TIAN YANG: What we're seeing this time around is a V-shaped bottom. It's gone down and it's gone straight back up. And if we do go on to make new highs, and in hindsight this is the bottom, this will be incredibly rare historically.
GDP doesn't go from, like, 2 to 1 to zero to minus 1, right? It's going to go along at 2, and then the next print is zero and it's minus 3, it tends to be a lot more of a gap. You can see that Swedish indicators have basically collapsed. So that's telling you there's more pain to come.
TIAN YANG: My name is Tian Yang, head of research at Variant Perception. So at Variant Perception, what we focus on are leading economic indicators.
If you look at the way the economy works, it tends to be more mechanical than people realize. There's a fixed sequence in which things have to happen in the economy.
For example, building permits necessarily have to go up before construction activity can pick up. Similarly, if you're an employer, you would typically hire or fire temp workers before you would hire or fire a full-time worker. So temporary employment will tend to turn before full-time employment.
So if you look for these, kind of leading, coincident lagging relationships within the economy, then it'll give you a much better sense of where the economy is going. It's almost like when you're driving a car and you see the car in front do something with indicator lights and you know they're going to turn before the car actually moves. That's what we're trying to do with lead indicators
Lead indicators are not necessarily new. They've been around since at least the 1980s, you know the likes of Geoffrey Moore wrote the original academic papers on it. However, what we are trying to do is actually apply it in a robust and repeatable way to real world investing.
So it's kind of like the Yogi Berra quote about, in theory there's no difference between theory and practice, but in practice there might be. And so it is with leading indicators.
A lot of traditional approaches to economic research are very theoretical in nature. You know you go to the World Bank, IMF, download the database, run your model. But in the real world, data is revised. You see the GDP print come out, and a few months later it's revised.
So there are a lot of these issues that, if you realize and overcome them, then these indicators can actually work for you to understand where we're going with the economy.
And the final thing to say on that is, ultimately, the key here is to focus on the economy rather than the market. There isn't actually a lead indicator that will lead the market 100% of the time. And even if there was, I probably wouldn't reveal it to you. And if I did, you know, it would probably stop working.
But what you can do is actually focus on where the economy's going and look for divergences between leading outcome indicators and market pricing.
Was the recent weakness in rebounds in US equities unusual?
TIAN YANG: US equities had quite a large rebound to start the year. By the technical definition, we were in a bear market badly back in December. Now, if it's truly over, this will be one of the rarest types of bear markets we've seen in history.
So if you look back at the past 100 years of equity market data, the shortest previous bear markets that occurred without a major recession scare was 1990 and 1987. In both cases, the bear market lasted about three months. Right now, we're about five months in from the original sell-off. Even for those very short bear markets, what you saw was actually a retest of the lows. Right? And this is ignoring all the major recession-related bear markets where markets fall, it takes years to recover. Even for the kind of very short ones, it tends to be more of either a W shape, or even the triple bottom one, and then a rally.
What we're seeing this time around is a V-shaped bottom. It's gone down and it's gone straight back up. And if we do go on to make new highs and hindsight this is the bottom, this will be incredibly rare historically.
Just in terms of how markets work, usually people want to retest support and resistance levels, just to get a sense of where the real buying and selling pressures are.
Why have the markets had a pronounced V-shaped rebound?
TIAN YANG: I think often narrative could also catch up to prices. Again, if you take a step back and just look at historical precedent, whenever you have a 10% plus down quarter in US equities, 80% of the time, there following quarter's been a win. The only exceptions are basically in the depths of recessions.
So, because we don't have a imminent recession, a rebound is kind of expected. When you drill into the flow and positioning data, you see that basically people got very short, and even throughout the rally this year, shorts have basically held on. There's been continued outflows. If you look at US ETF flow data, that's flowed out. You can track kind of CTAs, they're still short. Macro funds are short.
So I think it's been a case of more of a squeeze higher. And because you have a squeeze, you have this kind of relentless looking V shape up. But I think a lot more of it is positioning and flow-driven than the kind of narrative, right? You have a big down quarter, people get short, it squeezes higher.
The next stage, which is where we're at now is, what happens now when we start reacting to growth data that disappoints? To earnings downgrades? Maybe margins are being revised lower, but sales haven't. Sales projections are maybe still growing. That needs to come off.
So I think that's why we're at a tipping point, if you like, in where markets are going.
Why is the 2016 reflation narrative popular again?
TIAN YANG: The narrative is focused around the dovish pivot by the Fed. And there's a lot of talk that this is analogous to the 2016 reflation trade when Yellen, again, backed off. You know, there was the whole Shanghai Accord, currency coordination.
I think investors are drawing a lot of analogies, and it's easy to see the appeal of it on a kind of superficial level. There isn't an eminent US recession. The Fed's more dovish than expected. And China starting to ease. Right?
So if you take all three of those, you're like, OK, this looks similar to a 2016 set up, in which case the playbook is go long cyclicals, go long commodities, you know, there's going to be a wave of liquidity coming.
When you take each of those and start drilling down and digging into it, what we find is that the data does not match the narrative. Back in '16, it was actually very consistent. Lead indicators of both global growth and liquidity had already been turning up. So you had the hard data pickup to support the narrative, and that could fuel the market move.
I think today is more of a case of the narrative has front-run the data. There's zero signs in any lead indicators that the data is about to come through. So we have this setup where the narrative and markets are up here, the data's going to be there, and you're going to have extended period of data disappointments. And the question is, will markets be able to hold up to that?
And given the historical precedent about how long bear markets typically last, the fact you need a double bottom, I think the risk-reward probabilities really do favor a retest of the lows now.
Do you think the reflation narrative is valid?
TIAN YANG: I think the first thing to address is actually recession. So, we tend to think about recession slightly different from how most economists or investors think about it. Technical definition is about 2 negative consecutive quarters of growth. You know, it's all fine.
But in practice what you really care about is when recessions cause large cascade falls in risk assets. And the cascade fall is really kind of when there's a positive feedback loop between the economy and essentially financial markets or sentiment. So, the economy worsens, earnings worsen, investors react and drag equity prices down, which then in turn further dents sentiment, further dents investment choices. So you get this positive feedback loop.
This is almost our interpretation of what Soros meant by reflexivity, in terms of when these positive feedback loops kick in. So, that's kind of how we like to think about recessions. And as such, you need to think about them as regime shifts, rather than this economy that, you know, like the standard quadrant approach where the economy is accelerating, decelerating, you go into recession.
If you actually look at the data in practice, GDP doesn't go from like 2 to 1 to zero to minus 1, right? It's going to go along at 2, and then the next print is zero and it's minus 3. It tends to be a lot more of a gap, so you have to kind of think about it as a regime shift.
And the way we tend to model that is to focus on simultaneous deterioration in hard and soft data. For example, if credit spreads are widening at the same time as initial claims are rising, that's a very bad sign. That's the first sign that the positive feedback has already kicked in. Therefore, we're in the kind of recession loop. And then it's important to get defensive immediately.
What we've seen so far, and this is why I think people drew the analogy to 2016, is that financial markets were discounting a recession, but the hard data didn't react. And so, if you just don't think of it as regime shift and just think of it as a standard model, then you'll be like, you know, 50% risk of recession because all your financial market inputs are giving you a warning flag. But the hard data isn't. But if you think about it as this positive feedback loop, that's why we haven't seen it yet.
The other thing about thinking about it as a regime shift is that these things can move quickly. And so right now the situation we have is that lead indicators are not pointing to a recession, but they are pointing to a growth slowdown. If you look at US data, building permits, right, that's stopped growing. That's declining. Real money growth, real M1 in US, that's fallen a lot. A lot of the lagged effects from the previous tightening of liquidity, the previous rate hikes, are still feeding through.
So there's a danger that the hard data is about to deteriorate, which might happen when sentiments are elevated. Then the sentiment might come off as well.
So ex ante, it's very, very hard to predict when these recessions hit. You know, I see all these forecasts like, June 2020 is going to be the recession day. You know, we don't have a model that can time it necessarily. But what we do know is when the first sign's going to kick in.
So right now, hasn't quite kicked in. But because lead indicators for the US economy are rolling over, in addition to a lot of things like the fiscal stimulus, the effects are rolling off, the risk is very elevated. So I think that's the first thing that's a bit different to back in 2016.
The second point is clearly the Fed. So if you look at Fed pricing, you know, if you look at 1 year forward rate hikes priced, the chart looks very similar, right? You have 2, 3 hikes priced in for the year, and then suddenly the markets go to pricing cuts.
But I think that's kind of where the analogy almost ends with '16. The difference today is that labor markets are even tighter. You're three years further in. Evidence of wage growth is already coming through. If you look at core inflation pressures it's not surging, but it's actually moderate and present. Inflation is one of the most lagging indicators.
If you do something as simple as plot the ISM against core CPI, you'll see it's almost a perfect 2-year lead if you push ISM forward.
So because we've had that previous surge in growth, the underlying inflation pressure is there. The market is kind of very focused on transitory headline factors. So people focus on the dollar, on the falling oil prices, and therefore headline inflation will take a dip lower and the markets are pricing that. But once that transitory effect is out of the way in the second half of the year, the core underlying financial pressure is still there.
It's not necessarily so much that it's going to cause the Fed to aggressively hike, but it's certainly enough to prevent them easing policy. And that's really the key. The move so far has been from pricing of a very hawkish Fed to further tightening of liquidity, to now pricing, OK, they're going to stop and pause here. But just because they pause, it doesn't mean things are going to start improving immediately. The Fed balance sheet is still actually contracting.
Now, they might announce a taper soon, and obviously that's kind of widely anticipated. But if you actually look into Fed net credit, you know, even if they pause, because of the year-on-year impact, in terms of the base money flow through to commercial banks, it will actually still cause a contraction of liquidity.
It's important to think about defining liquidity correctly when you want to think about the Fed. Right now I see a lot of commentary on indices like the financial conditions index, right? Goldman have one. Morgan Stanley have one. And I think those indices are not particularly useful as lead indicators. They are, by definition, coincident. Within the definition, they have credit spreads and equity prices in them. So you can't really use it to be where asset prices are going. They're just telling you equities have fallen already or they tell you equities have rallied already.
The key is to focus on what we would call excess liquidity. And we define that as real M1 growth, minus economic growth, minus inflation. The intuition is that money is created from thin air by both central banks and commercial banks, and once it's created in the system, it basically has two major uses. It either flows to the real economy, or it goes to supporting asset prices, or it goes to inflation essentially.
So if you take the changing M1, remove the impact of inflation and economic growth, then what you're left with is kind of the pool of liquidity available to support asset prices. And on that measure, things have been declining and they're still in a downward trend.
Now, it's also important to explain why we focus on M1. So a lot of analysis typically only focus on very broad measures like debt-to-GDP or only focus on, say, the Fed balance sheet. I think that's why you have some of these spurious charts where people plot the Fed balance sheet against S&P, and it's perfect correlation right up till they started tapering, and then suddenly there's divergence, right.
And I think the reason is because people need to understand the definition of money. The balance sheet itself does not capture the whole concept of money. It's capturing, essentially, Fed balance sheet cash and reserves. But because commercial banks can also create money from making loans and deposits, you need to capture that impact.
But if you use broader measures like M2 and beyond that's