:06:45,720 --> 00:06:48,240 Speaker 1: you've been trained maybe with blinders on right, And you said, 115 00:06:48,560 --> 00:06:52,640 Speaker 1: what makes markets work? And it seems like what whatever 116 00:06:52,640 --> 00:06:55,760 Speaker 1: you wanna call it, traditional or conventional economics versus like 117 00:06:55,760 --> 00:07:00,840 Speaker 1: an Austrian is that traditional find economics thinks the market 118 00:07:01,120 --> 00:07:06,200 Speaker 1: is something too understand how it works and manage and 119 00:07:06,200 --> 00:07:10,160 Speaker 1: and and manipulate, versus Austroan economics understands that there is 120 00:07:10,160 --> 00:07:11,880 Speaker 1: no such thing as a market. All we have as 121 00:07:12,000 --> 00:07:16,720 Speaker 1: individuals wants, needs and desires. Yeah, what do you think 122 00:07:16,760 --> 00:07:19,120 Speaker 1: about that? And and how does that relate to studying 123 00:07:19,120 --> 00:07:22,240 Speaker 1: the market, especially for a brand? Yeah, I mean I 124 00:07:22,280 --> 00:07:24,200 Speaker 1: think I think that's a that's a fair summary, and 125 00:07:24,240 --> 00:07:28,760 Speaker 1: I think a lot of frustrations come from, uh, the 126 00:07:28,880 --> 00:07:30,560 Speaker 1: need if you if you were trying to focus in 127 00:07:30,600 --> 00:07:34,400 Speaker 1: on a specific area, you have to make compromises and sacrifices. 128 00:07:34,840 --> 00:07:39,000 Speaker 1: And often in economics the compromises and sacrifices around are 129 00:07:39,080 --> 00:07:45,160 Speaker 1: around uh, recognizing that or that we're not recognizing that 130 00:07:45,360 --> 00:07:49,800 Speaker 1: we are all emotional beasts right where you have emotions, 131 00:07:50,120 --> 00:07:54,119 Speaker 1: we're not rational players. And as soon as you start 132 00:07:54,160 --> 00:07:57,000 Speaker 1: to assume that we're rational players, then then you start 133 00:07:57,080 --> 00:07:59,480 Speaker 1: to lose understanding of how how the markets move and 134 00:07:59,520 --> 00:08:02,040 Speaker 1: how the more his work. So that's why I think 135 00:08:02,080 --> 00:08:06,320 Speaker 1: behavior economics is so much more relevant, particularly to the 136 00:08:06,360 --> 00:08:11,600 Speaker 1: world room today, and particularly to assets like bitcoin, which 137 00:08:11,640 --> 00:08:16,080 Speaker 1: are very retail market driven. So you have therefore, you know, 138 00:08:17,520 --> 00:08:21,320 Speaker 1: to your point, millions of individuals, all with their own emotions, 139 00:08:21,520 --> 00:08:26,560 Speaker 1: and when they are trying to determine what they should 140 00:08:26,600 --> 00:08:30,440 Speaker 1: do with their investments, they are often can be lit 141 00:08:30,480 --> 00:08:34,640 Speaker 1: by consensus. It's kind of like it's kind of like, um, 142 00:08:34,880 --> 00:08:38,800 Speaker 1: you say they're not rational, which I kind of agree. 143 00:08:39,520 --> 00:08:43,640 Speaker 1: Misses from Austrian school. He says that, um, it's always rational. 144 00:08:43,960 --> 00:08:47,240 Speaker 1: So I might look like I'm acting irrationally, but it's 145 00:08:47,320 --> 00:08:51,520 Speaker 1: rational to me because I have my own set of circumstances. 146 00:08:51,920 --> 00:08:55,000 Speaker 1: So even though bitcoin is gonna go to a million 147 00:08:55,040 --> 00:08:58,440 Speaker 1: dollars next year, I might sell it today for no 148 00:08:58,600 --> 00:09:01,240 Speaker 1: reason that looks irround national, but maybe my kid got 149 00:09:01,280 --> 00:09:04,600 Speaker 1: sick any of the money, right, So there's always national 150 00:09:04,679 --> 00:09:07,400 Speaker 1: to me. But you can't manage that because it's millions 151 00:09:07,400 --> 00:09:11,680 Speaker 1: of inputs exactly. And that's really a point around context, right, 152 00:09:12,080 --> 00:09:15,040 Speaker 1: which which going back to my previous employment, that that's 153 00:09:15,040 --> 00:09:17,400 Speaker 1: something we focused on a lot. You have to understand 154 00:09:17,440 --> 00:09:20,360 Speaker 1: people's context to really understand if you want to fully 155 00:09:20,440 --> 00:09:24,720 Speaker 1: understand their decision making process. But yeah, super interesting stuff. Yeah, anyway, Okay, 156 00:09:24,720 --> 00:09:28,160 Speaker 1: so your understanding market psychology, I think, like we said, 157 00:09:28,200 --> 00:09:30,520 Speaker 1: like the I think I could I could imagine that 158 00:09:30,600 --> 00:09:33,640 Speaker 1: the theory that you've learned in in economic school probably 159 00:09:33,679 --> 00:09:36,880 Speaker 1: helped you to start theorizing what kind of new metrics 160 00:09:36,960 --> 00:09:40,400 Speaker 1: we could look at in bitcoint. Yeah, yeah, absolutely, And 161 00:09:40,480 --> 00:09:42,520 Speaker 1: really is the combination the two, right, So you have 162 00:09:42,960 --> 00:09:47,880 Speaker 1: economic theory plus market psychology, and for a market like bitcoin, 163 00:09:47,960 --> 00:09:52,280 Speaker 1: that that is very useful because what we're seeing is 164 00:09:52,320 --> 00:09:55,400 Speaker 1: bigcoin is going through an adoption process, and on top 165 00:09:55,440 --> 00:09:58,920 Speaker 1: of that adoption process we have market cycles, and so 166 00:09:59,080 --> 00:10:03,640 Speaker 1: combining those two fields has been very useful um to 167 00:10:03,720 --> 00:10:05,520 Speaker 1: me as as a training investor in to try and 168 00:10:05,520 --> 00:10:09,240 Speaker 1: build some of these these valuation tools as well. A 169 00:10:09,320 --> 00:10:14,840 Speaker 1: couple of years. Yeah, so then you started trading bitcoin 170 00:10:14,920 --> 00:10:17,960 Speaker 1: on your own, and then you started realizing that we 171 00:10:18,000 --> 00:10:21,000 Speaker 1: don't really have any good metrics, and so you've decided 172 00:10:21,040 --> 00:10:23,360 Speaker 1: to dig in and started to try to see what 173 00:10:23,440 --> 00:10:26,680 Speaker 1: was available and what else you could come up with. Yeah, yeah, 174 00:10:26,720 --> 00:10:30,200 Speaker 1: that's right. So I've been trading for probably a couple 175 00:10:30,240 --> 00:10:34,280 Speaker 1: of years and that was all going well, but I 176 00:10:34,440 --> 00:10:37,920 Speaker 1: found that I wasn't really that passionate about becoming a 177 00:10:38,080 --> 00:10:42,160 Speaker 1: super techy technical analysis geek, and I was more drawn 178 00:10:42,280 --> 00:10:48,320 Speaker 1: to understanding the macro cycles of a bitcoin. And I 179 00:10:48,320 --> 00:10:51,280 Speaker 1: started playing around with different types of data, one of 180 00:10:51,320 --> 00:10:54,720 Speaker 1: which was someone chained data. So I was on, you know, 181 00:10:54,840 --> 00:10:59,200 Speaker 1: using sites like blockchain dot info which posts some pretty 182 00:10:59,240 --> 00:11:03,640 Speaker 1: basic on chain data, and probably late two thousand and seventeen, 183 00:11:03,679 --> 00:11:07,839 Speaker 1: I think, and I started to notice that on a 184 00:11:07,880 --> 00:11:12,839 Speaker 1: macro level, there was a relationship between volume running through 185 00:11:12,840 --> 00:11:18,800 Speaker 1: the blockchain on a daily basis and then also bitcoin price. So, uh, 186 00:11:20,200 --> 00:11:24,080 Speaker 1: when volume through the blockchain was hitting sufficient levels. It 187 00:11:24,120 --> 00:11:26,800 Speaker 1: was kind of a leading indicator to price moving up. 188 00:11:27,440 --> 00:11:31,760 Speaker 1: And um, I posted a chart on it on Twitter, 189 00:11:32,080 --> 00:11:36,800 Speaker 1: I think on tone vases Twitter channel, and a guy 190 00:11:36,840 --> 00:11:39,360 Speaker 1: called Willie Woo, who I imagine a lot of your 191 00:11:39,400 --> 00:11:43,079 Speaker 1: viewers have probably heard of. Willy Woo is like probably 192 00:11:43,160 --> 00:11:48,079 Speaker 1: the godfather of on chain analysis. He's pretty amazing and 193 00:11:49,000 --> 00:11:51,600 Speaker 1: I've learned a huge tone of stuff from him over 194 00:11:51,679 --> 00:11:55,120 Speaker 1: over the years. And he picked it up and he 195 00:11:55,200 --> 00:11:57,400 Speaker 1: was like, hey, you love this view. I hadn't seen 196 00:11:57,440 --> 00:11:59,240 Speaker 1: it before. I'd like to put it on my site 197 00:11:59,280 --> 00:12:01,400 Speaker 1: and you should write a pay for about it. And 198 00:12:01,400 --> 00:12:05,199 Speaker 1: so I did a called it Bitcoin network Momentum, and yeah, 199 00:12:05,200 --> 00:12:07,080 Speaker 1: it kind of so I probably at the time like 200 00:12:07,120 --> 00:12:08,960 Speaker 1: the first and followers on Twitter or something, and then 201 00:12:08,960 --> 00:12:11,720 Speaker 1: within a week I had like two thousand followers stars like, Okay, 202 00:12:12,240 --> 00:12:15,120 Speaker 1: clearly there's some interest in this, you know, clearly people 203 00:12:15,120 --> 00:12:17,240 Speaker 1: are interested in this sort of analysis. And then it 204 00:12:17,320 --> 00:12:19,840 Speaker 1: really went from there, you know, because I then just 205 00:12:19,840 --> 00:12:22,160 Speaker 1: started speaking to other people who are also looking at 206 00:12:22,200 --> 00:12:25,640 Speaker 1: this sort of analysis and trying to build these types 207 00:12:25,640 --> 00:12:29,720 Speaker 1: of indicators, and and then yeah, and that that whole 208 00:12:29,880 --> 00:12:34,040 Speaker 1: space now of valuing bitcoin is really exploded. And now 209 00:12:34,040 --> 00:12:37,000 Speaker 1: it is like you know, crypto funds with teams of 210 00:12:37,040 --> 00:12:39,320 Speaker 1: guys doing this types of analysis. So it's just going 211 00:12:39,360 --> 00:12:42,160 Speaker 1: to get bigger and bigger. So let's let's talk about that. 212 00:12:42,280 --> 00:12:45,600 Speaker 1: So first of all, um, you talk about on chain 213 00:12:45,760 --> 00:12:49,760 Speaker 1: data and indicators to help us understand bitcoin and maybe 214 00:12:49,800 --> 00:12:51,959 Speaker 1: identify where bitcoin is going. So what are what are 215 00:12:51,960 --> 00:12:54,720 Speaker 1: the indicators? What I mean and not specifically, but what 216 00:12:54,960 --> 00:12:57,000 Speaker 1: is generally? What is an indicator? What does that mean 217 00:12:57,080 --> 00:13:00,640 Speaker 1: to the average person? So an indicator area is really 218 00:13:00,640 --> 00:13:04,400 Speaker 1: so as an investor in its most simple form, as 219 00:13:04,400 --> 00:13:07,280 Speaker 1: an investor, a long term investor. So we're not talking 220 00:13:07,320 --> 00:13:11,120 Speaker 1: about trade short term trading here. I want to know 221 00:13:12,400 --> 00:13:14,080 Speaker 1: when is a good time for me to buy? When 222 00:13:14,160 --> 00:13:16,400 Speaker 1: is a good time for me to sell? And these 223 00:13:16,400 --> 00:13:21,440 Speaker 1: indicators show you on a historical level. So looking back 224 00:13:21,440 --> 00:13:24,920 Speaker 1: in bitcoins history, um, you know when this bitcoin being 225 00:13:24,960 --> 00:13:28,280 Speaker 1: extremely over oversold or other board and therefore when is 226 00:13:28,280 --> 00:13:30,360 Speaker 1: it When is a good time for me to buy ourselves? 227 00:13:31,040 --> 00:13:34,240 Speaker 1: And that's pretty much it. You know, when you dig 228 00:13:34,280 --> 00:13:36,200 Speaker 1: into the side, is a bit more there, but in 229 00:13:36,200 --> 00:13:38,640 Speaker 1: its essence, that's kind of it really. So it's you're 230 00:13:38,679 --> 00:13:43,120 Speaker 1: looking through data and basically it gives it tells you something. 231 00:13:43,200 --> 00:13:45,520 Speaker 1: That's the indicator, and it's indicating here I should either 232 00:13:45,600 --> 00:13:48,120 Speaker 1: buy or its indicating aations maybe sell or I should 233 00:13:48,160 --> 00:13:50,760 Speaker 1: watch it. And then you also talked about using on 234 00:13:51,040 --> 00:13:53,560 Speaker 1: chain data, So what does that mean? What what what 235 00:13:53,720 --> 00:13:58,439 Speaker 1: is on chain data? So on chain data is essentially 236 00:14:00,000 --> 00:14:04,319 Speaker 1: transactions that happened on the blockchain. So if you send 237 00:14:04,400 --> 00:14:07,200 Speaker 1: me some bitcoin tomorrow, which is more than welcome to 238 00:14:07,240 --> 00:14:10,800 Speaker 1: do it, will you know, have most your public address 239 00:14:10,840 --> 00:14:16,559 Speaker 1: there You're right, that will be recorded on the blockchain. 240 00:14:17,320 --> 00:14:21,920 Speaker 1: And that has happened ever since bitcoin started, and so 241 00:14:22,040 --> 00:14:24,520 Speaker 1: there is a huge amount of data available on the 242 00:14:24,520 --> 00:14:27,920 Speaker 1: blockchain to look at in terms of size of transactions, 243 00:14:28,040 --> 00:14:30,880 Speaker 1: the time that the transaction took place, the wallets that 244 00:14:30,960 --> 00:14:34,720 Speaker 1: it moved from, and too. And so you can use 245 00:14:34,800 --> 00:14:39,400 Speaker 1: that data and aggregated level to look at trends over 246 00:14:39,440 --> 00:14:42,240 Speaker 1: time really and those trends can give you clues as 247 00:14:42,240 --> 00:14:45,480 Speaker 1: we alluded to, as to when bitcoin is sold or 248 00:14:45,560 --> 00:14:48,720 Speaker 1: overbought and therefore what as you should action You could 249 00:14:48,720 --> 00:14:51,240 Speaker 1: take it as an investor. Yeah, I want to jump 250 00:14:51,280 --> 00:14:54,440 Speaker 1: into some of the indicators and tools, and so we'll 251 00:14:54,480 --> 00:14:57,240 Speaker 1: talk specifically about some of the arm chained data, because 252 00:14:57,240 --> 00:14:59,000 Speaker 1: I know there's a ton of n chained data. And 253 00:14:59,120 --> 00:15:03,240 Speaker 1: it's curious though, um you mentioned, um look at macro 254 00:15:03,360 --> 00:15:06,960 Speaker 1: cycles and and and having them be like leading indicators. 255 00:15:07,440 --> 00:15:10,560 Speaker 1: And I know one that has been used for for 256 00:15:10,640 --> 00:15:13,360 Speaker 1: many years was Google search data, and that's not on 257 00:15:13,480 --> 00:15:16,880 Speaker 1: chaine data. I understand what people would look at like 258 00:15:16,920 --> 00:15:20,680 Speaker 1: Google search and you could see how the volume of 259 00:15:20,720 --> 00:15:26,280 Speaker 1: bitcoin being searched on Google correlated with the price of bitcoin. Yeah, 260 00:15:26,520 --> 00:15:29,240 Speaker 1: and you know a lot of people think that's a 261 00:15:29,320 --> 00:15:32,520 Speaker 1: leading indicator. I've often thought it was a lagging indicator. 262 00:15:32,600 --> 00:15:37,040 Speaker 1: So leading means that, um, it tells us before the 263 00:15:37,080 --> 00:15:40,400 Speaker 1: move happens, and lagging tells us it happens after. And 264 00:15:40,440 --> 00:15:42,440 Speaker 1: it's kind of like a chicken or the egg argument 265 00:15:42,840 --> 00:15:46,480 Speaker 1: where um, because the bitcoin price went from seven thousand 266 00:15:46,560 --> 00:15:48,440 Speaker 1: to twenty thousand, everybody's searching it to figure out what 267 00:15:48,480 --> 00:15:51,760 Speaker 1: the heck it is that that would be after or 268 00:15:52,040 --> 00:15:54,680 Speaker 1: are they searching it and then they buy, which then 269 00:15:54,760 --> 00:15:59,160 Speaker 1: is a leading What do you think? Uh? So, I 270 00:15:59,240 --> 00:16:01,280 Speaker 1: have some friends You've done a fair beatter than analysis 271 00:16:01,360 --> 00:16:03,120 Speaker 1: on that, and the conclusion is that it's a pretty 272 00:16:03,200 --> 00:16:07,920 Speaker 1: lagging indicator. Actually, So I wouldn't. I wouldn't put too 273 00:16:08,000 --> 00:16:10,440 Speaker 1: much weight on it. Um. But you know, as with 274 00:16:10,480 --> 00:16:12,960 Speaker 1: there any of these things, right, it's just one tool, 275 00:16:13,040 --> 00:16:14,920 Speaker 1: and and it's something I talk about a lot, is 276 00:16:14,960 --> 00:16:18,440 Speaker 1: how even all the charts I'm looking to bitcoin. I mean, 277 00:16:18,640 --> 00:16:21,440 Speaker 1: the purpose of the site is really to help regular people, 278 00:16:21,840 --> 00:16:25,080 Speaker 1: not just large institutions, invest better in bitcoin. And it 279 00:16:25,160 --> 00:16:28,640 Speaker 1: does despite providing a range of tools, because I believe 280 00:16:28,720 --> 00:16:31,160 Speaker 1: that you shouldn't just try and hang your hat on 281 00:16:31,160 --> 00:16:33,520 Speaker 1: one metric. You've got to use a range of tools, 282 00:16:33,520 --> 00:16:36,880 Speaker 1: whether it's these sorts of indicators, whether it's technical analysis, 283 00:16:37,000 --> 00:16:39,560 Speaker 1: Google search trends to kind of join the dots and 284 00:16:39,800 --> 00:16:42,400 Speaker 1: build up your thesis. So definitely, So yeah, I think 285 00:16:42,440 --> 00:16:44,440 Speaker 1: it is a bit of a lugging an indicator. But yeah, sure, 286 00:16:44,440 --> 00:16:46,760 Speaker 1: all this stuff confused, so you think you think there's 287 00:16:46,800 --> 00:16:50,000 Speaker 1: other on chain data that is more of a leading indicator. 288 00:16:50,360 --> 00:16:53,480 Speaker 1: So you think there is some good stuff without getting 289 00:16:53,520 --> 00:16:56,360 Speaker 1: to the specifics of the actual specific indicators you have. 290 00:16:56,400 --> 00:16:57,720 Speaker 1: I mean, there are a couple of metrics that you 291 00:16:57,760 --> 00:17:02,360 Speaker 1: think could be good as leading. Yes, so I think 292 00:17:02,440 --> 00:17:06,560 Speaker 1: you can look at well, well we'll come on to 293 00:17:06,640 --> 00:17:09,840 Speaker 1: talk about them. But yeah, so on chained data specifically 294 00:17:09,880 --> 00:17:14,280 Speaker 1: like Bitcoin days destroyed. Uh that that is very useful 295 00:17:14,320 --> 00:17:17,639 Speaker 1: in terms of looking at um all guys who have 296 00:17:17,720 --> 00:17:19,760 Speaker 1: helped the kind of a long amount of time, like 297 00:17:19,880 --> 00:17:22,400 Speaker 1: are they are they moving funds from there? While it's 298 00:17:22,440 --> 00:17:25,679 Speaker 1: that can give you clues, essentially, you're constantly looking for 299 00:17:25,840 --> 00:17:29,280 Speaker 1: clues and hints as to what may be coming in 300 00:17:29,320 --> 00:17:31,720 Speaker 1: the market and so on. Chained data can do that, 301 00:17:31,760 --> 00:17:36,359 Speaker 1: but so can actually UM like price analysis analysis. So 302 00:17:36,800 --> 00:17:39,840 Speaker 1: you know, half the charts on the site are looking 303 00:17:39,880 --> 00:17:43,479 Speaker 1: at price data using moving averages to show you the 304 00:17:43,520 --> 00:17:47,000 Speaker 1: broad trend of the market where and whether we get 305 00:17:47,040 --> 00:17:50,600 Speaker 1: to points where the market might get ourtherheated or whereveryone 306 00:17:50,640 --> 00:17:53,960 Speaker 1: might actually be very fearful, you know, because a large 307 00:17:54,080 --> 00:17:58,080 Speaker 1: part about understanding the bitcoin market from an investment point 308 00:17:58,080 --> 00:18:02,040 Speaker 1: of view is about understanding it's market cycles. So it's 309 00:18:02,080 --> 00:18:06,879 Speaker 1: about understanding when is the general consensus of market participants, 310 00:18:06,880 --> 00:18:10,359 Speaker 1: When are they broadly over optimistic and that might be 311 00:18:10,400 --> 00:18:12,159 Speaker 1: a good time to take some profit of the table, 312 00:18:12,440 --> 00:18:15,080 Speaker 1: and when are they overly pessimistic? You know, when is 313 00:18:15,119 --> 00:18:17,480 Speaker 1: everyone really fearful? I think what is it? Warren Buffett, 314 00:18:17,520 --> 00:18:20,240 Speaker 1: he said, you know, be greedy when everyone else is fearful. Right, 315 00:18:20,480 --> 00:18:23,359 Speaker 1: If you fundamentally believe in the long term prospects of 316 00:18:23,440 --> 00:18:26,840 Speaker 1: big point, then I'm being able to identify those periods 317 00:18:27,119 --> 00:18:30,040 Speaker 1: can be very valuable to use an investor intend to 318 00:18:30,080 --> 00:18:35,919 Speaker 1: know when to invest. Yeah, and so um, somehow the 319 00:18:36,000 --> 00:18:38,560 Speaker 1: data can tell us when it's overpriced or when the 320 00:18:38,600 --> 00:18:42,600 Speaker 1: market psychology, the market as a whole is greedy or 321 00:18:42,960 --> 00:18:46,480 Speaker 1: is is that now? Uh? In investing, we've always said 322 00:18:46,520 --> 00:18:51,400 Speaker 1: that past performance is no guarantee of future. So I'm 323 00:18:51,440 --> 00:18:54,800 Speaker 1: guessing you have to take that into account. How do 324 00:18:54,840 --> 00:18:59,280 Speaker 1: you look at that? I agree with that one, you know, 325 00:18:59,480 --> 00:19:03,639 Speaker 1: And what would say is that, you know, history doesn't 326 00:19:03,640 --> 00:19:07,040 Speaker 1: always repeat, but it does influence the future. And we've 327 00:19:07,080 --> 00:19:10,440 Speaker 1: got like tend nearly eleven years worth of data now 328 00:19:10,480 --> 00:19:13,720 Speaker 1: and bitcoin, and so it does allow us to forecast 329 00:19:13,880 --> 00:19:17,240 Speaker 1: what may play out in the coming months or years. 330 00:19:17,840 --> 00:19:20,919 Speaker 1: But yeah, I mean, all of these tools, you know, 331 00:19:21,119 --> 00:19:24,080 Speaker 1: they none of them may work going forwards. But I 332 00:19:24,119 --> 00:19:27,000 Speaker 1: think there's such an array of different types of tools 333 00:19:27,000 --> 00:19:30,199 Speaker 1: that people are using now that again going back to 334 00:19:30,240 --> 00:19:32,280 Speaker 1: my point before, if you if you use a cross 335 00:19:32,320 --> 00:19:35,639 Speaker 1: section of them, all from different sources and kind of 336 00:19:35,720 --> 00:19:38,080 Speaker 1: join the dots and they can help you forecast what 337 00:19:38,280 --> 00:19:41,640 Speaker 1: may play out going forwards. Um. You know, which which 338 00:19:41,640 --> 00:19:43,719 Speaker 1: a lot of funds are doing now as well as 339 00:19:43,760 --> 00:19:47,280 Speaker 1: individuals with it with pretty high degree of success. So 340 00:19:47,760 --> 00:19:50,120 Speaker 1: I think there's a lot in it. But yeah, absolutely, 341 00:19:50,440 --> 00:19:53,520 Speaker 1: you know none of this is investment advice. And also 342 00:19:53,680 --> 00:19:56,960 Speaker 1: you know all of these tools are literally just educational 343 00:19:57,000 --> 00:19:59,600 Speaker 1: tools to try and help you out. So let's talk 344 00:19:59,600 --> 00:20:01,400 Speaker 1: about a couple of them. I know on your website, 345 00:20:01,440 --> 00:20:06,160 Speaker 1: I think you have ten or twelve different indicators. And 346 00:20:06,160 --> 00:20:08,800 Speaker 1: again I want to just impress on everybody that, uh, 347 00:20:08,920 --> 00:20:12,760 Speaker 1: one indicator by itself doesn't mean anything. Um. You want 348 00:20:12,800 --> 00:20:14,320 Speaker 1: to look at all of them, like like a good 349 00:20:14,359 --> 00:20:17,280 Speaker 1: example in the traditional markets might be everyone thought, oh, 350 00:20:17,320 --> 00:20:20,840 Speaker 1: when the yield curve inverts, when the bond yield curve inverts, 351 00:20:20,880 --> 00:20:24,080 Speaker 1: then the market's going to crash. Well that's one indicator, 352 00:20:24,320 --> 00:20:25,920 Speaker 1: all right, But when you look at all the other 353 00:20:25,920 --> 00:20:28,159 Speaker 1: indicators of the market, to me, it was telling me 354 00:20:28,200 --> 00:20:30,320 Speaker 1: that the market wasn't gonna crash. And I've been pretty 355 00:20:30,640 --> 00:20:33,040 Speaker 1: up now we're starting to geet rallied um. And so 356 00:20:33,119 --> 00:20:36,360 Speaker 1: you can't just look at one indicator like that, um. 357 00:20:36,440 --> 00:20:38,160 Speaker 1: And so that's kind of what we're talking about. And 358 00:20:38,160 --> 00:20:39,920 Speaker 1: and there's ten or twelve here, but there's other things, 359 00:20:40,000 --> 00:20:42,600 Speaker 1: right that you want to look at. I look at also, 360 00:20:42,720 --> 00:20:46,320 Speaker 1: like external things not on chain, like, um, what are 361 00:20:46,560 --> 00:20:49,400 Speaker 1: companies doing? Like, Uh, we've just seen in the last 362 00:20:49,400 --> 00:20:53,040 Speaker 1: couple of weeks, uh, close to a billion dollars get 363 00:20:53,080 --> 00:20:56,800 Speaker 1: raised for bitcoin mining. That's a serious investment for long 364 00:20:56,920 --> 00:20:59,159 Speaker 1: term and that tells me something. We saw, you know, 365 00:20:59,280 --> 00:21:01,840 Speaker 1: most of the the big elite in Wall Street jump 366 00:21:01,880 --> 00:21:04,480 Speaker 1: into bitcoin just in the last month or two, um, 367 00:21:04,520 --> 00:21:07,560 Speaker 1: you know, from fidality and back finally launched. And so 368 00:21:07,640 --> 00:21:10,800 Speaker 1: that's fundamental. I just want to impress on everybody you 369 00:21:10,840 --> 00:21:12,600 Speaker 1: want to look at all these things and what are 370 00:21:12,640 --> 00:21:15,200 Speaker 1: they telling you? But um, if we can, let's talk 371 00:21:15,240 --> 00:21:18,320 Speaker 1: about maybe just a couple of the indicators that you 372 00:21:18,400 --> 00:21:21,480 Speaker 1: have that we can explain without the need of charts 373 00:21:21,480 --> 00:21:23,280 Speaker 1: and whatnot, And and tell me what do you think 374 00:21:23,320 --> 00:21:26,080 Speaker 1: are maybe like your most powerful or most easy to 375 00:21:26,200 --> 00:21:30,919 Speaker 1: use ones. Yeah, sure, let's start with We'll, like you say, 376 00:21:30,960 --> 00:21:33,280 Speaker 1: given the we're not in front of the you know, 377 00:21:33,600 --> 00:21:35,639 Speaker 1: the website it self right now, let's start with one 378 00:21:35,640 --> 00:21:38,880 Speaker 1: of the simpler charts on the site. Uh. And in fact, 379 00:21:39,040 --> 00:21:41,639 Speaker 1: I kind of designed it to be as simple as 380 00:21:41,680 --> 00:21:44,600 Speaker 1: possible because I wanted this side to be useful for anyone, 381 00:21:44,600 --> 00:21:47,920 Speaker 1: whether they are you know, Omega on chain analytics geek. 382 00:21:48,000 --> 00:21:50,320 Speaker 1: There's some stuff on there for like people like that, 383 00:21:50,440 --> 00:21:54,000 Speaker 1: like charts I reserve risk. Uh, there's plumb stuff to 384 00:21:54,040 --> 00:21:56,240 Speaker 1: flow model, which I'm sure most people have probably heard 385 00:21:56,240 --> 00:21:58,600 Speaker 1: of now, and then mind your mind through some more 386 00:21:58,640 --> 00:22:01,200 Speaker 1: simple stuff. So let's start with arguably one of the 387 00:22:01,240 --> 00:22:04,359 Speaker 1: more simple ones. It's just called the Bitcoin Investor Tool, 388 00:22:05,200 --> 00:22:09,080 Speaker 1: and it uses a two year moving average line of 389 00:22:09,160 --> 00:22:12,760 Speaker 1: bitcoins price. So on the chart, you've got the price 390 00:22:13,160 --> 00:22:15,359 Speaker 1: a bitcoin, so you can see the price line, and 391 00:22:15,400 --> 00:22:18,640 Speaker 1: then you also have a two year moving average line 392 00:22:18,640 --> 00:22:21,760 Speaker 1: of bitcoins price. So for anyone who doesn't know what 393 00:22:21,800 --> 00:22:25,280 Speaker 1: I'm moving average line is, it's simply taking an average 394 00:22:25,400 --> 00:22:28,560 Speaker 1: of the daily closed prices over any given period of time. 395 00:22:29,440 --> 00:22:32,320 Speaker 1: So you could have a ten day moving average line, 396 00:22:32,320 --> 00:22:35,840 Speaker 1: which shows average price of the past ten days. You 397 00:22:35,840 --> 00:22:38,400 Speaker 1: could have a two day moving average line, which shows 398 00:22:38,440 --> 00:22:42,160 Speaker 1: average price over the past two in days. The result 399 00:22:42,240 --> 00:22:45,840 Speaker 1: is a smooth line versus the more erratic daily price 400 00:22:45,960 --> 00:22:49,760 Speaker 1: line because you're taking an average price over a number 401 00:22:49,800 --> 00:22:53,880 Speaker 1: of days and moving averages that are useful in markets 402 00:22:53,920 --> 00:22:56,760 Speaker 1: that tend to trend or have market cycles. Because the 403 00:22:56,800 --> 00:23:00,399 Speaker 1: moving average you can highlight when prices moving with or 404 00:23:00,640 --> 00:23:03,800 Speaker 1: against the trend. So in the market life, bitcoin is 405 00:23:03,800 --> 00:23:08,440 Speaker 1: actually super useful using moving averages. And here we used 406 00:23:08,440 --> 00:23:14,480 Speaker 1: the two year moving average because whenever price dips below 407 00:23:15,040 --> 00:23:19,520 Speaker 1: that line, it has historically been an excellent time to 408 00:23:19,600 --> 00:23:25,560 Speaker 1: buy bitcoin. So in bitcoin's now nearly eleven year history, 409 00:23:26,080 --> 00:23:29,840 Speaker 1: price has only dipped below the two year moving average 410 00:23:29,880 --> 00:23:33,639 Speaker 1: line three times, and it does. When it does it, 411 00:23:33,760 --> 00:23:37,280 Speaker 1: it does it for a few weeks or months, and 412 00:23:37,880 --> 00:23:41,439 Speaker 1: if you bought during that period, you would have achieved 413 00:23:41,440 --> 00:23:45,199 Speaker 1: outsized returns over the years because you would effectively be 414 00:23:45,280 --> 00:23:48,639 Speaker 1: buying the bottom. Right when when price dip below the 415 00:23:48,680 --> 00:23:51,480 Speaker 1: two year moving average, that is like the bottom of 416 00:23:51,480 --> 00:23:54,960 Speaker 1: the bear market. Um. So it's a as a as 417 00:23:55,000 --> 00:23:58,520 Speaker 1: a an investor who's able to remove their emotions a 418 00:23:58,560 --> 00:24:01,560 Speaker 1: little bit. You can see when price goes blurw it 419 00:24:01,640 --> 00:24:04,160 Speaker 1: to you moving average line, it's an excellent time. Did 420 00:24:04,160 --> 00:24:06,960 Speaker 1: it recently? Did it recently like in the last six months, 421 00:24:06,960 --> 00:24:09,240 Speaker 1: like that maybe November December? Did it did below that 422 00:24:09,280 --> 00:24:12,720 Speaker 1: line exactly exactly? So we saw it dip below the 423 00:24:12,760 --> 00:24:17,600 Speaker 1: line um in December, and obviously we bottomed out what 424 00:24:17,640 --> 00:24:21,240 Speaker 1: was it, three thousand dollars around there else around there, 425 00:24:21,600 --> 00:24:24,520 Speaker 1: and then it came back up above the line. And 426 00:24:24,600 --> 00:24:27,399 Speaker 1: I think March time, April time, I should have the 427 00:24:27,440 --> 00:24:30,480 Speaker 1: chart in front of me when we crossed about five 428 00:24:30,520 --> 00:24:33,359 Speaker 1: thousand dollars and then then shut up above the two 429 00:24:33,440 --> 00:24:36,800 Speaker 1: years moving average line. And interestingly we've actually just come 430 00:24:36,840 --> 00:24:39,440 Speaker 1: back to retest it, which we've done in previous sides 431 00:24:39,560 --> 00:24:42,439 Speaker 1: as well, and that tends to indicate we're about to 432 00:24:42,480 --> 00:24:45,360 Speaker 1: kick off now a new ball rumber when you when 433 00:24:45,359 --> 00:24:49,040 Speaker 1: you test the line exactly, yeah, which we've just done 434 00:24:49,119 --> 00:24:52,199 Speaker 1: literally a couple of weeks ago. And I know you 435 00:24:52,200 --> 00:24:53,760 Speaker 1: said you don't have the chart in front of you, 436 00:24:54,280 --> 00:24:57,880 Speaker 1: but maybe you can guess or approximate, uh if if 437 00:24:58,000 --> 00:25:00,480 Speaker 1: if it said to buy right around there, when Win 438 00:25:00,560 --> 00:25:02,879 Speaker 1: would have told us to sell, if you were to 439 00:25:02,880 --> 00:25:06,119 Speaker 1: back up, you know, yeah, yeah, well exactly. So as 440 00:25:06,119 --> 00:25:08,240 Speaker 1: an investor, you we talked about Earlione, you want to 441 00:25:08,240 --> 00:25:10,679 Speaker 1: know when to buying, went to sell, and so the 442 00:25:10,800 --> 00:25:13,200 Speaker 1: two year moving average line can tell you when to buy, 443 00:25:13,200 --> 00:25:16,119 Speaker 1: because when price goes beneath it, that's went to buy. 444 00:25:16,240 --> 00:25:19,159 Speaker 1: And what the other line on the chart does is 445 00:25:19,200 --> 00:25:24,439 Speaker 1: it simply is multiplying that two year moving average by five, 446 00:25:24,640 --> 00:25:27,000 Speaker 1: So the values of that two year moving average multiplied 447 00:25:27,040 --> 00:25:30,560 Speaker 1: by five. And what that does is it actually catches 448 00:25:30,640 --> 00:25:37,720 Speaker 1: the tops of bitcoins price cycles. So, for example, back 449 00:25:37,760 --> 00:25:43,280 Speaker 1: in December two thousand and seventeen, when we were, you know, 450 00:25:43,320 --> 00:25:45,080 Speaker 1: at the top of the last cycle, I think price 451 00:25:45,119 --> 00:25:47,760 Speaker 1: went from like, what was it, twelve thousand dollars to 452 00:25:47,880 --> 00:25:49,919 Speaker 1: like nearly twenty thousand dollars in the space of like 453 00:25:50,000 --> 00:25:54,359 Speaker 1: three weeks, wasn't it right, We saw using this indicator 454 00:25:54,840 --> 00:25:59,680 Speaker 1: that price moved above that time's five multiple moving average line, 455 00:25:59,720 --> 00:26:02,240 Speaker 1: and so that was indicating that actually, that's pretty good 456 00:26:02,240 --> 00:26:05,080 Speaker 1: time to be taking some profit off off the table 457 00:26:05,119 --> 00:26:08,119 Speaker 1: if you're a long term investor. And it has done 458 00:26:08,160 --> 00:26:12,640 Speaker 1: that for each of bitcoins market cycles going back eight 459 00:26:12,760 --> 00:26:16,439 Speaker 1: years now. So it's a very simple, very effective tool 460 00:26:16,880 --> 00:26:20,720 Speaker 1: to indicate when is the market overly pessimistic and where 461 00:26:20,760 --> 00:26:24,080 Speaker 1: is when is the market becoming overheated, And so then 462 00:26:24,119 --> 00:26:26,760 Speaker 1: as a long term investor, I mean it's going back 463 00:26:26,760 --> 00:26:29,200 Speaker 1: eight years, it would have it's been effective so far. 464 00:26:29,320 --> 00:26:31,120 Speaker 1: We don't know that hit in the future. But it's 465 00:26:31,119 --> 00:26:32,880 Speaker 1: been effective, and it would have told me to sell 466 00:26:32,880 --> 00:26:35,560 Speaker 1: that at the top in December of sen or January 467 00:26:36,320 --> 00:26:38,960 Speaker 1: and then buy back in at the bottom of December, 468 00:26:41,040 --> 00:26:44,480 Speaker 1: basically sat out of the market for a year, which correctly. 469 00:26:44,480 --> 00:26:46,400 Speaker 1: I mean if you if you're only using that one tool, 470 00:26:46,400 --> 00:26:50,720 Speaker 1: which that that one is not using on chain data, right, 471 00:26:50,800 --> 00:26:55,520 Speaker 1: that one's usually price action exactly exactly. And so now 472 00:26:55,520 --> 00:26:58,359 Speaker 1: what do you think about price action? Um, I know 473 00:26:58,520 --> 00:27:01,199 Speaker 1: some of the best technical analysts the market today, they 474 00:27:01,359 --> 00:27:03,800 Speaker 1: really believe that technical analysis, even though it's a math 475 00:27:04,480 --> 00:27:08,919 Speaker 1: um meaning like Fibernacci lines mathematical lines, it really works 476 00:27:08,960 --> 00:27:12,040 Speaker 1: off market psychology. And so do you think somehow this 477 00:27:12,200 --> 00:27:15,600 Speaker 1: moving average and the five times top lines somehow works 478 00:27:15,640 --> 00:27:20,000 Speaker 1: with market psychology. Having been someone that's that's studied that, yeah, 479 00:27:20,280 --> 00:27:22,160 Speaker 1: I think it is. I think it is because all 480 00:27:22,160 --> 00:27:25,920 Speaker 1: those moving averages are doing really is recognizing the bitcoins 481 00:27:25,920 --> 00:27:28,399 Speaker 1: on an adoption curve, so it's moving up. But on 482 00:27:28,520 --> 00:27:32,200 Speaker 1: top of that adoption curve you have we are experiencing 483 00:27:32,240 --> 00:27:35,639 Speaker 1: these very clear market cycles, right, and if you've been 484 00:27:35,680 --> 00:27:38,040 Speaker 1: in bitcoin for more than a couple of years, you 485 00:27:38,480 --> 00:27:41,160 Speaker 1: kind of know what we're talking about. We there are 486 00:27:41,520 --> 00:27:44,199 Speaker 1: times when the market is feeling pretty dad about the 487 00:27:44,200 --> 00:27:46,960 Speaker 1: prospects of it, quite like arguing we were back in 488 00:27:46,960 --> 00:27:52,080 Speaker 1: December and then this period where everyone's super excited piling in, 489 00:27:52,280 --> 00:27:54,119 Speaker 1: you know, like it was back in December two doesn't 490 00:27:54,119 --> 00:27:56,120 Speaker 1: sound seen. You know, you had all your friends coming 491 00:27:56,160 --> 00:27:57,760 Speaker 1: up to your gun. What's this bigcoin thing? How can 492 00:27:57,800 --> 00:28:01,040 Speaker 1: I get involved? And that is pure market psychology, and 493 00:28:00,800 --> 00:28:04,520 Speaker 1: that is just people becoming either overly pessimistic or over optimistic. 494 00:28:04,560 --> 00:28:06,479 Speaker 1: And and all the moving average lines do in this 495 00:28:06,520 --> 00:28:09,360 Speaker 1: instance is kind of cut through prices. It is, it's 496 00:28:09,520 --> 00:28:12,960 Speaker 1: doing those huge swings, and say, if you really step 497 00:28:13,040 --> 00:28:16,000 Speaker 1: back as like a long term bitcoin you opened up 498 00:28:16,000 --> 00:28:18,960 Speaker 1: with saying that you really believe bitcoin is this technology 499 00:28:19,000 --> 00:28:21,000 Speaker 1: that can really free us from the banking system and 500 00:28:21,240 --> 00:28:26,360 Speaker 1: really revolutionist everything. Um, as it gets bigger, the volatility 501 00:28:26,400 --> 00:28:30,040 Speaker 1: should go down. And eventually if it's so, do you 502 00:28:30,080 --> 00:28:33,480 Speaker 1: think this model would be adjusted? So right now it's 503 00:28:33,520 --> 00:28:36,760 Speaker 1: at a five times after two hundred, but maybe eventually 504 00:28:36,800 --> 00:28:40,040 Speaker 1: goes to four times and three times and two times. Yeah, yeah, 505 00:28:40,040 --> 00:28:42,320 Speaker 1: I mean I think you're right. I think it will 506 00:28:42,400 --> 00:28:46,200 Speaker 1: and I think a lot of these valuation tools that um, 507 00:28:46,240 --> 00:28:48,240 Speaker 1: all of us are working on at the moment, will 508 00:28:48,320 --> 00:28:50,720 Speaker 1: have to be adapted and some of them will just 509 00:28:50,960 --> 00:28:53,400 Speaker 1: out right stop working, right, And I think I think 510 00:28:53,520 --> 00:28:56,680 Speaker 1: a lot of these valuation models are effective whilst we're 511 00:28:56,680 --> 00:28:59,480 Speaker 1: in this early adoption phase for bit point and there's 512 00:28:59,600 --> 00:29:03,440 Speaker 1: very clear aggressive growth. But I suspect in the next 513 00:29:03,560 --> 00:29:06,560 Speaker 1: kind of couple of market cycles will then move into 514 00:29:06,560 --> 00:29:09,400 Speaker 1: a more mature market phase. As you mentioned, red volativity 515 00:29:09,440 --> 00:29:12,880 Speaker 1: will drop die down, the market cap will be you know, 516 00:29:13,440 --> 00:29:16,720 Speaker 1: over a couple of trillion dollars, and um, yeah, there 517 00:29:16,760 --> 00:29:18,680 Speaker 1: will need to be new metrics, and who knows those 518 00:29:18,760 --> 00:29:21,760 Speaker 1: those new metrics maybe more in line with you know, 519 00:29:21,840 --> 00:29:23,920 Speaker 1: some of the stuff you see in traditional markets. Because 520 00:29:23,920 --> 00:29:27,520 Speaker 1: I suspect, and this is just a theory, that bitcoin 521 00:29:27,560 --> 00:29:29,960 Speaker 1: will if it's still around, right, if it's still around 522 00:29:29,960 --> 00:29:32,400 Speaker 1: in ten years, I suspect it will start to be 523 00:29:32,520 --> 00:29:36,600 Speaker 1: more in sync with with global other global macro macro assets, 524 00:29:36,680 --> 00:29:40,480 Speaker 1: because by that time it will be pretty big. Yeah, 525 00:29:40,840 --> 00:29:43,520 Speaker 1: So that's the two year moving average. You call it 526 00:29:43,600 --> 00:29:46,120 Speaker 1: the bitcoin investor tour, and then one can check that 527 00:29:46,160 --> 00:29:48,600 Speaker 1: out a look into bitcoin dot com. Let's let's talk 528 00:29:48,600 --> 00:29:50,840 Speaker 1: about another one. Maybe you have one that actually uses 529 00:29:50,880 --> 00:29:54,880 Speaker 1: our chained data. Yep. So another one we can talk 530 00:29:54,920 --> 00:29:58,680 Speaker 1: about the users on chained data would be envy are 531 00:29:58,760 --> 00:30:02,000 Speaker 1: the Z school sounds a bit of a funny name, 532 00:30:02,640 --> 00:30:05,239 Speaker 1: But I love this chart. I didn't come up with 533 00:30:05,280 --> 00:30:08,000 Speaker 1: the matter behind it. It's not my idea. I just 534 00:30:08,080 --> 00:30:10,800 Speaker 1: created the visual you can see on the site to 535 00:30:10,880 --> 00:30:13,800 Speaker 1: try and make it easy for investors to use. But 536 00:30:13,880 --> 00:30:17,320 Speaker 1: I think the thinking behind it and the methodology is genius. 537 00:30:17,840 --> 00:30:22,280 Speaker 1: Mv r V Z school uses on chain analysis and 538 00:30:22,960 --> 00:30:27,600 Speaker 1: uh it was the original idea behind it came from 539 00:30:27,640 --> 00:30:31,480 Speaker 1: a couple of guys. Murad Mahmudov and David Kule came 540 00:30:31,560 --> 00:30:35,640 Speaker 1: up for the idea is behind NDRV school, and then 541 00:30:37,080 --> 00:30:40,800 Speaker 1: Z School was added on top of it. But essentially 542 00:30:40,960 --> 00:30:45,160 Speaker 1: it's pretty straightforward. So it uses three metrics. So if 543 00:30:45,160 --> 00:30:46,840 Speaker 1: you look at the chart, there's gonna be three lines 544 00:30:46,880 --> 00:30:51,120 Speaker 1: on the chart, and the first is market cap and 545 00:30:51,240 --> 00:30:54,880 Speaker 1: market cap, just like you have in traditional markets for 546 00:30:55,200 --> 00:30:58,840 Speaker 1: stocks and shares, where the market cap is the share 547 00:30:58,880 --> 00:31:01,520 Speaker 1: price multiplied by the number of shares. In the case 548 00:31:01,520 --> 00:31:04,280 Speaker 1: a bitcoin, market cap is the current price of bitcoin 549 00:31:04,760 --> 00:31:07,840 Speaker 1: multiplied by the number of coins in circulation. So that 550 00:31:07,880 --> 00:31:10,480 Speaker 1: gets you to market cap, right and the market capoin 551 00:31:10,560 --> 00:31:12,920 Speaker 1: is supplied on a chart looks pretty similar to price 552 00:31:12,960 --> 00:31:18,160 Speaker 1: because price is a cool component of it. The second 553 00:31:18,160 --> 00:31:21,800 Speaker 1: metric we use is slightly different, and this is where 554 00:31:21,800 --> 00:31:25,800 Speaker 1: we use the on chained data. So rather than taking 555 00:31:25,960 --> 00:31:31,680 Speaker 1: the current price of bitcoin, which market cap does, realized value, 556 00:31:31,960 --> 00:31:36,040 Speaker 1: takes the price of each bitcoin when it was last moved, 557 00:31:36,560 --> 00:31:39,440 Speaker 1: I the last time it was sent from one wallet 558 00:31:39,480 --> 00:31:45,600 Speaker 1: to another wallet. So it's like it's like a cast basis. Yeah, yeah, exactly. 559 00:31:45,640 --> 00:31:47,680 Speaker 1: You can think about it trying it, trying to guess 560 00:31:47,680 --> 00:31:50,640 Speaker 1: like what that person acquired that bitcoin for. So um 561 00:31:50,760 --> 00:31:54,200 Speaker 1: I I last moved it at five thousand. Today it's 562 00:31:54,240 --> 00:31:56,800 Speaker 1: at ten thousand, So my cast basis or whatever, I 563 00:31:57,520 --> 00:32:01,120 Speaker 1: only owe five thousand on that coin. Exactly. For calculating 564 00:32:01,160 --> 00:32:04,040 Speaker 1: realized value, it would use the five thousand dollar value 565 00:32:04,120 --> 00:32:08,840 Speaker 1: rather than today's past value. In doing so, what that 566 00:32:08,880 --> 00:32:11,440 Speaker 1: does is it strips out a lot of the short 567 00:32:11,560 --> 00:32:14,719 Speaker 1: term market sentiment that we have with the market cap metric, 568 00:32:15,600 --> 00:32:18,000 Speaker 1: and so it can give them will give a more 569 00:32:18,040 --> 00:32:21,480 Speaker 1: true long term measure of bitcoins of value. Why do 570 00:32:21,520 --> 00:32:24,840 Speaker 1: you think it strips that out? Because if I'm in 571 00:32:24,880 --> 00:32:27,600 Speaker 1: the money, if I'm in profit, I'm less likely to 572 00:32:27,640 --> 00:32:30,520 Speaker 1: capitulate or less likely to sell out, versus if I'm 573 00:32:30,600 --> 00:32:34,600 Speaker 1: upside down a negative more likely to sell out. Well, 574 00:32:34,800 --> 00:32:37,840 Speaker 1: the reason being is that all those considerations come into 575 00:32:37,880 --> 00:32:42,760 Speaker 1: play in more short term market market thinking, right, and 576 00:32:42,800 --> 00:32:47,520 Speaker 1: so realize value it can be registered recording values from 577 00:32:47,560 --> 00:32:51,160 Speaker 1: like last week or a year ago or five years ago, 578 00:32:51,600 --> 00:32:54,200 Speaker 1: and so it just takes out a lot of the 579 00:32:54,240 --> 00:32:57,640 Speaker 1: short term market sentiments. So when we're seeing in the 580 00:32:57,640 --> 00:33:00,120 Speaker 1: short term people might be an overly person this thing, 581 00:33:00,280 --> 00:33:03,800 Speaker 1: like we said, or over the optimistic, realized value doesn't 582 00:33:03,880 --> 00:33:05,880 Speaker 1: really capture that. So if you look at the chart 583 00:33:05,920 --> 00:33:11,080 Speaker 1: too much smoother, more steady line on the chart versus 584 00:33:11,320 --> 00:33:14,800 Speaker 1: market cap, which because prices are involved in it, is 585 00:33:15,000 --> 00:33:18,920 Speaker 1: very volatile and goes to the extremes of overpessimism and 586 00:33:19,000 --> 00:33:24,400 Speaker 1: over optimism. So that that's that's what realized value is, 587 00:33:24,560 --> 00:33:27,760 Speaker 1: and where we are interested in is looking at the 588 00:33:27,800 --> 00:33:31,840 Speaker 1: divergence between the two, so when market cap is much 589 00:33:31,920 --> 00:33:35,480 Speaker 1: much higher or much much lower, because that is when 590 00:33:35,600 --> 00:33:40,880 Speaker 1: the short term market is either over excited or over pessimistic, 591 00:33:41,680 --> 00:33:44,760 Speaker 1: and we can therefore use the next metric, which is 592 00:33:45,040 --> 00:33:48,440 Speaker 1: Z score, which is simply a standard deviation test that 593 00:33:48,480 --> 00:33:51,760 Speaker 1: pulls out the extremes in the data between market cap 594 00:33:52,200 --> 00:33:56,480 Speaker 1: and realized value. And essentially what it does to cut 595 00:33:56,520 --> 00:33:58,800 Speaker 1: to the chase, is that it's able to pick out 596 00:33:59,080 --> 00:34:02,120 Speaker 1: the tops in big point cycles and also the lows. 597 00:34:02,160 --> 00:34:04,280 Speaker 1: And it's actually so effective in doing it that it 598 00:34:04,320 --> 00:34:07,840 Speaker 1: can pick out the market cycle tops too within two weeks. 599 00:34:08,480 --> 00:34:12,759 Speaker 1: So back in December two thousand and eighteen, one week 600 00:34:12,840 --> 00:34:18,200 Speaker 1: before we peeked in price, m v RVs score indicated 601 00:34:18,239 --> 00:34:20,719 Speaker 1: actually the market was overheated and it was time to 602 00:34:20,719 --> 00:34:24,840 Speaker 1: take profit. Um. So, yeah, it's very valuable tool in 603 00:34:25,000 --> 00:34:29,040 Speaker 1: terms of being able to determine when as an investor 604 00:34:29,080 --> 00:34:32,640 Speaker 1: should I be taking money off the table or investing? Yeah, 605 00:34:32,920 --> 00:34:34,840 Speaker 1: and does that line up with that other tool we 606 00:34:34,840 --> 00:34:36,919 Speaker 1: just talked about, the Bitcoin Investor tool that it both 607 00:34:37,040 --> 00:34:38,680 Speaker 1: they both kind of line up and where they saw 608 00:34:38,760 --> 00:34:41,319 Speaker 1: the market cup. Yeah, they did, and you know that 609 00:34:41,320 --> 00:34:46,279 Speaker 1: that's where you know it's it's useful to use a 610 00:34:46,360 --> 00:34:48,799 Speaker 1: range of metrics, right like we were talking about, because 611 00:34:48,840 --> 00:34:50,640 Speaker 1: they actually both think the top in that instance, and 612 00:34:50,680 --> 00:34:57,279 Speaker 1: they also align with when the market bottoms earlier this year. Okay, yeah, 613 00:34:57,280 --> 00:35:00,799 Speaker 1: so so so we're seeing some good uh, good on 614 00:35:00,920 --> 00:35:03,040 Speaker 1: chain data with that, I mean I would think that 615 00:35:03,320 --> 00:35:06,319 Speaker 1: uh somewhat complex and probably the average person would never 616 00:35:06,360 --> 00:35:07,919 Speaker 1: be able to figure that out. Is trying to figure 617 00:35:07,960 --> 00:35:11,200 Speaker 1: out all the bitcoins that are owned and held out there, 618 00:35:11,200 --> 00:35:14,040 Speaker 1: what is the actual like realized value, what's what was 619 00:35:14,080 --> 00:35:16,480 Speaker 1: the cost basis of that? So that's that's some good 620 00:35:16,480 --> 00:35:18,160 Speaker 1: on chain data. I like. I like the use of 621 00:35:18,160 --> 00:35:22,120 Speaker 1: that good job on that. Um, do you have any 622 00:35:22,160 --> 00:35:24,759 Speaker 1: other ones that may use some good on chain data? 623 00:35:24,800 --> 00:35:26,759 Speaker 1: We could talk about one, maybe one more that that 624 00:35:26,800 --> 00:35:31,080 Speaker 1: would be easy for us to discuss. Uh. So the 625 00:35:31,120 --> 00:35:33,520 Speaker 1: on chain data stuff is probably the sort of stuff 626 00:35:33,560 --> 00:35:37,400 Speaker 1: you want to sit down and uh read about on 627 00:35:37,440 --> 00:35:41,560 Speaker 1: the on the site. So UM, underneath each live data 628 00:35:41,680 --> 00:35:45,239 Speaker 1: chart is a really sure clear explanation as to how 629 00:35:45,280 --> 00:35:49,319 Speaker 1: they work. UM, in the interests of us being on 630 00:35:49,320 --> 00:35:53,000 Speaker 1: a podcast and not having the charts in front of us. Uh. 631 00:35:53,160 --> 00:35:55,239 Speaker 1: Probably one of easy you want to talk about and 632 00:35:55,239 --> 00:35:58,840 Speaker 1: and to visualize is one called the Pice cycle top indicator, 633 00:36:00,080 --> 00:36:05,240 Speaker 1: and uh that uses price data and it uses two 634 00:36:05,360 --> 00:36:09,240 Speaker 1: very specific moving averages. So at shorter timeframe moving average, 635 00:36:09,680 --> 00:36:12,800 Speaker 1: the dred eleven day moving average, and then at times 636 00:36:12,880 --> 00:36:16,200 Speaker 1: to multiple of the three fifty day moving average, which 637 00:36:16,239 --> 00:36:18,920 Speaker 1: is pretty much a one year moving average. And the 638 00:36:19,000 --> 00:36:22,319 Speaker 1: really interesting thing about this chart is that when the 639 00:36:22,400 --> 00:36:25,760 Speaker 1: shorter time frame moving average crosses the other moving average, 640 00:36:26,280 --> 00:36:30,560 Speaker 1: it actually captures the tops of bitcoins price cycles to 641 00:36:30,640 --> 00:36:35,120 Speaker 1: within three days. So really really effective tool in terms 642 00:36:35,120 --> 00:36:38,600 Speaker 1: of identifying when is the market topping, when is the 643 00:36:38,640 --> 00:36:42,759 Speaker 1: market really overheated? And yeah it's I've yet to find 644 00:36:42,760 --> 00:36:45,719 Speaker 1: another tool that can pick those market tops as accurately, 645 00:36:45,800 --> 00:36:48,960 Speaker 1: So so that interests. That's our sell price action. That's 646 00:36:48,960 --> 00:36:52,200 Speaker 1: not really exactly exactly about just a couple of other 647 00:36:52,280 --> 00:36:54,440 Speaker 1: metrics that maybe you're digging enough of our chain. One 648 00:36:54,480 --> 00:36:56,560 Speaker 1: I know, and I think I think maybe we mentioned 649 00:36:56,560 --> 00:36:59,200 Speaker 1: about is maybe it was in one of our earlier conversations. 650 00:36:59,200 --> 00:37:02,920 Speaker 1: But it's a like average days or days destroyed, right, 651 00:37:02,960 --> 00:37:06,080 Speaker 1: so you can see like how long the bitcoin has 652 00:37:06,080 --> 00:37:09,319 Speaker 1: been sitting there? What's that one? Yes, so that that 653 00:37:09,520 --> 00:37:11,680 Speaker 1: is So there's a chart and the cycle reserve risk, 654 00:37:11,840 --> 00:37:15,840 Speaker 1: which was developed by the guys that Ikey Guy Fund, 655 00:37:15,960 --> 00:37:23,120 Speaker 1: which is a a crypto fund based out in l A. G. Yeah, yeah, yeah, 656 00:37:23,120 --> 00:37:28,359 Speaker 1: Travis and those guys and um, they did a lot 657 00:37:28,360 --> 00:37:32,880 Speaker 1: of analysis around bitcoin days destroyed and the concept around 658 00:37:32,880 --> 00:37:37,320 Speaker 1: Bitcoin days destroyed is simply, as you alluded to, UM 659 00:37:37,360 --> 00:37:41,319 Speaker 1: if looking at coins that haven't moved for a very 660 00:37:41,400 --> 00:37:45,640 Speaker 1: long time. So let's say a coin hasn't moved for 661 00:37:45,680 --> 00:37:48,719 Speaker 1: five years and then I decided to send it to 662 00:37:48,760 --> 00:37:53,480 Speaker 1: you today. When I send it to you, it would 663 00:37:53,480 --> 00:37:58,680 Speaker 1: be destroying in invert commerce five years worth of days, 664 00:37:58,760 --> 00:38:03,120 Speaker 1: if you like. And the reason why that is important 665 00:38:03,160 --> 00:38:06,440 Speaker 1: when we do certain types of one chain analysis is 666 00:38:06,440 --> 00:38:11,360 Speaker 1: it's because it's kind of telling you that um coins 667 00:38:11,360 --> 00:38:13,960 Speaker 1: that haven't moved for a long time are now being moved, 668 00:38:14,719 --> 00:38:17,719 Speaker 1: and that that is quite important because what we tend 669 00:38:17,800 --> 00:38:20,560 Speaker 1: to see is that participants have been in the market 670 00:38:20,560 --> 00:38:22,520 Speaker 1: for a long time. So like old guys O G, 671 00:38:22,800 --> 00:38:27,320 Speaker 1: s UM, they tend to understand bitcoin price movement very well, 672 00:38:27,520 --> 00:38:29,799 Speaker 1: especially when you compare it to a new entrance coming 673 00:38:29,840 --> 00:38:33,640 Speaker 1: into the market. And so people like Travis Kling and 674 00:38:33,880 --> 00:38:35,880 Speaker 1: other guys who do this sort of one chained data, 675 00:38:36,320 --> 00:38:39,960 Speaker 1: they give a lot of importance towards those guys. So 676 00:38:40,000 --> 00:38:42,920 Speaker 1: when they're seeing lots of Bitcoin days destroyed, they're sitting 677 00:38:42,960 --> 00:38:46,400 Speaker 1: up and paying attention. And actually they've built tools that 678 00:38:46,440 --> 00:38:49,160 Speaker 1: show you when there's a high level of bitcoin days 679 00:38:49,239 --> 00:38:51,279 Speaker 1: destroyed and you want to be sitting up with paying 680 00:38:51,280 --> 00:38:53,800 Speaker 1: attention in terms of whether people are buying and selling, 681 00:38:53,880 --> 00:38:56,759 Speaker 1: So yeah, there aren't. Chaine is destroyed. I mean it 682 00:38:56,840 --> 00:38:59,760 Speaker 1: kind of shows the Hardler's right, that shows like who's 683 00:38:59,800 --> 00:39:03,200 Speaker 1: whole thing, And when that number goes down, it means 684 00:39:03,239 --> 00:39:06,480 Speaker 1: those hoddlers, those o g s are starting to sell. 685 00:39:07,040 --> 00:39:09,280 Speaker 1: And then basically that would tell us like, oh shoot, 686 00:39:09,280 --> 00:39:12,160 Speaker 1: if these guys are starting to sell, then maybe the 687 00:39:12,160 --> 00:39:14,239 Speaker 1: markets starting to soften. Is that kind of how that 688 00:39:14,360 --> 00:39:17,680 Speaker 1: how that works? Yeah, yeah, exactly, it can work in 689 00:39:17,719 --> 00:39:20,800 Speaker 1: that way. Um. They actually then take it a couple 690 00:39:20,800 --> 00:39:25,640 Speaker 1: of steps further to show you, um, the sentiment therefore 691 00:39:25,960 --> 00:39:30,600 Speaker 1: of those old guys, those hoddlers, and where prices relatively 692 00:39:31,239 --> 00:39:33,960 Speaker 1: at this moment in time, and so therefore whether the 693 00:39:34,080 --> 00:39:38,880 Speaker 1: market is under all overvalued based on the sentiment of 694 00:39:38,920 --> 00:39:41,760 Speaker 1: those old guys. So they get pretty sophisticated with it. Um, 695 00:39:41,800 --> 00:39:44,960 Speaker 1: but yeah, really interesting stuff. So basically for everyone listening 696 00:39:45,000 --> 00:39:48,360 Speaker 1: that's not really following along, it basically looks at how 697 00:39:48,440 --> 00:39:51,840 Speaker 1: long the bitcoin has been sitting still. So if I 698 00:39:51,880 --> 00:39:53,680 Speaker 1: bought bitcoin and threw it into a hardware wallet and 699 00:39:53,680 --> 00:39:56,479 Speaker 1: it's been there, for five years. It knows that hey, 700 00:39:56,640 --> 00:39:58,359 Speaker 1: he's been hanging onto this for a really long time 701 00:39:58,400 --> 00:40:00,279 Speaker 1: and he only has a small, small amoun out, but 702 00:40:00,600 --> 00:40:02,400 Speaker 1: this guy has a lot of it, and it's been 703 00:40:02,440 --> 00:40:04,120 Speaker 1: sitting for a really long time. So it's kind of 704 00:40:04,120 --> 00:40:06,960 Speaker 1: the days that it's been sitting still, right, And then 705 00:40:07,000 --> 00:40:08,680 Speaker 1: it takes into some sort of a weight at score 706 00:40:08,680 --> 00:40:11,319 Speaker 1: based off of how much I have or how much 707 00:40:11,360 --> 00:40:15,359 Speaker 1: has been sitting in for how long. I'm curious using 708 00:40:15,360 --> 00:40:20,480 Speaker 1: that tool and looking backwards back to November of last year. Um, 709 00:40:20,560 --> 00:40:23,520 Speaker 1: you know, everyone in the market kept saying, oh, we 710 00:40:23,560 --> 00:40:26,960 Speaker 1: need capitulation, We need capitulation. The bottom won't be in 711 00:40:27,800 --> 00:40:31,520 Speaker 1: until we have capitulation. And and that means that there's 712 00:40:31,560 --> 00:40:34,200 Speaker 1: that final just sell off where one she says, all right, enough, 713 00:40:34,280 --> 00:40:38,319 Speaker 1: screw it, I'm out of here right um. And in November, 714 00:40:38,400 --> 00:40:42,560 Speaker 1: after the market had seemingly found its bottom, um in 715 00:40:42,680 --> 00:40:45,520 Speaker 1: November it dropped in half fift I mean it was 716 00:40:45,560 --> 00:40:48,560 Speaker 1: a message of from six thousand and three thousand approximately, 717 00:40:49,360 --> 00:40:51,919 Speaker 1: what did the what did what did that indicator show 718 00:40:52,000 --> 00:40:56,960 Speaker 1: during that time? Do you know so reserved risk? Uh 719 00:40:57,320 --> 00:41:01,479 Speaker 1: you can check it out on the site. Uh that actually, yeah, 720 00:41:01,520 --> 00:41:03,920 Speaker 1: we we just had further down to go. So it 721 00:41:04,120 --> 00:41:08,200 Speaker 1: was the issue around that time was that it was 722 00:41:08,400 --> 00:41:14,000 Speaker 1: price was kind of entering uh over over sould levels. 723 00:41:14,360 --> 00:41:16,200 Speaker 1: And that's why even a lot of the big funds 724 00:41:16,239 --> 00:41:18,719 Speaker 1: we're thinking on maybe the bottoms in, maybe the bottoms in, 725 00:41:19,120 --> 00:41:22,200 Speaker 1: and then the realities we just crashed down even further. Um. 726 00:41:22,239 --> 00:41:25,680 Speaker 1: So yeah, that metric, um, you know, we did go 727 00:41:25,719 --> 00:41:27,759 Speaker 1: down further and it did actually highlight the yeah, the 728 00:41:27,760 --> 00:41:30,719 Speaker 1: bottoms in. Now, I think tools that are even more 729 00:41:30,760 --> 00:41:35,160 Speaker 1: sensitive than that are ones like m v r VS score. 730 00:41:35,680 --> 00:41:38,319 Speaker 1: So that kind of that played out perfectly that and 731 00:41:38,360 --> 00:41:41,640 Speaker 1: that called it perfectly back in November December. Arguably that's 732 00:41:41,640 --> 00:41:45,919 Speaker 1: a more sensitive tool for picking the market bottoms. Um. 733 00:41:46,040 --> 00:41:48,640 Speaker 1: So yeah, going back to our point earlier, you always 734 00:41:48,680 --> 00:41:50,520 Speaker 1: want to be using a range of these tools because 735 00:41:50,560 --> 00:41:54,080 Speaker 1: Bitcoin days destroying that gave you some indication, but actually 736 00:41:54,120 --> 00:41:56,759 Speaker 1: wouldn't it wouldn't have been able to to highlight the 737 00:41:56,760 --> 00:42:01,360 Speaker 1: absolute bottom in that instance. All right, So interesting stuff, 738 00:42:01,520 --> 00:42:06,319 Speaker 1: interesting stuff, and I think, uh, let's move on to 739 00:42:06,400 --> 00:42:09,879 Speaker 1: something else that everybody is dying to know. So being 740 00:42:10,000 --> 00:42:13,600 Speaker 1: someone who studied economic studied market behavior, has been studying 741 00:42:13,600 --> 00:42:16,760 Speaker 1: on chain data, building models, building charts and so forth. 742 00:42:18,360 --> 00:42:23,160 Speaker 1: Just tell us what it means. Where where? Where? Where 743 00:42:23,160 --> 00:42:26,520 Speaker 1: do you think we are in the market cycle? Uh, 744 00:42:26,600 --> 00:42:28,840 Speaker 1: you're the you're the expert here, right Uh. I know 745 00:42:28,880 --> 00:42:30,560 Speaker 1: we used to look at each one individually. What are 746 00:42:30,600 --> 00:42:33,640 Speaker 1: you seeing in the market cycle today? Um? And where 747 00:42:33,680 --> 00:42:36,560 Speaker 1: do you think we are I don't know, twelve months, 748 00:42:36,680 --> 00:42:42,399 Speaker 1: twenty four months, etcetera. Cool? Uh, well, things are looking 749 00:42:42,440 --> 00:42:45,759 Speaker 1: pretty good good right now. I gotta say, you know, 750 00:42:45,840 --> 00:42:47,400 Speaker 1: I mean, if if you've been in the market for 751 00:42:47,400 --> 00:42:50,120 Speaker 1: a couple of years and you're still here like congrass, 752 00:42:50,160 --> 00:42:52,160 Speaker 1: because I think I think we've got some good times 753 00:42:52,160 --> 00:42:55,839 Speaker 1: coming up the next year or two. Um. So yeah. 754 00:42:55,840 --> 00:42:58,000 Speaker 1: I mean one of the childs we talked about earlier 755 00:42:58,040 --> 00:43:01,000 Speaker 1: one was the two and maybe an average multiplier. And 756 00:43:01,560 --> 00:43:03,879 Speaker 1: you know, as we said, we've seen price burst out 757 00:43:03,880 --> 00:43:08,640 Speaker 1: of that accumulation zone and retested, and now we're in 758 00:43:08,800 --> 00:43:12,080 Speaker 1: what I would call the first growth phase of the 759 00:43:12,160 --> 00:43:15,920 Speaker 1: coming bull market, and that is really where we have 760 00:43:16,120 --> 00:43:19,880 Speaker 1: this slow, steady rise. It will feel like a bit 761 00:43:19,920 --> 00:43:23,120 Speaker 1: of a choppy period when we're in it, but typically 762 00:43:23,160 --> 00:43:26,239 Speaker 1: we're grinding up more than we are popping down. They'll 763 00:43:26,239 --> 00:43:28,480 Speaker 1: be the odd little scare along the way. But then 764 00:43:28,520 --> 00:43:30,440 Speaker 1: there's also going to be a couple of big jumps 765 00:43:30,520 --> 00:43:34,120 Speaker 1: up UM and and that that's gonna last probably a 766 00:43:34,200 --> 00:43:37,000 Speaker 1: few months, I would imagine, into the start of next year. 767 00:43:38,239 --> 00:43:41,480 Speaker 1: And then stage two will probably be when we're a 768 00:43:41,560 --> 00:43:46,239 Speaker 1: fair way into UM next year. And if you use 769 00:43:46,320 --> 00:43:48,279 Speaker 1: one of the other tools on the website, actually it's 770 00:43:48,280 --> 00:43:51,839 Speaker 1: called golden ratio multiplier. When price breaks above the red 771 00:43:51,920 --> 00:43:57,000 Speaker 1: line on that chart, that's historically when we've seen Bitcoin 772 00:43:57,160 --> 00:44:01,040 Speaker 1: enter it's more aggressive second growth phase. And that's when 773 00:44:01,080 --> 00:44:04,080 Speaker 1: things get really exciting and people will start kind of 774 00:44:04,239 --> 00:44:06,640 Speaker 1: people from outside and start coming in saying, what the 775 00:44:06,640 --> 00:44:08,319 Speaker 1: hell is all this about? Tell me about it, tell 776 00:44:08,360 --> 00:44:10,080 Speaker 1: me out of by us. That's when we will be 777 00:44:10,120 --> 00:44:13,040 Speaker 1: into that phase. UM. But yeah, I mean so yeah, 778 00:44:13,080 --> 00:44:15,480 Speaker 1: I think I see those two phases coming up. We're 779 00:44:15,560 --> 00:44:17,399 Speaker 1: just in the start of the first phase. I think 780 00:44:17,400 --> 00:44:21,080 Speaker 1: it's gonna last a few more months. I suspect, you know, 781 00:44:21,280 --> 00:44:23,520 Speaker 1: the harving is going to have an impact. We are 782 00:44:23,560 --> 00:44:26,160 Speaker 1: going to see price rise and yeah, well I think 783 00:44:26,440 --> 00:44:29,960 Speaker 1: we'll be above the previous all time high Q one 784 00:44:30,080 --> 00:44:32,279 Speaker 1: Q two next year and then and then we're off 785 00:44:32,280 --> 00:44:37,400 Speaker 1: to the races and then and then obviously and then 786 00:44:37,520 --> 00:44:41,440 Speaker 1: and then obviously you know, we'll have hopefully some indication 787 00:44:41,480 --> 00:44:44,160 Speaker 1: as to when the market starts to top out towards 788 00:44:44,160 --> 00:44:46,719 Speaker 1: the end of that second growth phase, when we see 789 00:44:46,719 --> 00:44:49,480 Speaker 1: it start to see a range of these metrics shown 790 00:44:49,480 --> 00:44:52,000 Speaker 1: over sold, right, a combination of on trained metrics, in 791 00:44:52,080 --> 00:44:55,799 Speaker 1: quest analysis metrics, and you know, I'm sure there'll be 792 00:44:55,920 --> 00:44:58,720 Speaker 1: various sentiment metrics as well when people are going crazier 793 00:44:58,840 --> 00:45:02,319 Speaker 1: out there about to say, well, okay, now is maybe 794 00:45:02,320 --> 00:45:05,400 Speaker 1: a good time take some profit? Yeah. You know. The 795 00:45:05,440 --> 00:45:07,120 Speaker 1: one thing that I always trying to impress on people 796 00:45:07,239 --> 00:45:09,640 Speaker 1: with trying to do any kind of forecast. I don't 797 00:45:09,680 --> 00:45:11,680 Speaker 1: like to call them forecasts, I mean their guesses, right, 798 00:45:12,239 --> 00:45:15,040 Speaker 1: I like to talk about them in probabilities. Um, so 799 00:45:15,280 --> 00:45:17,440 Speaker 1: if this happens, then this happens kind of thing, and 800 00:45:17,480 --> 00:45:19,440 Speaker 1: so um. The one thing to keep in mind is 801 00:45:19,520 --> 00:45:21,440 Speaker 1: kind of what you're saying, You're not trying to project 802 00:45:21,480 --> 00:45:23,799 Speaker 1: when the next top is. Um, it's more like, hey, 803 00:45:23,840 --> 00:45:25,399 Speaker 1: let's keep an eye on the indicators and it will 804 00:45:25,440 --> 00:45:28,239 Speaker 1: tell us. So it's something that should be managed or 805 00:45:28,640 --> 00:45:31,440 Speaker 1: monitored right and watched. And it's kind of like driving 806 00:45:31,440 --> 00:45:33,080 Speaker 1: a car, right, you can't just close your eyes and 807 00:45:33,080 --> 00:45:34,640 Speaker 1: open when you get there. You need to be watching 808 00:45:34,640 --> 00:45:37,239 Speaker 1: the signs along the way exactly, and you want to 809 00:45:37,280 --> 00:45:39,400 Speaker 1: be managing your risk along the way as well. Right, 810 00:45:39,360 --> 00:45:42,279 Speaker 1: It's so important, Like even if if if what I 811 00:45:42,400 --> 00:45:45,040 Speaker 1: just described plays are then like you say, it might 812 00:45:45,080 --> 00:45:49,000 Speaker 1: do might not. Um, there's there's a decent chance it won't, right, 813 00:45:49,080 --> 00:45:52,080 Speaker 1: and so always be managing your race. Take some profit, 814 00:45:52,520 --> 00:45:54,520 Speaker 1: leaves to fight another day, man, because you know this, 815 00:45:54,640 --> 00:45:58,040 Speaker 1: this this market should be around for a while. So 816 00:45:58,120 --> 00:46:03,480 Speaker 1: always take some profit, managing risk and um yeah, enjoy it. Yeah, 817 00:46:03,520 --> 00:46:06,520 Speaker 1: switching gears just a minute. Um, Now, are you're over 818 00:46:06,600 --> 00:46:09,960 Speaker 1: in England? Is that right? I am? Yeah, yeah, you 819 00:46:09,960 --> 00:46:11,759 Speaker 1: can probably tell from the accident. I'm not from your 820 00:46:11,800 --> 00:46:14,600 Speaker 1: neck of the woods. I'm based in London in the UK. 821 00:46:14,840 --> 00:46:18,440 Speaker 1: What what do you what? You're just what what are 822 00:46:18,440 --> 00:46:21,840 Speaker 1: you picking up? As like market sentiment? Like what are 823 00:46:21,920 --> 00:46:24,960 Speaker 1: what are people thinking? What are what are people? Are? 824 00:46:24,960 --> 00:46:28,319 Speaker 1: Are people actually buying it? Young people? Old people? What 825 00:46:28,360 --> 00:46:30,880 Speaker 1: are um? You know, what are the stores thinking? What 826 00:46:31,320 --> 00:46:34,720 Speaker 1: is the government thinking? Give us an analysis for England 827 00:46:34,760 --> 00:46:37,840 Speaker 1: and maybe even what you're picking up in Europe? Sure 828 00:46:38,800 --> 00:46:40,879 Speaker 1: you're in the market psychology. You know, I would say 829 00:46:41,600 --> 00:46:45,799 Speaker 1: it's it's kind of it's really sleepy right in terms 830 00:46:45,880 --> 00:46:48,560 Speaker 1: if if I'm trying to gauge general market sentiments, I'm 831 00:46:48,560 --> 00:46:50,440 Speaker 1: not talking about people who are in crypto right now. 832 00:46:50,480 --> 00:46:55,000 Speaker 1: I'm talking about general market sentiment towards crypto. It's it's 833 00:46:55,120 --> 00:46:57,680 Speaker 1: super sleepy. I mean the same we are price wise, 834 00:46:57,719 --> 00:47:01,719 Speaker 1: where we are, you know, around ten thousand dollars um. Yeah, 835 00:47:01,800 --> 00:47:04,000 Speaker 1: interest just isn't there. People are, People are far more 836 00:47:04,040 --> 00:47:06,080 Speaker 1: interested in other things at the moment right Brexit is 837 00:47:06,080 --> 00:47:09,480 Speaker 1: obviously a huge talking point here. Just got a general 838 00:47:09,480 --> 00:47:12,320 Speaker 1: election coming up. That is what everyone is focused on it, 839 00:47:12,440 --> 00:47:16,319 Speaker 1: and you know, the issues behind that may you know, 840 00:47:18,000 --> 00:47:20,879 Speaker 1: drive a need for bitcoin for the majority, like further 841 00:47:20,920 --> 00:47:23,480 Speaker 1: down the line, but right now everyone's focused on on 842 00:47:23,480 --> 00:47:26,719 Speaker 1: on those issues, and I don't think people like kind 843 00:47:26,719 --> 00:47:30,640 Speaker 1: of Joe Public, it's really going to pay much attention 844 00:47:30,960 --> 00:47:34,120 Speaker 1: towards bitcoin until we are past the previous all time high. 845 00:47:34,160 --> 00:47:37,480 Speaker 1: So I think once we're above twenty k thirty k, 846 00:47:37,760 --> 00:47:39,759 Speaker 1: I think that's when it's going to start turning heads 847 00:47:39,800 --> 00:47:42,360 Speaker 1: again and when people will start to get interested. So 848 00:47:42,400 --> 00:47:46,759 Speaker 1: that's that's general public. I actually know I have some 849 00:47:46,920 --> 00:47:51,960 Speaker 1: friends who work in traditional finance and work for some 850 00:47:52,040 --> 00:47:55,560 Speaker 1: pretty big funds, traditional hedge funds, and so I talked 851 00:47:55,560 --> 00:47:57,640 Speaker 1: to them time to time kind of say how, you know, 852 00:47:57,640 --> 00:47:59,160 Speaker 1: asked them how their stuffs go, and ask me how 853 00:47:59,200 --> 00:48:03,239 Speaker 1: my stuffs going, and it's it's you know, it's interesting 854 00:48:03,239 --> 00:48:06,839 Speaker 1: to see their level of interesting Bitcoin, and I would 855 00:48:07,200 --> 00:48:10,480 Speaker 1: I would say it's still absolutely minimal, absolutely minimal. It's 856 00:48:10,520 --> 00:48:13,160 Speaker 1: it's not like you know, I think, because we we 857 00:48:13,280 --> 00:48:15,560 Speaker 1: live and breathing stuff every day, we think, oh, you know, 858 00:48:16,040 --> 00:48:17,680 Speaker 1: everyone's going to be in, like you know, in the 859 00:48:17,680 --> 00:48:21,560 Speaker 1: next few weeks, you know, when government's lower interest rates 860 00:48:21,560 --> 00:48:23,600 Speaker 1: by a court percent, then you know the big institution 861 00:48:23,640 --> 00:48:25,400 Speaker 1: is going to come in. I still think most of 862 00:48:25,440 --> 00:48:27,879 Speaker 1: the institutions are a long way off. And the reason, 863 00:48:27,960 --> 00:48:30,200 Speaker 1: the reason why is a lot of it is not 864 00:48:30,280 --> 00:48:33,200 Speaker 1: because they don't see the potential. Most of the reason 865 00:48:33,320 --> 00:48:36,080 Speaker 1: is because it's so tiny that they can't pay attention 866 00:48:36,080 --> 00:48:39,920 Speaker 1: to it. So that stuff in the you know, hundreds 867 00:48:39,920 --> 00:48:43,480 Speaker 1: of billions or even trillions of dollars markets and so 868 00:48:43,640 --> 00:48:45,799 Speaker 1: something with a hundred billion dollar market cap is just 869 00:48:45,840 --> 00:48:48,000 Speaker 1: too small for them. They can't they can't, they can't 870 00:48:48,080 --> 00:48:50,239 Speaker 1: move in enough or out. So I think there's a 871 00:48:50,320 --> 00:48:54,040 Speaker 1: lot of it there. UM. I'm curious though, because you know, 872 00:48:54,080 --> 00:48:57,279 Speaker 1: understanding the macroeconomic, the market cycle is happening in a 873 00:48:57,280 --> 00:48:59,520 Speaker 1: lot of countries is super important, so I study them 874 00:48:59,520 --> 00:49:01,759 Speaker 1: a lot. And and you said Brexit is at the 875 00:49:01,800 --> 00:49:06,440 Speaker 1: top of everyone's conversation. Um. Are people worried about the 876 00:49:06,560 --> 00:49:09,480 Speaker 1: damage that Brexit is going to cause to um? I 877 00:49:09,520 --> 00:49:12,000 Speaker 1: mean obviously a lot of damage to trade and whatnot, 878 00:49:12,040 --> 00:49:15,560 Speaker 1: but even just the currency, just your money, uh, witching 879 00:49:15,640 --> 00:49:18,000 Speaker 1: from the Euro back to the Sterling, and what's going 880 00:49:18,040 --> 00:49:20,080 Speaker 1: to happen with the money? I mean, does anybody think 881 00:49:20,120 --> 00:49:22,360 Speaker 1: about that? Or what are they what are they worried about? 882 00:49:23,760 --> 00:49:27,840 Speaker 1: I mean, I think again going back to Joe Public, 883 00:49:27,880 --> 00:49:32,360 Speaker 1: that they're they're all concerned about, uh, what does it 884 00:49:32,400 --> 00:49:36,000 Speaker 1: mean in terms of job prospects? And also what does 885 00:49:36,040 --> 00:49:38,600 Speaker 1: it mean in terms of our relationships with other market 886 00:49:38,640 --> 00:49:43,000 Speaker 1: with with other countries the trade right, in terms of trade, uh, 887 00:49:43,120 --> 00:49:45,040 Speaker 1: and also in terms of you know, I think people 888 00:49:45,080 --> 00:49:48,480 Speaker 1: who want to remain in Europe, they're quite fearful around 889 00:49:48,480 --> 00:49:50,759 Speaker 1: what does it mean socially in terms of how we 890 00:49:50,840 --> 00:49:55,359 Speaker 1: interact with other democratic markets and countries and cultures like 891 00:49:55,440 --> 00:49:57,120 Speaker 1: you know, those of you have in Europe. So I 892 00:49:57,120 --> 00:49:59,280 Speaker 1: think those are some of the concerns for most people. 893 00:49:59,840 --> 00:50:02,520 Speaker 1: M But you right, you obsolutely right. While so this 894 00:50:02,719 --> 00:50:05,359 Speaker 1: is going going, you know, the time is being devalued, 895 00:50:05,719 --> 00:50:08,960 Speaker 1: and he's allowing needs to continue whilst there's all this uncertainty, 896 00:50:09,000 --> 00:50:12,160 Speaker 1: and obviously people in traditional finds are much more concerned 897 00:50:12,200 --> 00:50:15,480 Speaker 1: about that. Yeah, you know, Um, it's unfortunate. And I'm 898 00:50:15,520 --> 00:50:18,080 Speaker 1: I'm imagining all over the world and and probably the 899 00:50:18,080 --> 00:50:20,279 Speaker 1: same in England as it is in the US is 900 00:50:20,520 --> 00:50:23,480 Speaker 1: they don't teach anybody about money, and I think almost 901 00:50:23,480 --> 00:50:25,720 Speaker 1: purposely right, they don't want you to know about money, 902 00:50:25,800 --> 00:50:29,480 Speaker 1: banking and whatnot. And actually, Henry Ford, the godfather of 903 00:50:29,520 --> 00:50:32,680 Speaker 1: the you know, automobile assembly line whatever, he was famously 904 00:50:32,760 --> 00:50:34,759 Speaker 1: quoted back in the early nineteen hundred saying that if 905 00:50:34,760 --> 00:50:37,120 Speaker 1: the average person understood the banking system, there would be 906 00:50:37,120 --> 00:50:40,600 Speaker 1: a revolution overnight. That was back then. Imagine how much 907 00:50:40,640 --> 00:50:44,920 Speaker 1: it's worse, how much worse it's gotten over a hundred years. Dalio, 908 00:50:45,080 --> 00:50:47,600 Speaker 1: who's one of the biggest fund managers in the world, 909 00:50:47,760 --> 00:50:51,120 Speaker 1: Bridgewater Capital, doing the dollars, he's been pretty outspoken recently 910 00:50:51,160 --> 00:50:54,560 Speaker 1: and I just retweeted one of he put out a 911 00:50:54,560 --> 00:50:58,680 Speaker 1: new paper yesterday and uh, quote from Ray Dalio said, 912 00:50:58,840 --> 00:51:00,439 Speaker 1: well that the name of the title is the world 913 00:51:00,480 --> 00:51:03,400 Speaker 1: has gone mad and the system is broken. Um and 914 00:51:03,440 --> 00:51:08,080 Speaker 1: he says, quote, money is almost free for those who 915 00:51:08,120 --> 00:51:11,319 Speaker 1: have money and credit worthiness. It is unavailable to those 916 00:51:11,360 --> 00:51:14,600 Speaker 1: who don't have money and credit worthiness. This contributes to 917 00:51:14,640 --> 00:51:18,560 Speaker 1: the rising wealth opportunity and political gaps, and everyone's mad 918 00:51:18,600 --> 00:51:21,520 Speaker 1: about the rich getting richer, and and in the US 919 00:51:21,600 --> 00:51:23,960 Speaker 1: we have Bernie Standers calling out to make billionaires being 920 00:51:24,000 --> 00:51:29,000 Speaker 1: illegal and right, and so everyone's kind of missing it 921 00:51:29,120 --> 00:51:32,080 Speaker 1: that the banks are ruining the money and that is 922 00:51:32,120 --> 00:51:34,680 Speaker 1: what's causing your purchasing power to fall and whatnot. So 923 00:51:34,960 --> 00:51:37,160 Speaker 1: that's what I was just curious. I mean, with Brexit happening, 924 00:51:37,440 --> 00:51:40,560 Speaker 1: there's a real risk of what can happen with your money, 925 00:51:40,719 --> 00:51:42,840 Speaker 1: both both the Sterling if you go back to that, 926 00:51:43,000 --> 00:51:45,680 Speaker 1: or the Euro. But probably I guess, as you're saying, 927 00:51:45,680 --> 00:51:49,759 Speaker 1: probably nobody knows that nobody's paying attention to that. Yeah, unfortunately, 928 00:51:49,760 --> 00:51:53,720 Speaker 1: not right, And I think people won't really start thinking 929 00:51:53,719 --> 00:51:57,759 Speaker 1: about it until they really really really have to, kind 930 00:51:57,760 --> 00:52:00,680 Speaker 1: of when it's almost becoming too late and you know 931 00:52:00,719 --> 00:52:03,960 Speaker 1: you're you're seeing that pop up around various countries around 932 00:52:04,000 --> 00:52:10,239 Speaker 1: the world. Right, all these issues like in Lebanon, Chile, Venezuela, Turkey, 933 00:52:10,280 --> 00:52:12,240 Speaker 1: you know, the least is just getting longer and longer 934 00:52:12,280 --> 00:52:17,239 Speaker 1: and longer. Um. All these issues in terms of government debt, um, 935 00:52:17,280 --> 00:52:21,600 Speaker 1: managing like I mentioned that, in monetary fiscal policies, um. 936 00:52:21,920 --> 00:52:25,240 Speaker 1: And yet just how wealthy and quality gaps. It's really 937 00:52:25,239 --> 00:52:27,960 Speaker 1: concerning in terms of the growth rate of a lot 938 00:52:28,000 --> 00:52:30,960 Speaker 1: of that stuff. Cool. Well, we won't get too far 939 00:52:31,000 --> 00:52:32,400 Speaker 1: into that. I just like to get a boots on 940 00:52:32,440 --> 00:52:35,040 Speaker 1: the ground viewpoint, especially with someone with your background of 941 00:52:35,120 --> 00:52:39,480 Speaker 1: market psychologies and whatnot. So I appreciate you jumping into that. 942 00:52:39,480 --> 00:52:41,480 Speaker 1: That ended the pool with me just for a little bit. 943 00:52:42,360 --> 00:52:46,480 Speaker 1: But all really really good, good information. I love these indicators. 944 00:52:46,520 --> 00:52:49,719 Speaker 1: I love having more tools at my disposal to put 945 00:52:49,760 --> 00:52:54,040 Speaker 1: all this together. Um, where can people learn more about 946 00:52:54,160 --> 00:52:58,120 Speaker 1: you and your work and follow you well? And you 947 00:52:58,200 --> 00:53:01,080 Speaker 1: can head to look into big line dot com to 948 00:53:01,400 --> 00:53:03,759 Speaker 1: check out all the live dates charts and there's a 949 00:53:03,800 --> 00:53:06,839 Speaker 1: whole bunch of learning materials there as well. Um, if 950 00:53:06,840 --> 00:53:09,640 Speaker 1: you're kind of new to that sort of stuff and 951 00:53:09,760 --> 00:53:13,080 Speaker 1: it's all tightly free, go and check it. Out and 952 00:53:13,120 --> 00:53:16,359 Speaker 1: then if people want to follow me on Twitter because 953 00:53:16,520 --> 00:53:18,839 Speaker 1: I tweet out a lot of my sort of analysis 954 00:53:19,080 --> 00:53:25,719 Speaker 1: on there, you can search at positive Crypto um. But 955 00:53:25,880 --> 00:53:28,239 Speaker 1: my name is Philip Swift, so you can probably find 956 00:53:28,239 --> 00:53:32,840 Speaker 1: me either way. I'm on there. Cool. Well, Philip, I 957 00:53:32,880 --> 00:53:34,880 Speaker 1: appreciate you taking the time to talk today. It was 958 00:53:35,200 --> 00:53:38,600 Speaker 1: it was awesome and hopefull everybody enjoyed it. Thanks very much. 959 00:53:38,600 --> 00:53:42,920 Speaker 1: Has been an absolute pleasure. Okay, hey, if you like 960 00:53:43,080 --> 00:53:46,680 Speaker 1: this episode of the Market Disruptors podcast, please help us 961 00:53:46,680 --> 00:53:49,200 Speaker 1: take this to the top of the podcast charts. Just 962 00:53:49,200 --> 00:53:52,279 Speaker 1: please do me a favor and rate, review and subscribe. 963 00:53:52,480 --> 00:53:55,239 Speaker 1: Taking fifteen seconds to just leave a quick review goes 964 00:53:55,280 --> 00:53:57,680 Speaker 1: a long way in helping us reach more people and 965 00:53:57,719 --> 00:54:00,839 Speaker 1: disrupt more markets. I really appreciate you listening and I'll 966 00:54:00,840 --> 00:54:03,240 Speaker 1: see you next time on the Market Instructors Podcast