Investing – Applied Macro

Migration to Substack

I have started a substack under the same name as this blog – Applied Macro. The link to the substack is here – Applied Macro | Colm O’Shea | Substack.

You can also find this link on the home page of this blog by clicking the ‘Substack’ button in the top right

I will be posting new material on substack and will no longer be posting on this blog.

Below is a copy of my new post, the introduction to a new series exploring whether we are currently in a stock market bubble. The follow-up pieces can be found on substack.

The 2026 Stock Market Bubble

The US stock market sits at levels that look extreme by any historical comparison. These extraordinary times require a more rigorous analysis than just high Price-Earnings (PE) ratios or anecdotes about AI company valuations.

If you have investments, such as a pension, 401(k) or an ISA, you need to make decisions about how you allocate your assets. Whether or not OpenAI is worth $840bn is not relevant to you, it is a private company. What matters to you is whether the broad public market is cheap, fair value or expensive.

Today’s elevated PE ratio in the S&P generates a lot of press attention, but it simply reflects strong optimism about future earnings. That alone cannot tell us whether we’re in a bubble like dot-com in 2000 or on the early stage of AI driven earnings revolution.

The US stock market has become enormous relative to the size of the economy. Below we show the value of US equities as a share of overall GDP. It is double what it was a decade ago, and far higher than we saw in the dot-com bubble of 2000.

The reason this chart looks more extreme than the simple PE chart is that underlying earnings as a share of GDP has already reached unprecedented levels over the past twenty years. This rise in corporate profits from around 8.5% to 13% of GDP has seen wages stagnate, widening economic inequality, and a political backdrop marked by discontent and populist movements such as MAGA.

Current valuations show the same level of optimism about future earnings growth as in 2000 dot-com bubble, except today’s level of earnings are far higher. It is this combination that is so extreme.

What would this earnings share need to be over the next decade for your stock market investment to simply keep pace with GDP growth? The chart below shows

The projections are stark.

Current valuations assume future jumps in profitability that dwarf anything ever seen. Can AI really deliver a surge in corporate profits far beyond the gains achieved in the last waves of globalisation or past technological booms?

This series will continue on substack and examines the extraordinary claims behind these extraordinary times.

Subscribe here – Applied Macro | Colm O’Shea | Substack

Desire – Why use a stop-loss?

Once you realise how central desire is to processing information and making decisions, you can appreciate how important it is to be able to deal with it. Just being aware of your desires as we discussed in the previous article sometimes is not enough. The process of investment has a direct impact on your emotions and desires – “Fear and Greed” are well known but that does not make them easy to deal with.

If you are not careful, this will be your process

Belief leads to investment
The investment leads to the desire it will succeed
Desire leads to reinforced belief in the trade
The belief leads to confirmation bias
The confirmation bias leads to even stronger belief.

By this stage, your emotional ties have now blended with your beliefs

The risk is that you cannot process new information correctly
You do not get out of the trade when you should and lose money

Introducing the stop-loss

The cycle above is often why books on trading make stop-losses a central element. In fact they are ubiquitous in trading culture, as a hedge fund manager investors would often ask where my stop-loss is on a given position. The theory is clear:

“If you have a rigid and clear stop-loss, which you decide before you enter a trade, and then remain disciplined in sticking to it, then you are protecting yourself from your own inability to objectively evaluate the position after you have put it on.”

This is great advice for most investors. Another great piece of advice would be:

“DON’T TRADE – you aren’t any good at it and will lose money”

The books tend not to mention that one.

IS there an alternative?

A problem with a stop-loss is the trade might still be a great trade. In fact, it could be better or worse that when you initially traded. New information will have become available, but by pre-committing to get out of the trade, you are not able to do anything about it.

There are other ways to manage positions aside from stop-losses. I borrowed a helpful way to think about this problem from George Soros – please read “The Alchemy of Finance” – a truly wonderful book with some very important ideas. One of Soros’ key ideas is the application of Popper’s scientific method to investing. The application of hypothesis testing.

Key is not to start with a “belief” that the trade will work, in fact the trade is a test of the hypothesis that the trade will do well.
Analysis is therefore considering what would falsify this hypothesis.
Hypotheses are falsified all the time and it is nothing to get very excited about.

Therefore, desire is not engaged or at least minimised.

This willing suspension of belief is critical to being able to remain objective later.

What can falsify a hypothesis. For example

Fundamental news invalidating the underlying idea
Price action that tells me what I thought matters in this market, is not what really matters
Price action that tells me there is something going on I do not understand.

In practice, this can look very similar to a stop-loss, but It leaves the door open to more discretion and flexibility. For example:

Fundamentals have worsened while the price action is fine
EXIT i.e. do not wait for the stop-loss
Fundamentals have improved while price action is poor
Do not automatically exit as some of the most profitable opportunities from these times of material mispricing. Do more investigation.
Possibly INCREASE the position size rather than cut it

Conclusion

Working with Soros, I observed that this process allows him to be enormously flexible. He does not seem to fall into the standard pitfall of emotional attachment to his trades. Instead fluidly cutting, increasing or reversing them when he changes his mind. This level of control and discipline sets him apart from the vast majority of traders I have seen.

Framework for valuing equities Part V – Relationships between Components

In Framework for Equity Valuation Part II I laid out this approach.

Breakdown of the Equity Price

Using some very simple algebra, I split the equity price into components:

Price = (Price/ Earnings) * Earnings

Price = (Price/ Earnings) * ( Earnings / Nominal GDP) * Nominal GDP

In this work, there was an assumption that the components are independent. I will now examine if this is sensible.

Are P/E and E/GDP independent?

I can find no consistent relationship between the two.
There appears to be a mild negative correlation overall, but at times there can be extended periods of both components falling, such as 1967-74 and 2000-2003, or both rising such as 1994-2000.

An intuitive relationship occurs when there is an expectation of a large rise or fall in earnings and the equity price rises or falls in anticipation. This means the PE ratio would rise in anticipation of earnings rising, and then fall back down as earnings expectations are realised. In this situation, I see earnings as the driver and the PE ratio as a passive variable.

A situation where PE was the independent driver was in the 1980s, when a broad fall in yields meant the PE ratio rose without any need for an expectation of a change in earnings. This supports the approach that we can look at the two factors as independent drivers.

Are Growth and PE ratio related?

This is a relationship that is often assumed to exist as we think periods of low growth or recession are associated with low confidence and high awareness of risk. This high “risk premium” means low PE ratio.

But the evidence to support this idea is not so clear. Of the past 9 recessions, the PE ratio only fell twice. There is some evidence to support the idea that the PE ratio falls in the year before the recession in anticipation of an earnings drop, then recovers quickly as those expectations are realised. This happened in 5 of the last 9 recessions so it is still a fairly mild effect.

Are Growth and earnings related?

I find the chart below intuitive and compelling. The reason that recessions drive equity markets down is because recessions drive corporate earnings down. If we look at earnings as a share of GDP from 1 year before the recession to the low during the recession they fell each time. The average fall was 21% with the smallest still a 9% fall and the largest (2008) down a massive 42%.

The rationale for this comes from thinking about the breakdown of national income in the NIPA data (Framework for Equity Valuation Part III Earnings Outlook). If there is downward pressure on nominal GDP whilst wages remain sticky, then the impact is felt in a magnified way in corporate earnings.

The magnitude of changes in earnings are very large during recessions and early recovery, so it is during these periods we should be especially alert when forming an equity outlook. The impact of whether growth is 2.5% or 2.8% is imperceptible by comparison. Lots of work by economists, strategists and asset managers is done to fine tune these types of economic forecast but a) it is not possible for them to be that accurate b) even if you could, the relationship to market prices is so loose as to make it useless information.

Conclusion

There is one important interrelationship we need to be very aware of. In previous recessions, earnings as a share of GDP have fallen rapidly and normally bottomed at around 7%. If that were repeated in the next recession, earnings would need to fall by 40% from current levels.

Framework for valuing equities Part IV – PE Outlook

In previous post (Framework for Equity Valuation Part II – Equity Drivers), we have seen that the PE ratio can be an important medium term driver of equity prices. Given the debatable outlook for aggregate corporate earnings, this makes the outlook for the PE ratio a critical factor in forming a view on equities.

Simple PE ratio

It should be very clear from the normalised chart below that the powerful driver of the equity market performance since 2012 has been an expansion of the PE ratio. The S+P has risen by 72% over that period, and the majority of that is explained by PE ratio which has risen from 14 to over 21, an increase of almost 50%.

Can PE ratios go higher from here?

If we look over the long run, it is very rare for the PE ratio to move higher from where we currently are. In fact, it has only happened 3 times; 1991, 1999 and 2009.

In 2 of these 3 examples, high PE ratios were observed during a recession and ensuing bear market with earnings falling even more than prices . For example, in 2009, the high PE ratio was driven by the collapse in earnings not the soaring of equity prices to record highs. These are not helpful precedents for equity bulls right now.

The only previous period where the PE ratio drove the market higher from this level was the dot com bubble. The name given to this period gives a big clue as to what we now think of what happened. If that were to be repeated, then there would be another 40% left in this rally due to PE expansion. This is not impossible but relying on a repeat of the biggest valuation bubble in a century is not reassuring to me.

“Fed Model”

The post I wrote about the Fed model implied that equities represent good value compared with bonds. This generates a counter-argument to my scepticism of a repeat of the dot-com bubble. We have never seen bond yields this low before, so why should we not also see unprecedented low yields in equities (high PE ratio)?

As I explained in my previous post (Framework for valuing equities Part 1- Compared to bonds), I do not think that bonds are good value and so simply beating their performance may not be a high enough benchmark. Most importantly, if QE-driven low yields are pushing up PE ratios, then the termination of QE and rising bond yields should be very harmful for equities.

The other problem is that, even if it is true that holding equities for the next 10 years may work out, the volatility and drawdown you experience may be hard to handle.

For example,
In May 2007 from my equity model (Framework for valuing equities Part 1- Compared to bonds), the expected 10 year return for equities was 8.1% (annualised)

It actually turned out to be 7.1% annualised – which resulted in a total return of almost 100% over 10 years.

That sounds pretty good.
But I bet it would not have felt so good less than 2 years later in March 2009 after a 53% drawdown.

With hindsight waiting for a better moment to enter the long equity trade would have been phenomenally better. If you had waited to buy in March 2009 instead (I know, ludicrous cherry picking, but just about any time around then was great) then your returns would have been a total of over 300%.

Conclusion

The outlook for equities from the perspective of high nominal GDP or high earnings growth look rather limited. Earnings is near record highs as a share of GDP and we are at the stage of the cycle where wages are rising instead.

If we rely on a PE expansion to make us optimistic, we need to be comfortable buying at levels which previously have been associated with a “bubble”.

We can perhaps consider equities being good value compared to bonds, but we must then remember that yields are too low given fundamentals and the termination of QE.

If you are happy to hold them for a decade and do not worry too much about drawdowns, then I come up with an expected annual return of 6.5%. This is higher than bonds right now but perhaps waiting for a better entry level will turn out to be a better strategy.