✨ How To Invest During A Recession - And In Fact, All The Time
✨ How To Invest During A Recession - And In Fact, All The Time
Understanding What Asymmetric Risk:Reward - and Value Investing - Really Means To Investors
Note from author: After putting pedal to the metal for 9 months nearly non-stop, I’ve decided to take a 1-month break for my sanity’s sake. I have paused billings for all paid subscribers for one month during this time of self-discovery and recuperation. See you all again in mid-September!
Until about 3 weeks ago, markets were utterly certain that the global economy was poised to enter into a deep and long-lasting recession. Not a day went by without some macro gypsy casting shades of grey over the very prospect of humanity itself - with news headlines promulgating scary clickbait titles like “A full-blown recession is 'almost certainly' coming” and “The Great Crash of 2022”. Strong phrases like “hard landing” and “no more forward guidance” were cast around like fertilizer for confirmation bias, and herd mentality led investors to stampede for the exits.
Then amidst all the carnage, markets let up for a bit all of a sudden - and investors suddenly found themselves coming up for a breath of fresh air. To be fair, the recent market optimism doesn’t invalidate any of the prior doomsday concerns - certainly nothing has changed in the macroeconomic fundamentals in a few mere weeks. Recent publications by some excellent economists such as The Macro Compass, Apricitas Economics and Bridgewater Associates did little to assuage concerns that the US economy hadn’t yet found its footing - pointing to disquieting data points such as Real Final Sales to Private Domestic Purchasers hitting the zero-bound and how most of Q2’s job growth actually came from the government sector:
I have my own thoughts on US macro, but adding them here to the veritable sea of macro opinions out there would contribute little added value. Rather, my point is to demonstrate how markets are fickle - they can sing a song one day and a requiem on the next. And just as market optimism recently rebounded overnight, so to can they reverse abruptly into a funk tomorrow, next week, month or quarter. Therefore, it pays to be prepared for that eventuality.
While it is certainly true that volatility does not equal fundamental risk, when markets are gesticulating like this it can be difficult to differentiate between the two. These are the times when self-proclaimed volatility-agnostic investors tend to throw in the towel - as share price volatility increasingly appears to look like actual risk. The question then begs - how do we tell the difference between the two, and how do we manage them?
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Valuation Methodology: Why Bottom-Up > Top-Down
If you look back over the global events of the past two years, you’ll agree with me that macroeconomics is effectively unpredictable (for all practical intents and purposes). There’s actually a very simple reason for that - the future has yet to be written, and nobody can really analyze how something might turn out when it doesn’t even exist yet.
Think about the major macro events that are expected to take place over the remainder of 2022 - the Italian elections, potentially more China lockdowns, Xi’s re-election in November, US midterm elections, the potential end of the Ukraine war, the future trajectory of oil prices, Taiwanese Strait developments, the impending food shortage of 2023… and so, so much more. Can anyone really predict the outcome of any of these with >80% certainty - much less all of them at the same time, and discern their impact on markets?
And yet we can all agree that these macro events do indeed have an outsized impact on the share prices of our investments. This implies that trying to predict the trajectory of markets in a top-down manner is futile - no matter how much elbow grease we may apply to the endeavor. This is what Warren Buffett means when he says that he “doesn’t believe anybody knows what the market is going to do tomorrow.”
As such, if trying to identify future macro outcomes from the top-down is infeasible as a portfolio strategy, then the only remaining way to approach them is from the bottom-up. By definition, a bottom-up approach towards macro positioning leaves our guesses regarding the final outcome open-ended - we are simply trying to figure out what all the potential likely outcomes might be in a probabilistic fashion, and then position ourselves accordingly in a risk-intelligent manner.
Allow me to illustrate. The way the status quo teaches investors to approach stock analysis is by trying to analyze what will happen over their investment horizon - and then through superior analysis, determine the exact series of events that will play out in order to arrive at a stock’s valuation. This is what we refer to as a top-down approach - and it tends to take the form of the DCF valuation model.
In contrast, investor who take a bottom-up approach to stock valuation approach things differently. They will take the present-day as their starting point, and look outwards into the future - and then assign probabilities to different possible future scenarios. Then, they will average all the potential Outcomes x Probabilities to arrive at the potential average impact and therefore average future valuation of the company. This is called the Expected Value methodology of valuation. (e.g. we might think there’s a 40% chance of the Ukraine war ending by December, which might justify cycling out of O&G stocks before then if the potential downside is high enough)
While the top-down approach to stock valuation will always be superior to the “average” bottom-up approach if the analysis is “correct”, it also risks the possibility of significant underperformance should the analysis turn out “wrong”. And when it does, the fallout can be tremendous (e.g. Tech stocks last year). An “average” Expected Value approach, on the other hand, would likely underperform if the analysis is “correct” but outperform if the analysis ends up “wrong”.
Notice what I’m saying here. In stark contrast to the popular notion of needing to be “correct” about your stock analysis, a bottom-up approach allows the investor to be “wrong”. Typically, the way that this would manifest is that the investor may lose an acceptable amount of money in the adverse scenario - but would typically escape relatively unscathed and live to try another day. In contrast, investors who are wrong about their DCF valuation typically get wiped out.
This downside protection becomes especially pertinent when you consider what I mentioned earlier - macro is completely unpredictable. Even a 12-year old could tell you today that the world feels significantly more uncertain than before the pandemic began - and yet a top-down valuation methodology requires us to get the analysis “correct”. It necessitates it - failure is simply not an option. Does proferring that level of foresight sound like how the world - and by extension, stock markets - behaves to you?
This bottom-up approach to investing in stock markets is perfectly encapsulated in George Soros’ quote below:
In his quote above, Soros specifically states that we do not need to be “right” about our stock analysis or valuation. Rather, we simply figure out what the odds are in both directions, and position our portfolios accordingly. This includes figuring out what the potential consequences/impact of our analysis being “wrong” are - and then deciding in advance whether those risks are worth taking (rather than after the fact, as most investors are wont to do).
Of course, the ideal outcome would be to always get our analysis “right” - indeed, this is what the status quo prescribes. And yet even an investing legend like Soros eschews this approach in favor of investing in a probabilistic fashion - for the simple reason that macro is unpredictable, yet can have drastic impacts on our portfolios.
But what of Buffett’s own advice to “buy good companies for the long term” and ignore short-term volatility? Let us now explore this below.
Is It Volatility, or Is It Risk?
Some amongst Buffett’s ilk might ask - why do we even need to consider macro portfolio positioning in the first place? Does value investing not advocate the complete eschewing of share price volatility as a concept (i.e. buy and hold) - and therefore that investing in wonderful businesses with great fundamentals should be enough? Why do we even need to care about volatility?
Firstly, allow me to clarify that Buffett is absolutely correct when he says that investors shouldn’t care about share price volatility. However, over the decades, investors seem to have taken that quote to the opposite extreme and morphed it into their own version - to the point of it becoming self-defeating and ignoring common sense. Remember, Buffett’s quote about investors ignoring volatility was in reference to avoiding speculation - represented by the complete eschewing of fundamental intrinsic value when performing stock valuation in favor of daily stock price fluctuations. In contrast, “long-term” investors today seem to be using that narrative to justify buying businessess with great fundamentals at any price. This is not the same as ‘ignoring volatility’, and is as much of a mistake as participating in speculation itself.
There are several problems with assuming that an investment bought at any price will eventually do well - and can therefore justify ignoring short-term volatility. Firstly, Buffett’s quote about ignoring volatility and focusing on the fundamentals comes from a businessman’s point of view. Certainly, most businessmen without a finance background get along just fine without having any knowledge regarding portfolio positioning or macroeconomics - and good businesses run by good management teams tend to weather market downturns just fine.
However, that is not the same as saying that one only needs to identify what the future of the business will look like in 5 years time and assume a straight-line performance will occur from today to then - where everything else can be discounted as noise. That is simply not what Buffett is preaching with regards to “ignoring volatility” - which is quite evident when you consider that even the fundamental intrinsic value of a business can change over time with new future developments (i.e. volatile fundamentals).
Also, this approach of “ignoring volatility” assumes that the shares of those good businesses were acquired at fair value. The businessman as described above would have an organic sense of what his business is worth - and would not buy into an incremental stake at much higher prices than fair value. In contrast, many stock market participants tend to latch onto the wonderful “moat” business and rely on the “ignore volatility” narrative to justify buying shares of their favorite business at any price - consoling themselves that they would simply hold them through downturns expecting an eventual recovery.
There is one big problem with this approach - if you buy into a good business at a far higher price than fair value and it drops back down to its fair value, that’s not volatility anymore - that’s permanent capital loss. A good example would be Netflix, which I wrote about back in May when it was trading at a mere 17x PE (some may disagree whether Netflix qualifies as a good business, but that’s besides the point). If you had bought NFLX shares when they were trading at 60x PE in Nov 2021, you’re probably not going to see your investment recover for awhile even if the underlying business remains intact. That’s a permanent capital loss, not short-term volatility anymore.
In this sense, while Buffett is certainly correct that investors should ignore share price volatility when making investment decisions, it is important to distinguish between what is volatility and what isn’t. Just because a business has great fundamentals doesn’t mean its shares can’t become overvalued - and the mantra of ‘buy and hold’ stops being relevant if you buy into its shares at significantly above fair value and end up permanently losing money (i.e. price risk), even if the business remains fine. When the piper finally comes calling, the price of the debt paid will be just as painful as if fundamental risk had materialized.
Circling back to my earlier suggestion about investing from the bottom-up (e.g. Expected Value) rather than using a top-down approach (e.g. DCF), it becomes apparent how following a dogmatic “buy and hold” approach can still end up being “wrong” and result in losses. This is especially pertinent when we factor in the aforementioned role of macroeconomics in stock valuation - which as we’ve established earlier, is completely unpredictable and can lead to the status quo changing.
There’s actually another problem with having to be “correct” when using a top-down stock valuation approach - it assumes that the current status quo will persist. For instance, analysts who had used the DCF model to estimate Tech stock valuations in early 2021 would likely have imputed interest rates staying at persistently low levels - since that was the status quo at the time. Similarly, O&G analysts today would likely be imputing the assumption that O&G supply chain disruptions would persist further - even if it remains possible for both sides of the war to unexpectedly reconcile overnight. If the latter scenario suddenly takes place, investors in O&G stocks might wake up to find out that the status quo has changed, and the share prices of their O&G stocks tanking overnight.
This is the problem with having to be “correct” all the time - by leaving no room for error in your investment decisions, being “wrong” can lead to unacceptably catastrophic portfolio consequences. Of course, it would be ideal if we could be “correct” all the time - but unfortunately as I’ve demonstrated above, that is impossible. In the absence of such an inhuman feat, the next best approach is to build in the possibility of being “wrong” into our investment models. And we need to do this due to the existence of “Bounded Rationality”.
Bounded Rationality & Risk:Reward
Many investors (including professionals) pay lip service to the idea of asymmetric risk:reward - but when probed, it quickly becomes apparent that their portfolio positioning bears no semblance of such a strategy. Rather, most investors tend to pursue a portfolio strategy of“maximum profit at maximum risk”.
To be fair, human nature is somewhat hardwired to pursue maximum ROI - to the point where not pushing the envelope for maximum profit is sometimes perceived as “waste”, or “leaving money on the table”. Hence, it is only natural for human stock market investors to pursue maximum ROI as their investment goals as well.
However, in the calculation of maximum ROI lies the assumption of “perfect rationality”. That is, human investors tend to unquestioningly believe that they are seeing the full picture at all times - and therefore that they are capable of perfectly rationality in their capital allocation decisions. Even worse, many humans tend to be unaware of the possibility that they may not be seeing the full picture when making their investment decisions.
To illustrate, say an investor needs to make a stockpicking decision depending on whether US inflation will go up or down. He may be able to foresee cooling economic developments in the US economy, and may even be aware of the possibility of further China lockdowns potentially introducing deflationary forces. However, he may not be aware of the impending food crisis that is currently developing in the Middle East & Africa - which could throw all his carefully crafted plans into the gutter if global inflation potentially rears its ugly head next year.
Here’s the thing - it would be one thing if the investor was simply unable to estimate the potential inflation in the Middle East for some reason, as it was an unknown that he could have been aware of (i.e. known unknown). The bigger issue is that these sort of things tend to relate to matters that the investor couldn’t possibly have been aware of in advance no matter how hard he tried - since the matter fell outside his perspective to begin with (i.e. unknown unknown). In military doctrine, we call this the “fog of war” - or more colloquially, what you don’t even know you don’t know. And yet despite such onerous terms, such an omission would clearly have an outsized impact on his portfolio.
This is a problem because prevailing finance theory (e.g. EMH) automatically assumes that investors have “perfect rationality” - whereas as I’ve clearly demonstrated, not only are there unknowns which could potentially impact our portfolios, but we may not even be aware that these unknowns exist (i.e. unknown unknowns). Keep in mind that macro factors which affect stock prices tend to encompass the entire globe - so there is ample opportunity for something material to slip past your filters undetected, and proceed to rampage your portfolio into oblivion a few quarters later.
Around a decade ago, the concept of “Behavioral Finance” became all the rage when it was popularized by the Nobel prize-winning author Daniel Kahneman of the bestselling book “Thinking Fast And Slow”. While behavioral finance had already made the rounds in academia long before then, it fired up into the financial zeitgeist around 2012 by challenging the incumbent notion of the Efficient Market Hypothesis (EMH).
At the heart of behavioral finance lies the concept of “bounded rationality”. As its name implies, humans are capable of being rational - but only within the limited perspectives that they are capable of perceiving at any one point in time (hence “bounded”). This means that if a factor relevant to our decision-making happens to fall outside of our perspective, it is possible to be rational and yet not end up with a perfectly rational decision - since that factor which was not within our field of vision at the time of our decision-making was not under consideration.
While humans are more than capable of being perfectly rational at local scales, bounded rationality starts to come into play once the scope of the matter at hand reaches a certain scale. Think about something like geopolitics or international trade - it is all too easy to miss something significant simply because of the sheer global scale of the subject matter. Unfortunately, all too often that thing which is missed and not considered tends to be material and eventually finds its way into markets - which means that an investor operating under ‘bounded rationality’ may not even know what he doesn’t know at the time of his investment decision. And if that investor mistakenly believes that he has considered the full picture when he actually hadn’t, that could lead to a lot of potential problems down the road.
Worst yet, top-down valuation methodologies like the DCF model completely ignores the existence of this natural human weakness. If you have performed a stock valuation with a DCF model before, you’ll know that it expects the user to have perfect rationality and be able to input all relevant information into the model to yield an accurate valuation. If we start with the assumption that the user might potentially be missing something material to the valuation, you might as well throw the resulting DCF model into the garbage. This inability to accommodate ‘bounded rationality’ makes rigid valuation methodologies like the DCF model basically useless when taken at face value - which might explain why the target prices of sellside analysts tend to consistently miss over time.
Hence, if ‘bounded rationality’ exists and we sometimes don’t even know what we don’t know - what could the solution possibly be? If a top-down valuation methodology doesn’t work, then perhaps a bottom-up version might.
The great thing about taking a bottom-up approach to portfolio positioning is that you don’t actually have to be pinpoint accurate in terms of predicting final outcomes. By definition, a bottom-up approach is anchored in the present-day rather than the end-destination - and rather than try and determine what will happen with certainty, the investor simply guesses at what could potentially happen “shotgun-style”. This allows the investor to consider all potential possibilities rather than simply hovering around the most likely outcome (i.e. consensus) - and by doing so, it forces him to cast his net wide and look in places most others might not even be considering.
Most importantly, a bottom-up “probabilistic” approach like this allows the investor to be “wrong”. Let’s say that an investor thinks there is a high chance (e.g. >80%) of a stock attaining 200% returns. Where the top-down “outcome” approach might inform him to go all-in in order to maximize his returns, the bottom-up “probabilistic” approach would force him to consider the potential consequences of the remaining 20% outcome materializing. If those potential consequences could be devastating enough to his portfolio, he might just end up tempering his conviction and take active steps to limit his potential downside in advance - which gives him room to be “wrong”, yet still end up with an acceptable outcome if it occurs. (at the tradeoff of maximum potential upside)
By giving himself room to be “wrong”, an investor can manage the consequences of ‘bounded rationality’ by positioning himself in a risk-intelligent manner after considering all reasonably predictable outcomes (i.e. non black-swans). This way, even if his valuation ends up being “wrong” due to the vastness of global macro, he shouldn’t be exposed to unacceptable losses - since his model had embraced the possibility of being “wrong” to begin with.
This bottom-up approach is encapsulated in the aforementioned Soros quote:
Here, Soros is saying that you don’t actually have to correctly predict what will happen (a la DCF model), but rather identify all the potential possible outcomes and prepare for them in advance. Obviously, the potential upsides represent “how much money you make when you’re right”, while the potential downsides represent “how much you lose when you’re wrong”.
As mentioned, the bottom-up approach as described above is a probabilitistic one. Using the present-day as his starting point, the investor looks around him and considers all possible future outcomes (rather than trying to predict only one outcome), assigns a probability of occurrence to each of them, and then invests using an Expected Value method (i.e. average Probability x Impact of all potential outcomes).
In the context of global macro forecasts, he might determine that there is a 20% chance of deflation and a 80% chance of inflation. Notably, he isn’t positioning himself such that inflation will definitely happen (despite the 80% probability of high inflation) - and tempers his expectations probabilistically as such.
The resulting Expected Value valuation represents the “Risk:Reward” of the stock. Rather than trying to determine outcomes with absolute certainty (and wipeout if we fail to), we are simply considering what the likely risks and rewards of all the potential outcomes are - and invest only when there exists asymmetric upside to downside (e.g. 3:1). Coincidentally, this also happens to be how most businessmen organically approach their decision-makin - rather than approaching decisions from a binary perspective.
However, up to this point we have only considered the “Risk:Reward” part of “Asymmetric risk:reward”. Here is where the “Asymmetric” part comes in.
Asymmetric Risk:Reward In Mispricings
To demonstrate why an “asymmetric risk:reward” approach might be superior to a “maximum profit” approach, let us use the current market environment in our scenario analysis example.
Recent market optimism notwithstanding, the fact remains that the global economy is still in significant flux. Seemingly at the same time, markets are worried about both inflation and deflation (i.e. recession) - but there also appears to be hope for a ‘soft landing’, throwing even more confusion into the prediction mix.
Now, how would a top-down investor approach forecasting in this market environment, if “maximum profit” was their goal? An investor who is convinced that hyperinflation will take hold might convince himself to hold tangible assets like gold or real estate; while an investor who is convinced that a ‘hard landing’ recession is upon us might decide to simply wait things out by switching to all-cash or fixed income. Finally, someone who believes that a ‘soft landing’ might be possible might choose to stay invested in equities - since he believes that the real economy will eventually recover, but may not want to time the recovery.
All their investment strategies above would be fine and dandy - if each of them was “right”. However, the problem is that all of them can’t be “right” at the same time; if one of them is “right”, then two of the others must be “wrong” - with the following consequences to their portfolios:
If the hyperinflationary hawk were “wrong”, he could end up holding gold while the USD recovered;
If the dovish bear were “wrong”, he could end up holding all-cash or fixed income in a bullish stock market;
If the ‘soft landing’ optimist were wrong, he could end up holding equities into a recession.
Naturally, the solution for the top-down investor appears simple at first glance - don’t be “wrong”! And that is indeed how the majority of market participants approach investment strategy. However, given the heightened levels of macro uncertainty as described above, very few professionals can truly put their money where their mouth is in claiming that they will definitely be “correct”. Ask any economist today and they will state that any of the aforementioned macroeconomic scenarios remain solidly in play today - hyperinflation seems unlikely now, but both the recession and ‘soft landing’ scenarios are still equally likely to happen.
Now throw in even more future unknowns like the results of US midterms in November and the forecasted end of the Ukraine war in December - and your forecasting efforts are basically the portfolio equivalent of trying to find a needle in a haystack.
In contrast, let us now turn our attention to the bottom-up investor who invests in a “probabilistic” fashion. As described earlier, he doesn’t try to pinpoint what “will” happen in markets in the coming months or years - rather, he tries to figure out what the respective “probabilities” of each of those outcomes materializing might be.
Continuing from the scenario above, let us assume that he ends up estimating that there is a 10% chance of hyperinflation, 40% chance of recession and 50% chance of a ‘soft landing’. As a rational investor, he might be able to afford putting aside the 10% possibility of hyperinflation - however, the 40% chance of recession and 50% chance of a ‘soft landing’ still remains a coin toss. And given the drastically different portfolio outcomes from choosing the “wrong” side, neither is it ideal for him to simply average both of their probabilities and pick something in the middle.
Well, what is our bottom-up investor to do? At this point, he has managed to determine the respective risks and rewards involved in the prevailing macro environment - but is still unable to transform that insight into an actionable strategy. Based on the portfolio risk:reward ratio that he has identified above (i.e 10:40:50), he could flip a coin and choose a side or take an average position firmly in the middle. All of which still exposes him to the possibility of being drastically “wrong” - either to the upside or downside.
Now, here’s where the “Asymmetric” part comes in.
Up to this point, our bottom-up investor has managed to determine what the risk:reward of the prevailing market environment is. And while this risk:reward distribution has left him paralyzed by inaction, he can still scour the market for positions which reflect an asymmetry of that risk:reward. Typically, that asymmetry will present itself in the form of mispricing. That is, a stock or other security will be on sale for a particular price that for some reason reflects a better risk:reward distribution than the baseline that he had previously identified.
Mispricings can occur for a variety of reasons. Sometimes, it could be due to idiosyncratic reasons unrelated to the wider macro environment - such as how Intel (INTC 0.00%↑) today is being lambasted for the sins of its past decade. Or it could be that the gains are obviously apparent to all, but remain far in the future and is therefore considered unattractive to shorter-term investors - such as with a recent US Railroad stock I wrote about, Canadian National Railway (CNI 0.00%↑) . (linked below)
In particular, we are not simply looking for mispricings to the upside (i.e. low-hanging fruit) - we are also looking for mispricings to the downside (i.e. margin of safety). The very notion of mispricings flies in the face of the EMH - since the latter asserts that all publicly available information is already priced in. As someone who has spent a considerable amount of time in markets, I can assure you that mispricings certainly exist - and if you look hard enough, you will find them eventually.
The objective of this exercise is that once such mispriced stocks are found, the bottom-up investor can feel very confident that these stocks represent an asymmetry to the baseline risk:reward that he had identified earlier. And if his portfolio is sufficiently diversified with stocks that all represent asymmetric risk:reward, the risk composition of his portfolio basically mimics the probability distribution of a bell curve - effectively providing him with the same risk distribution as a casino.
Circling back to our earlier scenario of a 40% chance of a ‘hard landing’ and a 50% chance of a ‘soft landing’, an investor might find a mispriced stock like Canadian National Railway (CNI 0.00%↑) which can manage both potential scenarios satisfactorily at the same time. It pays out all its annual earnings back to shareholders in the form of dividends and buybacks, making it a decent recession hedge - while at the same time benefitting from the incoming secular commodities boom which should allow it to do well in a recovery. And given how Class 1 US Railroads represent the picks & shovels of US Commodities (as described in my US Railroad industry primer below), CNI 0.00%↑ is also expected to do well in a hyperinflationary scenario:
Therefore, regardless of whether hyperinflation, recession or a ‘soft landing’ materializes in the future, investors can still be assured of getting what they want - since it takes the pressure of needing to be “right”. This is what Asymmetric Risk:Reward looks like.
It should be noted here how the investment objective here isn’t to obtain the best outcome (e.g. highest returns). The goal instead is to obtain the best odds/probabilities for your portfolio - which can be amplified further by asymmetry via mispricings. The idea here is that attempting to identify future outcomes at such massive scale is a futile effort; hence the next best thing is simply to play the odds in your favor (e.g. like a casino or insurance company).
In this vein, the bottom-up investor can adjust his portfolio to reflect the best risk:reward in changing market environments. As the status quo of markets change over time, so to will the perceived risk:reward of staying invested in certain positions. Hence, the bottom-up investor’s job is simply to respond to changing future information in the best way possible realistically (e.g. Buffett’s decision to dump his airline positions once COVID-19 hit - something which he could not have known in advance.
Notably, this can mean that you may not necessarily end up achieving the best returns in any given year - since a portfolio which had embraced worse odds and greater risk could end up outperforming a portfolio positioned for optimal risk:reward. However, over the long-term it is almost guaranteed that a risk-optimized portfolio will generate greater absolute returns.
In fact, empirical evidence supports this. In Howard Marks’ 1990 letter ‘The Route to Performance’, he cites the example of a pension fund manager who had occupied the first-quartile of outperformers over the long-term; but strangely had only ever occupied the ranks of second-quartile performers in the short-term:
The best part? When you invest in this manner, you’ll look back in hindsight and recognize that the type of stocks which you ended up picking look completely different from the type of stocks most investors who are seeking maximum returns tend to gravitate towards (e.g. Hibiscus and Innature). And because of that, there’s also less competition in terms of finding bargain share prices for these stocks (i.e. mispricings) - and therefore Asymmetric Risk:Reward.
Circling back to our title, this is a reliable and optimal way of Investing during Recessions - and in fact, All the Time - by exploiting the probabilities inherent in stock markets to secure long-term (financial) success.
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