What Makes a Currency a Safe Haven

Safe haven currencies explained: why the yen and Swiss franc strengthen when markets fall, the dollar’s dual role, and why haven status can change.

Performance Attracts Investors. Transparency Keeps Them

Transparency in asset management explained: why clear reporting, honest context and a visible process keep investors when performance alone cannot.

Position Sizing: The Decision That Comes Before the Trade

Position Sizing: The Decision That Comes Before the Trade Ask ten investors what makes a good trade and nine will talk about direction: where the market is going, and why. It is the glamorous half of investing, the part that fills interviews and headlines. Yet when portfolios fail, the autopsy rarely points to a wrong opinion about direction. It points to a defensible opinion held in indefensible size. Position sizing is the decision that comes before the trade: how much capital a single idea is allowed to put at risk, defined before the position exists and independent of how confident the idea feels. In professional currency management it is not an afterthought of the analysis. It is a policy, and in our experience it separates portfolios that survive their mistakes from portfolios that are defined by them. Why sizing errors hurt more than direction errors Every manager is wrong about direction regularly. That is not a flaw in the process; it is a property of markets. Decades of evidence show that even excellent currency strategies are wrong on a large share of their individual positions, and we have built our entire approach around that fact, as we described in why process beats prediction. Being wrong is survivable when the loss is bounded. What is not survivable is the combination of a wrong view and an oversized position, because losses do not scale linearly with recovery effort. A portfolio that loses ten percent needs roughly eleven percent to recover. One that loses forty percent needs sixty-seven. The arithmetic of drawdowns, which we examined in detail in our article on drawdown management, is the reason sizing is a survival discipline rather than an optimization exercise: the damage of being wrong grows faster than the benefit of being right. This is also why sizing cannot be left to conviction. Conviction is highest exactly where caution matters most, at the moments when a view feels obvious, the evidence seems overwhelming and the temptation to scale up is strongest. A sizing rule written in calm conditions exists precisely to overrule that feeling, because the feeling is not information about the future. It is information about the trader. What a sizing framework actually decides A disciplined framework answers three questions before any position is opened. The first is the maximum loss a single idea may inflict on the portfolio. Not the expected loss, and not the loss if things go mildly wrong: the loss if the position is stopped out at its predefined exit. That number is set as a fraction of capital small enough that no individual mistake, or short sequence of mistakes, threatens the portfolio’s ability to keep operating. The second is how positions combine. Two trades that look independent on a screen can be the same bet wearing different clothes: long one dollar pair and short another may both be, in substance, a single view on the dollar. Sizing limits that ignore correlation are limits in name only, which is why we treat this as part of the same discipline we described in our work on correlation risk: the unit being sized is the exposure, not the ticket. The third is how size responds to conditions. Volatility changes what a position of a given notional actually risks: the same size that is conservative in a quiet market is aggressive in a stressed one. A framework that holds risk constant must therefore let notional vary, trimming positions as volatility expands rather than discovering, after the fact, that the portfolio had grown without anyone adding a trade. Size as policy, not opinion The common thread in all three answers is that none of them depends on how good the idea looks. That is deliberate. Direction is an opinion, and opinions should compete, be challenged and sometimes be wrong. Size is a policy, and policies exist to be applied uniformly, especially when applying them is uncomfortable. In practice this means the sizing rule is decided at the level of the investment process, documented, and applied to every position without exception: not renegotiated trade by trade, not suspended for high-conviction ideas, not loosened after a good run. The moments when a manager most wants to make an exception are reliably the moments when the exception is most expensive, because overconfidence and risk concentration arrive together. There is a quieter benefit as well. When size is fixed by rule, the quality of decisions becomes measurable. A portfolio where every idea risks a comparable fraction of capital produces a track record that reflects judgment rather than courage, and errors become data instead of events. Over the many decisions that make up a year of currency management, that feedback loop is worth more than any single trade. The question that protects the next hundred decisions The practical test of a sizing discipline is a single question, asked before every trade: how much is this position allowed to lose if it is wrong? Not how much it should make, and not how likely it is to work. If the answer is a number fixed in advance by policy, sizing is doing its job. If the answer depends on how the idea feels, the portfolio is one streak of confidence away from a problem. Direction decides whether a trade makes money. Size decides whether the portfolio survives being wrong long enough for the process to work. Of the two decisions, only one can be fully controlled in advance, and professional management is, above all, the discipline of controlling what can be controlled. This article is provided for informational and educational purposes only. It does not constitute investment advice, an offer, or a solicitation to invest in any product or service. Income Capital Management s.r.o. is registered under §15 of the Czech Act on Investment Companies and Investment Funds (ZISIF). Past performance is not indicative of future results. Investing involves risk, including the possible loss of capital.

Fund Performance 2026: Positive Results in Difficult Markets Through September

Fund performance 2026: year-to-date results through September for our Forex, Real Estate, Global Growth and High Yield funds, achieved in difficult markets.

What Calm Markets Hide and Volatile Markets Reveal

What Calm Markets Hide and Volatile Markets Reveal The most expensive investment mistakes rarely happen during a crash. They happen months earlier, when nothing seems to be happening at all. This is one of the least intuitive facts in portfolio management, and one of the most consistent. Bull markets and quiet stretches feel safe, and that feeling is precisely the mechanism of the damage: comfort relaxes the habits that protection depends on, and by the time volatility arrives to test the portfolio, the vulnerabilities are already built in. Market volatility, when it finally comes, does not create the problems. It reveals them. This article looks at both halves of that cycle: what calm conditions quietly do to portfolios, and what volatile periods teach that no other environment can. The anatomy of complacency Calm markets change investor behavior in predictable ways, and the pattern is worth naming point by point, because every item feels reasonable while it is happening. Investors chase recent performance, adding to whatever has worked, which concentrates the portfolio in the most crowded and extended positions. Diversification erodes, not through any decision but through neglect: the winners grow, the offsets shrink, and nobody rebalances because nothing hurts. Risk gets underestimated, because the recent sample contains no pain and models fed on calm data report calm conclusions. Leverage creeps up, since every month that passes without incident makes a little more exposure feel justified. And decisions turn emotional in the most disguised way possible: not fear, but comfort, which does not feel like an emotion at all. None of these steps looks like a mistake in the moment. Each one is a small loosening of discipline that the environment immediately rewards, and that is what makes calm markets dangerous: they pay you, for a while, to become fragile. The result is a portfolio whose risk has grown exactly as its owner’s perception of risk has shrunk, the widest possible gap between the two, reached at the worst possible time. This is why risk management matters most before markets become volatile, not after. Protection built during stress is bought at crisis prices, when spreads are wide, liquidity is thin and options have narrowed. Protection built during calm is nearly free, and calm is the only period in which building it requires deliberate effort, because nothing is forcing it. Volatility as information When volatility finally arrives, the common reaction is to treat it as noise to be endured or a threat to be escaped. The professional reading is different: volatile periods are the most informative environment a portfolio ever gets, because they show, with real money and real prices, what every assumption was actually worth. Stress reveals where assumptions break. The position that was supposed to be defensive and was not. The strategy that was supposed to be uncorrelated and moved with everything else. Volatile periods show correlations rising in real time, exactly the dynamic we documented in our article on correlation risk and diversification, and they show it against your actual holdings rather than a historical dataset. Stress reveals what liquidity is really worth. Spreads widen, depth thins, and the difference between a position sized for calm markets and one sized for stressed markets becomes a number on a statement rather than a paragraph in a policy. The mechanics are the subject of our article on what happens when liquidity disappears; a volatile week is where those mechanics stop being abstract. And stress reveals the state of the investor’s own discipline: whether the rules written in calm conditions actually execute under pressure, or whether the process turns out to have been a document rather than a practice. Seen this way, volatility is not the enemy of good portfolio management. It is its auditor. An investor who studies what a volatile period exposed, and adjusts structure accordingly, converts the discomfort into the most valuable data available. An investor who merely waits for it to pass has paid the tuition and skipped the lesson. Closing the loop: rehearse in calm, learn in stress The two halves of this argument meet in a single practical discipline. Calm periods are when the work gets done: rebalancing drifted exposures, refreshing correlation assumptions, sizing positions to stressed liquidity, and testing the portfolio against adversity before adversity arrives, the practice we described in our article on stress testing in real portfolios. Volatile periods are when the work gets graded, and when the next round of improvements gets identified from what actually broke or held. Investors who follow this loop treat both environments as useful: calm as the time to build, volatility as the time to learn. Investors who follow their feelings do the opposite in both: they relax when they should be building and panic when they should be observing. The market will keep alternating between the two states, on its own schedule. The only real choice is which relationship to have with them, and the portfolios that compound across cycles are the ones that learned to distrust the comfortable periods and to read the uncomfortable ones. This article expands on two recent LinkedIn posts by Nicola Pinchi, on the mistakes investors make when nothing seems to be happening and on what markets teach during volatile periods. This article is provided for informational and educational purposes only. It does not constitute investment advice, an offer, or a solicitation to invest in any product or service. Income Capital Management s.r.o. is registered under §15 of the Czech Act on Investment Companies and Investment Funds (ZISIF). Past performance is not indicative of future results. Investing involves risk, including the possible loss of capital.

Preparing Portfolios for the Final Quarter: Structure Over Sentiment

Preparing Portfolios for the Final Quarter: Structure Over Sentiment The end of summer has a particular effect on investors. Desks refill, volumes return, and after weeks of thin markets there is a collective urge to form a view: what the last quarter will bring, where rates and currencies are heading, how to position for the year-end. The instinct is understandable. It is also, in most cases, the wrong starting point. The professional approach to the final quarter begins somewhere else entirely. Its goal is not to predict the next three months but to make sure the portfolio is aligned with its risk limits and its strategic objectives before the period begins, so that whatever the quarter delivers lands on a structure that was ready for it. Portfolio positioning for the final quarter is an exercise in preparation, and preparation reduces reaction time and improves decision quality exactly when volatility increases and judgment deteriorates. Why the last quarter deserves its own review Every quarter is different, but the last one has structural features worth naming, because they affect portfolios regardless of anyone’s market view. Liquidity thins as the year closes. December in particular sees participation fall as institutions lock in results and trading desks wind down, which means the same order moves prices further and exits cost more. Positioning also tends to be crowded coming out of summer, as many participants return to the same consensus themes at the same time, and crowded positions unwind together. Year-end flows add their own layer: rebalancing, fiscal-year considerations for funds, window dressing, and the mechanical buying and selling that follows the calendar rather than fundamentals. And historically, several of the sharpest market episodes have fallen in the autumn months, not because autumn is cursed, but because the combination of returning volume, crowded positioning and the approach of year-end tends to resolve accumulated imbalances quickly. None of this tells you which direction markets will move. All of it tells you that a portfolio entering the final quarter with exposures sized for August’s liquidity, or with limits calibrated during a calm summer, is carrying risk it has not measured. Preparation is not prediction This distinction is the entire argument, so it deserves precision. Prediction asks: what will happen? It produces a positioning bet whose outcome depends on being right, and its record, as we have documented in our article on why process beats prediction, is poor exactly when it matters. Preparation asks a different question: whatever happens, is this portfolio built to handle it inside its mandate? It produces alignment rather than a bet, and alignment pays off in every scenario, because its benefit is not a return but a reduction in the cost and delay of every decision that follows. The practical difference shows up at the moment of stress. The prepared portfolio already knows its exposures, its limits, its liquidity, and its rules; when volatility arrives, the only remaining task is execution. The unprepared portfolio has to discover all of that under pressure, at the worst possible time to learn anything. Preparation does not remove uncertainty from markets. It removes uncertainty from the response. The pre-quarter review: five checks Turning the principle into practice means running a defined review before the quarter starts, and the review is a short list of concrete questions. First, exposure drift. Summer markets move positions away from their intended weights without anyone deciding anything. Where does each exposure actually sit relative to its target, and which ones have grown into a larger share of risk than the framework allocated to them? Second, risk limits against current conditions. Limits set in a low-volatility environment can be too loose for a higher one, because the same position size carries more risk when volatility rises. Do current volatilities and correlations still fit the limits, or do the limits need recalibration before the quarter tests them? Third, liquidity for year-end. Can the portfolio raise cash, hedge, or reposition in December’s thinner markets without forced selling? Are position sizes consistent with stressed market depth rather than normal depth? The mechanics behind this question, and why it matters more than it appears, are the subject of our article on what happens when liquidity disappears. Fourth, the decision rules for a volatility spike. What, specifically, happens to exposure at defined levels of loss or volatility? If the answer is not written down before the quarter, it will be improvised during it. Running the portfolio through adverse scenarios now, the practice we described in our article on stress testing in real portfolios, is how those rules get checked against reality before reality checks them. Fifth, the correlation refresh. Do the diversifiers still diversify on current data? Correlation structure shifts with regimes, and a portfolio whose components have quietly converged over the summer is one position wearing several names. Readers of our mid-year review will recognize the DNA. The pre-quarter check is its shorter, forward-looking sibling: less about judging the past six months, more about making sure the next three cannot force a decision the framework did not anticipate. Structure over sentiment as the summer closes There is a temptation, at this point in the calendar, to treat the return from summer as a reset, a moment to rethink everything in light of whatever the market did in August. Disciplined portfolio construction resists that temptation on purpose. Markets will keep changing; the structure is what ensures continuity across those changes. The goal of the season’s turn is not to react to every movement it produces but to confirm that the portfolio remains aligned with its long-term strategy, adjusting only what the review shows has drifted. Sentiment is loud in September and it is usually wrong by December. Structure is quiet and it is still there in January. The portfolios that reach the year-end intact are rarely the ones with the best autumn forecast. They are the ones that spent the last week of August checking their limits, their liquidity and their rules, and then let the quarter

The Role of Stress Testing in Real Portfolios

The Role of Stress Testing in Real Portfolios Every portfolio carries a set of promises: this is how much risk we take, this is how the pieces offset each other, this is what happens if things go wrong. Most of the time, those promises are never checked against anything harder than a calm market, and their first real examination happens live, during a crisis, with capital on the line. Portfolio stress testing exists to move that examination forward in time. It is the practice of simulating adverse scenarios against the actual portfolio, today, to find out where the vulnerabilities are while there is still time to do something about them. Nothing about it is theoretical. It is the difference between discovering a weakness on paper and discovering it in a margin call, and the principle behind it fits in one sentence: you cannot manage what you have not tested. What stress testing actually is Standard risk statistics describe how a portfolio has behaved: its volatility, its correlations, its drawdowns over the observed period. The limitation is in the word observed. History as it happened is one sample, dominated by the regimes that happened to prevail, and a portfolio calibrated only on it is calibrated for the past. Stress testing asks a different question: what would this portfolio do under conditions we specify? The scenarios come in three families. Historical scenarios replay documented episodes against today’s positions: the leverage unwind of 2008, the liquidity collapse of March 2020, the rate-driven regime change of 2022. Hypothetical scenarios model shocks that have not happened in that form: a sudden rate surprise, a currency gap over a weekend, a correlated sell-off in positions assumed independent. Reverse stress tests work backwards: they start from an unacceptable outcome, a drawdown beyond the mandate, a forced liquidation, and search for the combinations of events that would produce it. The output is not a prediction. It is a map of sensitivities: which exposures dominate the damage in each scenario, and how far current conditions sit from the thresholds that matter. What it reveals that normal analysis cannot Run honestly, stress tests surface exactly the weaknesses that calm-market analysis hides. They reveal hidden concentration: positions that look independent on the books but respond to the same underlying factor, so that a single scenario moves them together. This is the correlation problem in its practical form, the one we examined in our article on correlation risk and diversification, and stress testing is where that analysis stops being abstract and produces numbers against your actual holdings. They reveal liquidity gaps: positions sized for the depth of a normal market that could not be exited at acceptable cost in a stressed one, and funding buffers sized for a portfolio that has since grown. The mechanics of that failure, and why it converts paper losses into permanent ones, are the subject of our article on what happens when liquidity disappears; the stress test is where those mechanics get checked against your own numbers before the market checks them for you. And they reveal whether the limit structure is real: whether the exposure caps and drawdown thresholds, applied to a genuinely adverse path, actually contain the damage within what the mandate promises, or whether the rules were calibrated for weather the portfolio no longer sails in. From test to decision A stress test that produces a report and nothing else is a ritual. The value is entirely in what changes because of it, and the changes follow a consistent pattern: position sizes adjusted where a single scenario produced outsized damage, hedges or offsets added where concentrations emerged, liquidity buffers resized to the portfolio as it is now, and limits recalibrated where the test showed them too loose for current conditions. The deeper point is timing. Every one of those adjustments is cheap before the scenario and expensive during it. Stress testing is how a portfolio makes its hard decisions in advance, calmly, with full information about its own structure, instead of improvising them under pressure with degraded judgment. It is the same logic that runs through everything we have written about process over prediction: the response to stress has to exist before the stress does, and the test is how you find out whether it actually would have worked. The honest limits of the exercise Stress testing deserves one caveat, stated plainly, because overselling it is its own risk. Scenarios are chosen by people, and the crisis that arrives is reliably the one nobody modeled in exactly that form. A stress test is a map, not the territory, and a portfolio that passes every test is not safe; it is prepared for the failures someone imagined. The professional response to that limit is not to abandon the exercise but to draw the right conclusion from it: keep buffers beyond what the tests require, keep leverage below what the tests permit, and treat every passed test as provisional. The purpose of stress testing is not to prove the portfolio is safe. It is to make sure that whatever surprises arrive, they land on a structure that has already survived a hundred rehearsals of its own worst days. Markets will eventually run the real test, on their schedule, without warning. The only choice a portfolio gets is whether that day is the first time its weaknesses are discovered, or merely the first time they are confirmed. This article expands on a recent LinkedIn post by Nicola Pinchi on the role of stress testing in real portfolios. This article is provided for informational and educational purposes only. It does not constitute investment advice, an offer, or a solicitation to invest in any product or service. Income Capital Management s.r.o. is registered under §15 of the Czech Act on Investment Companies and Investment Funds (ZISIF). Past performance is not indicative of future results. Investing involves risk, including the possible loss of capital.

The Mid-Year Portfolio Review: Judge the Process, Not the Performance

The Mid-Year Portfolio Review: Judge the Process, Not the Performance Every summer, investors sit down with six months of results and draw conclusions. Most of those conclusions are wrong, not because the numbers are inaccurate, but because six months of performance answers a different question than the one being asked. A half year of returns tells you what happened. It tells you very little about whether it happened for the right reasons, whether the risks taken were the ones intended, or whether the same approach will hold up when conditions change. That is what a proper portfolio review is for, and it is why the professional version of the exercise spends most of its time on process quality and only a fraction on the headline number. Why mid-year numbers distort The first half of any year is a small sample dominated by whatever regime happened to prevail. A strategy positioned for that regime looks brilliant; one positioned for resilience across several regimes looks unnecessarily cautious. Six months later the ranking often inverts, and the investor who re-allocated toward the winner discovers they bought the last regime just as the next one began. Recency does the rest. Recent gains inflate confidence and tempt investors to loosen the rules that produced them; recent losses trigger the urge to change everything, including the parts that worked. Both reactions treat a short-term outcome as a verdict on the process, which is exactly the inference a small noisy sample cannot support. Performance without process is incomplete information, and acting on incomplete information mid-cycle is how good strategies get abandoned and bad ones get funded. The corrective is to review the portfolio against questions the numbers alone cannot answer. Three of them do most of the work. Question one: were risks actually controlled? Not “was the return good,” but: did the portfolio stay inside its intended risk boundaries? Did any position, sector, or theme grow beyond its budgeted share, through market movement or through drift in discipline? Were the drawdowns, if any, within what the framework said should be possible, and did the pre-defined responses actually execute when thresholds were reached? A profitable half-year that quietly breached its risk limits is a warning dressed as a success: the same behavior in a different regime produces the loss the limits existed to prevent. The reverse also holds. A modest result achieved with risks fully controlled is evidence the machine works, and machines that work compound. Question two: was diversification effective? Owning many positions is not the test. The test is whether the portfolio’s components actually behaved differently when it mattered: on the worst days of the half-year, did the diversifiers diversify, or did everything move together? Mid-year is the right moment to re-run correlation analysis on current data rather than last year’s, because correlation structure shifts with rate regimes, inflation dynamics and liquidity conditions. Exposures that were genuinely independent in January can be one position wearing several names by July. We examined this failure mode in depth in our article on correlation risk and diversification; the mid-year review is where that analysis gets refreshed rather than assumed. Question three: was liquidity sufficient? The quietest question, and in stress the most important one. Could the portfolio have raised cash, met obligations, or repositioned during the half-year’s worst week without forced selling? Have position sizes drifted beyond what stressed market depth could absorb? Is the funding buffer still sized to the portfolio the buffer is protecting, or to the smaller one it protected a year ago? Liquidity failure is the mechanism that turns paper drawdowns into permanent losses, which is why it deserves its own line in every review even when, especially when, nothing went wrong. We covered the full mechanics in our article on what happens when liquidity disappears; the review is where its lessons become a checklist. Reading the numbers after the process None of this means ignoring performance. It means sequencing it correctly: process first, numbers second, so the numbers can be interpreted instead of merely felt. A result is informative only next to the risks that produced it and the environment it was produced in. Did the strategy behave as designed, in the conditions it was designed for? Did it earn its return from its stated edge, or from an exposure nobody chose? Would the same behavior have been acceptable in a worse regime? Answered honestly, these questions turn a performance figure from a verdict into a data point, one input among several in the ongoing evaluation of whether the process deserves continued trust. This is the review discipline we described in our article on why process beats prediction: judgment applied to the process, calmly and on schedule. The discipline of the calm moment There is a final reason the mid-year review matters, independent of anything it finds: it happens on the calendar, not in reaction to events. Reviews triggered by pain arrive when judgment is worst; reviews triggered by dates arrive when thinking is possible. Conducting the exercise in a quiet market, when nothing forces it, is itself the habit that makes the process real, because a process that only runs under pressure is not a process. Six months of returns will always attract more attention than the machinery behind them. The investors who last are the ones who learned to look at the machinery first. This article expands on a recent LinkedIn post by Income Capital Management on the mid-year market reality check. This article is provided for informational and educational purposes only. It does not constitute investment advice, an offer, or a solicitation to invest in any product or service. Income Capital Management s.r.o. is registered under §15 of the Czech Act on Investment Companies and Investment Funds (ZISIF). Past performance is not indicative of future results. Investing involves risk, including the possible loss of capital.

What Happens When Liquidity Disappears

What Happens When Liquidity Disappears Liquidity is the risk investors think about least, because in normal conditions it never announces itself. Positions can be opened and closed at quoted prices, spreads stay tight, and the ability to transact feels like a property of the market itself, permanent and free. Then conditions change, and the property turns out to have been a privilege. Liquidity risk is invisible until it is not, and by the time it becomes visible it is already expensive. This article looks at what liquidity actually is, why it vanishes precisely when it is needed most, what that does to a portfolio, and how professional liquidity planning turns an invisible risk into a managed one. What liquidity actually is Liquidity is usually defined as the ability to buy or sell an asset quickly without moving its price. That definition hides two separate things worth keeping apart. The first is market liquidity: the depth of the market for what you hold, the size that can be transacted near the quoted price, and how quickly. The second is funding liquidity: your own ability to meet obligations, margin calls, redemptions, and expenses without being forced to sell assets at a bad moment. The two interact viciously in a crisis, because funding pressure forces selling exactly when market depth has thinned, but they are managed differently, and a portfolio can be strong on one and fragile on the other. Both share a property that makes them treacherous: they are conditions of the environment, not attributes of the asset. An instrument that trades effortlessly in calm markets can become nearly unsellable at a fair price during stress. Measuring liquidity in normal times and assuming the measurement holds is one of the most common structural mistakes in portfolio construction. Why liquidity vanishes exactly when it matters Liquidity does not fade gradually. It disappears in a self-reinforcing spiral, and the mechanism is worth understanding because it explains why the disappearance always feels sudden. Stress begins with falling prices somewhere in the system. Falling prices trigger margin calls on leveraged holders, who must sell to raise cash. Their selling pushes prices down further, widening losses and triggering more calls. Market makers, facing the same volatility, reduce the size they are willing to quote or step away entirely. Buyers who might provide support wait, rationally, for lower prices. Within days, a market that comfortably absorbed large flows can only absorb small ones, at prices that gap rather than glide. The Bank for International Settlements documented this margin spiral in detail during the March 2020 dash for cash, when even US Treasuries, the most liquid instruments in the world, briefly traded like scarce assets as leveraged positions unwound. The uncomfortable conclusion is that liquidity is used up by the people who need it first. Whoever plans for stress in advance transacts near the old prices; whoever discovers the need during stress pays whatever the spiral demands. What it does to a portfolio When liquidity thins, three things happen to a portfolio at once, and together they explain much of the damage in every market crisis. Prices move faster. With less depth to absorb flows, the same selling pressure produces larger moves, so volatility rises mechanically even before sentiment deteriorates further. Correlations increase. Assets that normally move independently begin falling together, because the common driver is no longer fundamentals but the shared need for cash. Diversification measured in calm conditions quietly stops working, a dynamic we examined at length in our article on correlation risk and diversification. Execution becomes difficult and expensive. Spreads widen, order sizes shrink, and repositioning, hedging, or simply raising cash costs multiples of what it did weeks earlier. The portfolio’s crisis plan, if it assumed normal transaction costs, is now a document about a different market. The combined effect is the one that matters: options disappear. A portfolio facing stress with thin liquidity is pushed toward forced decisions, selling what can be sold rather than what should be sold, at the worst prices of the cycle. Forced selling is how temporary drawdowns become permanent losses, which is why liquidity failure sits underneath so many of the disasters that look, from outside, like something else. Liquidity planning as a process Because liquidity cannot be bought during stress at any reasonable price, it has to be built beforehand, and building it is a process with concrete components rather than a vague preference for caution. It starts with honest measurement: classifying every holding by how much could realistically be sold, how fast, and at what cost, under stressed conditions rather than average ones. It continues with structure: position sizes set relative to the market’s stressed depth, not its calm depth, so that exits remain possible at the scale the portfolio actually holds. It includes a funding buffer sized to survive margin calls and obligations without forced sales, held not as idle capital but as optionality, the ability to act while others are forced to react. And it is one reason market choice itself is a risk decision: the depth of the foreign exchange market, which remains functional when many markets thin out, is a structural input to how we approach the design of a professional forex fund. None of this shows up in returns during calm years, which is exactly why undisciplined portfolios skip it. The value of liquidity planning is realized entirely in the weeks when it is too late to start. The risk that hides in plain sight Liquidity risk earns so little attention because it presents no symptoms between crises. Volatility is visible daily; concentration shows up in any report; leverage is a number on a page. Liquidity sits quietly in the background, costing nothing, until the environment changes and it becomes the only thing that matters. The professional stance is to treat it accordingly: as a core dimension of portfolio construction, measured under stress, planned in advance, and reviewed as markets evolve, never as an afterthought to be handled when needed. We have

Why Drawdowns Matter More Than Returns

Why Drawdowns Matter More Than Returns Ask most investors to evaluate a strategy and they will reach for one number: the return. Annualized, cumulative, year-to-date, it hardly matters which version, because the instinct is the same. Returns are the score, and higher is better. Professional allocators read the same documents in a different order. Before the return, they look at the drawdowns: how deep the losing periods went, how long they lasted, and how the strategy behaved inside them. This is not pessimism. It is the recognition that drawdown management, more than return generation, determines whether a strategy survives long enough for its returns to matter at all. The arithmetic is not symmetrical The case starts with a mathematical fact that remains underappreciated no matter how often it is stated: losses and gains are not symmetrical. A 10% loss needs roughly an 11% gain to recover. A 20% loss needs 25%. A 30% loss needs about 43%, and a 50% loss needs a full 100%. The deeper the hole, the disproportionately harder the climb out. Time makes the asymmetry worse. A strategy earning a solid long-term average needs years, not months, to rebuild from a deep loss, and those are years in which the capital is working to repair damage rather than to compound. Two strategies with identical average returns can produce completely different final outcomes purely because one of them spent less time underwater. Over long horizons, the compounding you keep is decided less by the height of the peaks than by the depth of the valleys. This is why maximum drawdown and time-to-recovery deserve a place next to any return figure. A return number without its drawdown history is not information. It is advertising. What a drawdown reveals Beyond the arithmetic, drawdowns carry information that returns cannot. A good period tells you little: rising markets lift disciplined and undisciplined strategies alike, and luck is indistinguishable from skill on the way up. A drawdown, by contrast, is an involuntary disclosure. It shows how much risk the strategy was actually carrying, as opposed to how much it claimed to carry. The depth of a drawdown reveals concentration and leverage. Its breadth reveals correlation: a portfolio that falls in one piece was one position wearing several names, a failure mode we examined in detail in our article on correlation risk and diversification. And the strategy’s behavior during the drawdown reveals whether a process exists at all: did the stated rules execute, or did the approach quietly change once losses arrived? Allocators know this, which is why serious due diligence spends more time on the worst months of a track record than on the best ones. The worst months are where the truth lives. The second wound is behavioral The damage of a deep drawdown is paid twice. The first payment is the capital. The second, often larger, is behavioral, and it lands on the investor rather than the portfolio. Deep losses push people toward the worst decisions available: abandoning the strategy at the bottom, doubling exposure to recover faster, overriding rules that suddenly feel too slow. Each of these converts a temporary loss into a permanent one. The pattern is so consistent that it should be treated as a design constraint: a strategy whose drawdowns exceed what its investors can psychologically tolerate will be abandoned at the worst possible moment, and an abandoned strategy returns whatever the exit produced, not what the backtest promised. Shallow drawdowns, in this sense, are not just financially efficient. They are what keeps the investor in the game, and staying in the game is a precondition for every other statistic. Drawdown management in practice None of this happens by wishing for it. Keeping drawdowns shallow is an engineering outcome, produced by specific mechanisms that exist before losses begin. The first mechanism is position sizing scaled to volatility, so that no single exposure can produce a portfolio-level hole. The second is the limit structure: defined loss thresholds at which exposure is reduced according to pre-set rules, and deeper thresholds at which the strategy de-risks or pauses entirely. We described this architecture in our article on the structure behind a professional forex fund; the principle generalizes to any asset class. The third is diversification measured on stressed correlations rather than calm ones, so the portfolio’s pieces do not converge into a single falling block exactly when it matters. The common feature of all three is timing: they are decided in advance. A drawdown is the worst environment in which to design a response, because judgment degrades exactly as the need for it grows. The response has to already exist, written down, waiting. Reading a track record through its drawdowns For an investor evaluating any strategy or manager, this reframing produces a practical checklist that takes minutes to apply and reveals more than most pitch documents. What was the maximum drawdown, and does it fit your actual tolerance rather than your imagined one? How long did recovery take, and what was the strategy doing during that time? Were the losing periods consistent with the stated risk framework, or did they exceed what the rules should have permitted? And is the drawdown history independently verifiable, or does it exist only in the manager’s own presentation? A manager who answers these questions readily, with specifics, is describing a process built to be examined. Hesitation around drawdown questions is itself information, and rarely the good kind. The broader argument for judging strategies by their process rather than their predictions is one we made in our article on why process beats prediction; drawdown history is simply the place where that process leaves its most honest record. Returns tell you what happened when things went well. Drawdowns tell you what happens when they do not, and every long-term result is built out of both. The investors who last are the ones who chose, early, which of the two numbers to respect more. This article expands on a recent LinkedIn post by Nicola Pinchi