Are the markets ignoring reality?

If you look at global stock markets since 1 January 2020, the striking feature is that they're all moving in tandem.

Despite substantial differences in how governments in the US, Japan, Germany, Australia, and the UK have responded to the pandemic –  the economic policies that have been introduced, and also the differences in the infection rates and death rates – the markets seem to be moving as one.

This is a global problem, and the markets are treating it as if we're all in this together. So analysing any one of these markets is going to be fairly representative of what's happening globally across a large number of markets.

I'm now going to break it up into three phases: I'm going to talk about the build-up. What markets looked like in the lead up to the pandemic. The crash, and then what we've been seeing in the most recent two months.

So first the build-up: the starting point of where we entered the year was that we're at the end of the longest bull market on record.

Looking at stock market movements in the last 120 years, the striking feature is that this last run, this bull market run, has taken us from the GFC in 2009 right through to the end of last year.

As a result of this extremely strong bull market run, stock market valuations were also at record highs leading into the pandemic.

So the price to earnings ratios, with a few adjustments, were at levels that we've really only seen on two other occasions, historically.

One was during dot.com bubble of 2000, and we know how that ended. And then the second period in history where we've seen these types of valuations was immediately preceding the Great Depression.

So, equity markets were extremely hot, we had extremely high valuations going into this crisis.

We also saw that the yield curve in the US, in particular, and in some other currencies as well, was inverting, which is typically a sign of trouble up ahead.

Yet the markets hadn't responded to that yield curve inversion. So in many respects this looked like, a ticking time bomb in equities markets that was simply waiting for catalyst.

Then the catalyst arrives, and boy did it arrive, it was quick, bad information. So the market sort of peaked around late February.

And if we just take the US market as an example we saw a 35% decline in the market in the space of a month. An extremely rapid fall with a huge amount of volatility.

The market was hitting market-wide circuit breakers on a number of occasions, which is actually quite a rare thing for a market to have such extreme price movements on a daily basis.

So if you look at a plot of the volatility, what we see is that volatility spiked tremendously.

In fact, it hit levels that were equal or even slightly higher than the levels that we saw during the global financial crisis of 2009 – so extreme volatility.

Then from mid to late March comes a very strong rebound in markets. So if you measure the price movements in the US from 23 March to today, US markets have rebounded by about 32%.

It's a fairly similar number in Australia, a little bit less, but a very strong rebound.

Now that's happened in the space of two months. What this does is this takes the stock market back to valuations that we last saw in October 2019.

As we think about historically, what that implies, it means markets are back to where they were immediately prior to COVID breaking out in China – back where we came from.

It's as if this whole thing never happened.

What's really puzzling about this strong rebound, or bounce, is that this came at a time when there was a flow of really bad economic news.

So, just one example: An announcement from the IMF was talking about us heading into the worst recession since the Great Depression, far worse than the GFC.

So that's the sort of news that's flowing out while the market is rising 32%.

Disconnected from reality?

A number of market commentators have looked at this and come to the conclusion that the market simply seems disconnected from reality – the stock market seems to be ignoring the economy.

So, puzzling dynamics in stock markets, to put it lightly.

The question is how to make sense of this? Does this strong rebound in the stock market mean that we're headed for a strong economic rebound?

Can we expect a v shape recovery? Or is the market response somehow fooling us about the economic prognosis going forward?

With stocks overvalued to begin with, going into this crisis, after this 12 year bull market, why didn't the market correct earlier? Why do we have to wait for a pandemic like this to see the correction?

And so the more general question is what drives the market movements? Are they efficient? Are they linked to economic outcomes?

 Can we read information about the future of the economy from what the stock markets are doing?

These are the issues that I want to tackle. How I'm going to tackle these issues is by pointing out what I think are three important considerations to try to read the stock market reactions.

And these three considerations come from three recent research studies that, together with some co-authors, we've been working on.

Market efficiency

We know markets are good at forecasting in many, many contexts, they give very strong, often very accurate forward looking predictions of what's going to happen in the future.

But it's important to understand the subtleties of the different types of market efficiency, and when markets can be efficient, and when they can show signs of inefficiency.

What we do in this study is we split market efficiency into two sort of flavours or types.

One is micro level efficiency, which is all about how efficiently one stock is priced relative to another – it’s all about relative prices within the stock market.

So for example is ANZ correctly priced relative to BHP? Is one too cheap and the other is too expensive? So if you were to construct a long short position - long one, short the other, can you make a bet on how that long, short position is going to play out in terms of future returns?

If you can predict those future returns and that long short portfolio, the market is not particularly efficient in a micro sense, the related concept is micro level informativeness of prices.

So do stocks with higher valuations, for example a stock with a high p e ratio compared to another stock, is that a good predictor of the fact that the higher valued stock is going to have stronger earnings in the future?

So do stock valuations tell you something about the strength of earnings in the future? The fundamentals in other words?

Contrast that micro-level efficiency with macro efficiency, and now here I'm talking about the efficiency of absolute stock prices, so market wide valuations.

So is the market as a whole, overvalued, undervalued, or is it correctly valued?

Can you take the current market wide valuation ratios, compare them to historic averages of those ratios, and use that to predict the future market return.

If the valuations are high does that predict low future returns and vice versa?

Okay, so if it does, there's a degree of inefficiency at the market wide level.

The related concept is market wide informativeness, which whether the current valuation level of the stock market, or the stock market return, gives you a signal about the future market wide earnings with future economic activity.

That would be the case if you had a highly informative market at the macro level.

So we've got a number of measures of these various concepts but let me get into the evidence.

What we find is that markets are far more efficient at the micro-level, that is in relative pricing, than they are at the macro level, the absolute market wide valuation.

You can see that in the, in the, the plot here on the left hand side, the top curve is through time for the US stock markets, the degree of micro efficiency that is efficiency of relative prices.

And then we see in the small, the darker line here, the degree of macro efficiency.

And so you can see the micro efficiency is much higher than the macro efficiency and this is consistent with Samuelson's dictum Paul Samuelson predicted this type of effect.

Already a long time ago it's just remained largely untested until these recent studies.

The other observation here is that the wedge between the micro efficiency and macro efficiency is getting more pronounced, it's getting larger.

Stock markets are getting better and better at pricing stocks relative to one another, but worse at setting market wide valuation at levels that correlate with future economic activity.

In other words the markets are becoming decoupled from the economy, is what we are finding in these long time series analyses of these two types of efficiency.

Now we find that there is a number of drivers of this.

The rise of passive investing has driven this decoupling of stock markets with the economy.

So has the rise of delegated funds management, in particular rigid asset management allocations, such as 60/40 portfolios that hold 60% equities and 40% fixed income.

To give you an illustration, what does such a portfolio do well when the markets crash and the equity value in that portfolio has declined?

A fund with such an asset allocation will mechanically be forced to buy the stock market, irrespective of the future economic outlooks.

You get these bounces in markets that are unrelated to fundamentals as a result of this type of investment management.

A couple of implications from this:

Number one is, it explains why markets are very efficient in one sense, in the sense that you know relative pricing is really accurate, so fund managers find it hard to beat the market, that is generate alpha, but at the same time, market wide valuations often seem uncoupled from the actual economy.

You get this low degree of macro efficiency. From an investment perspective, it sort of implies, it's going to be difficult to really gain a lot of value from stock picking, but there is potentially a fair bit of value to be added to a portfolio from strategic dynamic asset allocation, that takes into consideration the market-wide evaluations.

Adapting to a high risk environment

The second consideration is what I'm going to refer to as post-traumatic stress disorder or the PTSD of markets.

Consider the effect when you walk from outside where it's sunny into a poorly lit room. The room will seem really dark at first, but then after a while, once you adapt to the level of lighting, it actually won't seem that dark, it will seem quite reasonable.

Okay, take another example, when you stare at a red screen for an extended period of time, and then look at a piece of white paper, the white paper will appear to have a greenish tinge to it. Eventually that green will disappear and you see white again.

These are both examples of perceptual biases that happen once a human is shifted away from an environment of a very strong stimulus into a more normal environment.

That perceptual bias lasts until perceptions adapt to the environment and catch up with reality.

This effect is known as habituation, or neuronal adaptation, depending on the field.

What does this mean for markets?

We tested the effects of this in financial markets in two settings.

First we did lab experiments: we took people through trading simulations where we could control the level of risk and volatility, and observe their perceptions of risk.

The second is we looked at the pricing of s&p 500 options and infered how implied volatility relates to future volatility to look for these distortions.

The key result that comes out of our studies is that people have a tendency to underestimate risk following periods of very high volatility.

When you drop from an extreme level of volatility, to a normal level of volatility, people feel like the environment is safer than it actually is.

Now, how that's relevant to understanding what's happening today is that we've just dropped off from a period of extreme volatility.

Remember VIX was up those all-time highs, and we have just backed down a bit into a period, which is still highly elevated, but is no longer as extreme as it was a couple of months ago.

Traders are saying “thank God we're back to normal”, which is an example of the bias because we're actually not back to normal.

We are at a level that is much higher, in terms of risk and uncertainty, than historical averages.

Now what does that do, this effect? What are the implications?

The implication is that following extreme volatility, as people underestimate risk, that's going to appear as excessive optimism.

 Okay so this effect is driven by, you know, a deeper neuro-biological adaptation to the high risk environment.

But what it means is that when you underestimate risk. You underestimate the discount rates that are required, which means you inflate the valuations.

Now you can think about that simply through a discounted cash flow model. What that means is markets will bounce following extreme volatility, until perceptions catch up with reality.

Once the perceptions catch up with reality, the discount rates adjust the valuations come back towards fundamentals.

So this is an effect that we found evidence for in the lab and in field studies, that's likely to explain some of the bounce in markets lately.

Fed Markets

The third major consideration is shifting away from free markets to what are called Fed markets.

Okay, so we've heard the US Federal Reserve say, we'll do everything it takes to stop this. The RBA has echoed that sentiment and said we'll transact in whatever quantities necessary to achieve this objective.

These days, the biggest market participant is not a hedge fund. It's the central bank.

We've got the Fed, the European Central Bank, the Reserve Bank of Australia, the Bank of Japan and the Bank of England, all intervening in markets.

So here's a plot of what the US Fed's balance sheet looks like from the point where they really started quantitative easing which was in response to global financial crisis.

Since that point, they've got the hang of intervening in markets, and the balance sheet of the Fed has expanded even though it's gone through some periods of contraction.

I've overlaid on this plot the S&P 500 index, and visually you should already be able to see that there's a link between the two here.

Now if you zoom in to this most recent period, what happens is just as the markets crash the Fed expands its balance sheet enormously and markets recover in response to them.

The Fed asset purchases have been at an unprecedented rate. The balance sheet is going from $4 trillion to about $7 trillion in the space of about one month.

That's 33% of GDP. So compared to other quantitative easing programs, the speed, the pace of this expansion and the magnitude, just makes the other quantitative easing look like it was negligible.

Now what does this do for markets? Here's some very early stage analysis of what this does to stock markets.

The lead lag correlations between Fed balance sheet expansion and stock market movements suggests that when markets decline, that tends to be followed by strong balance sheet expansion by the US Fed that expansion happens you know in the, in the space of two to five weeks after the strong market decline.

Subsequently, that asset purchase activity by the Fed tends to precede market rebounds, by the space of about zero to three weeks.

These correlations are very strong, but if we start modelling this a little bit more formally in a time series model that captures these lead lag causations between the two actors, we can actually construct a counterfactual which I think is quite interesting, which is what would market prices look like had the Fed not intervened.

I construct a time series model that models these two things and what this model tells us is, once you get a shock to the Fed's balance sheet, the market response takes about eight weeks to play out.

This is the stock market response plays out at a substantial magnitude, you end up with a decent fraction of the total balance sheet expansion being reflected in stock prices.

If we take the Fed asset purchases in March, and translate them according to this model as to what the impact the estimated impact of that is on the S&P 500, it's about a 13% increase in the s&p 500.

Now contrast that with the actual movement of the S&P of 32% since the low.

This is telling us that the Fed’s actions, even of themselves, explain over a third of this bounce in stock markets US dominance.

If you overlay the Australian market reactions and the US market reactions, you have a look at the point where the Fed really stepped in, two things happen at that point.

One is the markets turn, they spring back. And the second is from that point onwards, there's a disconnect between the US market, and the Australian market consistent with the notion that the US Federal Reserve's actions had a major impact on the stock market.

 

 

Conclusion

Now let's just bring this all together into one last slide that considers, what we can read from the current market reactions.

Number one takeaway is that the stock markets are increasingly decoupled from future economic conditions, and there's a number of factors been driving that decoupling.

This includes passive investing, delegated funds management, static asset allocations and so forth.

This means this in general, there's not too much to read from the stock market movement, if you're trying to predict future economic outcomes.

The second important consideration, is that following extreme volatility, risk tends to be underestimated, which then looks like excessive optimism.

It leads to inflated valuations, and market bounces, until perceptions have time to adjust the new environment and catch up with reality.

What that implies is that a strong market recovery doesn't imply a strong economic recovery.

And the last effect that was relevant here is that central banks are now playing a major role in setting overall market price levels.

Central bank actions contribute to rebounds in stock markets precisely at the time when economic outlook is looking gloomy.

However, balance sheet expansion cannot continue indefinitely.

So the bottom line is that I do not interpret these market rebounds, as an indication that the economy is back on track for a quick recovery.

The final thing that I'll close off on here is if we think about where markets are headed. I'm not in the industry of predicting market movements and I can't tell you with a high degree of certainty where the market will be at the end of the year.

If you think about these three effects, there's three different factors, at least, that distorts stock markets from fundamentals.

It just so happens that all three factors at this point in time happen to be pushing in one direction –  that is to keep the market propped up.

So if you think about something that is fundamentally being propped up, and now think about the amount of downside risk that's on the table compared to upside potential.

 It looks to me that on the balance of probabilities there's more downside risk than there is upside potential from this point onwards, because only it takes any one of these propping devices to fail or attenuate and the market could come back down towards fundamentals.

 

 

 

 

 

 

Questions

 

Five major companies, Amazon, Apple, Facebook etc in the US control 20% of stocks they all saw increase in revenue. For example, Amazon recorded 17% increase in revenue in the last quarter.

What role do these companies play in determining the stock price and effect the market.

World debt in the last quarter is 17 trillion, whereas last year the world debt was 8 trillion. How will this debt affect the market in post COVID.

The markets are highly concentrated, particularly in US markets, driven by a small number of extremely large companies.

That is yet another factor that wasn't sort of part of what I discussed that drives this disconnect between stock market movements and the economy.

If you think about who, in terms of companies, who's been the hardest hit by the COVID pandemic.

It's not the largest companies, it's not necessarily the tech companies that are driving us stock markets. It's the small and medium enterprises. So that's another reason why stock market movements aren't really reflecting the broader economy.

Now, the huge amounts of debt, I view them. In particular, sort of on government balance sheets. I view them as similar to fed balance sheet expansion. You can't keep expanding government debt, nor can you keep expanding fed balance sheets indefinitely as proportion of GDP.

So the fact that these levels are very high at the moment gives us less room to expand that fiscal monetary spending in the future.

And while it's unlikely that governments will sort of clamp back on the fiscal stimulus, and central banks will clamp back on monetary stimulus, in a very rapid manner that causes a decline in a sharp decline in markets, if they have to unwind these positions over a longer period of time, that simply means a dampening force on economic activity and on stock markets, which really doesn't look good for long term returns, long run returns on stock markets.

But then again, long run returns on fixed income are also not looking that good at the moment.

What are potential factors driving the underestimation of risk in such circumstances.

So, the underestimation of risk from the evidence we have in testing these effects in the laboratory and then, and then checking the field or the empirical evidence is the sort of deep, deep ingrained neurobiological biases that people have.

Once you become immersed in an environment with very high stimulus, you become desensitized to it. So take an example of, you know, traders in a market where on a given day the market can move 7% so unprecedented movements.

 After a while, of operating such a high risk environment where you have millions of dollars on the line every day, you become somewhat desensitized to that risk. Now once the risk jumps back down towards an elevated but closer to normal level. That seems like calm to a trader who has been operating in an extremely high risk environment.

So that's what triggers this underestimation of the risk, that these days even though we've got a high degree of uncertainty about earnings going forward, and economic conditions.

It just feels so much calmer compared to where we were in March, and that's the, that's one of the drivers of the underestimation of risk post extreme volatility. Now there's some another question

for you while we're on. Are you, are your findings consistent with a correlation between implied volatility and historical volatility.

One of our guests Allen says that he recalled earlier analysis showing realized option payouts are less than those implied by market prices for example future actual volatility is less than implied volatility. Could you comment on that Talis. Sure.

So I think perhaps what the question is. Relating to is the variance risk premium that, there tends to be a gap between implied volatility and realized volatility, which is explained by the variance risk premium are people willing to pay to hedge.

The possibility of spikes in volatility implied volatility from the empirical analysis we've done closely tracks realized volatility. It's a forward looking measure of course and realized volatility is backward looking, but the future expectations of volatility are heavily driven by current levels of volatility and the reasons is that volatility is a highly persistent variable.

The current level of volatility is a good predictor of the future. So this is in fact one of the, one of the empirical facts that we exploit to be able to identify distortions in risk perceptions, in US markets in the field.

So this is how we do our empirical version of the lab experiments that we've been running, and it's in those types of tests that we can see systematic distortions in implied volatility, compared to future realized volatility at particular times and those particular times.

Typically, when you come, come back down from a very high volatility level. It's at those points in time that even highly sophisticated and liquid markets like the US s&p 500 options market shows these distortions in implied volatility of how people are pricing volatility at those points.