Earlier this week, news broke that the U.S. government was able to retrieve some of the Bitcoin extorted from the Colonial Pipeline by hackers. Unfortunately, this was mischaracterized by several news outlets as the government “hacking” Bitcoin’s encryption.
Weiss crypto analyst Juan Villaverde explained just how ridiculous that claim was in yesterday’s issue.
But fear over whether the headline would push the price of Bitcoin down — and take the broad market with it — is still simmering.
Our response? Trust the cycles.
We’ve explained our cycles theory-based outlook before and why we believe we’re on the precipice of a parabolic cycle.
In this week’s Weiss Sunday Crypto Special, Juan is back, explaining his cycles model and how our analysts use it to provide you with the timeliest analysis.
Chris Coney:
Hi there, everyone, and welcome to the latest edition of the Weiss Crypto Sunday Special with me, your host, Chris Coney.
My guest today, once again, is Juan Villaverde, and today’s macroeconomic topic that we will be discussing is Juan’s number one specialty: market cycles. We’re going to talk about crypto market cycles and market cycles in general.
Juan, welcome back to the Sunday Special.
Juan Villaverde:
Thanks for having me, Chris.
Chris:
I’ll make sure we hit all levels of sophistication. So, what we’ll do is start off with just cycles in general, then we’ll drill down into how they apply to traditional markets, crypto markets and how they differ. ... We’ll dig into more detail as we go. You’re all right with that?
Juan:
Yeah, absolutely.
Chris:
Okay. Can you give us the basic components of a market cycle to begin with and how we can apply that to different markets?
Juan:
Let me see where I can begin ... So, I’ve seen several definitions of “cycle.” Let me start with what, according to my model, is a cycle.
Chris:
Okay.
Juan:
A cycle is basically a wave, like a sine wave. Think of something that starts at point A, peaks at point B, and it ends at point C. A cycle in my work refers to two lows that are a certain distance apart.
For example, if I say we have a 90-day cycle, I mean that we’re going to start on a low. We’re going to peak somewhere, ideally 45 days from that low. And then, 45 days later, we’re going to have another low. So, in total, it’s low number one. After 45 days, we have a high. Then 45 days after that high, we have another low.
In total, this is 90 days and is called a full cycle because it starts from a low, peaks at a high, then bottoms out at a low.
Now, ideally, the high is halfway between the two lows. This is ideal.
Chris:
Give or take, yeah.
Juan:
But it doesn’t usually work that way because these cycles are combined. These cycles are all aligned at the lows. Going back to this 90-day cycle, let’s say we also have a 45-day cycle. What that means is that when the 90-day cycle starts, a 45-day cycle is also starting.
Chris:
Okay.
Juan:
They’re aligned. If I say we also have a 22-and-a-half-day cycle, then I know that every 90-day-cycle low is also a 22-and-a-half-day-cycle low and 45-day-cycle low. That’s called synchronicity.
They’re synchronized at the lows. In other words, the highs don’t have to be aligned. So, a 90-day high is not necessarily a 45- or a 22-and-a-half-day high, but a 90-day low is necessarily a 22-and-a-half and a 45-day low.
This is how the model is built. It results in some pretty interesting outcomes.
What that means is I can have a series of tops. We saw that recently with Bitcoin (BTC, Tech/Adoption Grade “A-”) where you can start from an 80-day low on Bitcoin and also have a 20-day cycle.
There are basically three cycles that I track in crypto: 320 days, 80 days and 20 days. And recently, we saw a 320-day cycle top out, and that was lining up with 80 days. But then, immediately after, we saw a 20-day high. So what that usually looks like is you can see markets making several tops, each of them corresponding to a different cycle. Then, when they all point down, you have a big crash — which is something we had recently. When all the cycles — the 320-day, the 80-day and the 20-day pointed down — the big crash took place.
So, there are some interesting things that happen when you say the lows need to be aligned, but the highs don’t have to be. And this is a core of how this model works: You start from a low, you peak in a high, then come back to a low. Then, you start another cycle. When a cycle ends, another one begins. There’s a rhythm there.
Chris:
That is pretty good. That’s generally how market cycles work.
So, what came up from when you were talking there is there were some quite common and popular indicators — let’s call them methodologies — that are designed to follow certain cycles, like Elliott Wave Analysis, for example. Isn’t that a type of cycle predictor of some kind?
Juan:
So, the Elliott, I think, is a precursor to a more modern cycle theory. In Elliott waves, I believe one of the biggest differences is that each swing — when you go from a low to a high — is typically called a wave. That could be wave number one. Wave number two is a correction. Wave number three is typically referred to as the “biggest of all rallies.”
If you’re familiar with Elliot waves, a cycle in my model will be waves one and two. So, the rally component and the decline component are both combined for one cycle.
Chris:
Two of those.
Juan:
So, the Elliott wave is part of the model: Waves one and two are one cycle, waves three and four are another cycle. And then, you have wave five, which requires the corrected wave A to form another cycle.
They always come in pairs. The rally component and the sell-off component. That’s a full cycle.
Chris:
I see. From low to low ... that was the key takeaway from the first segment.
I didn’t actually realize that about your model, even though I’ve been following you for years: It’s about the lows. That’s how you know when the cycle starts and ends, and the bit in the middle varies. But that’s really how you know when a cycle starts and ends in 20 days, 80 days, 320 days, whatever, the different cycle links are.
Juan:
Yeah.
Chris:
And one contains the other, like an 80-day cycle has four 20-day cycles. That kind of thing.
Juan:
That’s correct.
Chris:
Okay. Then you’re looking for confluence, like you said. If they all line up at the same time, you’ve got almost like three lots of pressure pushing the price down. It’s not pushing the price down, not like that. The model doesn’t act on the market — it understands the market.
Juan:
Yes, it’s the other way around.
Chris:
Exactly. Let’s take that one level deeper now then. Does the basic structure of a market cycle play out the same in traditional markets as crypto? I assume yes because you didn’t say anything about equities or cryptos there; you’re just talking about price.
Juan:
Yeah. To answer your question, they are the same, mostly.
Chris:
Okay.
Juan:
But there is a difference, and that difference is their frequencies. As far as I’m aware, it could be the 24/7 nature of it. Or it could be something else. I have not seen an 80-day cycle in the stock market. I have seen a 70-day trading cycle in the stock market.
So, there’s a 70-trading day cycle in stocks. That breaks down into two 35-trading day cycles in the stock market. In traditional markets, I have seen these 35- and 70-day cycles pretty much everywhere. I’ve seen them in commodities, in bonds.
Now, I will say the 35- and 70-day cycles in traditional assets are the most prominent that you can see immediately when you study any of these asset classes.
But the bigger cycles, the multiyear cycles … they are different, too.
For example, gold has a three-and-a-half-year frequency. So do bonds. Then, the stock market has a four-year cycle, so slightly different.
But the fundamentals of how you study them, how they relate to one another ... in other words, you break down this four-year cycle into two-year components, then into one-year components. You keep breaking it down, and you get to these 35-, 70-day cycles.
So, it’s like building blocks. Let’s say the basic cycle is 35 days, and you can combine them in different ways to form different longer-term cycles. If you’re following the logic, you will say, “Well, it’s the same frequency, and it’s the same relationship, so it should be exactly the same cycle durations everywhere.” But it’s not because, for example, with gold, you’re going to have three years plus 13- to 14-month cycles that make up one three-and-a-half-year cycle. But in the case of the stock market, you’re going to have four one-year cycles, or rather a four-year cycle.
The number of cycles needed to create a bigger cycle is not fixed.
Chris:
Right. Yes.
Juan:
It is not fixed. It’s usually multiples of two or three. In crypto, it’s strange because it’s four; it’s always four. It works in a ... What’s the term? Fourth harmonic, I’ve seen it referred to, but it works in —
Chris:
It’s fractals.
Juan:
Yeah, it’s a fractal. The key number is four. Each cycle relates to one another by a factor of four. So, you divide it by four, you got a smaller cycle; multiply it by four, you got a bigger cycle.
In stocks, it’s typically a factor of two or three, and it depends on the cycle. So, you can have two 35-day cycles to form a 70-day cycle, then three 70-day cycles to form a 220- or a 210-day cycle, for example.
Chris:
You mentioned there about the cycle being different because crypto trades 24/7? And that made me think ...
The traditional markets are regulated, right? And I suppose having trading hours is a type of regulation. You’re only allowed to trade between, I think, 9:00 and 5:00, or whatever the timing may be. Do you think that has an impact on the differences?
And also, that confuses me because you’re modeling, right? So, you’re taking reality and then trying to abstract a model from it.
Juan:
Exactly. Abstracting it.
Chris:
I see. You’re actually observing what’s happening, right? Well, the result of regulation 24/7 trading ... it doesn’t really matter; you don’t care. Because you just take the data as it is and then model it. Right?
Juan:
Correct.
Chris:
And make observations.
Juan:
That’s what I do.
Chris:
Right.
Juan:
Yeah. There are some mathematical techniques that you can apply to price action to derive cycle frequencies, like a periodogram. We don’t have to get into that. But basically, you can take the price action, apply certain standard techniques and it’s going to give you a chart for you to look at with highlighted psycho frequencies.
So, when I ran this on Bitcoin — which is what I used — I had 20-day and 80-day frequencies and some evidence of a cycle that was either 240 days (so three 80-day cycles) or 320 days (four 80-day cycles). I didn’t know which one it was. I wasn’t sure. I kept running tests. And eventually, I concluded that it was 320 days.
So, it’s [a factor of] four, which makes sense because I had clear evidence for an 80-day and a 20-day cycle. The longer-term cycles were not clear because of insufficient data. There simply was not enough data for me to see ...
Chris:
In crypto?
Juan:
... What those frequencies might be. In crypto, yeah.
Chris:
OK, gotcha. That’s one of the biggest criticisms of market analysis in crypto — the idea that it just hasn’t been around long enough.
Juan:
Correct.
Chris:
The more data, the greater the accuracy.
Juan:
Yeah. The stock market has clean data for over two centuries.
Chris:
Right.
Juan:
I know of cycles as long as 50-plus years.
Chris:
That’s big.
Juan:
One that I trade around the lot, it’s a 16-year cycle.
Chris:
Okay.
Juan:
It’s a 16-year bull-bear cycle. Been around forever. So yeah, I don’t have anything of that sort in Bitcoin. In fact, I suspect Bitcoin does have a 16-year cycle because there’s a four-year cycle. So, I suspect there’s a 16-year cycle in Bitcoin, but Bitcoin hasn’t been around for 16 years, so we’ll have to see.
Chris:
Yeah. We’ll see. So, just sticking with this idea of the difference between the regulated, nonregulated markets —
And again, I’m going to have to keep reminding myself that you’re modeling what’s happening. So, any observation I make... like one I make in a moment, the model accounts for it. I’m already teaching myself about this right now.
But in traditional markets, when there were serious drops in price, I’ve heard of something called the plunge protection team at the Federal Reserve.
Juan:
Yeah.
Chris:
They hold trading, or they prevent the stock price from falling, which is obviously a free market intervention. So ...
Juan:
These are called circuit breakers. It’s the exchanges that have those.
Chris:
Right. But that doesn’t mess with the cycles, though, does it?
Juan:
No.
Chris:
No? Well, even if it does, like I just said, the model still accounts for that because it’s just observing what’s actually happening with price. You know?
Juan:
I can refer to intervention more broadly speaking. I think specifically the circuit breakers … they don’t affect the cycle. They can sometimes affect the magnitude.
Like I remember trading soybeans, for example, in 2016. I believe it was April. It was limit up every day. Limit up means it went up so much that they had to shut down trading.
Chris:
Stock price is going too fast.
Juan:
Correct. But it would continue to go up the very next day. Also, they —
Chris:
So, they can be so silly about it. Just like in crypto. It gets out of its system one way or another.
Juan:
Sure. As a trader that trades a lot of derivatives, I can tell you that there’s so much leverage in the system that if you don’t have circuit breakers on, you risk breaking the whole thing.
Chris:
Oh, I see what you mean.
Juan:
So, having them actually does make some sense. I don’t think we’ll ever see them in crypto due to the decentralized nature of trading in crypto. Even though we trade in centralized exchanges, it’s decentralized because you can trade all over.
So, some exchanges may choose to hold trading, while others are continuing to trade, and people can do arbitrage. How would that work? I don’t think it can. However, we’ve seen exchanges shut down when there’s too much activity.
There are circuit breakers in crypto, too. We don’t have to get deep into that, but there are some. They’re just different due to the different nature of how crypto trading works.
Typically, what [crypto] exchanges will do is de-lever everyone. In other words, they close all positions, and this is a way of intervening in the markets. Crypto exchanges do this when there’s leverage involved.
In traditional markets, they don’t have these. They have different mechanisms due to how collateral works in traditional markets. The exchange is basically on the hook for any loss that anybody can have. So, they have circuit breakers instead of what’s called auto deleveraging.
Now, how does the cycle model take all that? It just does because it studies the price action and includes all this intervention. Microeconomic intervention can also impact the cycles, and this is a big thing I’ve been writing about for many years, actually.
Macroeconomic intervention — in other words, money printing — does distort cycles. However, it distorts how much the cycle goes up during the up phase and how much it goes down during the down phase.
I have seen them very heavily distorted in the past 20 years, skewed to the upside — very, very skewed to the upside.
In other words, shallow corrections, extreme rallies.
And seeing that through the lens of my model, noticing this change in the way the cycles behave has actually led to ... it’s been an input in the way I see the world. I look at asset prices through the lens of my cycles model. My cycles model tells me, “Hey, these cycles appear distorted.” So then, I think, why might they be distorted? It must be the fact that they’re printing money.
The model has taught or showed me how big of an impact these policies are having on asset prices. Because if I compare a four-year cycle in the S&P 500 in the 21st century to the same cycle in the 18th and the 19th centuries, they’re completely different. And what was different back then is money was different. There was no intervention.
Chris:
So, you’re talking about the amplitude.
Juan:
Yes.
Chris:
The volatility, let’s say.
Juan:
The volatility of the cycle. Yeah.
Chris:
It’s high or low?
Juan:
Now, it’s lower.
Chris:
It’s lower now. Okay.
Juan:
It’s far lower now.
Chris:
Interesting.
Juan:
They have reduced volatility significantly, especially downside volatility. It’s basically nonexistent. And where a correction would take place over a year in the 19th century, now it takes one to two months, and then it’s done.
Chris:
And it’s not as severe, is that what you’re saying?
Juan:
Not nearly as severe.
Chris:
Because the central planning, they don’t want any kind of economic —
Juan:
They don’t want prices to fall.
Chris:
They want infinite growth some way.
Juan:
Exactly.
Chris:
Right.
Juan:
It’s typically ... You cannot allow deleveraging to take place because if market participants ...
Chris:
In a base system.
Juan:
... Deleverage... And in that base system, exactly.
Chris:
Absolutely.
Juan:
If you’re paying back debt, you’re destroying money. And if you destroy money, you destroy the economy. So, they can’t allow that to happen.
Chris:
That’s that whole financial weapons of mass destruction phrase that they use to describe the derivatives market — as being financial weapons of mass destruction. If they implode it, the collapse would be ungodly catastrophic.
Juan:
Exactly. So, it distorts the cycles.
Now, does this change the cycle? No. Does it change the analysis? No. Is it hard for the model to spot the cycle? No. I can still see them. You can still find the cycle. They may not be as good to trade for as, again, in the early 20th century. You could trade this four-year cycle perfectly and make a lot of money on the long side. But on the short side of the stock market, for example, you can’t anymore.
You’re better off just buying, maybe selling, when you’re anticipating the high in the four-year cycle and buying again when the low takes place. There’s no shorting. Shorting is dead.
Chris:
Okay. Well, in the traditional markets, I suppose?
Juan:
Yes.
Chris:
Yeah? In crypto, any good?
Juan:
I still think it’s pretty bad, simply due to the asymmetric returns of a long versus a short, you can make maybe 50%-60% on the short side of the market, but you can make tenfold on the long side of the market.
Chris:
Is this because crypto is in its hypergrowth phase?
Juan:
You risk adjusted returns. Yeah.
Chris:
Yeah, the probability of it going up is way higher than going down, even in a long term ... Even into those bear markets, the wind is blowing up at the minute, right?
Juan:
Based on what I’ve seen in crypto markets, if you want to go short, you would need to wait for the down phase of the longer cycle that I’ve seen, which is the four-year cycle.
I don’t think I mentioned that, but four 320-day cycles form a larger four-year cycle. This four-year cycle has been picked up by other analysts.
Chris:
Yes.
Juan:
They talk about this halving four-year cycle. We have discussed that here at Weiss, too … the four-year cycle. We talk about the halving cycle.
I want to make something clear: Nothing in my model has a halving cycle as an input. Specifically, the model and the logic of the model found this four-year cycle. It wasn’t like I said, “Well, we have the halving, so how about we plug this into the model?” No, I didn’t deal with that. The halving can go away ... Bitcoin can disappear and Ethereum (ETH, Tech/Adoption Grade “A-”) can replace it for a year, and [our model] will still have a four-year cycle.
Chris:
So, the model is not discriminating based on the nuances of the Bitcoin crypto asset. It’s just taking its price and treating it like any asset and looking at the price cycles.
Juan:
Nothing in the timing model that I have for crypto is specific to crypto.
Chris:
Right.
Juan:
No part of the code is specific to crypto. The logic is not specific to crypto. The rationale for how things work is not specific to crypto. You can apply the same logic to anything else.
Chris: So, the only thing you had to do was figure out the cycle lengths in crypto, that’s it?
Juan:
Right.
Chris:
And the model works just the same?
Juan:
Exactly.
Chris:
Okay, great.
Juan:
Yep.
Chris:
Now, this is probably a foregone conclusion. I was going to ask you, what were some of your favorite ways to track market cycles in traditional and crypto markets? The obvious answer to that is the cycles model that you’ve been working on for how many years?
Juan:
So, I started in 2012.
Chris:
Right. So ...
Juan:
So, it’s been about nine years now.
Chris:
Almost 10 years now. Right. Okay. But do you use any other indicators? You know, there are a million technical analysts out there that have a million different indicators to help you figure out what’s going to happen. Do you use any of that stuff?
Juan:
That’s a good question. I’m a purist. I just used the model. So, the model is very comprehensive. It’s very holistic in the sense that it’s able to explain most of what you see. By that, I don’t mean that markets are deterministic or that the model can tell you exactly what’s going to happen in the future. I mean that the price action you see can be described fully using the tools within the model.
In other words, anything else would be just extra. And yes, I have used other things in the past. For example, on Bitcoin or crypto assets in general, I will sometimes look at the flow in and out of exchanges. I do this because I happen to know that it correlates with a longer-term 320-day cycle — it correlates very neatly. So, I use that sentiment in the four-year cycle because I’ve seen it correlate.
In other words, sentiment tends to peak when the four-year cycle is peaking. So, people are the most negative around four-year lows. People tend to withdraw a lot of money from exchanges around 320-day highs. They tend to send money to exchanges to sell them around 320-day lows.
So, I will sometimes use auxiliary tools when they correlate, and they give another layer of analysis. If I find something, some fundamental factor that explains or correlates to a cycle that I know is there, I will use that sometimes as a leading indicator. But that really does depend on the market.
Chris:
But that’s like supplementary, right?
Juan:
Supplementary, yeah.
Chris:
The foundation is the cycles. That’s where everything begins.
Juan:
Let me put it this way. If I looked at the timing model and it said there’s a 320-day low here, and I looked at the flow into and out of exchanges and I saw nothing there, I would trust my model. I wouldn’t say, “Well, people are not withdrawing their assets, so the model must be wrong.” I will say, “Okay, maybe this indicator is not working because I trust my model.”
Chris:
Got you. If people want access to the insights from the model, there are a number of different Weiss products, like Weiss Crypto Investor? Although, Weiss Crypto Portfolio is the one that uses your timing model, right? Anything else?
Juan:
We’re working on a few more. The model has a lot of output. There are a lot of valuable tools that are provided by the model. [The Weiss Crypto Portfolio is] based around the timing model almost exclusively, and it’s very focused on trading, with some analysis there I write every week.
There are more things that the model is producing that we want to package into different product offerings. But we’re still working on those.
Off the top of my head, I would say the Weiss Crypto Investor also uses the model to some extent. But because we’ve been working for the past few months on a more robust version of the model, a more fully automated one, that will allow us to bring more things to our subscribers soon. And there will be more ways to look at the output of the model.
Chris:
In kind of a self —
Juan:
Exclusively trading-related.
Chris:
Right. In a way that’s like self-service? Is that what you mean?
Juan:
Yeah. One idea is you’re basically subscribed to a service that gives you some automated output that the model is already producing, but we’re not really offering that. I don’t know if that makes any sense.
Chris:
Totally. It’s in the works; let’s put it that way.
Okay. This is a great place to leave it. Juan, thanks very much for being on the Sunday Special once again.
Juan:
Thanks, Chris.
Chris:
I look forward to seeing you back again next time.
And that’s all for this edition of the Weiss Crypto Sunday Special on market cycles. Until our next one, it’s me, Chris Coney, saying bye for now.
