Speaker 1: So the big question is this, how do investors like
Speaker 1: us get access to the ideas, information, and most importantly,
Speaker 1: the right people that give us the tools and information
Speaker 1: we need to make conformed and educated decisions to have success.
Speaker 1: That is the question, and this podcast will give us
Speaker 1: the answers. This is Mark Moss, your host. Let's get
Speaker 1: this started. Everyone, Welcome to another episode of the Market
Speaker 1: Disruptors podcast. Today I am joined by Philip Swift and
Speaker 1: we are going to be talking about bitcoin on chain analytics,
Speaker 1: what they're looking like, how we can look at them,
Speaker 1: and what they tell us. Uh, super super interesting conversations
Speaker 1: that I've already had. I can't wait to jump in.
Speaker 1: So Philip, welcome to the show. Hey man, thanks very
Speaker 1: much for having me on the show. It's great to
Speaker 1: be here. And yeah, things are looking good at the
Speaker 1: market right now and it's great chatsy great right. So,
Speaker 1: you know, I know we've had some conversations. I've been
Speaker 1: watching some of the work that you've been doing UM
Speaker 1: online and on your website. But for those that don't know,
Speaker 1: why don't you just kind of fill us in on
Speaker 1: UM you know who, what you've been doing, how you
Speaker 1: got here, and what you're doing right now. Cool, thank you.
Speaker 1: So I am a full time bitcoin trader and investor.
Speaker 1: I have been for about two and a half years now,
Speaker 1: very passionate about bitcoin for a number of reasons, so
Speaker 1: not only from an investment opportunity, but also I believe
Speaker 1: it's probably one of the most important tools for human
Speaker 1: rights in the world right now in the coming years,
Speaker 1: as we see governments have more and more issues with
Speaker 1: their monetary and physical policies. Um. So yeah, full time trader, investor.
Speaker 1: But in addition to that, I also build valuation models
Speaker 1: for bitcoin, so indicators and tools that helped to identify
Speaker 1: when bitcoin is under or values. That's a pretty new
Speaker 1: and emerging space within bitcoin. It's probably been in existence
Speaker 1: for a couple of years now because obviously bitcoin itself
Speaker 1: is only ten coming up to eleven years old, so
Speaker 1: we haven't really had enough data until recently to be
Speaker 1: able to start to build valuation models for bitcoin. And
Speaker 1: because it's a unique asset class, so it has characteristics
Speaker 1: that are quite different to traditional finance instruments. Um, you
Speaker 1: can't use tools from the transitional finance world and just
Speaker 1: try and directly apply them to bitcoins, try and value
Speaker 1: it so you can't. So in traditional finance, for stocks
Speaker 1: and shares, you have things like price to earnings ratios
Speaker 1: and discarded cash flows. You can't really apply those to bitcoin.
Speaker 1: But what we can do is try and come up
Speaker 1: with some new tools and metrics to understand when bitcoin
Speaker 1: is under or overvalued. And that's what I do, and
Speaker 1: I launched, as you mentioned, a website last month called
Speaker 1: looking too bitcoin dot com and that has a hard
Speaker 1: bunch of these different valuation models and tools all for
Speaker 1: for uh choy to make them as user friendly and
Speaker 1: nice to look at as possible and kind of live
Speaker 1: chart data form. And yeah, it's all free and one
Speaker 1: can go and check them out. Yeah. Now, as you said, right,
Speaker 1: like typically when we're looking at trying to value financial
Speaker 1: stocks and we look at fundamentals, and the fundamentals are
Speaker 1: kind of like what you said, right, which are earnings
Speaker 1: ratios and things like that. Um, and a lot of
Speaker 1: people have always criticized cryptocurrencies because they don't have those fundamentals.
Speaker 1: You're talking about looking at different metrics that can give
Speaker 1: us the fundamentals because they're different, right, I get that,
Speaker 1: But um, that's an interesting way to look at it
Speaker 1: and I'm just curious. I I kind of know, but
Speaker 1: why don't you fill us in a little bit on
Speaker 1: your background and how maybe what shaped you? How did
Speaker 1: you get to the point to start looking at like this. Yes,
Speaker 1: so my book is probably a little bit different to
Speaker 1: a lot of other traders and investors in the space.
Speaker 1: Um So, I studied economics university, uh which was great
Speaker 1: in terms of giving me a good grounding in terms
Speaker 1: of how markets work. Um some macro principles around economics
Speaker 1: and maths. But like I think many of the people
Speaker 1: who studied economics, you kind of get to the end
Speaker 1: of it and think, man, this is so theoretical you
Speaker 1: kind of want to throw all your textbooks out of the
Speaker 1: the window because it's quite hard to apply a lot
Speaker 1: of it to the real world. So I kind of
Speaker 1: left university feeling a little bit jaded, but I was
Speaker 1: still very interested in the behavior economic side of things,
Speaker 1: so understanding what makes markets work. And so I then
Speaker 1: got a career actually working for major global dricks brands,
Speaker 1: uh so, companies that own brands like Jack Daniels, Gray,
Speaker 1: Goose Bug, Hendrix, gen Ster, Artoire. So if you like
Speaker 1: a drink, you've probably had one of those brands, Um,
Speaker 1: and I. She works in a unit within these companies
Speaker 1: which was really a strategic marketing function of thoughts. And
Speaker 1: unless you work for one of these big companies, you
Speaker 1: probably don't realize that these functions even exist. It's called
Speaker 1: Consumer Insight team and the role of these guys is
Speaker 1: to understand the psychology of your potential consumers and your consumers, right,
Speaker 1: so you're you're trying to segment them, understand their reasons
Speaker 1: for choosing your brand or for not choosing your brand.
Speaker 1: And that goes beyond just why they think about the sector.
Speaker 1: It's around their hopes and dreams and their fears and
Speaker 1: all that sort of stuff. So it deep goes quite
Speaker 1: deep in terms of market psychology. And really that's how
Speaker 1: these brands get so big is because they have a
Speaker 1: very sophisticated understanding of market psychology. Now, if I can
Speaker 1: just jump in at the rate there real quick. So, Um,
Speaker 1: you studied market psychology working for the big brands, and
Speaker 1: the economics was also um, trying to understand what markets
Speaker 1: are market psychology, you said, what makes markets work? Right? Yeah,
Speaker 1: I'm curious. Um, you said that a lot of is theoretical,
Speaker 1: which I think that theoretical part probably helps you today
Speaker 1: because trying to new ways to capture analytics, you have
Speaker 1: to be theoretical. I'm curious though, Uh, you know, from
Speaker 1: everyone that I've talked to, I didn't major in economics,
Speaker 1: but I I know a lot of people who did,
Speaker 1: and uh, you know they do not teach Austrian economics,
Speaker 1: which everybody basically ends up at after they've been studying bitcoin.
Speaker 1: It seems like yea, and sometimes the university training you
Speaker 1: had can can keep you from really understanding bitcoin because
Speaker 1: you've been trained maybe with blinders on right, And you said,
Speaker 1: what makes markets work? And it seems like what whatever
Speaker 1: you wanna call it, traditional or conventional economics versus like
Speaker 1: an Austrian is that traditional find economics thinks the market
Speaker 1: is something too understand how it works and manage and
Speaker 1: and and manipulate, versus Austroan economics understands that there is
Speaker 1: no such thing as a market. All we have as
Speaker 1: individuals wants, needs and desires. Yeah, what do you think
Speaker 1: about that? And and how does that relate to studying
Speaker 1: the market, especially for a brand? Yeah, I mean I
Speaker 1: think I think that's a that's a fair summary, and
Speaker 1: I think a lot of frustrations come from, uh, the
Speaker 1: need if you if you were trying to focus in
Speaker 1: on a specific area, you have to make compromises and sacrifices.
Speaker 1: And often in economics the compromises and sacrifices around are
Speaker 1: around uh, recognizing that or that we're not recognizing that
Speaker 1: we are all emotional beasts right where you have emotions,
Speaker 1: we're not rational players. And as soon as you start
Speaker 1: to assume that we're rational players, then then you start
Speaker 1: to lose understanding of how how the markets move and
Speaker 1: how the more his work. So that's why I think
Speaker 1: behavior economics is so much more relevant, particularly to the
Speaker 1: world room today, and particularly to assets like bitcoin, which
Speaker 1: are very retail market driven. So you have therefore, you know,
Speaker 1: to your point, millions of individuals, all with their own emotions,
Speaker 1: and when they are trying to determine what they should
Speaker 1: do with their investments, they are often can be lit
Speaker 1: by consensus. It's kind of like it's kind of like, um,
Speaker 1: you say they're not rational, which I kind of agree.
Speaker 1: Misses from Austrian school. He says that, um, it's always rational.
Speaker 1: So I might look like I'm acting irrationally, but it's
Speaker 1: rational to me because I have my own set of circumstances.
Speaker 1: So even though bitcoin is gonna go to a million
Speaker 1: dollars next year, I might sell it today for no
Speaker 1: reason that looks irround national, but maybe my kid got
Speaker 1: sick any of the money, right, So there's always national
Speaker 1: to me. But you can't manage that because it's millions
Speaker 1: of inputs exactly. And that's really a point around context, right,
Speaker 1: which which going back to my previous employment, that that's
Speaker 1: something we focused on a lot. You have to understand
Speaker 1: people's context to really understand if you want to fully
Speaker 1: understand their decision making process. But yeah, super interesting stuff. Yeah, anyway, Okay,
Speaker 1: so your understanding market psychology, I think, like we said,
Speaker 1: like the I think I could I could imagine that
Speaker 1: the theory that you've learned in in economic school probably
Speaker 1: helped you to start theorizing what kind of new metrics
Speaker 1: we could look at in bitcoint. Yeah, yeah, absolutely, And
Speaker 1: really is the combination the two, right, So you have
Speaker 1: economic theory plus market psychology, and for a market like bitcoin,
Speaker 1: that that is very useful because what we're seeing is
Speaker 1: bigcoin is going through an adoption process, and on top
Speaker 1: of that adoption process we have market cycles, and so
Speaker 1: combining those two fields has been very useful um to
Speaker 1: me as as a training investor in to try and
Speaker 1: build some of these these valuation tools as well. A
Speaker 1: couple of years. Yeah, so then you started trading bitcoin
Speaker 1: on your own, and then you started realizing that we
Speaker 1: don't really have any good metrics, and so you've decided
Speaker 1: to dig in and started to try to see what
Speaker 1: was available and what else you could come up with. Yeah, yeah,
Speaker 1: that's right. So I've been trading for probably a couple
Speaker 1: of years and that was all going well, but I
Speaker 1: found that I wasn't really that passionate about becoming a
Speaker 1: super techy technical analysis geek, and I was more drawn
Speaker 1: to understanding the macro cycles of a bitcoin. And I
Speaker 1: started playing around with different types of data, one of
Speaker 1: which was someone chained data. So I was on, you know,
Speaker 1: using sites like blockchain dot info which posts some pretty
Speaker 1: basic on chain data, and probably late two thousand and seventeen,
Speaker 1: I think, and I started to notice that on a
Speaker 1: macro level, there was a relationship between volume running through
Speaker 1: the blockchain on a daily basis and then also bitcoin price. So, uh,
Speaker 1: when volume through the blockchain was hitting sufficient levels. It
Speaker 1: was kind of a leading indicator to price moving up.
Speaker 1: And um, I posted a chart on it on Twitter,
Speaker 1: I think on tone vases Twitter channel, and a guy
Speaker 1: called Willie Woo, who I imagine a lot of your
Speaker 1: viewers have probably heard of. Willy Woo is like probably
Speaker 1: the godfather of on chain analysis. He's pretty amazing and
Speaker 1: I've learned a huge tone of stuff from him over
Speaker 1: over the years. And he picked it up and he
Speaker 1: was like, hey, you love this view. I hadn't seen
Speaker 1: it before. I'd like to put it on my site
Speaker 1: and you should write a pay for about it. And
Speaker 1: so I did a called it Bitcoin network Momentum, and yeah,
Speaker 1: it kind of so I probably at the time like
Speaker 1: the first and followers on Twitter or something, and then
Speaker 1: within a week I had like two thousand followers stars like, Okay,
Speaker 1: clearly there's some interest in this, you know, clearly people
Speaker 1: are interested in this sort of analysis. And then it
Speaker 1: really went from there, you know, because I then just
Speaker 1: started speaking to other people who are also looking at
Speaker 1: this sort of analysis and trying to build these types
Speaker 1: of indicators, and and then yeah, and that that whole
Speaker 1: space now of valuing bitcoin is really exploded. And now
Speaker 1: it is like you know, crypto funds with teams of
Speaker 1: guys doing this types of analysis. So it's just going
Speaker 1: to get bigger and bigger. So let's let's talk about that.
Speaker 1: So first of all, um, you talk about on chain
Speaker 1: data and indicators to help us understand bitcoin and maybe
Speaker 1: identify where bitcoin is going. So what are what are
Speaker 1: the indicators? What I mean and not specifically, but what
Speaker 1: is generally? What is an indicator? What does that mean
Speaker 1: to the average person? So an indicator area is really
Speaker 1: so as an investor in its most simple form, as
Speaker 1: an investor, a long term investor. So we're not talking
Speaker 1: about trade short term trading here. I want to know
Speaker 1: when is a good time for me to buy? When
Speaker 1: is a good time for me to sell? And these
Speaker 1: indicators show you on a historical level. So looking back
Speaker 1: in bitcoins history, um, you know when this bitcoin being
Speaker 1: extremely over oversold or other board and therefore when is
Speaker 1: it When is a good time for me to buy ourselves?
Speaker 1: And that's pretty much it. You know, when you dig
Speaker 1: into the side, is a bit more there, but in
Speaker 1: its essence, that's kind of it really. So it's you're
Speaker 1: looking through data and basically it gives it tells you something.
Speaker 1: That's the indicator, and it's indicating here I should either
Speaker 1: buy or its indicating aations maybe sell or I should
Speaker 1: watch it. And then you also talked about using on
Speaker 1: chain data, So what does that mean? What what what
Speaker 1: is on chain data? So on chain data is essentially
Speaker 1: transactions that happened on the blockchain. So if you send
Speaker 1: me some bitcoin tomorrow, which is more than welcome to
Speaker 1: do it, will you know, have most your public address
Speaker 1: there You're right, that will be recorded on the blockchain.
Speaker 1: And that has happened ever since bitcoin started, and so
Speaker 1: there is a huge amount of data available on the
Speaker 1: blockchain to look at in terms of size of transactions,
Speaker 1: the time that the transaction took place, the wallets that
Speaker 1: it moved from, and too. And so you can use
Speaker 1: that data and aggregated level to look at trends over
Speaker 1: time really and those trends can give you clues as
Speaker 1: we alluded to, as to when bitcoin is sold or
Speaker 1: overbought and therefore what as you should action You could
Speaker 1: take it as an investor. Yeah, I want to jump
Speaker 1: into some of the indicators and tools, and so we'll
Speaker 1: talk specifically about some of the arm chained data, because
Speaker 1: I know there's a ton of n chained data. And
Speaker 1: it's curious though, um you mentioned, um look at macro
Speaker 1: cycles and and and having them be like leading indicators.
Speaker 1: And I know one that has been used for for
Speaker 1: many years was Google search data, and that's not on
Speaker 1: chaine data. I understand what people would look at like
Speaker 1: Google search and you could see how the volume of
Speaker 1: bitcoin being searched on Google correlated with the price of bitcoin. Yeah,
Speaker 1: and you know a lot of people think that's a
Speaker 1: leading indicator. I've often thought it was a lagging indicator.
Speaker 1: So leading means that, um, it tells us before the
Speaker 1: move happens, and lagging tells us it happens after. And
Speaker 1: it's kind of like a chicken or the egg argument
Speaker 1: where um, because the bitcoin price went from seven thousand
Speaker 1: to twenty thousand, everybody's searching it to figure out what
Speaker 1: the heck it is that that would be after or
Speaker 1: are they searching it and then they buy, which then
Speaker 1: is a leading What do you think? Uh? So, I
Speaker 1: have some friends You've done a fair beatter than analysis
Speaker 1: on that, and the conclusion is that it's a pretty
Speaker 1: lagging indicator. Actually, So I wouldn't. I wouldn't put too
Speaker 1: much weight on it. Um. But you know, as with
Speaker 1: there any of these things, right, it's just one tool,
Speaker 1: and and it's something I talk about a lot, is
Speaker 1: how even all the charts I'm looking to bitcoin. I mean,
Speaker 1: the purpose of the site is really to help regular people,
Speaker 1: not just large institutions, invest better in bitcoin. And it
Speaker 1: does despite providing a range of tools, because I believe
Speaker 1: that you shouldn't just try and hang your hat on
Speaker 1: one metric. You've got to use a range of tools,
Speaker 1: whether it's these sorts of indicators, whether it's technical analysis,
Speaker 1: Google search trends to kind of join the dots and
Speaker 1: build up your thesis. So definitely, So yeah, I think
Speaker 1: it is a bit of a lugging an indicator. But yeah, sure,
Speaker 1: all this stuff confused, so you think you think there's
Speaker 1: other on chain data that is more of a leading indicator.
Speaker 1: So you think there is some good stuff without getting
Speaker 1: to the specifics of the actual specific indicators you have.
Speaker 1: I mean, there are a couple of metrics that you
Speaker 1: think could be good as leading. Yes, so I think
Speaker 1: you can look at well, well we'll come on to
Speaker 1: talk about them. But yeah, so on chained data specifically
Speaker 1: like Bitcoin days destroyed. Uh that that is very useful
Speaker 1: in terms of looking at um all guys who have
Speaker 1: helped the kind of a long amount of time, like
Speaker 1: are they are they moving funds from there? While it's
Speaker 1: that can give you clues, essentially, you're constantly looking for
Speaker 1: clues and hints as to what may be coming in
Speaker 1: the market and so on. Chained data can do that,
Speaker 1: but so can actually UM like price analysis analysis. So
Speaker 1: you know, half the charts on the site are looking
Speaker 1: at price data using moving averages to show you the
Speaker 1: broad trend of the market where and whether we get
Speaker 1: to points where the market might get ourtherheated or whereveryone
Speaker 1: might actually be very fearful, you know, because a large
Speaker 1: part about understanding the bitcoin market from an investment point
Speaker 1: of view is about understanding it's market cycles. So it's
Speaker 1: about understanding when is the general consensus of market participants,
Speaker 1: When are they broadly over optimistic and that might be
Speaker 1: a good time to take some profit of the table,
Speaker 1: and when are they overly pessimistic? You know, when is
Speaker 1: everyone really fearful? I think what is it? Warren Buffett,
Speaker 1: he said, you know, be greedy when everyone else is fearful. Right,
Speaker 1: If you fundamentally believe in the long term prospects of
Speaker 1: big point, then I'm being able to identify those periods
Speaker 1: can be very valuable to use an investor intend to
Speaker 1: know when to invest. Yeah, and so um, somehow the
Speaker 1: data can tell us when it's overpriced or when the
Speaker 1: market psychology, the market as a whole is greedy or
Speaker 1: is is that now? Uh? In investing, we've always said
Speaker 1: that past performance is no guarantee of future. So I'm
Speaker 1: guessing you have to take that into account. How do
Speaker 1: you look at that? I agree with that one, you know,
Speaker 1: And what would say is that, you know, history doesn't
Speaker 1: always repeat, but it does influence the future. And we've
Speaker 1: got like tend nearly eleven years worth of data now
Speaker 1: and bitcoin, and so it does allow us to forecast
Speaker 1: what may play out in the coming months or years.
Speaker 1: But yeah, I mean, all of these tools, you know,
Speaker 1: they none of them may work going forwards. But I
Speaker 1: think there's such an array of different types of tools
Speaker 1: that people are using now that again going back to
Speaker 1: my point before, if you if you use a cross
Speaker 1: section of them, all from different sources and kind of
Speaker 1: join the dots and they can help you forecast what
Speaker 1: may play out going forwards. Um. You know, which which
Speaker 1: a lot of funds are doing now as well as
Speaker 1: individuals with it with pretty high degree of success. So
Speaker 1: I think there's a lot in it. But yeah, absolutely,
Speaker 1: you know none of this is investment advice. And also
Speaker 1: you know all of these tools are literally just educational
Speaker 1: tools to try and help you out. So let's talk
Speaker 1: about a couple of them. I know on your website,
Speaker 1: I think you have ten or twelve different indicators. And
Speaker 1: again I want to just impress on everybody that, uh,
Speaker 1: one indicator by itself doesn't mean anything. Um. You want
Speaker 1: to look at all of them, like like a good
Speaker 1: example in the traditional markets might be everyone thought, oh,
Speaker 1: when the yield curve inverts, when the bond yield curve inverts,
Speaker 1: then the market's going to crash. Well that's one indicator,
Speaker 1: all right, But when you look at all the other
Speaker 1: indicators of the market, to me, it was telling me
Speaker 1: that the market wasn't gonna crash. And I've been pretty
Speaker 1: up now we're starting to geet rallied um. And so
Speaker 1: you can't just look at one indicator like that, um.
Speaker 1: And so that's kind of what we're talking about. And
Speaker 1: and there's ten or twelve here, but there's other things,
Speaker 1: right that you want to look at. I look at also,
Speaker 1: like external things not on chain, like, um, what are
Speaker 1: companies doing? Like, Uh, we've just seen in the last
Speaker 1: couple of weeks, uh, close to a billion dollars get
Speaker 1: raised for bitcoin mining. That's a serious investment for long
Speaker 1: term and that tells me something. We saw, you know,
Speaker 1: most of the the big elite in Wall Street jump
Speaker 1: into bitcoin just in the last month or two, um,
Speaker 1: you know, from fidality and back finally launched. And so
Speaker 1: that's fundamental. I just want to impress on everybody you
Speaker 1: want to look at all these things and what are
Speaker 1: they telling you? But um, if we can, let's talk
Speaker 1: about maybe just a couple of the indicators that you
Speaker 1: have that we can explain without the need of charts
Speaker 1: and whatnot, And and tell me what do you think
Speaker 1: are maybe like your most powerful or most easy to
Speaker 1: use ones. Yeah, sure, let's start with We'll, like you say,
Speaker 1: given the we're not in front of the you know,
Speaker 1: the website it self right now, let's start with one
Speaker 1: of the simpler charts on the site. Uh. And in fact,
Speaker 1: I kind of designed it to be as simple as
Speaker 1: possible because I wanted this side to be useful for anyone,
Speaker 1: whether they are you know, Omega on chain analytics geek.
Speaker 1: There's some stuff on there for like people like that,
Speaker 1: like charts I reserve risk. Uh, there's plumb stuff to
Speaker 1: flow model, which I'm sure most people have probably heard
Speaker 1: of now, and then mind your mind through some more
Speaker 1: simple stuff. So let's start with arguably one of the
Speaker 1: more simple ones. It's just called the Bitcoin Investor Tool,
Speaker 1: and it uses a two year moving average line of
Speaker 1: bitcoins price. So on the chart, you've got the price
Speaker 1: a bitcoin, so you can see the price line, and
Speaker 1: then you also have a two year moving average line
Speaker 1: of bitcoins price. So for anyone who doesn't know what
Speaker 1: I'm moving average line is, it's simply taking an average
Speaker 1: of the daily closed prices over any given period of time.
Speaker 1: So you could have a ten day moving average line,
Speaker 1: which shows average price of the past ten days. You
Speaker 1: could have a two day moving average line, which shows
Speaker 1: average price over the past two in days. The result
Speaker 1: is a smooth line versus the more erratic daily price
Speaker 1: line because you're taking an average price over a number
Speaker 1: of days and moving averages that are useful in markets
Speaker 1: that tend to trend or have market cycles. Because the
Speaker 1: moving average you can highlight when prices moving with or
Speaker 1: against the trend. So in the market life, bitcoin is
Speaker 1: actually super useful using moving averages. And here we used
Speaker 1: the two year moving average because whenever price dips below
Speaker 1: that line, it has historically been an excellent time to
Speaker 1: buy bitcoin. So in bitcoin's now nearly eleven year history,
Speaker 1: price has only dipped below the two year moving average
Speaker 1: line three times, and it does. When it does it,
Speaker 1: it does it for a few weeks or months, and
Speaker 1: if you bought during that period, you would have achieved
Speaker 1: outsized returns over the years because you would effectively be
Speaker 1: buying the bottom. Right when when price dip below the
Speaker 1: two year moving average, that is like the bottom of
Speaker 1: the bear market. Um. So it's a as a as
Speaker 1: a an investor who's able to remove their emotions a
Speaker 1: little bit. You can see when price goes blurw it
Speaker 1: to you moving average line, it's an excellent time. Did
Speaker 1: it recently? Did it recently like in the last six months,
Speaker 1: like that maybe November December? Did it did below that
Speaker 1: line exactly exactly? So we saw it dip below the
Speaker 1: line um in December, and obviously we bottomed out what
Speaker 1: was it, three thousand dollars around there else around there,
Speaker 1: and then it came back up above the line. And
Speaker 1: I think March time, April time, I should have the
Speaker 1: chart in front of me when we crossed about five
Speaker 1: thousand dollars and then then shut up above the two
Speaker 1: years moving average line. And interestingly we've actually just come
Speaker 1: back to retest it, which we've done in previous sides
Speaker 1: as well, and that tends to indicate we're about to
Speaker 1: kick off now a new ball rumber when you when
Speaker 1: you test the line exactly, yeah, which we've just done
Speaker 1: literally a couple of weeks ago. And I know you
Speaker 1: said you don't have the chart in front of you,
Speaker 1: but maybe you can guess or approximate, uh if if
Speaker 1: if it said to buy right around there, when Win
Speaker 1: would have told us to sell, if you were to
Speaker 1: back up, you know, yeah, yeah, well exactly. So as
Speaker 1: an investor, you we talked about Earlione, you want to
Speaker 1: know when to buying, went to sell, and so the
Speaker 1: two year moving average line can tell you when to buy,
Speaker 1: because when price goes beneath it, that's went to buy.
Speaker 1: And what the other line on the chart does is
Speaker 1: it simply is multiplying that two year moving average by five,
Speaker 1: So the values of that two year moving average multiplied
Speaker 1: by five. And what that does is it actually catches
Speaker 1: the tops of bitcoins price cycles. So, for example, back
Speaker 1: in December two thousand and seventeen, when we were, you know,
Speaker 1: at the top of the last cycle, I think price
Speaker 1: went from like, what was it, twelve thousand dollars to
Speaker 1: like nearly twenty thousand dollars in the space of like
Speaker 1: three weeks, wasn't it right, We saw using this indicator
Speaker 1: that price moved above that time's five multiple moving average line,
Speaker 1: and so that was indicating that actually, that's pretty good
Speaker 1: time to be taking some profit off off the table
Speaker 1: if you're a long term investor. And it has done
Speaker 1: that for each of bitcoins market cycles going back eight
Speaker 1: years now. So it's a very simple, very effective tool
Speaker 1: to indicate when is the market overly pessimistic and where
Speaker 1: is when is the market becoming overheated, And so then
Speaker 1: as a long term investor, I mean it's going back
Speaker 1: eight years, it would have it's been effective so far.
Speaker 1: We don't know that hit in the future. But it's
Speaker 1: been effective, and it would have told me to sell
Speaker 1: that at the top in December of sen or January
Speaker 1: and then buy back in at the bottom of December,
Speaker 1: basically sat out of the market for a year, which correctly.
Speaker 1: I mean if you if you're only using that one tool,
Speaker 1: which that that one is not using on chain data, right,
Speaker 1: that one's usually price action exactly exactly. And so now
Speaker 1: what do you think about price action? Um, I know
Speaker 1: some of the best technical analysts the market today, they
Speaker 1: really believe that technical analysis, even though it's a math
Speaker 1: um meaning like Fibernacci lines mathematical lines, it really works
Speaker 1: off market psychology. And so do you think somehow this
Speaker 1: moving average and the five times top lines somehow works
Speaker 1: with market psychology. Having been someone that's that's studied that, yeah,
Speaker 1: I think it is. I think it is because all
Speaker 1: those moving averages are doing really is recognizing the bitcoins
Speaker 1: on an adoption curve, so it's moving up. But on
Speaker 1: top of that adoption curve you have we are experiencing
Speaker 1: these very clear market cycles, right, and if you've been
Speaker 1: in bitcoin for more than a couple of years, you
Speaker 1: kind of know what we're talking about. We there are
Speaker 1: times when the market is feeling pretty dad about the
Speaker 1: prospects of it, quite like arguing we were back in
Speaker 1: December and then this period where everyone's super excited piling in,
Speaker 1: you know, like it was back in December two doesn't
Speaker 1: sound seen. You know, you had all your friends coming
Speaker 1: up to your gun. What's this bigcoin thing? How can
Speaker 1: I get involved? And that is pure market psychology, and
Speaker 1: that is just people becoming either overly pessimistic or over optimistic.
Speaker 1: And and all the moving average lines do in this
Speaker 1: instance is kind of cut through prices. It is, it's
Speaker 1: doing those huge swings, and say, if you really step
Speaker 1: back as like a long term bitcoin you opened up
Speaker 1: with saying that you really believe bitcoin is this technology
Speaker 1: that can really free us from the banking system and
Speaker 1: really revolutionist everything. Um, as it gets bigger, the volatility
Speaker 1: should go down. And eventually if it's so, do you
Speaker 1: think this model would be adjusted? So right now it's
Speaker 1: at a five times after two hundred, but maybe eventually
Speaker 1: goes to four times and three times and two times. Yeah, yeah,
Speaker 1: I mean I think you're right. I think it will
Speaker 1: and I think a lot of these valuation tools that um,
Speaker 1: all of us are working on at the moment, will
Speaker 1: have to be adapted and some of them will just
Speaker 1: out right stop working, right, And I think I think
Speaker 1: a lot of these valuation models are effective whilst we're
Speaker 1: in this early adoption phase for bit point and there's
Speaker 1: very clear aggressive growth. But I suspect in the next
Speaker 1: kind of couple of market cycles will then move into
Speaker 1: a more mature market phase. As you mentioned, red volativity
Speaker 1: will drop die down, the market cap will be you know,
Speaker 1: over a couple of trillion dollars, and um, yeah, there
Speaker 1: will need to be new metrics, and who knows those
Speaker 1: those new metrics maybe more in line with you know,
Speaker 1: some of the stuff you see in traditional markets. Because
Speaker 1: I suspect, and this is just a theory, that bitcoin
Speaker 1: will if it's still around, right, if it's still around
Speaker 1: in ten years, I suspect it will start to be
Speaker 1: more in sync with with global other global macro macro assets,
Speaker 1: because by that time it will be pretty big. Yeah,
Speaker 1: So that's the two year moving average. You call it
Speaker 1: the bitcoin investor tour, and then one can check that
Speaker 1: out a look into bitcoin dot com. Let's let's talk
Speaker 1: about another one. Maybe you have one that actually uses
Speaker 1: our chained data. Yep. So another one we can talk
Speaker 1: about the users on chained data would be envy are
Speaker 1: the Z school sounds a bit of a funny name,
Speaker 1: But I love this chart. I didn't come up with
Speaker 1: the matter behind it. It's not my idea. I just
Speaker 1: created the visual you can see on the site to
Speaker 1: try and make it easy for investors to use. But
Speaker 1: I think the thinking behind it and the methodology is genius.
Speaker 1: Mv r V Z school uses on chain analysis and
Speaker 1: uh it was the original idea behind it came from
Speaker 1: a couple of guys. Murad Mahmudov and David Kule came
Speaker 1: up for the idea is behind NDRV school, and then
Speaker 1: Z School was added on top of it. But essentially
Speaker 1: it's pretty straightforward. So it uses three metrics. So if
Speaker 1: you look at the chart, there's gonna be three lines
Speaker 1: on the chart, and the first is market cap and
Speaker 1: market cap, just like you have in traditional markets for
Speaker 1: stocks and shares, where the market cap is the share
Speaker 1: price multiplied by the number of shares. In the case
Speaker 1: a bitcoin, market cap is the current price of bitcoin
Speaker 1: multiplied by the number of coins in circulation. So that
Speaker 1: gets you to market cap, right and the market capoin
Speaker 1: is supplied on a chart looks pretty similar to price
Speaker 1: because price is a cool component of it. The second
Speaker 1: metric we use is slightly different, and this is where
Speaker 1: we use the on chained data. So rather than taking
Speaker 1: the current price of bitcoin, which market cap does, realized value,
Speaker 1: takes the price of each bitcoin when it was last moved,
Speaker 1: I the last time it was sent from one wallet
Speaker 1: to another wallet. So it's like it's like a cast basis. Yeah, yeah, exactly.
Speaker 1: You can think about it trying it, trying to guess
Speaker 1: like what that person acquired that bitcoin for. So um
Speaker 1: I I last moved it at five thousand. Today it's
Speaker 1: at ten thousand, So my cast basis or whatever, I
Speaker 1: only owe five thousand on that coin. Exactly. For calculating
Speaker 1: realized value, it would use the five thousand dollar value
Speaker 1: rather than today's past value. In doing so, what that
Speaker 1: does is it strips out a lot of the short
Speaker 1: term market sentiment that we have with the market cap metric,
Speaker 1: and so it can give them will give a more
Speaker 1: true long term measure of bitcoins of value. Why do
Speaker 1: you think it strips that out? Because if I'm in
Speaker 1: the money, if I'm in profit, I'm less likely to
Speaker 1: capitulate or less likely to sell out, versus if I'm
Speaker 1: upside down a negative more likely to sell out. Well,
Speaker 1: the reason being is that all those considerations come into
Speaker 1: play in more short term market market thinking, right, and
Speaker 1: so realize value it can be registered recording values from
Speaker 1: like last week or a year ago or five years ago,
Speaker 1: and so it just takes out a lot of the
Speaker 1: short term market sentiments. So when we're seeing in the
Speaker 1: short term people might be an overly person this thing,
Speaker 1: like we said, or over the optimistic, realized value doesn't
Speaker 1: really capture that. So if you look at the chart
Speaker 1: too much smoother, more steady line on the chart versus
Speaker 1: market cap, which because prices are involved in it, is
Speaker 1: very volatile and goes to the extremes of overpessimism and
Speaker 1: over optimism. So that that's that's what realized value is,
Speaker 1: and where we are interested in is looking at the
Speaker 1: divergence between the two, so when market cap is much
Speaker 1: much higher or much much lower, because that is when
Speaker 1: the short term market is either over excited or over pessimistic,
Speaker 1: and we can therefore use the next metric, which is
Speaker 1: Z score, which is simply a standard deviation test that
Speaker 1: pulls out the extremes in the data between market cap
Speaker 1: and realized value. And essentially what it does to cut
Speaker 1: to the chase, is that it's able to pick out
Speaker 1: the tops in big point cycles and also the lows.
Speaker 1: And it's actually so effective in doing it that it
Speaker 1: can pick out the market cycle tops too within two weeks.
Speaker 1: So back in December two thousand and eighteen, one week
Speaker 1: before we peeked in price, m v RVs score indicated
Speaker 1: actually the market was overheated and it was time to
Speaker 1: take profit. Um. So, yeah, it's very valuable tool in
Speaker 1: terms of being able to determine when as an investor
Speaker 1: should I be taking money off the table or investing? Yeah,
Speaker 1: and does that line up with that other tool we
Speaker 1: just talked about, the Bitcoin Investor tool that it both
Speaker 1: they both kind of line up and where they saw
Speaker 1: the market cup. Yeah, they did, and you know that
Speaker 1: that's where you know it's it's useful to use a
Speaker 1: range of metrics, right like we were talking about, because
Speaker 1: they actually both think the top in that instance, and
Speaker 1: they also align with when the market bottoms earlier this year. Okay, yeah,
Speaker 1: so so so we're seeing some good uh, good on
Speaker 1: chain data with that, I mean I would think that
Speaker 1: uh somewhat complex and probably the average person would never
Speaker 1: be able to figure that out. Is trying to figure
Speaker 1: out all the bitcoins that are owned and held out there,
Speaker 1: what is the actual like realized value, what's what was
Speaker 1: the cost basis of that? So that's that's some good
Speaker 1: on chain data. I like. I like the use of
Speaker 1: that good job on that. Um, do you have any
Speaker 1: other ones that may use some good on chain data?
Speaker 1: We could talk about one, maybe one more that that
Speaker 1: would be easy for us to discuss. Uh. So the
Speaker 1: on chain data stuff is probably the sort of stuff
Speaker 1: you want to sit down and uh read about on
Speaker 1: the on the site. So UM, underneath each live data
Speaker 1: chart is a really sure clear explanation as to how
Speaker 1: they work. UM, in the interests of us being on
Speaker 1: a podcast and not having the charts in front of us. Uh.
Speaker 1: Probably one of easy you want to talk about and
Speaker 1: and to visualize is one called the Pice cycle top indicator,
Speaker 1: and uh that uses price data and it uses two
Speaker 1: very specific moving averages. So at shorter timeframe moving average,
Speaker 1: the dred eleven day moving average, and then at times
Speaker 1: to multiple of the three fifty day moving average, which
Speaker 1: is pretty much a one year moving average. And the
Speaker 1: really interesting thing about this chart is that when the
Speaker 1: shorter time frame moving average crosses the other moving average,
Speaker 1: it actually captures the tops of bitcoins price cycles to
Speaker 1: within three days. So really really effective tool in terms
Speaker 1: of identifying when is the market topping, when is the
Speaker 1: market really overheated? And yeah it's I've yet to find
Speaker 1: another tool that can pick those market tops as accurately,
Speaker 1: So so that interests. That's our sell price action. That's
Speaker 1: not really exactly exactly about just a couple of other
Speaker 1: metrics that maybe you're digging enough of our chain. One
Speaker 1: I know, and I think I think maybe we mentioned
Speaker 1: about is maybe it was in one of our earlier conversations.
Speaker 1: But it's a like average days or days destroyed, right,
Speaker 1: so you can see like how long the bitcoin has
Speaker 1: been sitting there? What's that one? Yes, so that that
Speaker 1: is So there's a chart and the cycle reserve risk,
Speaker 1: which was developed by the guys that Ikey Guy Fund,
Speaker 1: which is a a crypto fund based out in l A. G. Yeah, yeah, yeah,
Speaker 1: Travis and those guys and um, they did a lot
Speaker 1: of analysis around bitcoin days destroyed and the concept around
Speaker 1: Bitcoin days destroyed is simply, as you alluded to, UM
Speaker 1: if looking at coins that haven't moved for a very
Speaker 1: long time. So let's say a coin hasn't moved for
Speaker 1: five years and then I decided to send it to
Speaker 1: you today. When I send it to you, it would
Speaker 1: be destroying in invert commerce five years worth of days,
Speaker 1: if you like. And the reason why that is important
Speaker 1: when we do certain types of one chain analysis is
Speaker 1: it's because it's kind of telling you that um coins
Speaker 1: that haven't moved for a long time are now being moved,
Speaker 1: and that that is quite important because what we tend
Speaker 1: to see is that participants have been in the market
Speaker 1: for a long time. So like old guys O G,
Speaker 1: s UM, they tend to understand bitcoin price movement very well,
Speaker 1: especially when you compare it to a new entrance coming
Speaker 1: into the market. And so people like Travis Kling and
Speaker 1: other guys who do this sort of one chained data,
Speaker 1: they give a lot of importance towards those guys. So
Speaker 1: when they're seeing lots of Bitcoin days destroyed, they're sitting
Speaker 1: up and paying attention. And actually they've built tools that
Speaker 1: show you when there's a high level of bitcoin days
Speaker 1: destroyed and you want to be sitting up with paying
Speaker 1: attention in terms of whether people are buying and selling,
Speaker 1: So yeah, there aren't. Chaine is destroyed. I mean it
Speaker 1: kind of shows the Hardler's right, that shows like who's
Speaker 1: whole thing, And when that number goes down, it means
Speaker 1: those hoddlers, those o g s are starting to sell.
Speaker 1: And then basically that would tell us like, oh shoot,
Speaker 1: if these guys are starting to sell, then maybe the
Speaker 1: markets starting to soften. Is that kind of how that
Speaker 1: how that works? Yeah, yeah, exactly, it can work in
Speaker 1: that way. Um. They actually then take it a couple
Speaker 1: of steps further to show you, um, the sentiment therefore
Speaker 1: of those old guys, those hoddlers, and where prices relatively
Speaker 1: at this moment in time, and so therefore whether the
Speaker 1: market is under all overvalued based on the sentiment of
Speaker 1: those old guys. So they get pretty sophisticated with it. Um,
Speaker 1: but yeah, really interesting stuff. So basically for everyone listening
Speaker 1: that's not really following along, it basically looks at how
Speaker 1: long the bitcoin has been sitting still. So if I
Speaker 1: bought bitcoin and threw it into a hardware wallet and
Speaker 1: it's been there, for five years. It knows that hey,
Speaker 1: he's been hanging onto this for a really long time
Speaker 1: and he only has a small, small amoun out, but
Speaker 1: this guy has a lot of it, and it's been
Speaker 1: sitting for a really long time. So it's kind of
Speaker 1: the days that it's been sitting still, right, And then
Speaker 1: it takes into some sort of a weight at score
Speaker 1: based off of how much I have or how much
Speaker 1: has been sitting in for how long. I'm curious using
Speaker 1: that tool and looking backwards back to November of last year. Um,
Speaker 1: you know, everyone in the market kept saying, oh, we
Speaker 1: need capitulation, We need capitulation. The bottom won't be in
Speaker 1: until we have capitulation. And and that means that there's
Speaker 1: that final just sell off where one she says, all right, enough,
Speaker 1: screw it, I'm out of here right um. And in November,
Speaker 1: after the market had seemingly found its bottom, um in
Speaker 1: November it dropped in half fift I mean it was
Speaker 1: a message of from six thousand and three thousand approximately,
Speaker 1: what did the what did what did that indicator show
Speaker 1: during that time? Do you know so reserved risk? Uh
Speaker 1: you can check it out on the site. Uh that actually, yeah,
Speaker 1: we we just had further down to go. So it
Speaker 1: was the issue around that time was that it was
Speaker 1: price was kind of entering uh over over sould levels.
Speaker 1: And that's why even a lot of the big funds
Speaker 1: we're thinking on maybe the bottoms in, maybe the bottoms in,
Speaker 1: and then the realities we just crashed down even further. Um.
Speaker 1: So yeah, that metric, um, you know, we did go
Speaker 1: down further and it did actually highlight the yeah, the
Speaker 1: bottoms in. Now, I think tools that are even more
Speaker 1: sensitive than that are ones like m v r VS score.
Speaker 1: So that kind of that played out perfectly that and
Speaker 1: that called it perfectly back in November December. Arguably that's
Speaker 1: a more sensitive tool for picking the market bottoms. Um.
Speaker 1: So yeah, going back to our point earlier, you always
Speaker 1: want to be using a range of these tools because
Speaker 1: Bitcoin days destroying that gave you some indication, but actually
Speaker 1: wouldn't it wouldn't have been able to to highlight the
Speaker 1: absolute bottom in that instance. All right, So interesting stuff,
Speaker 1: interesting stuff, and I think, uh, let's move on to
Speaker 1: something else that everybody is dying to know. So being
Speaker 1: someone who studied economic studied market behavior, has been studying
Speaker 1: on chain data, building models, building charts and so forth.
Speaker 1: Just tell us what it means. Where where? Where? Where
Speaker 1: do you think we are in the market cycle? Uh,
Speaker 1: you're the you're the expert here, right Uh. I know
Speaker 1: we used to look at each one individually. What are
Speaker 1: you seeing in the market cycle today? Um? And where
Speaker 1: do you think we are I don't know, twelve months,
Speaker 1: twenty four months, etcetera. Cool? Uh, well, things are looking
Speaker 1: pretty good good right now. I gotta say, you know,
Speaker 1: I mean, if if you've been in the market for
Speaker 1: a couple of years and you're still here like congrass,
Speaker 1: because I think I think we've got some good times
Speaker 1: coming up the next year or two. Um. So yeah.
Speaker 1: I mean one of the childs we talked about earlier
Speaker 1: one was the two and maybe an average multiplier. And
Speaker 1: you know, as we said, we've seen price burst out
Speaker 1: of that accumulation zone and retested, and now we're in
Speaker 1: what I would call the first growth phase of the
Speaker 1: coming bull market, and that is really where we have
Speaker 1: this slow, steady rise. It will feel like a bit
Speaker 1: of a choppy period when we're in it, but typically
Speaker 1: we're grinding up more than we are popping down. They'll
Speaker 1: be the odd little scare along the way. But then
Speaker 1: there's also going to be a couple of big jumps
Speaker 1: up UM and and that that's gonna last probably a
Speaker 1: few months, I would imagine, into the start of next year.
Speaker 1: And then stage two will probably be when we're a
Speaker 1: fair way into UM next year. And if you use
Speaker 1: one of the other tools on the website, actually it's
Speaker 1: called golden ratio multiplier. When price breaks above the red
Speaker 1: line on that chart, that's historically when we've seen Bitcoin
Speaker 1: enter it's more aggressive second growth phase. And that's when
Speaker 1: things get really exciting and people will start kind of
Speaker 1: people from outside and start coming in saying, what the
Speaker 1: hell is all this about? Tell me about it, tell
Speaker 1: me out of by us. That's when we will be
Speaker 1: into that phase. UM. But yeah, I mean so yeah,
Speaker 1: I think I see those two phases coming up. We're
Speaker 1: just in the start of the first phase. I think
Speaker 1: it's gonna last a few more months. I suspect, you know,
Speaker 1: the harving is going to have an impact. We are
Speaker 1: going to see price rise and yeah, well I think
Speaker 1: we'll be above the previous all time high Q one
Speaker 1: Q two next year and then and then we're off
Speaker 1: to the races and then and then obviously and then
Speaker 1: and then obviously you know, we'll have hopefully some indication
Speaker 1: as to when the market starts to top out towards
Speaker 1: the end of that second growth phase, when we see
Speaker 1: it start to see a range of these metrics shown
Speaker 1: over sold, right, a combination of on trained metrics, in
Speaker 1: quest analysis metrics, and you know, I'm sure there'll be
Speaker 1: various sentiment metrics as well when people are going crazier
Speaker 1: out there about to say, well, okay, now is maybe
Speaker 1: a good time take some profit? Yeah. You know. The
Speaker 1: one thing that I always trying to impress on people
Speaker 1: with trying to do any kind of forecast. I don't
Speaker 1: like to call them forecasts, I mean their guesses, right,
Speaker 1: I like to talk about them in probabilities. Um, so
Speaker 1: if this happens, then this happens kind of thing, and
Speaker 1: so um. The one thing to keep in mind is
Speaker 1: kind of what you're saying, You're not trying to project
Speaker 1: when the next top is. Um, it's more like, hey,
Speaker 1: let's keep an eye on the indicators and it will
Speaker 1: tell us. So it's something that should be managed or
Speaker 1: monitored right and watched. And it's kind of like driving
Speaker 1: a car, right, you can't just close your eyes and
Speaker 1: open when you get there. You need to be watching
Speaker 1: the signs along the way exactly, and you want to
Speaker 1: be managing your risk along the way as well. Right,
Speaker 1: It's so important, Like even if if if what I
Speaker 1: just described plays are then like you say, it might
Speaker 1: do might not. Um, there's there's a decent chance it won't, right,
Speaker 1: and so always be managing your race. Take some profit,
Speaker 1: leaves to fight another day, man, because you know this,
Speaker 1: this this market should be around for a while. So
Speaker 1: always take some profit, managing risk and um yeah, enjoy it. Yeah,
Speaker 1: switching gears just a minute. Um, Now, are you're over
Speaker 1: in England? Is that right? I am? Yeah, yeah, you
Speaker 1: can probably tell from the accident. I'm not from your
Speaker 1: neck of the woods. I'm based in London in the UK.
Speaker 1: What what do you what? You're just what what are
Speaker 1: you picking up? As like market sentiment? Like what are
Speaker 1: what are people thinking? What are what are people? Are?
Speaker 1: Are people actually buying it? Young people? Old people? What
Speaker 1: are um? You know, what are the stores thinking? What
Speaker 1: is the government thinking? Give us an analysis for England
Speaker 1: and maybe even what you're picking up in Europe? Sure
Speaker 1: you're in the market psychology. You know, I would say
Speaker 1: it's it's kind of it's really sleepy right in terms
Speaker 1: if if I'm trying to gauge general market sentiments, I'm
Speaker 1: not talking about people who are in crypto right now.
Speaker 1: I'm talking about general market sentiment towards crypto. It's it's
Speaker 1: super sleepy. I mean the same we are price wise,
Speaker 1: where we are, you know, around ten thousand dollars um. Yeah,
Speaker 1: interest just isn't there. People are, People are far more
Speaker 1: interested in other things at the moment right Brexit is
Speaker 1: obviously a huge talking point here. Just got a general
Speaker 1: election coming up. That is what everyone is focused on it,
Speaker 1: and you know, the issues behind that may you know,
Speaker 1: drive a need for bitcoin for the majority, like further
Speaker 1: down the line, but right now everyone's focused on on
Speaker 1: on those issues, and I don't think people like kind
Speaker 1: of Joe Public, it's really going to pay much attention
Speaker 1: towards bitcoin until we are past the previous all time high.
Speaker 1: So I think once we're above twenty k thirty k,
Speaker 1: I think that's when it's going to start turning heads
Speaker 1: again and when people will start to get interested. So
Speaker 1: that's that's general public. I actually know I have some
Speaker 1: friends who work in traditional finance and work for some
Speaker 1: pretty big funds, traditional hedge funds, and so I talked
Speaker 1: to them time to time kind of say how, you know,
Speaker 1: asked them how their stuffs go, and ask me how
Speaker 1: my stuffs going, and it's it's you know, it's interesting
Speaker 1: to see their level of interesting Bitcoin, and I would
Speaker 1: I would say it's still absolutely minimal, absolutely minimal. It's
Speaker 1: it's not like you know, I think, because we we
Speaker 1: live and breathing stuff every day, we think, oh, you know,
Speaker 1: everyone's going to be in, like you know, in the
Speaker 1: next few weeks, you know, when government's lower interest rates
Speaker 1: by a court percent, then you know the big institution
Speaker 1: is going to come in. I still think most of
Speaker 1: the institutions are a long way off. And the reason,
Speaker 1: the reason why is a lot of it is not
Speaker 1: because they don't see the potential. Most of the reason
Speaker 1: is because it's so tiny that they can't pay attention
Speaker 1: to it. So that stuff in the you know, hundreds
Speaker 1: of billions or even trillions of dollars markets and so
Speaker 1: something with a hundred billion dollar market cap is just
Speaker 1: too small for them. They can't they can't, they can't
Speaker 1: move in enough or out. So I think there's a
Speaker 1: lot of it there. UM. I'm curious though, because you know,
Speaker 1: understanding the macroeconomic, the market cycle is happening in a
Speaker 1: lot of countries is super important, so I study them
Speaker 1: a lot. And and you said Brexit is at the
Speaker 1: top of everyone's conversation. Um. Are people worried about the
Speaker 1: damage that Brexit is going to cause to um? I
Speaker 1: mean obviously a lot of damage to trade and whatnot,
Speaker 1: but even just the currency, just your money, uh, witching
Speaker 1: from the Euro back to the Sterling, and what's going
Speaker 1: to happen with the money? I mean, does anybody think
Speaker 1: about that? Or what are they what are they worried about?
Speaker 1: I mean, I think again going back to Joe Public,
Speaker 1: that they're they're all concerned about, uh, what does it
Speaker 1: mean in terms of job prospects? And also what does
Speaker 1: it mean in terms of our relationships with other market
Speaker 1: with with other countries the trade right, in terms of trade, uh,
Speaker 1: and also in terms of you know, I think people
Speaker 1: who want to remain in Europe, they're quite fearful around
Speaker 1: what does it mean socially in terms of how we
Speaker 1: interact with other democratic markets and countries and cultures like
Speaker 1: you know, those of you have in Europe. So I
Speaker 1: think those are some of the concerns for most people.
Speaker 1: M But you right, you obsolutely right. While so this
Speaker 1: is going going, you know, the time is being devalued,
Speaker 1: and he's allowing needs to continue whilst there's all this uncertainty,
Speaker 1: and obviously people in traditional finds are much more concerned
Speaker 1: about that. Yeah, you know, Um, it's unfortunate. And I'm
Speaker 1: I'm imagining all over the world and and probably the
Speaker 1: same in England as it is in the US is
Speaker 1: they don't teach anybody about money, and I think almost
Speaker 1: purposely right, they don't want you to know about money,
Speaker 1: banking and whatnot. And actually, Henry Ford, the godfather of
Speaker 1: the you know, automobile assembly line whatever, he was famously
Speaker 1: quoted back in the early nineteen hundred saying that if
Speaker 1: the average person understood the banking system, there would be
Speaker 1: a revolution overnight. That was back then. Imagine how much
Speaker 1: it's worse, how much worse it's gotten over a hundred years. Dalio,
Speaker 1: who's one of the biggest fund managers in the world,
Speaker 1: Bridgewater Capital, doing the dollars, he's been pretty outspoken recently
Speaker 1: and I just retweeted one of he put out a
Speaker 1: new paper yesterday and uh, quote from Ray Dalio said,
Speaker 1: well that the name of the title is the world
Speaker 1: has gone mad and the system is broken. Um and
Speaker 1: he says, quote, money is almost free for those who
Speaker 1: have money and credit worthiness. It is unavailable to those
Speaker 1: who don't have money and credit worthiness. This contributes to
Speaker 1: the rising wealth opportunity and political gaps, and everyone's mad
Speaker 1: about the rich getting richer, and and in the US
Speaker 1: we have Bernie Standers calling out to make billionaires being
Speaker 1: illegal and right, and so everyone's kind of missing it
Speaker 1: that the banks are ruining the money and that is
Speaker 1: what's causing your purchasing power to fall and whatnot. So
Speaker 1: that's what I was just curious. I mean, with Brexit happening,
Speaker 1: there's a real risk of what can happen with your money,
Speaker 1: both both the Sterling if you go back to that,
Speaker 1: or the Euro. But probably I guess, as you're saying,
Speaker 1: probably nobody knows that nobody's paying attention to that. Yeah, unfortunately,
Speaker 1: not right, And I think people won't really start thinking
Speaker 1: about it until they really really really have to, kind
Speaker 1: of when it's almost becoming too late and you know
Speaker 1: you're you're seeing that pop up around various countries around
Speaker 1: the world. Right, all these issues like in Lebanon, Chile, Venezuela, Turkey,
Speaker 1: you know, the least is just getting longer and longer
Speaker 1: and longer. Um. All these issues in terms of government debt, um,
Speaker 1: managing like I mentioned that, in monetary fiscal policies, um.
Speaker 1: And yet just how wealthy and quality gaps. It's really
Speaker 1: concerning in terms of the growth rate of a lot
Speaker 1: of that stuff. Cool. Well, we won't get too far
Speaker 1: into that. I just like to get a boots on
Speaker 1: the ground viewpoint, especially with someone with your background of
Speaker 1: market psychologies and whatnot. So I appreciate you jumping into that.
Speaker 1: That ended the pool with me just for a little bit.
Speaker 1: But all really really good, good information. I love these indicators.
Speaker 1: I love having more tools at my disposal to put
Speaker 1: all this together. Um, where can people learn more about
Speaker 1: you and your work and follow you well? And you
Speaker 1: can head to look into big line dot com to
Speaker 1: check out all the live dates charts and there's a
Speaker 1: whole bunch of learning materials there as well. Um, if
Speaker 1: you're kind of new to that sort of stuff and
Speaker 1: it's all tightly free, go and check it. Out and
Speaker 1: then if people want to follow me on Twitter because
Speaker 1: I tweet out a lot of my sort of analysis
Speaker 1: on there, you can search at positive Crypto um. But
Speaker 1: my name is Philip Swift, so you can probably find
Speaker 1: me either way. I'm on there. Cool. Well, Philip, I
Speaker 1: appreciate you taking the time to talk today. It was
Speaker 1: it was awesome and hopefull everybody enjoyed it. Thanks very much.
Speaker 1: Has been an absolute pleasure. Okay, hey, if you like
Speaker 1: this episode of the Market Disruptors podcast, please help us
Speaker 1: take this to the top of the podcast charts. Just
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Speaker 1: Taking fifteen seconds to just leave a quick review goes
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