Time in the market vs timing the market: the complete case
25th September 2026
Markets have been jumpy again this week, and weeks like this are exactly when the temptation to do something is strongest. This piece looks properly at what the evidence says about trying to time markets versus simply staying in them.
The maths: what a handful of days really costs you
Being fully invested in the S&P 500 for the past 20 years produced an average annualised return of around 10.3%. An investor who missed just the 10 best trading days of that same 20-year period saw their return nearly cut in half. Miss the best 30 days and the numbers turn brutal: one widely cited J.P. Morgan analysis covering a 2003 to 2022 window found that $10,000 invested at the start would have grown to $64,844 fully invested, but missing the best 60 days of that period reduced the same starting stake to around $4,205, below the original investment.
The reason this matters so much is compounding. Annualised return figures hide an enormous amount of variance in where the actual gains land. A small number of exceptional days generate a disproportionate share of a multi-decade return. Pull ten or twenty of those days out of the sequence, even while leaving every other day untouched, and the compounding engine that was meant to run for 20 years loses several of its most productive years.
Morgan Housel's book The Psychology of Money makes a version of this point using a different lens: long tails, the small number of extreme outcomes at the far edges of a distribution, drive a hugely disproportionate share of results in investing. Housel notes that a small starting base, left to compound without interruption, can produce results that look almost illogical from the outside. An interruption to compounding at the wrong moment is costly for the same reason a long tail is rewarding: both are about what happens in a small number of days or years that cannot be identified in advance. His central practical argument follows from this: the single most powerful thing an investor can do is increase the amount of time an investment is given to compound without being disturbed. Being financially unbreakable, in Housel's phrase, structured so that no single shock forces an exit, matters more to long-run outcomes than chasing a marginally higher return.
Why the best days and the worst days are the same days
This is where the argument usually gets interesting, because there is an obvious objection: surely if you could dodge the worst days too, timing would work. Data going back to 1990 shows the median gap between one of the market's ten worst days and one of its ten best days is around a single week. Three of the thirty best trading days in market history, and five of the thirty worst, all fell within eight trading days of each other in March 2020 alone.
This clustering is not coincidental. Big moves in either direction are driven by the same thing: a spike in uncertainty. When uncertainty spikes, options pricing reflects it, forced selling and short covering both accelerate, and prices swing hard in both directions within the same short window. The conditions that would frighten someone into selling are, statistically, the same conditions that tend to produce the sharpest rebounds. Stepping out during a downturn to wait for calm means stepping out during exactly the period when a large share of the market's best days are concentrated.
The full data set is more nuanced than the version usually shared. One long-run study going back to 1930 found that removing each decade's ten worst days from the S&P 500's history would have lifted cumulative returns dramatically, from roughly 19,975% to over 4 million percent. Removing only the ten best days each decade collapsed the same return to 45%. Removing both sets together produced a return that beat staying fully invested throughout. The popular "missing the best days" chart is one row of a bigger table: avoiding the worst days matters more than capturing the best ones, but the two cannot be separated in practice, because nobody can identify in real time which day belongs to which category until it has already happened.
That is the entire case against timing in a single sentence. The prize is real. There is no reliable way to collect it.
Why nobody can do this, including the professionals
A natural response to the above is: fine, but a sufficiently skilled investor or fund manager should be able to navigate this better than random chance. The data on that question has been unambiguous for decades.
S&P Dow Jones Indices publishes the SPIVA scorecard twice a year, tracking how actively managed funds perform against their benchmark index. In 2025, 79% of all active large-cap US equity funds underperformed the S&P 500, worse than the 65% rate in 2024 and the fourth-worst year in the 25-year history of the study. Over a 20-year horizon, roughly 92% of domestic equity funds underperformed their benchmark, with the least successful category, large-cap growth, at a 97% underperformance rate. The SPIVA scorecard has told a version of the same story every year since it began, across almost every market and asset class it covers globally.
These are professional managers with research teams, institutional data access, and full-time mandates to do exactly this. The case for an individual investor confidently entering and exiting the market around headlines is weak before any other evidence is considered.
There is a deeper reason this should be expected rather than surprising. A stock market price is the output of millions of participants worldwide, each holding some piece of information, some view on interest rates, some assessment of a company's prospects, buying and selling continuously and forcing that collective judgement into a single number within seconds. That number updates again the moment new information arrives, often before an individual investor has finished reading the headline that caused it. Beating that process consistently requires knowing something material that this vast, continuously updating, competitively motivated crowd does not already know or has not already priced in. Doing that once is luck. Doing it repeatedly over a career, without a real information or structural edge, is what the SPIVA data above shows almost nobody manages.
Being fully invested in the S&P 500 for the past 20 years produced an average annualised return of around 10.3%. An investor who missed just the 10 best trading days of that same 20-year period saw their return nearly cut in half. Miss the best 30 days and the numbers turn brutal: one widely cited J.P. Morgan analysis covering a 2003 to 2022 window found that $10,000 invested at the start would have grown to $64,844 fully invested, but missing the best 60 days of that period reduced the same starting stake to around $4,205, below the original investment.
The reason this matters so much is compounding. Annualised return figures hide an enormous amount of variance in where the actual gains land. A small number of exceptional days generate a disproportionate share of a multi-decade return. Pull ten or twenty of those days out of the sequence, even while leaving every other day untouched, and the compounding engine that was meant to run for 20 years loses several of its most productive years.
Morgan Housel's book The Psychology of Money makes a version of this point using a different lens: long tails, the small number of extreme outcomes at the far edges of a distribution, drive a hugely disproportionate share of results in investing. Housel notes that a small starting base, left to compound without interruption, can produce results that look almost illogical from the outside. An interruption to compounding at the wrong moment is costly for the same reason a long tail is rewarding: both are about what happens in a small number of days or years that cannot be identified in advance. His central practical argument follows from this: the single most powerful thing an investor can do is increase the amount of time an investment is given to compound without being disturbed. Being financially unbreakable, in Housel's phrase, structured so that no single shock forces an exit, matters more to long-run outcomes than chasing a marginally higher return.
Why the best days and the worst days are the same days
This is where the argument usually gets interesting, because there is an obvious objection: surely if you could dodge the worst days too, timing would work. Data going back to 1990 shows the median gap between one of the market's ten worst days and one of its ten best days is around a single week. Three of the thirty best trading days in market history, and five of the thirty worst, all fell within eight trading days of each other in March 2020 alone.
This clustering is not coincidental. Big moves in either direction are driven by the same thing: a spike in uncertainty. When uncertainty spikes, options pricing reflects it, forced selling and short covering both accelerate, and prices swing hard in both directions within the same short window. The conditions that would frighten someone into selling are, statistically, the same conditions that tend to produce the sharpest rebounds. Stepping out during a downturn to wait for calm means stepping out during exactly the period when a large share of the market's best days are concentrated.
The full data set is more nuanced than the version usually shared. One long-run study going back to 1930 found that removing each decade's ten worst days from the S&P 500's history would have lifted cumulative returns dramatically, from roughly 19,975% to over 4 million percent. Removing only the ten best days each decade collapsed the same return to 45%. Removing both sets together produced a return that beat staying fully invested throughout. The popular "missing the best days" chart is one row of a bigger table: avoiding the worst days matters more than capturing the best ones, but the two cannot be separated in practice, because nobody can identify in real time which day belongs to which category until it has already happened.
That is the entire case against timing in a single sentence. The prize is real. There is no reliable way to collect it.
Why nobody can do this, including the professionals
A natural response to the above is: fine, but a sufficiently skilled investor or fund manager should be able to navigate this better than random chance. The data on that question has been unambiguous for decades.
S&P Dow Jones Indices publishes the SPIVA scorecard twice a year, tracking how actively managed funds perform against their benchmark index. In 2025, 79% of all active large-cap US equity funds underperformed the S&P 500, worse than the 65% rate in 2024 and the fourth-worst year in the 25-year history of the study. Over a 20-year horizon, roughly 92% of domestic equity funds underperformed their benchmark, with the least successful category, large-cap growth, at a 97% underperformance rate. The SPIVA scorecard has told a version of the same story every year since it began, across almost every market and asset class it covers globally.
These are professional managers with research teams, institutional data access, and full-time mandates to do exactly this. The case for an individual investor confidently entering and exiting the market around headlines is weak before any other evidence is considered.
There is a deeper reason this should be expected rather than surprising. A stock market price is the output of millions of participants worldwide, each holding some piece of information, some view on interest rates, some assessment of a company's prospects, buying and selling continuously and forcing that collective judgement into a single number within seconds. That number updates again the moment new information arrives, often before an individual investor has finished reading the headline that caused it. Beating that process consistently requires knowing something material that this vast, continuously updating, competitively motivated crowd does not already know or has not already priced in. Doing that once is luck. Doing it repeatedly over a career, without a real information or structural edge, is what the SPIVA data above shows almost nobody manages.
The behaviour gap: what investors actually earn versus what their funds return
DALBAR has tracked the difference between what mutual funds return and what the investors inside those funds actually earn since 1994, using fund inflows and outflows to reconstruct real investor behaviour rather than assuming a hypothetical buy-and-hold investor. The gap this produces is called the behaviour gap, and it exists because investors do not hold funds passively. They buy after a rally and sell after a fall, and the sequencing of those decisions destroys value that the fund itself never lost.
The scale of the gap varies sharply by year, and the range tells its own story. In 2024, a year in which the S&P 500 returned 25.02%, the average equity fund investor earned 16.54%, an 848 basis point shortfall and the second-largest gap of the past decade. In 2025, the gap narrowed to just 0.72%, the third-smallest gap since DALBAR's records began in 1985 and the smallest since 2012. Investor behaviour did not structurally improve between those two years. Markets were calmer in 2025, and the gap is a direct measure of how much emotional trading investors did during the period in question. Over the 20 years to the end of 2024, the average equity investor earned 9.24% annualised against the S&P 500's 10.35%, a gap that looks modest year to year and compounds into a very large sum of money over two decades.
The mechanism behind this does not require any special weakness on the part of any individual investor. Loss aversion means a fall in portfolio value registers, psychologically, as roughly twice as painful as an equivalent gain feels good. Recency bias means a market that has just fallen feels more likely to keep falling, and a market that has just risen feels safe to buy into, even though neither instinct has predictive value. These are standard features of how human brains process risk, and they operate on financially literate, intelligent people exactly as they operate on anyone else, which is why the DALBAR gap has persisted across more than 30 years of published data and a huge range of investor types.
The evidence above shows that professional managers, working full time with institutional resources, mostly cannot beat a simple index, and that individual investors, acting on instinct, cost themselves a well-documented, measurable amount most years. Intervention in a portfolio has been shown, repeatedly and across decades of independent data, to be more likely to damage an outcome than improve it. The harder question, given how clear that evidence is, is why intervening remains so difficult to resist. The honest answer is that this has always been a discipline problem rather than a knowledge problem, and discipline under pressure is what a proper financial plan, agreed before the pressure arrives, is built to supply.
Worked examples: what actually happened to someone who stayed invested
Numbers in the abstract can be harder to internalise than a specific story with a start and end date. Several of the worst entry points in modern market history make the case concretely.
An investor who bought at the market peak in October 2007, immediately before the global financial crisis, watched the S&P 500 fall 57% to its trough in March 2009, the deepest drawdown in the US market since the Great Depression. On a nominal price basis, that investor did not see the index recover to its October 2007 high until late March 2013, roughly five and a half years later. An investor who sold at or near the March 2009 bottom locked in the loss permanently and needed to correctly time their re-entry to recover any of it. An investor who did nothing was, by 2013, whole again, and every dollar of the market's subsequent multi-decade advance from that low was still ahead of them.
An investor who bought at the peak in January 1973, just before the oil crisis and stagflation produced a 48.2% decline, faced the slowest recovery in modern market history: 69 months, close to six years, before the index reclaimed its previous high on a nominal basis. This is the closest historical parallel to a true worst-case outcome for a long-term investor. Even here, the investor who held through the full 69 months was restored to their starting position and then participated fully in the strong bull market that followed through the rest of the 1970s and into the 1980s.
Black Monday, October 1987, illustrates how misleading a single headline can be. The Dow fell 22.6% in one session, still the largest one-day percentage decline on record, and the S&P 500 declined 33.5% peak to trough. Reaching a new high took 20 months, a slower recovery than the scale of the crash alone would suggest, because the initial fall itself took only three months. An investor watching the news that October had no way to know, from the size of the daily headline, whether they were looking at the start of a multi-year collapse or a sharp correction that would fully recover within two years, which is what it turned out to be.
An investor who was fully invested through the COVID crash of February and March 2020, the fastest bear market in modern history at a 33.9% decline in 33 calendar days, saw the index reclaim its previous high by August 2020, roughly five months later, the quickest recovery of any major drawdown on record. Someone who sold in the panic of late March 2020 missed one of the sharpest rallies in market history in the process of trying to avoid further losses.
The pattern across all four periods, separated by nearly fifty years and entirely different causes, holds. The market fell hard. It eventually recovered. The recovery timeline was never knowable in advance, sometimes five months and sometimes nearly six years, and the only approach that worked in every case without requiring a correct forecast was staying invested throughout.
Why the headlines feel worse than ever, and why that is by design
Every downturn now seems to feel like a uniquely severe crisis, and that feeling is itself data, just not data about markets. Research published in Nature Human Behaviour, testing more than 100,000 real headlines against real reader behaviour on the same underlying stories, found that each additional negative word in a headline increased the click-through rate by 2.3%, while positive words reduced it. Separate research has found that people amplify a story's negativity further when sharing it with others, adding new negative language beyond what the original report contained. This is a straightforward commercial incentive, not a conspiracy: in an attention economy where every outlet is measured by clicks and every platform's algorithm favours whatever keeps people scrolling, negative framing is simply what performs.
The result is a media and social media environment that is structurally biased towards framing ordinary volatility as extraordinary danger, because that framing performs better than an accurate one. Every historical episode above was reported at the time using the same language now used for far smaller and more ordinary market moves: crisis, collapse, unprecedented, historic. Some of those episodes truly were historic. Most ordinary corrections are not, and the volume and tone of coverage rarely draws that distinction in the moment, because the distinction does not generate engagement.
The intensity of a headline measures how well that headline was designed to be clicked. Treating it as a measure of an event's actual significance to a long-term portfolio is exactly the mechanism that produces the behaviour gap described above.
DALBAR has tracked the difference between what mutual funds return and what the investors inside those funds actually earn since 1994, using fund inflows and outflows to reconstruct real investor behaviour rather than assuming a hypothetical buy-and-hold investor. The gap this produces is called the behaviour gap, and it exists because investors do not hold funds passively. They buy after a rally and sell after a fall, and the sequencing of those decisions destroys value that the fund itself never lost.
The scale of the gap varies sharply by year, and the range tells its own story. In 2024, a year in which the S&P 500 returned 25.02%, the average equity fund investor earned 16.54%, an 848 basis point shortfall and the second-largest gap of the past decade. In 2025, the gap narrowed to just 0.72%, the third-smallest gap since DALBAR's records began in 1985 and the smallest since 2012. Investor behaviour did not structurally improve between those two years. Markets were calmer in 2025, and the gap is a direct measure of how much emotional trading investors did during the period in question. Over the 20 years to the end of 2024, the average equity investor earned 9.24% annualised against the S&P 500's 10.35%, a gap that looks modest year to year and compounds into a very large sum of money over two decades.
The mechanism behind this does not require any special weakness on the part of any individual investor. Loss aversion means a fall in portfolio value registers, psychologically, as roughly twice as painful as an equivalent gain feels good. Recency bias means a market that has just fallen feels more likely to keep falling, and a market that has just risen feels safe to buy into, even though neither instinct has predictive value. These are standard features of how human brains process risk, and they operate on financially literate, intelligent people exactly as they operate on anyone else, which is why the DALBAR gap has persisted across more than 30 years of published data and a huge range of investor types.
The evidence above shows that professional managers, working full time with institutional resources, mostly cannot beat a simple index, and that individual investors, acting on instinct, cost themselves a well-documented, measurable amount most years. Intervention in a portfolio has been shown, repeatedly and across decades of independent data, to be more likely to damage an outcome than improve it. The harder question, given how clear that evidence is, is why intervening remains so difficult to resist. The honest answer is that this has always been a discipline problem rather than a knowledge problem, and discipline under pressure is what a proper financial plan, agreed before the pressure arrives, is built to supply.
Worked examples: what actually happened to someone who stayed invested
Numbers in the abstract can be harder to internalise than a specific story with a start and end date. Several of the worst entry points in modern market history make the case concretely.
An investor who bought at the market peak in October 2007, immediately before the global financial crisis, watched the S&P 500 fall 57% to its trough in March 2009, the deepest drawdown in the US market since the Great Depression. On a nominal price basis, that investor did not see the index recover to its October 2007 high until late March 2013, roughly five and a half years later. An investor who sold at or near the March 2009 bottom locked in the loss permanently and needed to correctly time their re-entry to recover any of it. An investor who did nothing was, by 2013, whole again, and every dollar of the market's subsequent multi-decade advance from that low was still ahead of them.
An investor who bought at the peak in January 1973, just before the oil crisis and stagflation produced a 48.2% decline, faced the slowest recovery in modern market history: 69 months, close to six years, before the index reclaimed its previous high on a nominal basis. This is the closest historical parallel to a true worst-case outcome for a long-term investor. Even here, the investor who held through the full 69 months was restored to their starting position and then participated fully in the strong bull market that followed through the rest of the 1970s and into the 1980s.
Black Monday, October 1987, illustrates how misleading a single headline can be. The Dow fell 22.6% in one session, still the largest one-day percentage decline on record, and the S&P 500 declined 33.5% peak to trough. Reaching a new high took 20 months, a slower recovery than the scale of the crash alone would suggest, because the initial fall itself took only three months. An investor watching the news that October had no way to know, from the size of the daily headline, whether they were looking at the start of a multi-year collapse or a sharp correction that would fully recover within two years, which is what it turned out to be.
An investor who was fully invested through the COVID crash of February and March 2020, the fastest bear market in modern history at a 33.9% decline in 33 calendar days, saw the index reclaim its previous high by August 2020, roughly five months later, the quickest recovery of any major drawdown on record. Someone who sold in the panic of late March 2020 missed one of the sharpest rallies in market history in the process of trying to avoid further losses.
The pattern across all four periods, separated by nearly fifty years and entirely different causes, holds. The market fell hard. It eventually recovered. The recovery timeline was never knowable in advance, sometimes five months and sometimes nearly six years, and the only approach that worked in every case without requiring a correct forecast was staying invested throughout.
Why the headlines feel worse than ever, and why that is by design
Every downturn now seems to feel like a uniquely severe crisis, and that feeling is itself data, just not data about markets. Research published in Nature Human Behaviour, testing more than 100,000 real headlines against real reader behaviour on the same underlying stories, found that each additional negative word in a headline increased the click-through rate by 2.3%, while positive words reduced it. Separate research has found that people amplify a story's negativity further when sharing it with others, adding new negative language beyond what the original report contained. This is a straightforward commercial incentive, not a conspiracy: in an attention economy where every outlet is measured by clicks and every platform's algorithm favours whatever keeps people scrolling, negative framing is simply what performs.
The result is a media and social media environment that is structurally biased towards framing ordinary volatility as extraordinary danger, because that framing performs better than an accurate one. Every historical episode above was reported at the time using the same language now used for far smaller and more ordinary market moves: crisis, collapse, unprecedented, historic. Some of those episodes truly were historic. Most ordinary corrections are not, and the volume and tone of coverage rarely draws that distinction in the moment, because the distinction does not generate engagement.
The intensity of a headline measures how well that headline was designed to be clicked. Treating it as a measure of an event's actual significance to a long-term portfolio is exactly the mechanism that produces the behaviour gap described above.
Why markets recover: the structural tailwind underneath the volatility
Beyond the behavioural case for staying invested, there is a structural one. The US M2 money supply, a broad measure of currency and readily accessible bank deposits, has grown from around $286 billion when the series began in 1959 to roughly $23.3 trillion today. This is a sustained, multi-decade expansion of the money circulating through the economy, running on an entirely different clock to any single market cycle, driven by central bank policy, government deficit spending, and ordinary credit creation through the banking system.
This matters directly for asset prices, including equities, because more money circulating through an economy tends, over time, to bid up the nominal price of the assets that money is used to buy. A large part of the equity market's long-run upward bias in nominal terms comes from this, alongside real corporate earnings growth: the currency those valuations are measured in becomes worth somewhat less most years, a mechanism connected to the currency devaluation risk discussed elsewhere in Brigantia's content. Individual company and sector risk still requires proper diversification and ongoing scrutiny. Underneath that risk, a market denominated in a currency subject to sustained monetary expansion carries a persistent tailwind that a single bad week does not capture.
That same expansion of money and credit is also where leverage builds up. The longer a market rises in a relatively straight line, the more borrowed money tends to accumulate behind that rise, through margin debt, corporate leverage, or derivatives exposure, because a rising market makes leverage look safe right up until it does not. This is the standard mechanism behind most sharp corrections: an extended, low-volatility advance quietly builds the leverage that then unwinds violently once a catalyst appears, and the unwind looks sudden even though the vulnerability had been accumulating for months or years beforehand. This has recurred across essentially every cycle discussed in this piece and is ordinary market mechanics, not evidence that something is uniquely broken.
The offsetting factor, and a real part of why recovery periods have generally shortened over time, is that central banks and governments have become considerably more willing and able to intervene during a crisis than they were in 1973. The scale and speed of the 2020 policy response, compared with the slower and more constrained response in 1973 to 1974, is a large part of why one recovery took five months and the other took nearly six years. This is a real, evidenced shift in how modern central banks behave once a downturn becomes severe, and a meaningful part of why permanent structural collapse has such a poor track record as a market call. It offers no guarantee about the specific timing or scale of the next crisis.
What actually justifies a change to a portfolio
A portfolio can and should change over time. The argument above is specifically against changing one in reaction to a headline, a feeling, or a single volatile week, and the two triggers are different.
A change is justified when the long-term outlook for an asset class has materially shifted on evidence, or when a considered, evidence-based decision has been made about a specific structural risk. A recent example from Brigantia's own portfolio work illustrates this. Clients have recently been moved toward an equal-weight holding of the S&P 500 rather than the traditional capitalisation-weighted version, because the data shows the equal-weight approach has outperformed the standard index across almost every meaningful time horizon: S&P Global's own research found the Equal Weight Index returned 11.48% annualised over 20 years against 10.29% for the standard cap-weighted index. The three-year window is a notable exception, where the concentrated AI-driven rally in a small number of mega-cap names has meant the cap-weighted index performed better over that specific short period, precisely because so much of the market's return has been concentrated in so few names, the same concentration risk highlighted elsewhere in Brigantia's content.
This is the correct model for how a portfolio should evolve: a minor, evidence-based adjustment to how existing equity exposure is structured, made once and reviewed periodically. A wholesale exit from the market followed by an attempt to re-enter at a better moment is a different exercise entirely, and it is the one the evidence above argues against.
When de-risking part of a portfolio actually makes sense
There is one circumstance in which reducing risk in a portfolio is not just justified but the correct, planned response, and it has nothing to do with market conditions on any given day. It is the time horizon before that money is actually needed.
Everything argued above rests on one condition: that the money in question has enough time to recover from a drawdown before it needs to be spent. The historical examples cited range from five months to almost six years to reach a full recovery. An investor with a 20 or 30-year horizon can absorb even the worst of those outcomes without materially altering their plan. An investor who needs to draw on a specific portion of their capital within the next few years cannot assume the same, because a 2008 or 1973-style event landing at the wrong moment could force a sale at the bottom of a drawdown rather than allowing time for recovery.
As a general guide, once capital is roughly five years or less from being needed, the calculation changes, and a proper cashflow plan should identify exactly how much of the portfolio that timeline actually applies to. The correct response is to identify the specific portion required for near-term spending, whether that is school fees due in three years, a planned property purchase, or the early years of retirement drawdown, and move only that portion into lower-volatility assets where a market downturn cannot force a badly timed sale, leaving the entire portfolio untouched otherwise. The remainder, for goals still a decade or more away, keeps its full growth allocation and continues to benefit from everything discussed above.
Beyond the behavioural case for staying invested, there is a structural one. The US M2 money supply, a broad measure of currency and readily accessible bank deposits, has grown from around $286 billion when the series began in 1959 to roughly $23.3 trillion today. This is a sustained, multi-decade expansion of the money circulating through the economy, running on an entirely different clock to any single market cycle, driven by central bank policy, government deficit spending, and ordinary credit creation through the banking system.
This matters directly for asset prices, including equities, because more money circulating through an economy tends, over time, to bid up the nominal price of the assets that money is used to buy. A large part of the equity market's long-run upward bias in nominal terms comes from this, alongside real corporate earnings growth: the currency those valuations are measured in becomes worth somewhat less most years, a mechanism connected to the currency devaluation risk discussed elsewhere in Brigantia's content. Individual company and sector risk still requires proper diversification and ongoing scrutiny. Underneath that risk, a market denominated in a currency subject to sustained monetary expansion carries a persistent tailwind that a single bad week does not capture.
That same expansion of money and credit is also where leverage builds up. The longer a market rises in a relatively straight line, the more borrowed money tends to accumulate behind that rise, through margin debt, corporate leverage, or derivatives exposure, because a rising market makes leverage look safe right up until it does not. This is the standard mechanism behind most sharp corrections: an extended, low-volatility advance quietly builds the leverage that then unwinds violently once a catalyst appears, and the unwind looks sudden even though the vulnerability had been accumulating for months or years beforehand. This has recurred across essentially every cycle discussed in this piece and is ordinary market mechanics, not evidence that something is uniquely broken.
The offsetting factor, and a real part of why recovery periods have generally shortened over time, is that central banks and governments have become considerably more willing and able to intervene during a crisis than they were in 1973. The scale and speed of the 2020 policy response, compared with the slower and more constrained response in 1973 to 1974, is a large part of why one recovery took five months and the other took nearly six years. This is a real, evidenced shift in how modern central banks behave once a downturn becomes severe, and a meaningful part of why permanent structural collapse has such a poor track record as a market call. It offers no guarantee about the specific timing or scale of the next crisis.
What actually justifies a change to a portfolio
A portfolio can and should change over time. The argument above is specifically against changing one in reaction to a headline, a feeling, or a single volatile week, and the two triggers are different.
A change is justified when the long-term outlook for an asset class has materially shifted on evidence, or when a considered, evidence-based decision has been made about a specific structural risk. A recent example from Brigantia's own portfolio work illustrates this. Clients have recently been moved toward an equal-weight holding of the S&P 500 rather than the traditional capitalisation-weighted version, because the data shows the equal-weight approach has outperformed the standard index across almost every meaningful time horizon: S&P Global's own research found the Equal Weight Index returned 11.48% annualised over 20 years against 10.29% for the standard cap-weighted index. The three-year window is a notable exception, where the concentrated AI-driven rally in a small number of mega-cap names has meant the cap-weighted index performed better over that specific short period, precisely because so much of the market's return has been concentrated in so few names, the same concentration risk highlighted elsewhere in Brigantia's content.
This is the correct model for how a portfolio should evolve: a minor, evidence-based adjustment to how existing equity exposure is structured, made once and reviewed periodically. A wholesale exit from the market followed by an attempt to re-enter at a better moment is a different exercise entirely, and it is the one the evidence above argues against.
When de-risking part of a portfolio actually makes sense
There is one circumstance in which reducing risk in a portfolio is not just justified but the correct, planned response, and it has nothing to do with market conditions on any given day. It is the time horizon before that money is actually needed.
Everything argued above rests on one condition: that the money in question has enough time to recover from a drawdown before it needs to be spent. The historical examples cited range from five months to almost six years to reach a full recovery. An investor with a 20 or 30-year horizon can absorb even the worst of those outcomes without materially altering their plan. An investor who needs to draw on a specific portion of their capital within the next few years cannot assume the same, because a 2008 or 1973-style event landing at the wrong moment could force a sale at the bottom of a drawdown rather than allowing time for recovery.
As a general guide, once capital is roughly five years or less from being needed, the calculation changes, and a proper cashflow plan should identify exactly how much of the portfolio that timeline actually applies to. The correct response is to identify the specific portion required for near-term spending, whether that is school fees due in three years, a planned property purchase, or the early years of retirement drawdown, and move only that portion into lower-volatility assets where a market downturn cannot force a badly timed sale, leaving the entire portfolio untouched otherwise. The remainder, for goals still a decade or more away, keeps its full growth allocation and continues to benefit from everything discussed above.
What this means for expat investors specifically
British expats living and investing across Thailand, Southeast Asia and the world face a version of this problem with extra layers attached. Time zones, financial news cycles, and currency moves in GBP, USD and local currency terms are all visible around the clock, which creates more opportunities to react to short-term noise than a UK-based investor checking a portfolio quarterly. Distance from a familiar regulatory and market environment can also heighten the instinct to feel more in control by acting.
The evidence above does not change because an investor is based overseas. The maths of missed days, the clustering of extremes, the professional track record, and the behaviour gap all apply identically regardless of where the account holder happens to be living. What does change is the practical antidote: a proper financial plan, agreed in advance of a downturn rather than during one, with an asset allocation that reflects the level of risk the investor is actually able to tolerate and a clear-eyed cashflow model showing which portion of the portfolio, if any, falls inside that five-year horizon, removes the need to make an emotional decision at the worst possible moment.
The case for structure over instinct
None of this is an argument for ignoring risk or for treating every market fall as automatically survivable regardless of individual circumstances. Someone approaching retirement with insufficient time to recover from a 1973-style drawdown holds a materially different risk position from someone twenty years from retirement, and that distinction belongs in a proper cashflow model, not in a decision made in response to a headline. The evidence in this piece supports a narrower and more specific claim than either extreme: the act of guessing short-term market direction, in isolation from a wider plan, has a well-documented, decades-long record of destroying value rather than protecting it, for professional and individual investors alike. Structure, put in place in advance, is the approach the data actually supports.
You can book an initial call below.
British expats living and investing across Thailand, Southeast Asia and the world face a version of this problem with extra layers attached. Time zones, financial news cycles, and currency moves in GBP, USD and local currency terms are all visible around the clock, which creates more opportunities to react to short-term noise than a UK-based investor checking a portfolio quarterly. Distance from a familiar regulatory and market environment can also heighten the instinct to feel more in control by acting.
The evidence above does not change because an investor is based overseas. The maths of missed days, the clustering of extremes, the professional track record, and the behaviour gap all apply identically regardless of where the account holder happens to be living. What does change is the practical antidote: a proper financial plan, agreed in advance of a downturn rather than during one, with an asset allocation that reflects the level of risk the investor is actually able to tolerate and a clear-eyed cashflow model showing which portion of the portfolio, if any, falls inside that five-year horizon, removes the need to make an emotional decision at the worst possible moment.
The case for structure over instinct
None of this is an argument for ignoring risk or for treating every market fall as automatically survivable regardless of individual circumstances. Someone approaching retirement with insufficient time to recover from a 1973-style drawdown holds a materially different risk position from someone twenty years from retirement, and that distinction belongs in a proper cashflow model, not in a decision made in response to a headline. The evidence in this piece supports a narrower and more specific claim than either extreme: the act of guessing short-term market direction, in isolation from a wider plan, has a well-documented, decades-long record of destroying value rather than protecting it, for professional and individual investors alike. Structure, put in place in advance, is the approach the data actually supports.
You can book an initial call below.
