Bear on its Back? (Part II)

Have we seen the bottom, or is this rally just another bear-snap?

In Part I of this series, I explored the fundamental drivers of the stock-market as I see them. In this Part II, I will first describe the Problem of Induction and how I think it applies to markets. Secondly, I will discuss the 6th and final fundamental driver of equity markets, and finally I will attempt to put the puzzle together and answer the question in the title.

You can read Part I here:

Bear on its Back? (Part I)

Quoted from Part I:

“On October 13th the S&P 500 dipped deep below the 200-week moving average but quickly regained this level. Bullish divergence between price and the RSI also confirmed on the weekly chart. This was a very bullish setup in classical technical analysis terms and for short-term traders it was a golden opportunity for a snap-back swing-trade.”

Since Part I was posted, we have had a lower-than-expected CPI print of (7.7% YoY) for October and the S&P 500 has subsequently moved higher and is currently 15% above the low of October 13th. So does the market continue higher, or are lower lows around the corner?

1. How important is historical data in forming a view on markets?

1.1. The Bear-killer

Let’s start with some chart-porn:

According to the data in the chart above, 9 out of the past 26 major lows in the S&P 500 since 1932 occurred in the month of October. Relative to other months, October certainly seems like a bear-killer. Assuming that the data is correct, I would however, not base any investment decisions on cherry-picked statistics such as this. Even though we might well have seen the 10th repetition of an October major low last month, viewed in isolation, this single piece of information, holds little to zero signal. Why?

To attach any value to the above observation, you would have to come up with a good explanation for October being such an outlier and then you would have to be convinced that this explanation holds true for the bear-cycle that we are currently in. the only explanation, other than chance, I can think of, is seasonality.

The chart below shows that seasonally, October, November and December are bullish months on average. So, under “normal” conditions (i.e., absent any other major macro drivers) one could attribute some positive credence to October being a generally more bullish month, but I would argue that the current situation is everything but “normal” with respect to the macro environment. Therefore, seasonality might have an effect in the short run, especially when considering the prevailing extremely bearish market sentiment and short positioning at present. but to attribute the end of the bear to seasonal effects, is misguided IMO. You only have to look at the deviation from the seasonal pattern during the period Jan to May this year to illustrate this point (See chart below). No, If the bottom was indeed in October, we will have to look for supporting evidence elsewhere.

If we separate out the seasonal data into bull and bear markets, (See below) one could argue that the current path in 2022 matches (so far) the bear seasonal pattern much more closely. But even this argument isn’t one to base any investment decisions on. Matching patterns with no good explanation for why they match, is simply useless.

Perhaps the best argument against the 9 out of 26 major bottoms occurring in October (as illustrated by the first chart above), holding any meaningful signal, is that 9 out of 26 is only a 35% chance that October will be the bottom of the bear — this is worse odds than a coin toss, and worse by so much that one could be forgiven for actually using this data as an argument for October not being the bear-bottom.

Interestingly, if we only look at proper bear markets (Drawdown > 19%) since WWII, 6 out of 17 also bottomed in October, which is the exact same 35% odds as the 9/26 mentioned above. See table below.

Over-analyzing and relying heavily on historical data such as the above monthly returns and weekly price chart, can be a trap, in my opinion. Trying to build confidence in a thesis of what to expect in the future, using only historical observations, without good explanations of why those specific observations materialized, is an example of the “Problem of Induction” as contemplated by philosopher Karl Popper. Without good explanations for the observations, there is no understanding, only patterns.

1.2. Turkeys and the Problem of Induction

Induction, as a method of gaining knowledge, says that a thesis can be derived directly from a set of observations. Then, when subsequent observations fall within the extrapolations of that thesis, the thesis is proven to be correct, without having to explain the causal link between the thesis and the observations.

A simple example illustrating the problem with this method, is the often quoted (and very apt) “Thanksgiving turkey”. It goes something like this:

A turkey who gets fed every day at the same time for three hundred days, using the method of induction, could conjecture that the farmer is a caring, turkey-loving person and that on the next day he will be fed again just as it was fed every day for as long as the turkey can remember. If the next day, the farmer feeds the turkey again, the turkey will feel that its thesis has held up and that it must therefore be true. For every subsequent day it gets fed, this belief will be strengthened. That is until the day before Thanksgiving. On this day, the turkey might see that the farmer is not approaching the pen with a bucket of feed, but instead, with a butcher’s knife. The inductivist turkey might explain this by saying, “I know what butcher’s knives are used for, but I have never observed that the farmer has used the knife on me in that way and therefore this new information is irrelevant to my thesis.” Needless to say, the turkey was going to get the surprise of its life, and not in a good way.

It is important to note that I do not exclude historical observations as part of the process of understanding the environment, on the contrary, observations are critical to test one’s theories. The problem arises when you induce your thesis directly from the observations and thereby skipping the critical step of coming up with good explanations of why the thesis led to those observations and therefore has a good probability (all else being equal) of leading to the same outcomes in the future.

At the risk of stepping on some toes, I think many (not all) technical analysts find themselves (unknowingly) ensnared in this problem of induction. I would include an earlier version of myself here. Nothing against TA — It is a powerful and useful tool within its applicable domain, as long as you stick to that domain, understand the problem of induction, and know how to avoid it.

Now for an example of a recent “turkey”:

(Don’t worry Ryan, you are not the turkey)

The table below (by @RyanDetrick) shows that since the S&P 500 was introduced in 1957, once a drawdown of more than -20% occurred, and half of that drawdown was retraced, the index never went below the prior low again. On 16 August, the criteria for this were indeed met. As 15 out of 15 times (up until the time of the tweet) this has happened in the past, can we say with any confidence that this time will be the same? It seems like a very compelling argument, but here we are — the S&P 500 has indeed made a new low (3495 on October 13th). Yes, for the first time ever. Thanksgiving has arrived for the turkey. (And today being the 24th of November, for everyone else as well).

@Ryan. I know you did not say that the S&P won’t make new lows, you just said it is a good sign. I do not suggest that you are the turkey. You simply made this very interesting observation. The turkey would be someone who bet the farm on the pattern holding.

In conclusion of this section on the importance of historical data I’ll summarize: Blindly relying on statistics without considering the effect that underlying economic and market fundamentals might have on the probability of the outcome, is reckless. Understanding the qualitative cause-effect relationships of the underlying drivers of the market says more about what might happen next than what history of what has happened, tells us.

This does not mean history is useless — no, history can tell us about those cause-effect relationships, but the data-points without good explanations can be misleading. As David Deutsch puts it: “The overwhelming majority of theories are rejected because they contain bad explanations (or no explanation at all), not because they fail experimental tests.”

So, if your back-test gives you 15 out of 15 positive results, without a good fundamental explanation of why those results were achieved, it is a worthless signal, or worse, no signal at all. Yes, it took the wise words of a physicist who has zero interest in markets to make me realize this truth.

2. What are the fundamental drivers of the stock-market and how can we explain the cause-effect relationships they have with price?

2.1. The first 5 categories

In Part I, I categorized the market drivers into 6 broad categories and discussed the first five. I will briefly list them again here:

• 1) Market liquidity and fund flows (Monetary & Fiscal policy and Credit conditions)
• 2) Economic outlook (GDP growth, inflation & employment)
• 3) Company earnings outlook (Revenues, profit margins and EPS)
• 4) Risk appetite (PE Multiple expansion/contraction &Equity Risk Premium)
• 5.) External Risk Environment (Geopolitics, natural disasters, systemic risks)

For the deep dive, read Part I here:

Bear on its Back? (Part I)

2.2. The 6th category — Market positioning, sentiment and technical structure

(6 drivers)

In this final category, we have to decide how much of the analysis in the first 5 categories have already been priced into the market. Getting this step wrong could mean the difference between success and failure. Because it is impossible to know for certain, risk management is the most important part of investing and trading. Ideally one should position one’s portfolio in such a way that you will make money (or at least not lose a lot) even if your analysis turns out to be wrong. This can be done with proper portfolio construction and risk management. But most importantly, knowing what to monitor for signals that your analysis was wrong and then to know how to adjust quickly.

In Part I, we have seen that the leading indicators are pointing to a high probability of a pretty nasty slowdown and recession in the next few months. That is if we’re not already in one. BUT, here’s the thing: markets are reflexive which means that the anticipation of something that seems to be inevitable in the data, can affect the actions of participants, thereby preventing the anticipated event from happening. This is the nature of a complex system where the observer is also a participant and what they observe and perceive, can influence the outcomes within the system. In other words, if everyone is expecting a recession, is this already priced into the market?

This is what makes predicting markets near impossible and why this 6th part in our analysis is the most difficult one. Understanding human behavior (and the behavior of the trading algorithms they conjure up) is key to this step.

Apart from understanding human behavior, you have to be aware of your own biases as well — and not just be aware of them but be able to guard against being influenced by them in your analysis and resultant investment decisions. It is in this process where most investors/traders fail. It requires deep introspection and brutal honest self-criticism — a process most humans find near impossible for many psychological reasons. (Perhaps a topic for yet another article).

The above is also one of my motivations for publishing these articles. If I cannot write a logical argument for my decisions, then I’m probably being swindled by my own biases. I also hope to provoke constructive criticism from readers to point out potential mistakes or biases in my reasoning.

2.2.1. Surveyed investor sentiment and portfolio allocations

According to AAII, sentiment is at extreme levels of pessimism:

The chart below shows that the surveyed equity allocations do not correspond to surveyed sentiment.

Fund managers might be super bearish, but if their investors (individuals/households) have not started to redeem yet, they have no reason to sell. After all, they have a mandate to be fully invested. The chart below shows that the % of managers who are overweight equities are declining, but they are still receiving net inflows of capital from investors.

Once individual investors start panicking and fund managers start receiving redemptions, another leg down in equity markets could unfold. More on the psychology behind “the second leg down” later.

Looking at cash allocations in mutual fund portfolios, we can see that cash has ticked up in recent months and is now close to March 2020 levels. But it is nowhere near the highs seen during the 2008 and 2001 bear markets. I’m not suggesting that we should expect the carnage of the 2008 GFC, but the market now, has to unwind much more inflated valuations than back then, and there is much more room to fall before cash allocations start spiking to levels where one could begin looking for a bottom.

What do financial advisors think? They seem to be super bearish, just like the fund managers. Note that similar levels of bearishness have marked major bottoms in the past, but the bearishness can also linger for much longer before a bottom in the market is found

What are insiders thinking and doing? They think there is value in the stocks of the companies they manage:

2.2.2. Derivative positioning

Equity index futures positioning is extremely short, hovering around March 2020 levels. This begs the question: Who is left to sell? Well, we’ve answered that question above — individual investors have not yet started selling out of their investment funds. However, the extremely short positioning in the futures markets can provide rocket fuel for the current bear market rally to continue, should there be a catalyst which moves the market higher and sends all the shorts to cover their asses. The lower-than-expected CPI print for October, released on November 10th was just such a catalyst.

The chart below shows that investors are buying put options as if they are expecting another 2008-style crash. Buying put options is another way of being short of the market, i.e. buying protection against equity downside. Put-buying activity on the 22nd of November reached levels last seen in the 2008–2009 bear market. This reiterates the point made above on rocket fuel for a bear rally to continue.

But if we look at a longer average (3 month) of Put-Call flows (not daily positioning as above) then it seems that the bubble is still unwinding and the market needs more time to find a bottom.

2.2.3. Market internals.

The chart below shows how a downtrend builds momentum as on every consecutive low, a larger number of stocks participate in making new lows of their own. But when each subsequent low in price is marked by a smaller number of stocks making new lows, that is a sign that the momentum of the trend is waning and an inflection point could be near.

2.2.4. Leverage used in trading

Margin Debt as a % of total market cap (Latest available data — 30 Sep 2022)

Margin debt as a % of total market cap has been declining over the past 12 months as the market deleveraged on increasing interest rates. This metric is now 1.3 standard deveations below its long term average, but nowhere near the 2 to 3 standard deviations below the average typical of major bear markets. Key point — there is room for more downside.

2.2.5. Loss of price momentum

When a shorter term moving average crosses below a longer term moving average, this is an indication that momentum has shifted to the downside. The chart below shows that the 50 week MA (blue) has now crossed below the 100 week MA (red). The past two times this happened was in the beginning stages of the 2008 and 2000 bear markets.

2.2.6. Market Psychology

Having observed markets for many years and having been caught in many of the psychological states of an investor/trader in many different market regimes, I think the following description by David Steets of “the second leg down phenomenon”, is the best account of the current market psychology. He posted this article on July 26 after the 19% July — August bear rally started to unfold. The market having made new lows since then and sentiment being even more bearish now, I think this article is now even more germane than it was back then. I’m going to quote parts from this article directly as I couldn’t describe it better myself.

“After a long, resilient period of exuberant sentiment (March 2020 — Jan 2021) with few and minor market setbacks, a prolonged stock market downturn will need several weeks or months to trigger a rise of extreme pessimism in traders and investors. Initially, they tend to remain anchored to the previous market regime, which handsomely rewarded a Buy the Dip mentality.

But over time mounting losses will cause this attitude to change, and inevitably filter through into actual investor positioning. They will decrease exposure to stocks as sentiment deteriorates, until there are fewer and fewer marginal sellers left. Despite a flurry of negative news and bad fundamental data stocks will stop going down — they simply can’t anymore, because everyone currently willing to sell their stocks or to bet on a falling market has already done so!

So this is where we are now: Equities hover above their lows and finally stage a recovery rally.

A long bear-market rally becomes a necessity, simply because deeply negative sentiment (and with it positioning) needs to reset for potential sellers to re-appear in the market. Once sentiment has normalized, and more and more investors are becoming convinced that the bottom is in, the stage is set for the next leg of the journey. Now the reality of the core macro environment becomes the decisive factor: Either the economy powers through a temporary slowdown (often aided by a dovish pivot in FED policy), or the fundamental deterioration continues, which, in the worst case, leads to a deep recession.

Today, I fear, lasting hawkish FED policy (caused by the toxic combination of resilient unemployment numbers in concert with steeply rising inflation) will cause a prolonged deterioration. For this reason, my main expectation (but not the only scenario I prepare for) is that we will see a strong second leg down — counter-intuitively it is likely to be worse the more enthusiastically investors are embracing the current rally as a potential turnaround.”

You can find David’s article here:

Second Leg Down Phenomenon - systematic individual investor

The answer to the question whether the market has priced in a recession, I think, is no. The chart below shows that in past recessions the stock market bottoms before the coincident and lagging indicators. But in the current situation, these indicators have not even started to roll over. So, if we are going to see a recession, I think it will be premature to say that the stock market has bottomed.

But if an impending recession is so obvious (as per the leading economic indicators) and everyone is expecting it, how can it not be priced in?

• Investors have been conditioned by the abundant liquidity regime since 2009 that “buy the f**k’n dip” is the best strategy out there. Like the turkey discussed in the first part of this article, every time they bought the dip, it worked out well for them and so the “thesis” was confirmed. Especially the last iteration which was in March 2020 when you kicked yourself if you did not buy the dip. I suspect Thanksgiving might have arrived for those turkeys — Oh, I mean, investors.
• Everyone seems to be expecting a pivot, or at least a pause by the Fed. But as discussed above, this time is actually different — the difference being a 40-year high inflation rate.
• The last proper bear market (2008–2009) was so long ago that many current market participants were too young to have been active in markets at that time. Those who were active, might have forgotten what it was like.

All of the above points are examples of recency-bias which is probably the most common and costly bias amongst investors.

To end this section on market sentiment, positioning and structure, I will quote George Soros, from his book The Alchemy of Finance: “It will be recalled that in the boom-bust model events tend to reinforce prevailing trends most of the time and contradict them only at the inflection point, and inflection points are notoriously difficult to identify. Now that the contrarian view has become the prevailing bias, I have become a confirmed anti-contrarian”

3. Putting it all together

(4 sections)

The question we want to answer is: “Was the 13th of October the bottom of the bear market, or will we see lower lows?”

In the analysis above and in Part I, I discussed the most important drivers (as I see it), that move equity markets, and I attempted to come up with explanatory theories as to how they do that. Now it is time to put the puzzle together and to come up with some conclusions.

To this end, I am going to use a simple Bayesian model to help me synthesize all the components of our analysis into a probability distribution of possible outcomes. Don’t worry, it is much simpler than it sounds and actually quite rudimental.

The Bayesian method can be summed up in three steps:

• Establish some prior credence for each of the possible outcomes.
• Look at the current data and adjust the prior credences to calculate posterior credences.
• Keep adjusting the creedances as the process evolves and new data becomes available.

As opposed to the method of inference called Induction (discussed above) Bayes’ Theorem is a method of inference, called Abduction.

3.1. Prior Credences

This is one of the areas where historical data is very useful. I will use the bear market data in the table below by Charlie Bilello (twitter: @charliebilello) as the source from which to calculate my priors. (For the philosophers amongst the readers, I am ignoring the Frequentist vs Bayesian conflict for purposes of this analysis.)

The current bear market duration has been 9 months with a drawdown of -28% so far, which is in line with the average and mean duration (12 & 7 months) and DD (-29% & -26%) of past non-recessionary bear markets. But we want to calculate a probability distribution, and not rely on only averages and means.

Using the data in the table above we can calculate the frequency and therefore the probability distributions of each of the 3 sets in the table below. Note that historical frequency does not necessarily reflect future frequency, but it is a good start. Also note that the 100% probability of a bottom being in after a drawdown equal to the worst historical DD is wrong. There is always a possibility of an even deeper DD in the future.

The line with the blue border is where we find ourselves at the moment with the current DD being -28%. According to this historical data, if we are not going into a recession, odds are 60/40 in our favor that the bottom is in, but if a recession is coming, chances are only 46%. Therefore, our credences, clearly depend on whether a recession is imminent or not.

3.2. Adjusting priors according to our analysis of the underlying market drivers.

(6 points)

3.2.1. Market liquidity and fund flows

In Part I we saw that the global liquidity cycle is now at similar levels to where it bottomed and turned up in past cycles. The lower-than-expected CPI number for October seems to suggest that inflation has peaked and that further aggressive rate hikes might not be required. But J Powell has made it clear that he will not be lowering rates until inflation is back down at 2%. He does not want to make the same mistake as Paul Volcker in the 1970’s when inflation came back with a vengeance after he lowered rates prematurely. See the two waves of inflation and the Fed Funds Rate in the chart below.

So, even if inflation keeps coming down, I think rates and financial conditions will remain restrictive for at least 1–3 more quarters, unless something in the financial system forces a pivot. However, as the economy slows down, the government’s tax collections decline, and they start having problems with new bond issuance, the Fed will have to start monetizing the new debt, thereby pumping liquidity back into the system to prevent sovereign insolvency.

For now, the tighter liquidity conditions in the short term, increases the odds for a recession to materialize and I will take this into account when adjusting our prior credences in the next section.

3.2.2. Economic outlook

(GDP growth, inflation & employment)

The leading economic indicators discussed in Part I and the tighter liquidity conditions in the short term, discussed above, points to a high probability of recession in the near future. I am assigning a discretionary probability of 65% for a recession to start in the next 1 to 2 quarters. If there is a 65% probability of a recession, then there is a 35% probability of no recession. So, let’s adjust our priors accordingly:

(% of total refers to the historical frequency of a bottom occurring in each DD-band)

This adjusted probability distribution indicates a probability of 51% that October 13th was the bottom of the bear.

3.2.3 Company earnings outlook

(Revenues, profit margins and EPS)

First margins start declining and then earnings follow. See chart below by Jurrien Timmer (@TimmerFidelity).

In Part I, I sketched my base case for earnings to decline in the months ahead, largely due to declining margins, the inflation bull whip and impending recession. But has this been priced in? Equity Risk Premium and Price-Earnings ratio will shed some light on this question.

3.2.4 Risk appetite

(PE Multiple expansion/contraction & Equity Risk Premium)

In Part I I discussed the current PE ratio and the CAPE ratio which is a better indicator of valuation as it is less sensitive to LTM (last twelve months) and NTM (next twelve months) earnings. I then calculated the price levels for the S&P 500 for each 10 percentage point increments between a 40% over-valuation and a 40% under-valuation relative to the long term mean of 20 (for the CAPE ratio). Reversion to this mean will put the S&P 500 price at 2700.

In order to incorporate this CAPE mean reversion into our Bayesian model, we need to determine probabilities for each level of mean reversion. I could not find historical data on this and therefore, somewhat arbitrarily, filled in the probability distribution below. My reasoning is that the S&P 500 is an index and cannot really go to zero, therefore with each 10 percentage points drop, the probability of dropping further should decrease. As pointed out above, the probability of 100% that the bottom is in on a CAPE ratio of 12.8 is wrong, but for simplicity I’ve made this, perhaps reckless assumption.

Now we need to bundle these results into our prior determined drawdown bands and update our credences. I’ve used a discretionary weighting of 30% for the CAPE Mean Reversion factor:

3.2.5. External Risk Environment

(Geopolitics, natural disasters, systemic risks)

As discussed in Part I, these risks cannot be quantified and can therefore not be incorporated into our Bayesian model.

“For purposes of this article, suffice to say that we are in an environment of heightened external risk and high volatility. Being on the defense is more appropriate than swinging for the fences”

3.2.6. Market positioning, sentiment, and technical structure

As discussed above, several indicators point to a potential continuation of a rally in the short term (1–3 months). However, once the rally has unwound the extreme bearishness and everyone starts believing that the bull is back, this will set the stage for “the second leg down” due to the fundamental drivers discussed above. This is not a prediction, but my current base case (Right reserved to change my mind). Therefore, I will stick to the adjusted probability distribution calculated above and won’t adjust it for a more bullish outcome, unless changes in the indicators demand it.

According to our simple Bayesian exercise, we can say that there is a 47% probability that October 13th was the bottom of the bear, and therefore there remains a 53% probability that we will see lower lows. These are not very high conviction odds and therefore caution and a defensive stance remains the best investment strategy at present.

In conclusion of the Bayesian discussion, I need to point out its non-trivial flaws and shortcomings:

• The data-points used for determining the prior credences was a fairly small sample size.
• I used many discretionary weights and probabilities and therefore the calculated result is susceptible to my own preconceived biases.
• The 100% probabilities in the tables above are wrong — in markets nothing is ever certain.
• Many of the market drivers discussed cannot be quantified or I don’t have the knowledge to calculate the quantities and therefore the model is incomplete.

Despite these shortcomings, I think the process is useful in that it forces one to think rationally about all the drivers of the market and how they might affect the future outcomes. It also highlights which indicators are important to keep an eye on and at which levels of the S&P 500 we can start looking for a long-term bottom.

3.3. My base-case, summarized

All the leading indicators show that recession is coming, but while the coincident and lagging indicators show that the economy is still resilient, monetary policy will most probably remain tight and the liquidity cycle will remain depressed. Once the slowdown starts to show up in the lagging indicators, liquidity might come back quickly if the downswing is severe, but if the recession is mild and inflation stays elevated, money could stay tight for much longer. The Fed will not pivot as easily as before because of inflation. Jerome Powell does not want to make the same mistake as Volcker in the 70’s when he started lowering rates too soon and a second wave of inflation hit which was even worse than the first one (See chart above, under 3.2.1).

October 13 was a local low and I expect a period of more bullish price action to unfold over the next 2 or 3 months. The seasonal pattern, together with the current over-bearish positioning is a nice setup for the ongoing relief-rally to extend further. If a recession is averted and inflation keeps trending down, Oct 13 might well have been the final bottom of the bear, but if the slowdown is severe and/or inflation stays elevated, then stocks will have to reprice and make new lows.

As the current relief rally gains momentum, the market will get incrementally more bullish on the following narratives:

• “A Fed pivot is around the corner”,
• “A soft landing for the economy is sure”,
• “Large cap tech has capitulated” and
• “Inflation is dead”

Then when the recession is deeper than anticipated, CPI turns out to be more sticky than expected, and the Fed pauses, but keeps rates higher for longer, the “second leg down” will unfold. This time, households will start redeeming their investments and finally cash allocations will spike. Then the lagging indicators will finally confirm the recession, and everyone will reach maximum bearishness and it will be time to look for THE bottom. Again, this is not a prediction but my current base case which could and will probably change as the future unfolds).

Should the above base case come to fruition, then it will be time to start averaging in on stocks. However, this time simply buying the index will not be the best strategy. What you buy will be very important this time round. Reasons for this and what to buy will be discussed in a future article.

Although I am expecting a second leg down, it is not a sure thing and therefore the time for turning defensive and raising cash was in May. See my article about this here:

From Pandemic to Putin to your Portfolio

While I still think defense is the best strategy until the recession is confirmed, and one could still raise some cash on bounces, I don’t think aggressive selling makes sense at this time. It is too late for that.

3.4. How will I know if I’m wrong?

One of the worst errors one can make in an analysis such as this article series, is to look for evidence that confirms one’s preconceived biases or opinions. While it is impossible to ever be completely unbiased, it helps to be aware of this possibility and try to look at both sides of the coin.

My current base case is bullish in the short term and bearish on a longer timeframe, but I understand that I might be wrong, and I have to constantly be on the lookout for signs that might confirm this.

Therefore, I will be watching all 6 stock market drivers and their leading indicators like a hawk to update my base case if it becomes clear that something else is happening.

I find it very useful to try and come up with scenarios under which my thesis will be wrong, and when I will have to reconsider everything. I can think of the following scenarios:

• 1. If inflation starts plummeting before a recession starts, and the Fed has no more reason to keep rates as high as they are now. In this scenario the Fed will be reluctant to cut rates too soon to avoid the double top inflation scenario discussed above, but rates should come down gradually and potentially avoid a deep recession. The chart below shows the reliability of Real Retail Sales (YoY % Change) as a leading indicator for inflation. Real Retail Sales (YoY % change) has declined sharply and is already in negative territory. This scenario is probably the most likely one after my base case.

• 2. If a recession does not materialize, or if it is very short and shallow and inflation keeps declining slowly. In this scenario The Fed will not need to keep raising interest rates and earnings might start ticking up again.
• 3. If something forces the Fed to start cutting rates aggressively or to start buying bonds in the open market, but the “something” does not affect company earnings adversely. It could be liquidity in treasury markets drying up or perhaps pension fund insolvency as we saw recently in the UK.
• 4. If the government approves a massive spending bill that stimulates energy and commodity production, rather than demand. For example, energy and base metal exploration and nuclear build programmes. This spending will bring down prices of energy and commodities without stimulating demand for final goods and services. This will bring inflation down, while the Fed will have to monetize the treasury issuance as there is no way that the bond market can absorb more bond supply on its own. In my opinion, this is the best way out of the mess, but also the most unlikely scenario due to politics and a lack of leadership.
• 5. If Fed Chair J Powell gets spooked by a deep recession scare or feels political pressure to cut rates before a recession is confirmed.
• 6. If the dollar keeps strengthening, the whole world economy is at risk because the dollar is the world’s reserve currency and the vast majority of global debt is denominated in dollars. Therefore, the whole world is short dollars and if the dollar keeps rising, the debt that needs to be repaid keeps increasing in value. This is unsustainable and if left to rise indefinitely, the world economy will collapse under an upward spiraling debt load. So, in this scenario the world’s central banks might come together to come up with a plan to weaken the dollar deliberately against other currencies. This was done in the 70’s with the “Plaza Accord” for these exact same reasons. In this case, the dollar will depreciate, world economic growth will pick up and stocks will start a new bull run.

4. Conclusion

This has been a long article, so well done and thank you for making it this far.

Investing and trading is not about predicting the future or about extrapolating patterns in historical data. It is about understanding the cause-effect relationships between the underlying fundamental market drivers, while knowing that anything could still happen, regardless of how well you think you understand markets. It is understanding that anything could happen, but nothing “should” happen — Markets simply “are”, they “aught” not to do anything. It is about having the imagination to see what the future could look like, to be prepared and to react appropriately to any of the possible outcomes. It is about knowing when to be aggressive and when to be defensive — about recognizing opportunity while protecting against downside. It is about using your knowledge to manufacture favorable asymmetrical risk-reward decisions and therefore asymmetrical returns over the long run.

In conclusion of this article, my final observation is that buying the S&P 500 at the 200-week moving average has been good entries in the past decade:

But accumulating shares below the 200-week MA has been the true winning strategy over the past 3 decades:

I think we are going to get another such chance soon. Embrace this rare opportunity if it presents itself. Both the historical data and fundamental market-driver-analysis support this thesis.

Happy Thanksgiving! (Albeit 4 days late)

I’m looking forward to your comments — especially to those with opposing views.

Good luck out there.

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Disclaimer

The views expressed in this article are the views of Johan Kirsten and are subject to change at any time based on market and other conditions. This is not financial or investment advice, nor a solicitation for investment funds and should not be construed as such. References to specific securities and issuers are for illustrative purposes only and are not intended to be, and should not be interpreted as, recommendations to purchase or sell such securities.