We had a pretty volatile week last week, with crude selling off pretty sharply early in the week. In this episode, we looked at energy backwardation, and Tracy educated us on what’s happening in those markets.
We also had some comments from Putin about a multipolar world. Albert talked through that.
And then on Friday, unfortunately, we saw the assassination of Japan’s former Prime Minister Abe. We talked about the Japan post-Abe and what that means for the region.
Putin’s Multi-Polar world
What’s ahead for next week?
This is the 25th episode of The Week Ahead, where experts talk about the week that just happened and what will most likely happen in the coming week.
0:00 Start 0:54 Key Themes for the week 1:28 Catalyst of the energy sell-off on Tuesday 5:44 Will we see more action in energy prices? 6:57 Is it cost-ineffective to make hydrogen with natgas prices? 8:11 Diesel 9:20 Vladimir Putin’s multipolar world. 13:44 Japan post-Abe 20:29 What’s for the week ahead?
Listen to the podcast version on Spotify here:
TN: Hi. Welcome to the Week Ahead. I’m Tony Nash. Thanks for joining us. I’m with Tracy and Albert today. Sam is away, but we are talking about a pretty volatile week this week. Before we get started, actually, please like and subscribe. Please ask any questions below, make any comments. We want to make sure this is interesting for you, so just let us know any additional info you want or comments. We’re happy to address those.
We had a pretty volatile week this week with crude selling off pretty sharply early in the week. So we’re going to look at energy backwardation, and Tracy is going to educate us all on what’s happening in those markets. We also had some comments out of Putin about a multipolar world. We’re going to have Albert talk through that. And then on Friday, unfortunately, we saw the assassination of Japan’s former Prime Minister Abe. So we’re going to talk about the Japan post Abe and what that means for Japan and the region.
So first let’s get into energy. Tracy, obviously, we had a big sell off in energy early in the week, and then we saw it come back later. What was really the catalyst for that energy sell off on Tuesday?
TS: What happened is that we started on July 5, right? We opened with low liquidity in the market in general. Then we saw a sell off in the general markets and commodities and risky assets that kind of exacerbated that trade. And then on the 6th, we saw a liquidation of a couple of very large positions in that market. And so fundamentally, basically, there is no reason for this sell off other than technicalities.
In fact, if we’re looking at this market, this spreads, the calendar spreads, which means month to month, were exploding higher during this entire move. That implies that the physical market at least, is very tight right now because you’re seeing backwardation increase significantly when we’re seeing a $10 move in ZZ, which is crazy.
TN: Can you tell us what that means? A $10 move in ZZ. What does that mean for the rest of us?
TS: If you’re talking about calendar schedule, we’re talking about monthly. So we can talk about the current front month is August. So we look at August, September, September to October, October to November, et cetera, et cetera. And once these spreads start exploding higher, that means that we’re seeing people want to dump oil in the front month market because that’s more lucrative than keeping it in storage.
So if I’m an investor and I’m looking and I want to invest in a backwardated market, I’m looking at a convex market that goes from right to left, and I’m going to invest in, say, a back month, and I want my investment to move higher…
TN: I’m investing further in the future.
TS: Right. That’s what it backwards. If you’re in a contangable market, we’re looking at the opposite situation, where you’re looking at a convex structure going from right to left, whereas if I invest in December, by the time my investment reaches Frontline X free, I’m losing money. I’m losing value in my investment.
TS: And so that’s how we kind of have to look at that situation.
TN: Yes. You had a great tweet this week explaining that with visuals.
TS: I did. It’s on Twitter, if anyone wants to see it.
TN: Exactly. We saw this in crude. We also saw it in a natural gas. Right?
TS: Yes. We’re kind of seeing a major pullback in many of the commodities markets. Right. We’re seeing a little bit of a bounce this week because we’re looking at China. China has recently announced we have one last announcement with $200 billion bond sale rate. So we’re looking at a lot of stimulus out of China that’s giving commodities the boost. Right now, we have to see I think the markets are still going to wait on, particularly the industrial and base medical markets are going to wait until we actually see some action in China to really see investment back into these markets after this huge goal.
TN: So nobody believes the China stimulus story right now. It’s kind of a show me the money period. Right. But once they do start to show the money, do you think we’ll see much more action in energy prices?
TS: I think you’ll see more action in metal prices than you will equity prices.
TN: Copper’s way off compared to, say, the last 18 months. But it’s not way off, given historical copper prices. If we go back before, say, Q1 of 2020, it’s kind of where it had been previously in the ballpark, at least. Right. So we haven’t necessarily reverted back to pre-COVID, necessarily. We’re just in the start-stop manufacturing world, and that’s what’s affecting base metals like copper. Is that fair to say?
TS: Oh, absolutely. If you look at, like, a monthly chart rather than looking at a five-minute chart, and the market has kind of just been consolidating, really, for the last two years, until we see a really big break above, say, $5, a really big break below $3, we’re still kind of in that consolidation zone.
TN: 3.50 to 4.50 kind of range. Interesting. Okay. Sorry, Albert.
AM: Yeah. I got a question for Tracy. Nat gas, as we’re talking, since we discussed it a little bit, that’s used to make hydrogen, if I’m not mistaken, and since the nat gas price seems to be elevated, isn’t that going to be a little bit too cost-ineffective to make hydrogen, which causes a diesel problem, if I’m not mistaken? I’m not sure about that. That’s what I’m asking.
TS: No, absolutely. I think that would be a problem. Looking forward. I think there’s a lot of problems if we’re looking at the hydrogen market. There’s still a lot of problems when we’re talking about taking this idea to actual fruition. Right. Because if you look at the hydrogen market, there’s like a rainbow of green hydrogen, blue hydrogen, this hydrogen, this hydrogen. But we really haven’t gotten to the point that can overtake, not gas the allure of the situation is that you can take hydrogen, mix it with nat gas, you can send it down the same pipeline, and that saves a lot of money.
TS: The situation is this is not a great idea in theory, but we’re just not there yet.
TN: Okay, got you. Albert’s, question about diesel. Diesel is not any less tight than it was a week or two ago. Right? In fact, that’s just as tight or tighter than it was, say, a couple of weeks ago or a month ago.
TS: Yeah, I think the diesel market is still very tight.
AM: Maintenance season starts, isn’t it? From September to November?
TS: Yes, we will start maintenance seasons.
TS: I would actually look for some of these refineries to maybe put off maintenance season. So that’s what I would watch to the maintenance season happen. And it’s happened before. If we have it such a tight market, we could see them putting off maintenance seasons. It’s not unheard of.
TN: Okay, so hurricane season and maintenance season are upon us, but we may see at least maintenance season for all of us.
TS: Oh, not I just moved to Florida.
TN: Good luck with that. I’m in Texas. We don’t get as many of you, but it’ll be a fun season for you.
Okay, let’s move on, guys, to some comments out of Putin this week. Vladimir Putin had some comments about us, the multipolar world becoming more and more of reality. We heard this ten years ago. We heard this 20 years ago, and it came up again this week. So, Albert, can you kind of let us know what’s going on there?
AM: Tony, I’ve used this multipolar example for the US. Dollar dominance I got for years now. And the fact of the matter is, we are not in a multipolar world. We are not even going into multipolar world.
People are confusing a little bit of weakness in the US. Leadership and errors and decision making, foreign policy for multipolars, it’s just a multipolarity, and it’s just not the case for the world to be in a multipolar scenario, you would need multiple countries with equal militaries and economies. We are nowhere near that.
The Russian economy is 2.5 trillion. The American economy is pushing 30 trillion. This is just a joke by Vladimir Putin. Simply undermine the US dominance both in the world stage and the dollar.
TN: Aside from some dumpster pundits who write for The Atlantic or whatever, who believes that nonsense?
AM: A lot of Europhiles that want to see the United States take a step down, they can do it. A lot of crypto guys, a lot of gold guys. These guys have to make that argument, because without multipolarity, you cannot have a neutral reserve asset to settle trade. And that’s just the fact of the matter.
The problem becomes, if you have a multipolar world, you’re on the verge of another world war, because there always has to be one alpha that takes hold of the system. You just can’t have equal people.
TN: And the cost of the transaction? Cost? The cost of trade, everything goes up. If you have multiple rights go up, everything goes up.
AM: It’s completely unstable.
TS: Inflation from other countries to other countries.
TN: The world is built on China exporting deflation. Has been for 15, 20 years. And it will continue. If they could just keep their ports open, it will continue. And it makes people happy. Right.
AM: No, you’re right. That’s just the way our system works right now, with the dollar underpinning all of it. It’s the lifeblood that makes trade work. And people are not going to like it. But I promise you, no one alive today is going to see anything other.
TN: So let me just take a step back. Who does he think the polls are? Russia, China and the US? Or Germany or something?
AM: He’s trying to make an assumption to say that Russia and China are the new contenders to the United States. The problem with that is they don’t have military power projection globally like the United States does. They can’t even invade Ukraine. China can’t even invade Taiwan. Otherwise they would have taken it if they’ve it could have. This is the world we live.
TN: Yeah. Russia can stir up problems in Libya or the Middle East or whatever.
AM: There’s no question that they can stir up problems and they can fill in gap vacuums that we leave right, unintentionally, unintentionally. But they cannot hold that territory. They cannot force changes in governments like the United States did.
TN: And every time I hear somebody talk about the Belt and Road as a sign of China’s dominance, it reminds me of Napoleon’s march to Russia. Right? I mean, they’re spreading themselves so thin. They can’t keep that up.
AM: They can’t. That’s perfect example to do that, to make that thing actually successful, you need to back that up to secure your trade line, trade with the military. Right. China has like, what, two military bases outside of China? Like one in Djibouti and something else. I mean, they can’t send ships over to their armor.
AM: Yeah. This is beyond a joke to me. I don’t take anybody seriously that even brings this part up, right. Vladimir Putin included.
TN: That’s good. So anybody watching this, if you have an alternative view, let us know in the comments. Honestly, we’d love to hear it. We just want to hear some credible.
TS: Put your notes in the comments.
TN: Yes, absolutely. Okay. Now, finally today I woke up in the US to the really tragic news of Japan’s foreign Prime Minister Abe, being assassinated.
I saw Abe in his first stint as PM in the mid 2000s. And then when he came back in, in 2013, and with the Abenomics plan, which was really difficult to pull off, ultimately successfully. The guy was smart. He was all about Japan. He’s all about Japan recovering, all about Japan being competitive. I put a picture up of Abe shaking hands with Prime Minister Modi of India. Japan and India were very tight. A lot of Japanese investment going to India, a lot of partnership across those two countries and in Africa, both to defend against China in Asia and other parts of the world. So Prime Minister Abe will be missed.
I think what Abe did partly was bring back Japan’s ability to defend itself by passing a constitutional change that allowed the Japanese military to defend itself where previously it wasn’t even allowed to do that. So there’s a lot of dignity that Japan kind of got back, and we can rub Japan’s nose in World War II for eternity, but it’s not going to be constructive. What happened, happened. They’ve paid their dues, and that’s kind of what Abe said, look, we paid our dues, we’re going to move on now and join the 21st century. And that’s what Japan did.
So I’m just curious to get your thoughts, guys, on Japan post Abe. What do you see as of course they moved on to another prime minister. Japan has already moved on from the Abe government. He wasn’t a sitting prime minister. But what do you see kind of the challenges of Japan’s role in Asia particularly, but also in the world post Abe?
AM: I think the most pressing issue for Japan would be contending with China, both militarily and economically. Abe was, like you said, brilliant statesman and patriot for the Japanese people. So he’s going to be sorely missed. And it’s not just he’s going to be missed, but his cabinet and the people that his network is going to be missed because they’re losing a big part of what he brought to the table in terms of strategy and ideology. It was a big shift.
I think that the Japanese are probably going to struggle for strategy in the next five to ten years. And it’s a sad thing, but I’m sure the Japanese, they’re resilient people and they’ll move on and they’ll recover.
TS: No, I absolutely agree with what Albert said. I think the thing is that people are painting him, the media right now, in particular the Western media, painting them with some villain, which is very interesting to me. And I think that people should really just look at his legacy and respect what he’s done instead of jumping on the bandwagon.
TN: So they’re portraying him as some ultra nationalist, but he’s as ultra nationalist as Modi as in India, or Jokowi is in Indonesia, or Lee is in Singapore, you name it. Tsai Ing-wen in Taiwan. It’s an Asian direction now. Right. And has been for the last ten to 15 years.
AM: Yeah. The media also, Tony, is desperate to not allow any center right or even right nationalist figures be murderers or looked up upon. They just can’t stomach it. They just can’t help themselves to demonize a person that is absolutely unjustifiably demonized by being called an ultra-nationalist and even worse, by the NPR.
NPR had two other headlines that they had to delete because it was just so atrocious. This is a.. And Modi, Abe, I don’t want to put Victor Orban into that, but all these right leaning leaders just get attacked and the media can’t help it.
TN: Right, yeah. I think from an economic plan, if we look at what Abe did with Abenomics, of course, the Japanese Central Bank is kind of “independent,” right. But they really took the JPY from kind of 76 to the dollar to, say, 120 to the dollar, and it really allowed Japanese manufacturing to be competitive again. Right.
And it took somebody with that clarity of economic vision, as well as the clarity of, say, the military vision and political vision, to be able to pull off what they did. And in terms of, say, energy sustainability under Abe, they also created much deeper relationships in the Middle East with places like Qatar, UAE.
TS: And they also looked forward to nuclear, where you looked at the west was looking to shut things down, Abe was looking to invest in nuclear projects. You’re looking for energy security, energy going forward. There are a lot of things that he did to advance that sector in Japan, which is admirable.
TN: Right. Albert if we take a US perspective on this? The US has worked hard to kind of hold a line against China. Do you think with the mediocre leadership we have in the US right now, do you think it’s possible that some of that US say coalition falls apart a little bit? Or do you think we just kind of take a breather and then it resumes based on the institutional stamina of parts of the Japanese government?
AM: That’s a great question, Tony. That’s actually a really good question. And I think where we have to look for we have to separate the Biden foreign policy cabinet with the Pentagon. Because the Pentagon is actually leading this charge for the Pacific with Japan and Australia in charge. I really don’t think that the Japanese are going to take a step back or the US is going to take a step back. I think the system is pretty much, the train has already left the station and it’s rolling.
There might be an argument from the opposition in Japan, but I don’t think. That it’s going to take hold to derail this new initiative by the US and the Pacific.
TN: Great, that’s good to hear. Okay, guys. Hey, on that somber note, we’ll end it, but let’s look at the week ahead. Guys, what are you looking for in the week ahead? We’ve had this real turnaround this week. What do you see going into next week? Do you see things calming a bit?
We saw it coming into Friday. Things really turn up in US markets and in commodity markets. Do we see things stabilizing a bit going into the Fed meeting after we’ve had some Fed comments late this week?
AM: I want to see the comments of where they might signal a 50 basis point rate hike versus a 75. I absolutely believe 75 points is coming just from the jobs data that they posted. It was obviously massaged a little bit.
TN: Just a little bit.
AM: Of course it is. Yeah, but this was a good one. And then the revision too, and it just seems to me that they want another 75 basis point rate hike.
TN: To really kill it?
AM: They got to tackle inflation. I mean, they’re looking at 8.8 on the next CPI, which is just.. And you’re staring on the barrel at 9% and 9.2 and 9.3 in the coming months, which is absolutely a political nuclear bomb that goes off.
TN: Okay, Tracy, what are you looking for in the next week especially in commodities?
TS: Yeah, I mean, I agree we probably will see 75 after non farm payroll this week, which I was looking for a clue kind of are we going to get 50, are we going to get 75? It looks like 75 for sure.
So looking in the coming weeks, I’m really looking to China right now and to see what comes to fruition with these sort of stimulus plans. What does that do to the base in industrial medals markets? And I think those are the two things that you should be focusing on right now, particularly if you’re invested in commodities markets.
TN: Very good. Okay. Yeah. I’m kind of hoping they give in to 50, but I’m not hopeful. I do think they’ll on the kind of conservative hawkish side and go 75. But if they can pick up the bat phone and talk to China, and the China guys will unload a dump truck of cash over the next week or so, then I think they’ll be a little bit lighter and do 50 basis points. But I think a lot of it depends on China ECB. They can’t get their act together, so there’s nothing ECB can do to really help.
And Europe is in so much trouble that it doesn’t really matter what they do. They have huge problems anyway. So. I think you’re right. And tell me what you think about this. But I don’t necessarily think we see massive chop. I think we see just a lot of fairly sideways moved for the next week or so.
AM: I would be wary if we jumped up to 4000 or even, like, 3970. I think a rug pull would be in an order right after that. That’s what they do. They bowl everybody up and then pull the rug out.
TS: Yeah. After this big move down in the oil market, in particular, because we did have sort of a flow event coupled with a couple of large funds kind of workforce to liquidate. So I could see that we still could go a little bit higher next week. Sideways to higher next week.
TN: Very good. Okay, guys, be interesting to see. Thanks for joining us. Thanks very much. Have a great weekend. And have a great week ahead.
TN: Very good. Thank you, guys.
AM: I struggle with the headache through that whole thing.
MG: The Lead Lag Report joining us for the hour here is Tony Nash of Complete Intelligence has found a lot of people that I respect following. Tony, I saw a few people saying they were excited to hear what Tony has to say. So hopefully we’ll have a good conversation here.
Tony for those who aren’t familiar with your background talk about who you are how’d you get involved in the data side of markets and forecasting in general. And what you’re doing with Complete Intelligence.
TN: Sure, Michael. First of all, thanks for having me. I have followed you for probably 10 or 15 years.
MG: I am very sorry for that I am very very sorry for that.
TN: But yeah so, I got involved in data way back in the late 90s when I was in Silicon Valley and I built a couple of research firms focused on technology businesses. I then took about probably eight years to become an operator. I did a turnaround in Asia of a telecom firm. I built a firm in Sri Lanka during the Civil War and then I started down the research front again. I was the Global Head of Research for the Economist and I was the Asia Head of Consulting for a company called IHS Markit which is now owned by S&P and then after that I started Complete Intelligence.
So, you know my background is really all about data but it’s also all about understanding the operational context of that data. And I think it’s very hard for people to really understand what data means without understanding how people use it.
MG: Okay. So that’s maybe a good direction to start with that point about context with data because I think part of that context is understanding what domains data is more appropriate for forecasting and others. Right? So, I always made this argument that there are certain domains in particular when it comes to, I would argue investing that have sort of a chaotic system element to them. Right? Where small changes can have ripple effects. So, it’s hard to necessarily to sort of make a direct link between a strong set of variables and the actual outcome because there’s always a degree of randomness. Whereas, something that’s more scientific right that doesn’t have that kind of chaos theory element is it’s clearer.
So, talk about that point about context when it comes to looking at data. And again, the kind of domains where data is more appropriate to really have more conviction in than others.
TN: Yeah. Okay. So, that’s a great place to start. So, the first thing I would say is take every macro variable that you know of and throw it out the window. It’s all garbage data 100 of it. Okay? I would never trade based on macro data.
We’ve tested macro data over the years and it’s just garbage. It doesn’t matter the country. You know we hear people saying that China makes up their data. Well, that may be true you can kind of fill in the blank on almost any country because I don’t know how much you guys understand about macro data. But it is not market clearing data. Okay? Like an equity price or a commodity price.
Macroeconomic data is purely academic made-up data that is a proxy for activity. It’s a second or third derivative of actual activity by the time you see, say, a CPI print which is coming out tomorrow. Right? And it’s late and it’s really all not all that meaningful. So, I wouldn’t really make a trade or put a strategy together based on macro data even historical macro data. Every OECD country revises their data by what four times or something.
So, you see, a print for CPI data tomorrow that’s a preliminary print and that’s revised several times before it’s put on quote-unquote actual. And so, you know, you really can’t make decisions using macroeconomic data beyond a directional decision. Okay? So, if you follow me on Twitter, you see I’m very critical macro data all the time. I’m very sarcastic about it.
I think the more specific you can get… You know if you have to look at say national data or macroeconomic data, I would look at very low-level data the more specific you can get the better. Things like household surveys or you know communist and socialist countries. Chinese data at the very specific level can be very interesting. Okay? Government data the high-level data in every country I consider it garbage data in every country. So, you’re looking at very low-level very specific government or multilateral data, that’s interesting.
The closer you get to market clearing data the better because that’s a real price. Right? A real price history on stuff is better and company data is the best. And of course, company data is revised at times but that really helps you understand what’s happening at the kind of firm level. And what’s happening at the transaction level. So, you know, those are the kind of hierarchies of data that I would look at.
MG: So, okay this is a great. That’s a great point you mentioned that it’s you said very these variables is macro variables they’re proxies for activity. Right? They’re really more proxies for narratives. Right? Because and that’s where I think… You mentioned sarcasm almost 99 of my tweets at this point are sarcasm because when Rome is burning, what else I’m not going to do except joke about it. Right? Because I can’t change anything. Right?
So, and to that point I share a lot of that cynicism around data that people will often reference in the financial media that sounds really interesting, sounds like it’s predictive but when you actually test it to your point, you throw it out because it doesn’t work. Right? There’s no real predictive element to it.
So, we’ll get into some of the predictive stuff that you talk about but I want to hit a little bit on this market clearing phrase you kept on using. Explain what you mean by market clearing.
TN: Data is where there is a buyer and a seller.
MG: To actual prices of some asset class or something like that.
TN: Yep. That’s right.
MG: Okay. So, that makes sense. Okay. Now again I go back to the certain domains that data is more clear in terms of cause and effect and getting a sense of probabilities the challenge with markets. As we know is that the probabilities change second by second because not only does that mean meaningless data change second by second but the market clearing data changes second by second. Right? Going back to that point.
So, with what you do with Complete Intelligence, talk us through a little bit. What are some of the variables that you tend to find have some predictive power? And how do you think about confidence when it comes to any kind of decision made based on those variables?
TN: Sure. Okay. So, before I do that let me get into why I started Complete Intelligence because if none of you have started a firm before don’t do it. It’s really really hard so…
MG: From the people in the back because I got to tell you I’m an entrepreneur, I’m going through. And all you got is people on Twitter kicking you when you’re down when it’s the small sample anyway.
TN: Absolutely. So, I was where I had worked for two very large research firms The Economist and IHS Markit. And I saw that both of them claimed to have very detailed and intricate models. Okay? Of the global economy industries, whatever. Okay? For all of the interior models. And I have never spoken with a global research firm a data firm that is different from this. And if I’m wrong then somebody please correct me. But at the end of that whole model pipeline is somebody who says “no that’s a little bit too high” or “a little bit too low” and they change the number. Okay? To whatever they wanted it to be in the first place. So, and I tell you 100% of research firms out there with forecasts today have a manual process at the end of their quote-unquote model. A 100% of them. Again, if there’s somebody else that doesn’t do that, I am happy to be corrected. Okay? But I had done that for a decade and I felt like a hypocrite when I would talk to clients.
So, I started Complete Intelligence because I wanted to build a 100% machine driven forecasts across economics, across market, across equities, across commodities, across currencies. Okay? And we’ve done that. So, we have a multi-phase, multi-layer machine learning process that takes in billions of data items. We’re running trillions of calculations every week when we reforecast our data. Right? Now the interval of our forecast is monthly interval forecast. So, if people looking at daily prices that’s not what we’re doing now. Okay? We will be launching daily interval forecasts. I would say probably before the end of the year to be conservative but we’re doing monthly interval forecasts now.
Why is everything I’ve said is meaningless unless we measure our error. Okay? So, for every forecast that we do. And if you log into our website, you can see whether it’s the gold price, the S&P 500, USD, JPY, molybdenum or whatever. We track our error for every month, for everything that we do. Okay? So, if you want to understand your risk associated with using our data it’s there right in front of you with the error calculations. Okay? It’s only fair, If I’m gonna say sell you a forecast, you should be able to understand how wrong we’ve been in the past, before you use that as a decision-making input.
MG: Well, maybe just add some framework on that because I think that’s interesting. So, what you call error I call luck. Right? Because luck is both good or bad. I always make that point that with any equation any set of variables you’re going to have that error is the luck component that you can’t control. And that doesn’t necessarily mean that the equation is wrong. Right? It’s just means that for whatever reason that error in that moment in time was higher or lower than you might otherwise want. Okay?
TN: There is no such thing as zero error. And anybody who tells you that they have zero error is obviously they’re an economist and they don’t understand how markets work. So, there is always error in every calculation.
So, the reason we track error is because that serves as a feedback loop into our machine learning process. Okay? And we have feedback loops every week as we and what we’re doing right now is every Friday end of day. We will download global data process over the weekend have a new forecast on Monday morning. Okay? And so all of that error whether it’s near-term error, short-term error or say medium-term error, we feed that all back in to help correct and understand what’s going on within our process. And we have like I said, we have a multi-phase process in our machine learning platform. So, error is simply understanding the risk associated with using with using our platform.
MG: Right, which is basically how apt is a thing that you’re forecasting to that error which is again luck good or bad. I’m trying to put in sort of a qualitative framework also because I think… Yeah, there’s errors in life obviously, too. Right? And so, when they’re good or bad. But you know those elements.
TN: Right. But here’s what I would and I don’t know, I don’t want to dispute this too much but I think there is. So, you use the word luck and that’s fine but I think luck has a bit to do with the human element of a decision. Okay? We’re using math and code there’s zero human interaction with the data and with the process. And so, I wouldn’t necessarily call it luck. I mean, it literally is error like our algorithms got it wrong. So, if you want to call luck that’s absolutely fine but I would say luck is more of a human say an outcome associated with a human decision. More than something that’s machine driven that’s iterating. Again, we’re doing trillions of calculations every week to get our forecasts out there.
MG: Yeah, no that’s fair and maybe for the audience, Tony. Explain what machine learning is now.
MG: I once developed an app called “How Edition”. I was having dinner with the head developer once and he said he just came back from a conference about machine learning and he was just basically well, having drinks with me laughing and joking saying everybody use this term machine learning but it’s really just regression analysis. Right? So, talk about machine learning what is actual machine learning? How important is recent data to changes in the regression? Because I assume that’s part of the sort of dynamic nature of what you do just kind of riff on that for a bit.
TN: Okay. So, when I first started Complete Intelligence, I was really cynical about AI. And I spoke to somebody in Silicon Valley and asked the same question: what is AI? And this person said “Well AI is everything from a basic I say, quadratic equation upward.” I’m not necessarily sure that I agree that something that simple would be considered artificial intelligence. What we’re really doing with machine learning is there are really three basic phases. Okay? You have a preprocess which is looking at your data to understand things like anomalies, missing data, weird behavior, these sorts of things. Okay? So, that’s the first phase that we look at to be honest that’s the hardest one to get right. Okay?
A lot of people want to talk about the forecasting methodologies and the forecasting algorithms. That’s great and that’s the sexy part of ML. But really the conditioning and the pre-process is the is the hardest part and it’s the most necessary part. Okay? When we then go into the forecasting aspect of it, we’re using what’s called an ensemble approach. So, we have a number of algorithms that we use and let’s say they’re 15 algorithms. Okay? That we use we’re looking at a potential combinatorial approach of any individual or combination of those algorithms based on the time horizon that we’re forecasting. Okay?
So, we’re not saying a simple regression is the way to go we’re saying there may be a neural network approach, there may be a neural network approach in combination with some sort of arima approach. We’re saying something like that. Right? And so, we test all of those permutations for every historical period that we’re looking at.
So, I think traditionally when I look back at kind of quote-unquote building models in excel, we would build a formula and that formula was fairly static. Okay? And every time you did say a crude oil forecast you had this static formula that you set your data against and a number came out. We don’t have static formulas at all.
To forecast crude oil every single week we start at obviously understanding what we did in the past but also re-testing and re-weighting every single algorithmic approach that we have and then recombining them based upon the activity that happened on a daily basis in that previous week. And in the history. Okay?
So, that’s phase two the forecasting approach and then phase three is the post process. Right? And so, the post process is understanding the forecast output. Is it a flat line? Right? If it’s a flat line then there’s something wrong. Is it a straight line up? Then that there’s something you know… those are to use some extremes. Right? But you know we have to test the output to understand if it’s reasonable. Right? So, it’s really an automated gut check on the reasonableness of the outcome and then we’ll go back and correct outliers potentially reforecast and then we’ll publish. Okay?
So, there are really three phases to what we do and I would think three phases to most machine learning approaches. And so, when we talk about machine learning that’s really what we’re talking about is that that really generally three-phase process and then the feedback loop that always goes back into that.
MG: Yeah. No that makes sense. Let’s get…
TN: That’s really boring after a while.
MG: No, no, no but I think that’s it’s part of what I want to do with these spaces is try to get people to understand you know beyond sort of just the headline or the thing that is thrown out there. As a term to what does that actually mean in practice you don’t have to know it fully in depth the way the that you do. But I think having that context is important.
TN: I would say on the idea generation side and on the risk management side right now. Okay? Now the other thing that I didn’t cover is obviously we’re doing markets but we also do… we use our platform to automate the budgeting process within enterprises. Okay? So, we work with very large organizations and the budget process within these large organizations can take anywhere from say four to six months. And they take hundreds of people. And so, we take that down to really interacting with one person in that organization and we do it in say less than 24 hours. And we build them a continuous budget every month.
Once accounting close happens we get their new data and then we send them a new say 18-month forward-looking forecast for them. So, their FPA team doesn’t have to dig around and beg people for information and all that stuff. So, some of this is on the firm event could be on the firm evaluation side, as well. Right? How will the firm perform? Nobody’s using us for that but the firms themselves are using that to help them automate their budgeting process. So, some of that could be on this a filtering side and the idea generation side, as well.
So, we do not force our own GL structure onto the clients. We integrate directly with their SAP or Oracle or other ERP database. We take on their GL structure at whatever levels they want. We have found that there is very little deterioration from say, the second or third level GL to say the sixth or seventh level GL, in terms of the accuracy of our forecast. And when we started doing this it really surprised me. We do a say a team level forecast for 10, 12 billion organizations, six layers down within their GL. And we see very little deterioration when we go down six levels than when we do it at say two levels. Which is you know it really to me it speaks to the robustness of our process but would we consider Anaplan a competitor not really, they’re not necessarily doing the kind of a budget automation that we’re doing at least, that I’m aware of. I know that there are guys like Hyperion who do what we’re doing but again their sophistication isn’t necessarily. What we’re doing and they do a great job and Hyperion is a great organization. I think Oracle gave them a new name now but they’re not necessarily using the same machine learning approaches that we’re using. And our clients have told us that they don’t get the same result with using that type of say ERP originated or ERP add-on budgeting process.
Yep. So, I would say we can’t we can do company-specific information for a customer if that’s what they want. Okay? We don’t necessarily have that on our platform today aside from say individual ticker symbols. Okay? But we’re not forecasting say the P&L of Apple or something like that or the balance sheet of Apple. Something we could do in a pretty straightforward manner but we do that on a customer-by-customer basis.
So, what we’re forecasting right now are currency pairs, commodities about 120 commodities and global equity indices. Okay? We are Beta testing individual equity tickers and we probably won’t introduce those fully on the platform until we have our daily interval forecast ready to go to market. But those are still we’re still working some kinks out of those and we’ll have those ready probably within a few months.
MG: Okay. So, let’s talk about commodities here for a bit tonight. Obviously, this is where a lot of people’s attention has gone to. What kind of variables and I know you said you have a whole bunch of variables that are being incorporated here but are there certain variables in particular when it comes to oil and other commodities that have a higher predictive power than others.
TN: There are I think one of the stories that I tell pretty often and this really shocks people is when we look at things like gold. Okay? I’m not trying to deflect from your oral question but just to you know we’ve spoken with the number of sugar traders over the years. Okay? And so, we tell them that say the gold price and the sugar price there may not necessarily be a say short term say correlation there but there is a lot of predictive capability there and we talk them through why. And I think the thing that we get out of the machine learning approach and we cast a wide net. We’re not forcing correlations is that we’ll find some unexpected say drivers. Although drivers implies a causal nature and we’re not trying to imply causality anywhere. Okay?
We’re looking at kind of co-movement in markets over time and understanding how things work in a lead lag basis with some sort of indirect causality as well as say a T0 or current state movement. So, with crude oil you know there are so many supply side factors that are impacting that price right now, that I can’t necessarily point to say another commodity that is having an impact on that. It really is a lot of the supply side and sentimental factors that are impacting those prices right now.
MG: That makes a lot of sense. And I’m curious how did you mention it’s I think the intervals once a month. Right? So, given the speed with which inflation has moved and yields have moved how does a machine learning process adapt to sudden spikes or massive deltas in in variable movement. Right? Because there’s always a degree of randomness going back to error. Right? And you can make an argument that the larger move is the that may actually be more error but I think that’s an interesting discussion.
TN: So, I’ll tell you where we were say two years ago when 2020 hit versus today. Okay? So, in March of 2020, April 2020 everything fell apart. I don’t think there were any models that caught what was going to happen. It was an exogenous event that hit markets and it happened very quickly. So, in June, I was talking with someone who is with one of the largest software companies in the world and they said “Hey has your AI caught up to markets yet because ours is still lost” And you guys would be shocked if I told you who this was because you would expect them to know exactly what’s going to happen before it happened. Okay? I’ll be honest I think it was all of them but the reality is you know Michael you where you were saying that ML is just regression analysis.
I think a lot of the large firms that are doing time series forecasting really are looking at regression and derivatives of regression as kind of their only approaches because it works a lot of the time. Right? So, we had about a two-month delay at that point and part of it was because… So, by June we had caught up to the market. And we had started in February to iterate twice a month, we were doing once a month; I hope you guys can understand with machine learning two factors are we’re always adjusting our algorithms. Okay? We’re always incorporating new algorithms. We’re always you know making sure that we can keep up with markets because you cannot be static in machine learning. Okay? The other thing is we’re always adding capacity why? Because we have to iterate again and again and again to make sure that we understand the changes in markets. Okay?
So, at that time we were only iterating twice a month and so it took us a while to catch up. Guys like this major technology firm and other major technology firms they just couldn’t figure it out. And I suspect that some of them probably manually intervened to ensure that their models caught up with markets. I don’t want to accuse any individual company but that temptation is always there. Especially, for people who don’t report their error. The temptation is always there for people to manually intervene in their forecast process. Okay?
So, now, today if we look for example at how are we catching changes in markets. Okay? So, if I look at the S&P 500 for April for example, our error rate for the S&P 500 for April I think was 0.6 percent. Okay? Now in May it changed it deteriorated a little bit to I think four or six percent, I’m sorry I don’t remember the exact number offhand but it deteriorated. Right? But you know when there are dramatic changes because we’re iterating at least once a week, if not twice a week we’re catching those inflections much much faster. And what we’re having to do, and this is a function of the liquidity adjustments, is where in the past you could have a trend and adjust for that trend and account for that trend. We’re really having to our algorithms are having to select more methodologies with recency bias because we’re seeing kind of micro volatility in markets. And so again…
MG: So, kind of like the difference between a simple moving average versus like an exponential moving average. Right? Where you’re waiting the more recent data sooner.
TN: It could be. Yeah.
TN: Yeah. That’s a very very simple approach but yeah it would be something like that, that’s right. Yeah. What so when we work with enterprise customers that level of engagement is very tight because when we’re getting kind of the full set of financial data from a client obviously, they’re very vested in that process. So, that’s different from say a small portfolio manager subscribing to RCF futures product where we’re doing forecasts and they have their own risk process in place. And they can do whatever they want with it. Right? But again, with our enterprise clients we are measuring our error so they can see the result of our continuous budgeting process. Okay?
So, if we’re doing let’s say, we launch with a customer in May, they close their mate books in June get them over to us redo our forecast and send it over to them and let them know what our error rate was in May. Okay? So, they can decide how we’re doing by department, by team, by product, by whatever based upon the error rates that we’re giving at every line item. Okay? So, they can select and we’re not doing kind of capital projects budgets we’re doing business as usual budgets so they can decide what they want to take and what they don’t want to take. It’s really up to them but we do talk through that with them and then over time they just start to understand how we work and take it on within their own internal process.
MG: So, back a little bit Tony. So, you mentioned you do this machine learning forecasting work when it comes to broad economics, markets and currency; of those three which has the most variability and randomness in other words which tends to have a higher error? Whenever you do any kind of machine learning to try to forecast what comes next?
TN: I would say it depends on the equity market but probably equity markets when there are exogenous shocks. So, our error for April of 2020 again, we don’t hide this from anybody it was not good but it wasn’t good for anybody. Right? And so, but in general it depends on the equity market but some of the emerging equity markets, EM equity markets are pretty volatile.
We do have some commodities like say rhodium for example. Okay? Pretty illiquid market, pretty small base of people who trade it and highly volatile. So, something like rhodium over the years our air rates there have not necessarily been something that we’re telling people to use that as a basis to trade but obviously, it’s a hard problem. Right? And so, we’re iterating that through our ML process and looking at highly volatile commodities is something that we focus on and work to improve those error rates.
MG: Here, I hope you find this to be an interesting conversation because I think it’s a part of the of the way of looking at markets, which not too many people are themselves maybe using but is worth sort of considering. Because I always make a point that nobody can predict the future but we all have to take actions based on that unknowable future. So, to the extent that there might be some data or some conclusions that at least are looking at variables that historically have some degree of predictive power. It doesn’t guarantee that you’re going to necessarily be better off but at least you have something to hang your hat on. Right? I think that’s kind of an aspect to investing here.
Now, I want to go a little bit Tony to what you mentioned earlier you had lived abroad for a while in Europe. And when I was starting to record these spaces to put up on my YouTube channel the first one, I did that on was with Dan Arvis and the topic of that space was around this sort of new world order that seemed to be shaping up. I want you to just talk from a geopolitical perspective how you’re viewing perhaps changing alliances because of Russia, Ukraine. And maybe even dovetail that a little bit into the machine learning side because geopolitics is a variable. Which is probably quite vault in some periods.
TN: Yeah, absolutely. Okay. So, with the evolving geopolitical order I would say rather than kind of picking countries and saying it’s lining up against x country or lining up with x country or what country. I would say we’ve entered an era of opportunistic geopolitics. Okay? We had the cold war where we had a fairly static order where people were with either red team or blue team. That changed in the 90s of course, where you kind of had the kind of the superpower and that’s been changing over the last say 15 years with say, China allegedly becoming kind of stronger and so on and so forth. So, but we’ve entered a fairly chaotic era with say opportunistic macroeconomic relation or sorry, geopolitical relationships and I think one of the kinds of top relationships that is purely opportunistic today is the China-Russia relationship.
And so, there’s a lot of talk about China and Russia having this amazing new relationship and they’re deep. And they’re gonna go to war together or whatever. We’ve seen over the past say three, four months that’s just not the case. And I’ve been saying this for years just for a kind of people’s background. Actually, advised the Chinese government the NDRC which is the economic planning unit of the central government on a product or on an initiative called the belt and road initiative. Okay? I did that for two years. I was in and out of Beijing. I never took a dime for it. I never took expense reimbursement just to be clear, I’m not a CCP kind of pawn. But my view was, if the Chinese Government is spending a trillion dollars, I want to see if I can impact kind of good spend for that. So, I have seen the inside of the Chinese Government and how it works and I also in the 80s and 90s spoke Russian and studied a lot on the Russian Government and have a good idea about how totalitarian governments work.
So, I think in general if we thought America first was offensive in the last administration then you really don’t want to learn about Chinese politics and you really don’t want to learn about Russian politics because they make America first look like kindergarten. And so, whenever you have ultra-ultra-nationalistic politics, any diplomatic relationship is an opportunistic relationship. And I always ask people who claim to be China experts but say please tell me and name one Chinese ally. Give me one ally of China and you can’t, North Korea, Pakistan. I mean, who is an ally of China there isn’t an ally of China. There is a transactional opportunistic relationship with China but there is not an ally with China.
And so, from a geopolitical perspective if you take that backdrop looking at what’s happening in the world today it makes a whole lot more sense. And a lot of the doomsayers out there saying China is going to fall and it’s going to have this catastrophic impact. And all this other stuff, the opportunism that we see at the nation-state level pervades into the bureaucracy. So, the bureaucracy we hear about Xi Jinping. And Xi Jinping is almost a fictional character. I hate to be that extreme on it but there is the aura of Xi Jinping and there is the reality of Xi Jinping, just a guy, he’s not Mao Zedong. He doesn’t have the power that supposed western Chinese experts claim that he has. He’s just a guy. Okay?
And so, the relationships within the Chinese bureaucracy are purely transactional and they are purely opportunistic. So again, if you take that perspective and you look at what’s happening in geopolitics, hopefully you can see things through a different lens.
MG: Now, I’m glad you’re framing that in those terms because I think it’s very hard for people to really understand some of these dynamics when it’s almost presented like a like the story for a movie. Right? For what could be a conflict to come by the media because and it’s almost overly simplified. Right? When you hear this type of talk. So again, I want to go back into how does that dovetail into actual data. Right? Maybe it doesn’t at all. When you have some of these dynamics and you talk about market clearing data, you’re going to probably see mark movement somewhat respond off of geopolitical changes. Talk about anything that you’ve kind of seen as far as that goes and how should investors consider geopolitical risk or maybe not consider geopolitical risk?
TN: Yeah, I think, well when you see geopolitical adjustments today all that really is… I don’t mean overly simplified but it’s a risk calibration. Right? So, you know Russia invades Ukraine, that’s really a risk calibration. How much risk do we want to accept and then what opportunities are there? Right?
So, when you hear about China, you have to look at what risk is China willing to accept for actions that it takes? Keeping in mind that China has a very complicated domestic political environment with COVID shutdown, lockdowns and all of this stuff. So, having worked with and known some really smart Chinese bureaucrats over the years, these guys are very concerned with the domestic environment. And I don’t although there are idiot you know generals and economists here and there who say really stupid stuff about China should take over TSMC and China should invade Taiwan, these sorts of things. My conversations over the years have been with very pragmatic and professional individuals within the bureaucracy.
So, do I agree with their policies? Not a lot of them but they are well thought out in general. So, I think just because we hear talk from some journalist in Beijing who lives a very sheltered life about some potential thing that may happen. I don’t think we necessarily need to calibrate our risk based on the day-to-day story flow. I think we need to look at like… so there’s a… I’m sure you all know who Leland Miller is in China beige book like?
MG: Yeah, he’s not too long ago.
TN: Yeah. He has a proxy of the Chinese economy and that’s a very interesting way to look at an interesting lens to look through China or through to look at China or whatever. But so, I think that the day-to-day headlines, if you follow those, you’re really just going to get a lot of volatility but if you try to understand what’s actually happening, you’ll get a clearer picture. It’s not necessarily a connection of a collection of names in China and the political musical chairs, it’s really asking questions about how does China serve China first. What will China do to serve China first and are some of these geopolitical radical things that are said do they fit within that context of China serving China first? So, that’s what I try to look at would I be freaked out if China invaded Taiwan? Absolutely. I think everybody would right but is that my main scenario? No, it’s not.
MG: In terms of the data inputs on the machine learning side how granular is the data meaning? Are you looking at where geographically demand might be picking up or is it simply this is what the price is and who cares the source? Because again with hindsight if you knew that the source of China and kind of had a rough sense of the history of Russia-Ukraine maybe that could have been an interesting tell that war was coming.
TN: Yes or No. To be honest it had more to do with the value of the CNY. Okay? And I’ll tell you a little bit about history with the CNY. We were as far as I know, the only ones who called the CNY hitting 6.7 in August of 2019 with a six-month lead time. And so, we have a very good track record with USD-CNY and I would argue that China’s buying early in 2022 had a lot more to do with them from a monetary policy perspective needing to devalue CNY. So, they were hoard buying before they could devalue the CNY and I think that had a lot more to do with their activity than Russia-Ukraine. Okay? And if you notice they’ve made many of their buys by mid-April and once that happened you saw CNY, go to 6.8. Right? It’s recovered a little bit since then but China has needed to devalue the CNY for probably at least nine months. So, it’s long overdue but they’ve been working very hard to keep it strong so that they could get the commodities they needed to last a period of time. Once they had those commodities, they just let the parachute go and they let it do value to 6.8 and actually slightly weaker than 6.8.
MG: The point of the devaluation is interesting. I feel if I had enough space but we were talking about the Yen and what’s happened there. And this observation that usually China will start to devalue when they see the end as itself going through its own devaluation.
How does some of those cross correlations play out with some of the work that on machine learning you’re doing? Because there’s a human element to the decision to devalue a currency. Right? So, the historical data may not be valid I would think because you might have kind of a more humanistic element that causes the data to look very different.
TN: Well, they’re both export lab economies. Right? And we’ve seen a number of other factors dollar strength and we’ve seen changing consumption patterns. And so, yes when Japan devalues you generally see China devalue as well but also, we’ve seen a lot of other activities in on the demand-pull side and on the currency side especially with the US dollar in… I would say over the last two quarters. So, yes, that I would say that the correlation there is probably pretty high but there are literally thousands of factors that contribute to the movement of those of those currencies.
MG: Is there anything recently Tony in the output that machine learning is spitting out that really surprises you? That you know… And again, I understand that there’s a subjective element which is our own views on the world and of course then the pure data. But I got to imagine it’s fascinating sometimes if you’re sitting there and seeing what’s being spit out if it’s surprising. Is there anything that’s been kind of an outlier in in the output versus what you would think would likely happen going forward?
TN: Yeah. You know, what was really surprising to me after we saw just to stick on CNY for a minute because it’s the first thing that comes to mind, when we saw CNY do value to 6.8. I was looking at our forecast for the next six months. And it showed that after we devalued pretty strong it would moderate and reappreciate just a bit. And that was not necessarily what I was hearing say in the chatter. It was kind of “okay, here we go we’re going to go to seven or whatever” but our data was telling us that that wasn’t necessarily going to happen that we were going to hit a certain point in May. And then we were going to moderate through the end of the year. So, you know we do see these bursty trends and then we see you know in some cases those bursty trends continue for say an integer period. But with CNY while I would have on my own expected them. I expected the machines to say they need to keep devaluing because they’ve been shut down and they need to do everything they can to generate CNY fun tickets. The machines were telling me that we would you know we’d see this peak and then we would we would moderate again and it would kind of re-appreciate again.
So, those are the kind of things that we’re seeing that when I talk about this it’s… Oh! the other thing is this: So, in early April we had a we have people come back to us on our forecast regularly who don’t agree with what we’re saying and they complain pretty loudly.
MG: So, what do you say I talk when I hear that because whenever somebody doesn’t agree with the forecast, they are themselves making a fork.
TN: Of course. Yeah. Exactly. Right? Yeah, and so this person was telling us in early April that we’re way wrong that the S&P was going to continue to rally and you know they wanted to cancel their subscription and they hated us and all this other stuff. And we said okay but the month’s not over yet so let’s see what happens this was probably a week and a half in April. And what happened by the end of April things came in line with our forecast and like I said earlier we were like 0.4 and 0.6 percent off for the month. And so that person had they listened to us at the beginning of the month they would have been in a much better position than they obviously ended up being in. Right? And so, these are the kind of things that we see on a… I mean, we’ve got hundreds of stories about this stuff but these are the kind of things that we see on a regular basis. And we mess up guys I’m not saying we’re perfect and but the thing that we when we do mess up, we’re very open about it. Everything that we do is posted on our on our website. Every call we make, every error we have is their wars and all. Okay? And so, we’re not hiding our performance because if you’re using our data to make a trade, we want you to understand the risk associated with using our data. That’s really what it comes down to.
MG: It reminds me of back in 2011 and in some other periods I’ve had similar situations, where I was writing and I was very adamant in saying the conditions favored a summer crash. Right? I was saying that for the summer and the market should be going up and people would say oh where’s your summer crash and I would say this summer hasn’t started. Like it’s amazing how people, I don’t know, what it is, I don’t know if it’s just short-termism or just this kind of culture of constantly reacting as opposed to thinking but it is it is remarkably frustrating.
Going back to your point at the very beginning being entrepreneur don’t do it, that you have to build a business with people and customers who in some cases are just flat out naïve.
TN: That’s all right though. That’s a part of the risk that we accept. Right?
MG: Yeah, the other thing right now that happens with every industry but from the entrepreneur’s standpoint. It’s what you’re doing the likely outcome of your product of your service. You’re trying to communicate that to end clients but then in the single role of the die the guy the end client who comes to you exactly for that simply because they disagree with you know the output, now says I want out.
TN: Oh! Yeah! Well, your where is your summer call from 2011 the analogy today is where is your recession call. Right? So, that’s become the how come you’re not one of us calls right now. So, it’s just one of those proof points and if you don’t agree with that then you’re stupid.
So, I would say you never finish with that there is always a consensus and a something you’re you absolutely, must believe in or you don’t know what you’re talking about.
MG: Yeah, well, thankfully. What you’re talking about so appreciate everybody joining this space Tony the first time you and I were talking. I enjoyed the conversation because I think it said on investing and I encourage you to take a look at Tony’s firm and follow him here on twitter. So, thank everybody. Thank you, Tony and enjoy.
We’ve seen so much about oil for rubles, gas for bitcoin, etc this week. Does it represent a fundamental shift for energy markets? And is the dollar dead? The yen fell pretty hard versus the dollar this week. Why is that happening, especially if the dollar is dead? Bonds spike pretty hard this week, especially the 5-year. What’s going on there and what does it mean?
Key themes from last week:
Oil for rubles (death of the Dollar?)
Rapidly depreciating JPY
Hawkish Fed and the soaring 5-year
Key themes for The Week Ahead:
New stimulus coming to help pay for energy. Inflationary?
How hawkish can the Fed go?
What’s ahead for equity markets?
This is the 12th episode of The Week Ahead in collaboration of Complete Intelligence with Intelligence Quarterly, where experts talk about the week that just happened and what will most likely happen in the coming week.
0:00 Start 0:34 CI Futures 1:22 Key themes this week 1:48 Oil for rubles (death of the Dollar?) 3:15 Acceptance of cryptocurrency? 5:34 Petrodollar Petroyuan? 7:32 Rapidly depreciating JPY 10:12 Hawkish Fed and the soaring 5-year 11:58 Housing is done? 13:10 Stimulus for energy 15:53 How hawkish can the Fed go? 17:34 What’s ahead for equity markets?
TN: Hi, everyone, and welcome to The Week Ahead. My name is Tony Nash. I’m here with Albert Marko, Sam Rines, and Tracy Shuchart. Before we get started, please, if you can like and subscribe to our YouTube channel, we would really appreciate it.
Also, before we get started, I want to talk a little bit about Complete Intelligence. Complete Intelligence, automates budgeting processes and improves forecasting results for companies globally. CI Futures is our market data and forecast platform. CI Futures forecasts approximately 900 assets across commodities, currencies and equity indices, and a couple of thousand economic variables for the top 50 economies. CI Futures tracks forecast error for accountable performance. Users can see exactly how CI Futures have performed historically with one and three month forward intervals. We’re now offering a special promotion of CI Futures for $50 a month. You can find out more at completeintel.com/promo.
Okay, this week we had a couple of key themes. The first is oil for rubles and somewhat cynically, the death of the dollar. Next is the rapidly depreciating Japanese yen, which is somewhat related to the first. But it’s a big, big story, at least in Asia. We also have the hawkish Fed and the soaring five-year bond. So let’s just jump right into it. Tracy, we’ve seen so much about oil for rubles and Bitcoin and other things over the past week. Can you walk us through it? And is this a fundamental shift in energy markets? Is it desperation on Russia’s behalf? Is the dollar dead? Can you just walk us through those?
TS: All right, so no, the dollar is not dead. First, what people have to realize is that there’s a difference. Oil is still priced in USD. It doesn’t matter the currency that you choose to trade in because you see, in markets, local markets trade gasoline in all currencies. Different partners have traded oil in different currencies. But what it comes down to is it doesn’t matter because oil is still priced in dollars. And even if you trade it in, say, the ruble or the yuan, those are all pegged to the dollar. Right. And so you have to take dollar pricing, transfer it to that currency. And so it really doesn’t matter.
And the currency is used to price oil needs three main factors, liquidity, relative stability, and global acceptability. And right now, USD is the only one that possesses all three characteristics.
TN: Okay, so two different questions here. One is on the acceptance of cryptocurrency. Okay. I think they specifically said Bitcoin. Is that real? Is that happening? And second, if that is happening and maybe, Albert, you can comment on this a little bit, too. Is that simply a way to get the PLA in China to spend their cryptocurrency to fuel their army for cheap? Is that possibly what’s happening there?
TS: It could be. Russia came out and said, we’ll accept Bitcoin from friendly countries. Mostly, they were referring to Hungary and to China. Right. And I don’t think that is a replacement for USD no matter what because not every country except for perhaps China really accepts or El Salvador really accepts Bitcoin or would actually trade in Bitcoin. Right.
TN: In Venezuela, by the way. I think. Right. So on a sovereign basis. Okay. So Sam and Albert, do you guys have anything on there in terms of Bitcoin traded for energy? Do you have any observations there?
AM: No, this is a little bit of… This is even a serious conversation they’re having? With El Salvador going to be like the global hub for Russian oil now because they can use Bitcoin?
TN: That would be really interesting.
AM: But this is just silly talk. Every time there’s some kind of problem geopolitically and they start talking about gold for oil or wine or whatever you want to throw out, they start talking about the US dollar dying and whatnot.
I mean, like Tracy, I don’t want to reiterate what Tracy said, but her three points were correct. On top of that, we’re the only global superpower.
AM: That’s it.
SR: Yeah. My two cent is whatever on Bitcoin for a while.
TN: I think that all makes sense now since we’re here because we’re already here because we all hear about the death of the petrodollar and the rise of the petroyuan and all this stuff. So can we go there a little bit? Does this mean that the petrodollar is dead? I know that what you said earlier is all oil is priced in dollars. So that would seem to be at odds with the death of the petrodollar.
AM: Well, Tony, in my perspective, the petrodollar is a relic of the 1970s. Right. Okay. Today it’s the Euro dollar. It’s not the petrodollar that makes the American economy run like God on Earth at the moment. It’s the Euro dollar. Forget about Petro dollar. Right. Because it’s not simply just oil that’s priced in it in dollars. It’s every single piece of commodity globally that’s priced in dollars.
TN: And Albert, just for viewers who may not understand what a Euro dollar is, can you quickly help them understand what a Euro dollar is?
AM: They’re just dollars deposited in overseas banks outside the United States system. That’s all it is.
TN: Okay with that. Very good.
SR: And the global economy runs on them. Full stop.
AM: It’s the blood of the global economy.
TN: So the death of the petrodollar, rise of the petroyuan and all that stuff, we can kind of brush that aside. Is that fair?
TS: Yeah. I mean, even if you look at say, you know, China started their own Yuan contract rights, oil contract and Yuan futures contract. But that still pegged to the price of the Dubai contracts. Right. That are priced in dollars.
TN: Let’s be clear, the CNY and crude are both relative to dollars. Right?
TN: You have two things that are relative to dollars trying to circumvent dollars to buy that thing. The whole thing is silly.
AM: Yeah, of course. Because Tony, the thing is, if China decides to sell all their dollars and all their trade or whatever, everything they’ve got, they risk hyperinflation. What happens to the Renminbi and then what happens in the world? Contracts trying to get priced right.
TN: Exactly. It’s a good point. Okay. This is a great discussion.
Now, Albert, while we’re on currencies, The Japanese yuan fell pretty hard versus the dollar this week. Do you mind talking through that a little bit and helping us understand what’s going on there?
AM: Yeah, I got a real simple explanation. The Federal Reserve most likely green light in Japan To devalue their yen to be able to show up the manufacturing sector in case China decides to get into a bigger global geopolitical spat with the United States. Simple as that.
TN: Great. Okay. So that’s good. This is really good. And I want people to understand that currencies are very relevant to geopolitics or the other way around. Right. Whenever you see currency movements, there’s typically a geopolitical connection there.
AM: Of course. And on top of that, if it was any other time and they started to devalue the currency like this, the Federal Reserve where the President would start calling the currency manipulators. And there’d be page headlines on the financial times.
AM: And because that didn’t happen, It’s an automatic signal to me that this is what’s happening at the moment. Right.
What’s also interesting to me, Albert, is we’ve seen last week we saw Japan approach the Saudis and the Emiratis about oil contracts. We saw Japan call. There’s a meeting in Japan next week, I think, with China. So Japan is becoming this kind of foreign policy arm, whether we want to admit it or not, they’re kind of becoming foreign policy arm for the US. Because the US is not well respected right now. Is that fair to say?
AM: It’s more than fair to say, I believe Biden’s conference with South Asian leaders was just canceled on top of everything else.
TS: Sorry. And we saw this week Japan and India just signed, like, a $42 billion trade deal. So it kind of seems like they’re smoothing over the rough edges because the United States kind of came after India a little bit earlier about two weeks ago.
TN: Yeah, that’s a good call, Tracy. I think Japan and India have had a long, positive relationship. It’s especially intensified over the past, say, seven or eight years as China has tried to invest in India and the Japanese have kind of countered them and giving the Indians very favorable terms for investment and for loans. And so this is kind of a second part of that investment that was, I think, announced in, say, 2014 or 2015, something like that. And again, as we talked about it’s, Japan intervening to help the US out and obviously help Japan out at the same time. Thanks for that.
Now, Sam. We saw bonds spike pretty hard this week, especially the five year. I’ve got a Trading View source up there on the five year up on the screen right now. So can you walk us through what’s happening with US bonds right now, especially the five year?
SR: Sure. I mean, it’s pretty straightforward. The Fed is getting very hawkish and the market is adopting it rather quickly. And I don’t know how forcefully to say this. The current assumption coming from city is four straight 50 basis point hikes and then ending the year with just a couple of 25. That is a pretty incredibly fast off zero move time, some quantitative tightening, and you’re somewhere around three and a half percent to 4% worth of tightening in a year. That’s a pretty fast move.
So the two year to five years reflecting that the Fed is moving very quickly, you’re likely having the long end of the curve is lagging a little bit. You saw flattening, not steepening this week. The long end of the curve is telling you that the terminal rate may, in fact, actually be at least somewhat sticky around two and a half and might actually be moving a little bit higher. And that terminal rate is really important because that is how high the Fed can go and then stay there. It is also how fast the Fed can get there and how much above it the Fed is willing to go. So I think there’s a lot of things that happened on the curve this week.
TN: Okay. Albert, what’s in on those? Yes, go ahead, Albert.
AM: Oh, I’ve heard whispers that the long bond is going to 2.8% and maybe even 3%. That’s what the whispers have been telling me about that, which is going to absolutely devastate housing.
TN: But that was my actual idea.
SR: Oh, yeah. Housing is done. I mean, you saw pending home sales were supposed to be up a point and down 4%. That’s the first signal. The next signal will be when lumber goes back to $300.
TN: Okay. It seems to me you’re saying by say Q3 of this year we’re going to see real downside in the housing market. Is that fair to say?
SR: Oh, in Q2, you’re going to see real downside in the housing market. Yeah.
SR: Pending sales are, I think, one of the most important indicators of how the housing market is going. Right. It’s a semi forward looking indicator. If you begin to see a whole bunch of these homes in the ground stay as homes that are not being built. Right. So if you begin to see just a bunch of pads out there, it’s going to become a significant problem considering a lot of people have already bought the materials to build it off. And you’re going to begin to have some really interesting spirals that go back into some of the commodity markets that have been on fire on the housing front.
TN: Wow. Okay. That’s a big call. I love this discussion. Okay, good. Okay. So let’s move on to the week ahead. Tracy, we’ve had some stimulus announced to help pay for energy. Can you help us understand? Do you expect we’ve seen California and some other things come out? Are more States going to do this or more countries going to do this, and what does that do to the inflation picture?
TS: Well, absolutely. We saw California, Delaware, Germany, Italy talking about it. Japan already. They’re coming out of the woodwork right now. There’s actually too many to list. It’s just that we’re just now this week just starting to see the US kind of joining this on a state to state basis. The problem is that this is not going to help inflation whatsoever. You’re literally creating more demand and we still do not have the supply online. So all of these policies are going to have the opposite of the intended effect that they are doing. Right. It’s just more stimulus in the market.
TN: Do we think there’s going to be some federal energy stimulus coming?
TS: They’ve talked about different options. I mean, really, the only thing that they could do right now is get rid of the federal excise tax, but that’s only really a few cents. And they kind of don’t want to do that because that goes towards repairing roads, et cetera. That doesn’t fit into their plan that they just passed back in the fall. Right. We had infrastructure plan, so they need to pay for that. That’s already passed. So they probably won’t do that.
The other options that they have that they’re weighing are more SPR release, which is ridiculous at this point because they could release it all and it would still not have a long lasting effect on the market. And that’s our national security. It’s a national security issue. And we’re experiencing all these geopolitical events right now. We have bombs in Saudi Arabia. We’ve got Russia, Ukraine. So I think that’s like a poor move altogether.
TN: So if more States are going to come in, is it suspects like Massachusetts, New York, Illinois, those types of places?
TN: Okay. So all inflationary, it’s going in the wrong direction.
TS: It’s going to create demand, which is going to drive oil prices higher because we still don’t have the supply on the market.
TN: Okay. Wow. Thanks for that. Sam. As we look forward, you mentioned a little bit about how hawkish the Fed would be. But what are you looking at say in the bond market for the next week or so? Do we expect more activity there, or do you think we’re kind of stabilizing for now?
SR: We’re going into month end. So I would doubt that we’re going to stabilize in any meaningful way as portfolios either head towards rebalancing or begin to rebalance into quarter end. So I don’t think you’re going to see stabilization. And I think some of the signals might be a little suspect. But I do think back to the housing front. I’m going to be watching how housing stocks react, how the dialogue there really reacts, probably watching lumber very closely, a fairly good indicator of how tight things are or aren’t on the housing front.
And then paying a little bit of attention to what the market is telling us about that terminal rate. If the terminal rate keeps moving higher, to Albert’s point, that’s going to be a big problem for housing, but it’s going to be a big problem for a number of things as we begin to kind of spiral through, what the consequences of that are. It will be for the first time in a very long time.
TN: Okay. So it’s interesting. We have, say, energy commodities rising. We have, say, housing related commodities potentially falling, and we have food commodities rising. Right. It seems like something’s off. Some of it’s shortages based, and some of it is really demand push based. So energy stuff seems to be stimulus based or potentially so some interesting divergence in some of those sectors.
Okay. And then, Albert, what’s ahead for equity markets? We’ve seen equity markets continue to push higher. How much further can they go?
AM: Last week they eliminated, I think, up to about $9 trillion inputs, short squeeze, VIX crush. I mean, they went all out these last two weeks. It’s absolutely stunning. From my calculations, I think they expanded the balance sheet another $150 billion. Forget about this tapering talk. There’s no tapering. They just keep on going. How high can they go? That’s anybody’s guess right now. I think we’re like 6% off all time highs. On no news.
TN: So potentially another 6% higher?
AM: Honestly, I know that there’s hedge funds waiting, salivating at 4650. Just salivating to short it there. So I don’t think they can even get close to that, to be honest with you. So I don’t know, maybe 4590 early in the week before they start coming down.
TN: Okay. Interesting. So you think early next week we’ll see a change in direction?
AM: Yeah, we’re going to have to this has been an epic run, like I said, 90% short squeeze, 10% fixed crush. You don’t see this very often. Okay, Sam, what do you think, Sam? Similar?
SR: On equities, I like going into the rip higher. I’m kind of with Albert, but a little less bearish. I think you chop sideways from here looking for a catalyst in either direction. Bonds ripping higher today, yields ripping higher today. Bond prices plummeting. That I thought was going to be a catalyst for equities to move lower. It wasn’t. That kind of gives me a little bit of pause on being too bearish here, but it’s hard for me to get bullish.
TS: What’s interesting? I’ll just throw in like, Bama, weekly flows. We actually saw an outflow from equities for the first time in weeks. It wasn’t a lot 1.9 billion. But that says to me people are getting a little nervous up here. Profit taking, as they say on CNBC.
TN: All right, guys. Hey, thank you very much. Really appreciate the insight. Have a great week ahead.
AM, TS: Thanks.
SR: You too, Tony.
TN: Fabulous. Look. I’m married. I’m a man. I don’t notice anything. I noticed the other guys laughed at that. Uncomfortably. That’s great. Okay. I’m just going to start that over, guys. And we’re going to end it.