Case Study 8 — The 2021 NEPSE Mania

First published 26 Aug 2026 · Last verified 29 Aug 2026

Case Study 8 — The 2021 NEPSE Mania

My name is Suman Kandel, and for eleven months in 2020 and 2021, I was a genius. I want to start this case study with that sentence because it is the most important sentence in it. I was not a genius. I was a schoolteacher in Kathmandu with a Mero Share account, a Smartphone, and a lot of free time during the pandemic lockdowns. But for eleven months, every share I touched went up, and I began to believe that this was because of something I understood and other people did not.

I am telling you this story now, several years later, because NEPSE — the Nepal Stock Exchange, the single exchange where all publicly listed Nepali shares trade — went through one of the most dramatic bull-and-bust cycles of any market, anywhere, between 2020 and 2023. The benchmark NEPSE index fell to roughly 1,100 points in the panic of March and April 2020, when the country went into its first COVID-19 lockdown and the market itself closed its doors for weeks. Then it climbed, almost without pausing to catch its breath, past 2,000, past 2,800, and finally to an all-time closing high of 3,198.60 points in mid-August 2021. Then it fell for the better part of two years, grinding down to an intraday-era low of 1,848.28 points on June 23, 2022, drifting into the high 1,800s by the end of that year, and staying depressed well into 2023.

If you have read Part XVI of this Canon up to now, you already know the shape of a case study: real numbers, a narrator who lived it, and a set of lessons that connect back to the earlier chapters of the book. This chapter connects most directly to Chapters 50 through 53, where we studied the specific behavioural biases that make Nepali investors — not foreign investors, not institutional investors, but ordinary NEPSE retail investors like me — lose money even in markets that are, overall, rising. It also connects to Chapters 54 through 58, where we studied liquidity, circuit breakers, and what happens when everyone tries to sell at once in a market that is thin to begin with. The 2021 mania and the correction that followed it is the single best real-world laboratory Nepal has produced for testing every idea in those chapters at once. So let's walk through it, year by year, and then let's ask the only question that matters for you as a reader of this Canon: what would a disciplined process — a Canon Score, a position-sizing rule, a written exit plan — have actually done differently, in real time, while everyone around it was either euphoric or terrified?

Lesson 90.1 — The Setup: How a Pandemic Built a Bull Market

To understand why NEPSE went from roughly 1,100 points to over 3,000 points in about sixteen months, you have to understand four things that were happening in the Nepali economy at the same time, none of which had anything to do with company earnings.

First, interest rates collapsed. Nepal Rastra Bank, the central bank we have discussed throughout this Canon as the referee of the country's money supply, cut its policy rates and flooded the banking system with liquidity to keep the economy from seizing up during the lockdowns. Fixed deposit rates at commercial banks, which had been a comfortable 9 to 11 percent for ordinary savers in earlier years, fell toward 5 to 7 percent and in some cases lower. For a retail saver in Nepal, a fixed deposit is normally the safe, boring alternative to the stock market — you lock your money in a bank for a year, and it grows slowly and predictably. When that boring option stops paying you enough to beat inflation, money that would otherwise have sat quietly in a bank account starts looking for somewhere else to go.

Second, remittances did something almost nobody expected. Nepal is a remittance economy — a large share of national income arrives as money sent home by Nepali workers abroad, mostly in the Gulf and Malaysia, mostly to support families rather than to invest. Economists expected remittances to collapse during a global pandemic, since migrant workers were losing jobs too. Instead, remittance inflows stayed resilient and in some periods even grew, partly because workers stranded abroad with fewer spending opportunities sent more of their earnings home, and partly because families used formal banking channels more than informal ones during lockdowns. That money landed in Nepali bank accounts. Some of it paid down debt or covered household expenses. Some of it, for the first time in many households' history, found its way into a demat account.

Third, there was simply nothing else to do with your money or your time. Nepal's lockdowns were long and strict. Shops were closed. Foreign travel was impossible. Weddings, festivals, and the ordinary social life that usually absorbs household income and attention were suspended. Meanwhile, the entire process of opening a demat account — the electronic account required to hold shares, administered through the Central Depository System and Clearing Limited, or CDSC — and a trading account with a broker had become easier thanks to online systems like Mero Share and the broker-side Trading Management System, or TMS, which let you place buy and sell orders from a phone instead of standing in a broker's office. CDSC's own published figures show the number of demat accounts roughly tripling from the years just before the pandemic to past four million by 2021, with a very large share of those new accounts opened in 2020 and 2021 specifically. A market that had been the preserve of a relatively small circle of regular investors was suddenly full of first-time participants, many of them opening an account for the first time in their lives during a lockdown, with a phone in one hand and nothing else to do.

Fourth — and this is the part that turns a recovery into a mania — brokers extended margin lending, meaning loans specifically for buying shares, using the shares themselves as collateral, more aggressively than they had before. If you want to buy 100,000 rupees of shares but you only have 40,000 rupees, a margin loan lets a bank or finance company lend you the rest against the value of the shares you already hold or are about to buy. This is not unique to Nepal — margin lending exists in every stock market in the world — but in a small, illiquid market like NEPSE's, where a relatively modest amount of new buying can move prices a long way, margin lending acts like pouring petrol on a fire that is already burning.

None of these four forces — low interest rates, resilient remittances, lockdown boredom, and expanding margin lending — is a company-specific reason to buy a share. None of them tells you anything about a bank's loan book, a hydropower company's power purchase agreement, or an insurer's claims ratio. They are liquidity forces: they describe how much money is chasing how many shares, not what those shares are actually worth. Chapter 12 of this Canon, on the difference between price and value, made exactly this point in the abstract. The 2021 mania is what it looks like when that abstract point becomes a lived national experience.

I remember the day I opened my Mero Share account. It was during the second lockdown, in the middle of 2021 — the second wave of restrictions, running roughly from late April to mid-August that year, not the longer first lockdown of 2020 that had closed the market entirely. My cousin, who worked at a finance company, told me that "share ta paisa haldai jane ho" — with shares, you just keep putting money in and it keeps growing. I put in the modest amount I had saved rather than spent, since there was nowhere to spend it. Within a few months, that amount had grown by more than half. I did not attribute this to low interest rates or remittance inflows. I attributed it to my own judgment.

Lesson 90.2 — The Mania: New Accounts, Margin Loans, and the Language of Certainty

By early 2021, something had changed in the texture of everyday conversation in Kathmandu. Share prices came up at tea shops, at family gatherings, in the WhatsApp groups of my former college classmates. People who had never mentioned NEPSE in their lives were now asking me — a schoolteacher — for stock tips. I gave them. I want you to sit with that sentence, because it is the clearest single signal of a mania that this Canon can offer you: when people who have no professional or informational advantage in a market start giving each other confident advice, and when the target of that advice is not "should I invest at all" but "which specific script will double fastest," you are no longer in a market driven by analysis. You are in a market driven by social proof.

Chapters 50 through 53 named several specific biases that explain why this happens, and it is worth naming them again here, because the 2021 mania produced textbook cases of every one of them.

Herding, covered in Chapter 51, is the tendency to do what everyone around you is doing, on the assumption that a crowd this large cannot all be wrong. In 2021, herding showed up as a kind of contagious script-picking: certain hydropower, finance, and microfinance shares would circulate through social media and messaging groups as the "next one to move," and buying would concentrate in whatever name was currently being discussed, regardless of that company's actual fundamentals. Trading volumes in a handful of small-capitalisation scripts would spike for a few days, the price would move up sharply, and then attention would move to the next name.

Recency bias, covered in Chapter 52, is the tendency to assume that the recent past — especially the very recent past — is the best guide to the future, discounting longer and less flattering history. Nepali investors who had only ever experienced NEPSE as an index that went from 1,100 to 3,000 quite reasonably, if you only look at that one stretch of time, assumed the next move was also up. Very few new entrants in 2020 and 2021 had any personal memory of NEPSE's previous major bust — the 2016 correction, or the much larger 2008 to 2011 crash, when the index fell for years after an earlier boom. If your entire investing experience is sixteen months long and every one of those months has been good, "the market always goes up" feels like an observed fact rather than a dangerous generalisation.

Overconfidence, covered in Chapter 50, is the tendency to overestimate your own skill and underestimate the role luck played in your results. I certainly had this. Every trade I made in that period that went well, I attributed to my reading of the market. The handful that went badly, I dismissed as bad luck or bad timing, not as evidence that my method — which, honestly, amounted to buying whatever my cousin's finance-company colleagues were discussing — had no method in it at all.

There is a fourth bias, discussed in Chapter 53, that I think is the most Nepal-specific of the group: what that chapter calls "borrowed conviction," the practice of holding a position not because you have evaluated it yourself but because someone you trust — a relative, a broker, a WhatsApp group administrator — told you to hold it. Borrowed conviction is dangerous precisely because it cannot survive contact with bad news. If you own a share because you did the work and understood the business, bad news makes you re-evaluate. If you own a share because your brother-in-law told you to buy it, bad news just makes you anxious, and anxiety is a poor basis for decision-making.

The margin lending side of the mania deserves its own attention, because it is where individual bad decisions turned into a system-wide vulnerability. Loan-against-share facilities, offered by banks and finance companies, typically let a borrower pledge shares as collateral and borrow a percentage of their value — the loan-to-value ratio, or LTV. In the boom years, LTV ratios offered in practice crept upward, and total margin lending outstanding across the banking and finance system grew very quickly, far faster than deposits or overall credit growth. The mechanics matter here, so let's be precise about them, because they are the hinge on which the entire second half of this case study turns.

Notice what that table shows: margin lending does not just amplify an individual investor's outcome. It links investors to each other. When enough borrowers are using margin loans against the same pool of shares, a price fall that starts for any reason — profit-taking, a piece of bad economic news, a regulatory statement — can trigger margin calls that force selling, and that forced selling becomes the bad news that triggers the next round of margin calls. This is exactly the liquidity spiral described in Chapter 56, and in 2021 Nepal built the conditions for one without most participants realising it.

I took a margin loan in mid-2021. I remember the finance officer explaining the LTV ratio to me almost as an afterthought, the way you might explain a minor administrative detail. What he did not explain, and what I did not ask, was what would happen to my position if the shares I had pledged fell by thirty percent in a matter of weeks. I found out later. Everyone did.

Lesson 90.3 — The Peak: August 2021 and the Signs Nobody Wanted to See

NEPSE closed at 3,198.60 points on August 18, 2021 — its highest level in the exchange's history at that time, and a figure that market commentators still cite today as the symbolic top of the mania. I want to be honest about what that day felt like from where I was sitting, because the honesty is the whole point of a behavioural case study. It did not feel like a peak. It felt like Tuesday. There was no bell that rang. Prices had been going up for so long that a new all-time high had stopped feeling like news and started feeling like the natural order of things.

But if you apply the tools from Chapters 54 through 58 — the chapters on liquidity, market breadth, and circuit breakers — with the benefit of hindsight, the warning signs were already visible in the market's own mechanics, not just in hindsight commentary.

The first sign was in circuit breakers themselves. NEPSE, like most emerging market exchanges, uses circuit breakers — automatic trading halts triggered when a share price or the overall index moves by more than a set percentage in a session — specifically to slow down panics and manias alike by forcing a pause for reflection. Individual scripts on NEPSE are subject to daily price bands, commonly cited at up to about 10 percent in either direction depending on the rules in force at the time, and the exchange has historically triggered market-wide circuit halts on unusually sharp single-day index moves. Through 2021, an increasing number of trading sessions saw dozens of individual scripts hit their upper circuit — meaning they rose the maximum allowed amount and then simply stopped trading for the day, with buy orders queued and unfilled because no seller would part with shares at that price. A market where a large fraction of listed scripts are hitting upper circuit on a regular basis is not a healthy, broadly rising market. It is a market where liquidity has become one-directional: everyone wants to buy, almost nobody wants to sell, and price discovery — the process by which a market finds a fair price through the honest disagreement of buyers and sellers — has effectively broken down.

The second sign was breadth — a concept covered in Chapter 55 — meaning whether a market's rise is broad-based across many sectors and companies, or narrow, concentrated in a small number of names that are pulling the index average up while many other listed companies go nowhere or fall. Sub-indices for hydropower and for finance companies and microfinance institutions rose dramatically faster than the broader index and faster than sectors like manufacturing, hotels, or trading companies. A market where two or three sectors are doing almost all the work, while the index headline number climbs regardless, is telling you that the rally has a narrow foundation — and narrow foundations do not hold weight well when the wind changes.

The third sign, and in some ways the most important for a retail investor to have watched, was the sheer velocity of new account openings and margin borrowing, both of which were still accelerating even as the index approached its all-time high. In a healthy, fundamentals-driven bull market, new participation tends to track earnings growth and economic activity with some lag. In August 2021, new demat account openings and margin lending growth had become self-referential: people were opening accounts and borrowing to buy shares because share prices were rising, and share prices were rising in part because people kept opening accounts and borrowing to buy shares. That circularity is the definition of a mania, not a metaphor for one.

I did not see any of this at the time, or rather, I saw pieces of it and dismissed each piece individually. I remember noticing that a friend's favourite hydropower script had hit upper circuit for four sessions running, unable to be sold at any price above the circuit limit because there were no sellers willing to sell there and no way to trade above it. I took this as proof that the company was fantastic. It did not occur to me to ask why, if the company were genuinely worth so much more than its previous price, existing shareholders — who presumably knew the company at least as well as I did — were not selling into that demand.

This is the point in the story where the Canon Score, introduced in earlier parts of this book as a structured way to evaluate a position against a checklist of value, quality, and risk criteria rather than against how a share has performed recently, would have done something genuinely different from what I did. A Canon Score does not ask "has this gone up." It asks questions like: is this company's valuation, measured against earnings or book value, historically reasonable or historically stretched? Is the volume and price action explainable by business fundamentals, or only by flows of new money? Is my position sized so that a serious drawdown would hurt but not destroy me? None of those questions care about how many upper circuits a script has hit. All of them would have been flashing amber, and in some cases red, by the middle of 2021, for exactly the scripts that most retail investors, including me, were most excited about.

Lesson 90.4 — The Tightening: How NRB Pulled the Punch Bowl Away

Every mania eventually meets a policy response, because the same forces that inflate a mania — rapid credit growth, rising leverage, capital flowing away from productive uses — eventually show up in other places a central bank is required to watch: the trade deficit, foreign exchange reserves, and overall financial stability. Nepal Rastra Bank's job, as this Canon has discussed in earlier chapters, is not to manage the stock market. It is to manage the currency, the banking system, and the broader economy. But those responsibilities intersect with the stock market whenever bank and finance company balance sheets become heavily exposed to share-backed lending, which is exactly what had happened by late 2021.

Nepal's broader economy was under real strain in this period for reasons that had nothing to do with the stock market directly. Import demand recovered strongly as lockdowns eased, pulling in foreign currency to pay for goods from vehicles to construction materials, at the same time that remittance growth, while still positive, could not keep pace. Foreign exchange reserves, which the country needs to maintain to pay for essential imports including fuel, came under pressure. In response, NRB tightened monetary policy through 2021 and into 2022 on multiple fronts: raising policy rates, tightening the cash reserve ratio that requires banks to hold a certain proportion of deposits rather than lend them all out, and imposing stricter, more explicit limits on margin lending against shares, including lower loan-to-value ceilings and, at various points, caps on the total amount of margin lending an individual bank or finance company could extend.

Here is the mechanism that made this tightening so consequential for the stock market specifically, and it connects directly back to the margin lending table from Lesson 90.2. When NRB tightened the loan-to-value ratio banks and finance companies were permitted to offer against pledged shares, existing margin borrowers were not grandfathered comfortably — many faced demands to either deposit additional collateral or reduce their loan, precisely because the value of the collateral, relative to the now-lower permitted ratio, had become insufficient. This is functionally identical to a margin call, even when it originates from a regulatory ratio change rather than from a falling share price. And when a large number of borrowers across the system face similar demands at similar times, the market fills with sell orders from people who are not selling because they have changed their mind about a company, but because they have no choice.

Interest rates on ordinary bank credit also rose sharply through this period, drawing money that had been sitting in trading accounts back toward interest-bearing deposits, and raising the cost of holding a margin loan at the same time its permitted size was shrinking. Both effects pushed in the same direction: less money available to buy shares, and more pressure on existing leveraged holders to sell.

I remember the specific week I understood something had changed. My broker's TMS app began showing red across almost every script I owned, for several consecutive sessions, without any single piece of company-specific news to explain it. I called my cousin at the finance company. He told me, in a tone that had lost the earlier confidence, that the company was tightening margin terms for existing clients, not just new ones. I did not understand, at that moment, that this was a small, individual version of the exact system-wide mechanism I have just described to you. I only understood that money I thought I had was, quite suddenly, money I might have to find from somewhere else.

Lesson 90.5 — The Crash: Circuit Breakers, Forced Selling, and the Long Grind Down

What followed, through 2022 and into 2023, was not a single dramatic crash day of the kind you might picture from famous global market crashes. It was something slower and, in its own way, more painful: a long, uneven grind downward, punctuated by short rallies that drew hopeful buyers back in, followed by fresh legs down that took the index to new lows. By the middle of 2022, NEPSE had fallen from its 3,198.60 peak to roughly the 1,900 to 2,000 range — a decline of well over a third from the top — and it spent the rest of 2022 and part of 2023 grinding lower still, dipping into the high 1,800s by December 2022 (closing at 1,899.70 that December, per contemporary reporting) and staying in a depressed band roughly between 1,800 and 2,000 for much of the following year, a fraction of its 2021 highs, before beginning a slow, uneven recovery in later years.

The mechanics of the decline mirror, in reverse, everything that built the boom. Circuit breakers, which had spent 2021 mostly halting scripts on the upside because there were no willing sellers, now spent long stretches halting scripts on the downside because there were no willing buyers at the falling price. This is the other half of the lesson from Chapter 54 that this case study makes vivid: a circuit breaker is a symmetrical tool. It slows down euphoria on the way up, by forcing a pause instead of letting a price run unchecked; and it slows down panic on the way down, by the same mechanism. But a circuit breaker cannot manufacture a buyer who does not exist. When a script hits its lower circuit — falls the maximum permitted amount for the day — and stays there because nobody wants to buy at that price either, the position is technically "protected" from falling further that day, but it is also, in practical terms, unsellable. You can watch your account value fall on paper without being able to convert a single share into cash, because the order book on the buy side is simply empty.

This is precisely the liquidity trap discussed in Chapter 57: the idea that the ease of selling a position is not a fixed property of that position, but a variable one that depends on overall market conditions, and that it tends to disappear exactly when you need it most. During the mania, everyone believed their shares were liquid, because in a rising, crowded market, there was always a buyer willing to pay slightly more than the last price. During the correction, that assumption was tested and, for many retail holders, failed. The shares had not changed. The willingness of anyone else to own them at that price, at that moment, had.

Margin-related forced selling compounded the decline in exactly the way the earlier table predicted. As share prices fell, the collateral value backing existing margin loans fell with them, triggering fresh margin calls on top of the regulatory tightening that had already begun the process. Borrowers who could not or would not post additional collateral had their pledged shares sold by the lender, adding supply to a market that already had too little demand, which pushed prices down further, which triggered the next round of calls on other borrowers holding similar or adjacent scripts. This is the liquidity spiral from Chapter 56 playing out at national scale, and it is precisely why circuit breakers, sensible margin rules, and position-sizing discipline are not bureaucratic inconveniences — they are the mechanisms that determine whether a correction stays a correction or becomes a cascading collapse.

I sold most of what I owned in stages through the first half of 2022, at prices well below where I had bought, not because I had done fresh analysis of the businesses I owned, but because I could no longer sleep, and because the margin lender was asking for money I did not have sitting elsewhere. I want to be precise about what that experience teaches, because it would be easy to draw the wrong lesson from it. The wrong lesson is "the stock market is dangerous and ordinary people should stay out of it." The right lesson, which the rest of this Canon has been building toward across dozens of chapters, is that the stock market is dangerous specifically for money you cannot afford to have locked up, specifically when it is combined with borrowed capital, and specifically when your reason for holding a position is "it has been going up" rather than "I have evaluated what it is worth and I can afford to be patient." I had violated all three conditions simultaneously, and the correction found me exactly where those violations had left me: exposed, illiquid, and forced to sell into the worst possible market at the worst possible time.

Lesson 90.6 — What the Canon Score Would Have Done Differently

Let's now do the exercise this whole case study has been building toward: apply the Canon Score and the risk-management rules from earlier in this book to my own actual decisions in 2021, and see, point by point, where a disciplined process would have produced a different outcome — not a perfect outcome, since no process eliminates risk entirely, but a materially better one. Because this case study is about a whole market rather than one company, there is no single ticker to run Chapter 64's real seven-dimension rubric against. So, in the same spirit as Chapter 64's own illustrative "Himalaya Unnati Bank" composite, here is a numeric Canon Score for a composite that stood in for dozens of real names in 2021: a small, single-plant hydropower developer of exactly the kind that kept hitting upper circuit in Kathmandu's tea-shop conversations that year, built from the real, aggregate conditions this chapter has already documented — thin disclosure, heavy project debt, a single-buyer PPA, and a share price disconnected from any of it.

Thirty-nine out of a hundred, Weak/Avoid — for a script that, in real 2021 trading, kept hitting its upper circuit and drawing exactly the kind of excitement I described in Lesson 90.3. That gap, between a real Canon Score in the high thirties and a market price that several people I knew treated as a can't-miss opportunity, is the entire chapter compressed into two numbers. Nothing about this composite's business changed between "before the mania" and "during the mania" — the moat, the debt load, the earnings, the governance record were all exactly the same company either way. Only the price changed, and the price is not one of Chapter 64's seven dimensions. It never has been.

Start with valuation discipline, from the Canon Score's fundamental screen. A basic version of this screen asks whether a company's price relative to its earnings, or its price relative to its book value, is high or low compared to that company's own history and to reasonable sector norms. Applied to the hydropower and finance-sector darlings of 2021, this screen would have flagged many of the most popular names as trading well above any level their earnings history could support, particularly in the run-up through mid-2021. That does not mean the screen would have told me to never own these sectors — hydropower and financial services are legitimate, important parts of the Nepali economy, and this Canon has never argued that whole sectors should be avoided. It means the screen would have told me that the specific price I was paying, at the specific moment I was paying it, was disconnected from the specific earnings those companies were generating, and that disconnection is exactly the information a momentum-following retail investor systematically ignores.

Next, position sizing, from the risk-management chapters. A basic position-sizing rule caps how much of your total investable capital can sit in any single script, and separately caps how much of your total capital can be borrowed rather than your own. Had I followed even a simple version of this rule — say, no single script above a modest fraction of my total portfolio, and no margin borrowing at all, or margin borrowing capped far below what the finance company was willing to offer me — the 2022 correction would have reduced my paper wealth, which no rule can prevent, but it would not have forced me into distress selling, because I would not have been receiving margin calls I could not meet. This is the single largest difference a disciplined process makes in a story like this one: it does not predict the crash, but it removes the mechanism by which the crash becomes a forced, and therefore worst-timed, sale.

Next, the exit discipline covered in the liquidity chapters. A Canon Score approach treats rising prices not as pure good news but as a trigger to re-check the original thesis: has anything about the company's actual earnings or business changed to justify this new, higher price, or has only the price changed? Applied honestly in 2021, this discipline would have prompted trimming — selling a portion of a winning position, not all of it — as prices rose well beyond what fundamentals justified, purely as a risk-management action rather than a market-timing prediction. I want to be careful here not to claim the Canon Score would have called the exact top of 3,198.60 in August 2021; no honest framework claims to call tops. What it would have done is systematically move capital out of the most stretched, most narrowly-supported positions and into cash or more reasonably valued assets well before the peak, simply because "stretched relative to fundamentals" was true for months before the peak, not just on the peak day itself.

Next, the behavioural checks from Chapters 50 through 53 directly. A disciplined investor using this Canon's framework is trained to treat certain observations as warning signals rather than confirmations: unsolicited stock tips from people with no particular expertise, a sudden social atmosphere where everyone is discussing the same handful of scripts, and — most specifically to this case — a pattern of a script hitting its upper circuit repeatedly with no company-specific news to explain it. Each of these, individually, is exactly the kind of observation that recency bias and herding cause an untrained investor to interpret as bullish confirmation, and that a trained investor is taught to interpret as a caution flag instead. I had every one of these signals available to me in mid-2021. I read every one of them backward.

Finally, and this is a point the earlier liquidity chapters made carefully and that this case study now gives real weight to, the Canon Score approach treats a position's liquidity — how easily and at what cost you can actually convert it back to cash — as a genuine risk factor, not an afterthought. A script that only trades because of one-directional, momentum-driven demand is a script whose liquidity will evaporate the moment that momentum reverses, precisely because there was never a stable base of buyers who wanted it for its business fundamentals rather than its recent price action. Weighing liquidity risk explicitly, rather than assuming that "if I bought it, I can sell it," would have meant treating several of the most popular 2021 scripts as lower-quality holdings than their price charts suggested, specifically because the case for owning them depended entirely on other people continuing to want to buy them too.

None of this means a disciplined investor would have avoided the correction's effects entirely, or would have sold everything in early 2021 and sat in cash for two years congratulating themselves. Markets are genuinely hard to time, and this Canon has never promised otherwise. What the comparison shows is narrower and, I think, more useful: a disciplined process changes the size of the mistake and, critically, whether the mistake is forced or chosen. A disciplined investor in 2021 likely still owned shares that fell in 2022. But they owned less of any single stretched position, owed no margin lender an explanation, and had already banked some gains along the way — which meant the correction was a setback to be endured with patience, not a crisis that dictated the timing and price of their sales for them.

That is the entire difference, and it is not a small one. I did not choose when I sold in 2022. My margin lender chose for me, at a price my lender needed, not at a price I would have chosen if the decision had genuinely been mine.