Risk Management: The Art of Long-Term Survival
Risk Management
Imagine a hero standing at a crossroads with three paths.
If he takes the road to the right, he will face a serious challenge with a difficulty level of 100. At the end of this path, however, he will be rewarded with five gold bars.
The middle road leads to ten gold bars, but the hero will encounter not one, but three challenges along the way. Each of them is no less difficult than the one on the right-hand road. Taken together, their total difficulty amounts to 300.
The left road involves a less demanding challenge with a difficulty of 60, but the reward is modest — only one gold bar.
Which path would you choose if you were in the hero’s place?
Now suppose the hero chose a balanced level of risk, but along the way he was bitten by a snake and never even reached the challenge.
This is exactly what risk-taking in financial markets looks like.
In the real world, risk is first and foremost the probability of loss.
Risk is an inevitable consequence of the fact that the future is unknown. At any given moment, there are far more possible outcomes than those that ultimately materialize. It is precisely this gap — between the range of potential outcomes and the single realized result — that gives rise to risk. The future cannot be viewed as a predetermined or predictable script; it is a spectrum of possibilities that includes both favorable and unfavorable outcomes.
An investor may estimate the range of the most likely scenarios and base their expectations of the future on them. However, even the most probable event offers no guarantee that it will actually occur.
Risk comes in many forms, and the probability of loss is only one of them. Another important type is the risk of missed opportunities — the risk of taking too little risk. Staying on the sidelines can cause an investor to miss a recovery or a growth phase and ultimately drop out of the investment process altogether.
Particularly destructive is the risk of selling at the bottom. In this case, the investor not only locks in losses but also forfeits the chance to participate in the subsequent recovery, which often leads to a permanent exit from the market.
There are also risks associated with rare but catastrophic events. These risks may remain hidden for a long time, creating the illusion that a strategy is safe — until they suddenly materialize with severe consequences, as in the example of the hero and the snake.
Risk has a contradictory and deceptive nature. It depends not only on the asset or the market itself, but also on the behavior of market participants. When people feel safe and confident, they tend to act less cautiously, and actual risk increases.
Conversely, when risk is recognized and perceived as high, behavior becomes more restrained, and risk may decrease.
Paradoxically, rising prices often increase risk, while falling prices can make an asset safer — even though most people intuitively perceive the opposite.
Risk management is not a one-time action or a reaction to a crisis; it is a continuous process.
Since it is impossible to know in advance when adverse events will occur, risk control must be present at all times, not only during periods of obvious threat.
The essence of a sound approach is not the complete avoidance of risk, but its conscious acceptance, analysis, and limitation. An investor takes on risks they understand, can diversify, and are adequately compensated for.
Ultimately, the investor’s task is to build an asymmetric outcome profile: to participate in upside when events unfold favorably, and to lose less when negative scenarios materialize.
Such asymmetry is a hallmark of true skill and reflects a deep understanding of probability distributions, hidden risks, and acceptable loss limits.
How to Form Your Own Risk Assessment in a Specific Situation
To address this question, it is useful to turn to the work of Ed Seykota. One of his core ideas can be summarized as follows:
Risk is not the size of a potential loss in itself, but the probability of that loss occurring given the current market structure.
An important implication follows from this:
The profit-to-loss ratio (risk/reward) is not an independent criterion of trade quality.
The risk of a specific trade is determined by two key factors:
the market environment,
the distribution of profits and losses.
However, the decisive element is not the absolute size of the potential profit, but the probability of achieving it, as defined by the market context
Consider a situation where the potential profit is relatively small compared to the possible loss. From a formal risk/reward perspective, such a trade appears unattractive. But if the market conditions suggest that the probability of a positive outcome is high — for example, around 90% — the risk no longer appears unreasonable. In this case, the trade is justified not by the magnitude of the payoff, but by the stability of the probabilistic edge.
An individual trade, taken in isolation, is meaningless. What matters is how similar situations play out over a large sample size.
Even with a very high probability of success, risk becomes unjustified if:
a negative scenario is capable of destroying a significant portion of the capital;
or a single rare loss outweighs the cumulative result of many successful trades.
This is why, within any robust system, probability and loss control must always go hand in hand. High probability without loss limitation is not trading — it is gambling.
Unjustified Risk
Suppose a trader manages to earn 5% on their account over the course of a month , while the benchmark — for example, the Nasdaq — delivers a return of 8% over the same period. What does this imply?
To answer this, we turn to the concept of alpha .
Alpha is a metric that measures how much a strategy’s or trader’s performance deviates from the benchmark return, after accounting for the level of market risk taken.
If a trader engages in active intraday trading — assuming operational, market, behavioral, and tail risks — yet achieves a return lower than that of the benchmark, this indicates that risk was taken without adequate compensation . The critical issue is not the mere presence of risk, but the relationship between risk and outcome.
By its nature, intraday trading involves high engagement, frequent decision-making, exposure to market noise, commissions, slippage, and psychological pressure. All of these factors increase the strategy’s total risk profile. If, despite this, the final result underperforms a passive benchmark, alpha becomes negative. This means that each unit of risk taken was not only unrewarded, but actually worsened the overall financial outcome.
In such a case, alpha does more than simply indicate “underperformance relative to the market.” It highlights the inefficiency of the risk taken . The trader is effectively performing a more complex and uncertain task while achieving a result that could have been matched — or exceeded — through passive exposure, without active trading and its associated risks.
This is precisely what constitutes unjustified risk: risk that does not increase expected returns and does not improve the distribution of outcomes.
Thus, intraday trading with returns below the benchmark is an example of risk-taking without economic rationale. Alpha here serves not as a goal, but as a diagnostic tool. If alpha is negative, it indicates that the trading risk is not merely unjustified — it is value-destructive relative to a passive alternative.
Integration into Trading
1. Market Context Comes Before the Trade
In real trading, the first object of analysis is not the entry, not the stop, and not the take-profit — it is the state of the market itself.
The key question you must answer is:
Is there a recurring market situation here that historically shifts the probability in my favor?
If the situation is not repeatable and lacks a clear internal logic, the trade is not considered at all — regardless of how attractive the risk/reward ratio may look.
2. Probability Matters More Than Potential Profit
Once the situation has been identified, the focus shifts not to profit, but to the probability of the scenario playing out.
In practical terms, this means:
You must understand why the market is more likely to continue the move rather than reverse.
The reason for entry should explain why continuation is more probable, based on the logic of market participants’ behavior — not merely be the result of a formal signal.
Even if the potential profit is relatively small, a trade may still be justified if:
The probability of success is consistently above random;
The situation is reproducible over a large sample size.
3. Loss Is Defined in Advance — and Rigidly
A loss is not something to “figure out along the way.”
It is defined before entering the trade and is not revised in the hope that the market will “come back.”
The core integration rule is simple:
No single loss should be capable of damaging the integrity of the system
This implies:
Strictly limited risk per trade;
No scenarios in which one unfavorable outcome wipes out the results of many successful trades.
4. Serial Thinking Instead of Evaluating Individual Trades
True integration happens at the mental level. You stop evaluating trades in terms of “profit or loss.”
Each trade is viewed as:
One element within a series;
One roll of the dice with a known probability bias.
In practice, this leads to:
No emotional reaction to a single loss;
No euphoria from a single winning trade.
5. Trade Selection Instead of Increased Activity
Integrating this approach almost always reduces the number of trades.
You enter the market only when:
The market provides a readable context;
The scenario has a statistical edge;
The risk is clearly defined in advance.
If the market does not offer these conditions, you do not “look for trades” — you wait.
6. Evaluating Results by Process, Not by Money
In real trading, success is not measured by daily PnL, but by:
Adherence to the logic of situation selection;
Discipline in loss limitation;
Consistency of execution.
A losing day can be a perfect day if all decisions were made within the framework of the system.
Risk Management Framework in Investing
Risk should be distributed not only across trading instruments, but also across sources of returns.
A portfolio composed of assets dependent on a single growth scenario creates an illusion of diversification while remaining structurally fragile. True diversification implies exposure to different sectors, asset classes, and underlying economic processes.
An important element of risk management is time diversification. Entering positions in stages reduces the risk of poor timing and mitigates the impact of short-term market fluctuations. Investing the full amount at a single price point turns an investment into a timing bet rather than a conviction in the underlying idea.
Liquidity risk must also be taken into account. An asset that cannot be sold without a significant discount carries hidden danger. Liquidity matters not during calm periods, but during times of stress, when exiting a position may become critically important.
Diversification also means being willing to keep part of the capital out of the market. Holding free liquidity reduces decision-making pressure and allows the investor to respond to opportunities that arise during periods of panic. Full capital deployment increases the risk of forced actions.
Risk reduction becomes necessary when uncertainty rises. Increasing correlations between assets, changes in macroeconomic conditions, growing leverage, or excessive market optimism are signals to reassess portfolio structure. In such periods, capital preservation takes precedence over returns.
An increase in investment risk is acceptable only when there is a sufficient margin of safety. Expanding exposure to higher-risk assets is justified when capital is growing, the investment horizon is long, and acceptable losses are clearly defined. An investor does not increase risk in an attempt to “catch up with the market.”
Portfolio structure should reflect not only the investor’s expectations, but also their ability to withstand unfavorable periods. There is no universal allocation; however, practical guidelines help keep risk within manageable limits.
Portfolio Structure Guidelines
Low-risk allocation serves as the foundation and stabilizer of the portfolio.
Typically, it represents 50–70% of total capital . This segment includes highly liquid assets with relatively predictable behavior. Its purpose is not to maximize returns, but to preserve capital and reduce overall portfolio volatility.
Moderate-risk allocation usually accounts for 20–40% of the portfolio. These are assets with growth potential but without critical dependence on a single scenario. They generate the core long-term returns and absorb part of the market’s fluctuations.
High-risk allocation is limited to 5–15% of capital. This segment includes assets with high volatility, asymmetric payoff potential, and an elevated probability of deep drawdowns. Losses in this zone must never threaten the integrity of the entire portfolio. If an asset can go to zero, its position size must be small enough for that outcome to be non-critical.
Rebalancing and Capital Discipline
Rebalancing is a mandatory component of risk management. As high-risk assets appreciate, their weight increases automatically, and part of the gains should be reallocated toward more stable segments. During market declines, the portfolio structure is reviewed based on changing conditions rather than emotional reactions.
Increasing exposure to high-risk assets is appropriate only when capital is growing, the investment horizon is long, and potential losses are clearly understood. Reducing exposure becomes necessary during periods of heightened uncertainty, macroeconomic shifts, or declining personal risk tolerance.
A portion of the portfolio should be held in cash. Cash is not inactivity or a missed opportunity — it is an asset that serves both defensive and strategic functions.
Typically, cash represents 10–30% of the portfolio , depending on market conditions and uncertainty. During stable growth phases, it may sit near the lower end of this range. In periods of elevated volatility, uncertainty, or after prolonged market rallies, increasing the cash allocation becomes prudent.
A cash position reduces overall portfolio risk and alleviates psychological pressure.
Free liquidity allows decisions to be made calmly, without the need to sell assets under unfavorable conditions.
The key principle lies not in finding the perfect percentage, but in maintaining the chosen structure . Discipline in risk allocation is more important than precision in initial calculations.
A Risk Management Framework in Trading
Risk management in trading does not begin with entering a trade; it begins with accepting the fact that any trade can end in a loss. A trader who is not internally aligned with this reality will inevitably violate their own rules. Accepting losses as a legitimate outcome is a fundamental condition for survival in the market.
Position sizing is more important than the entry point. Even a strong idea loses its value if its size is disproportionate to potential adverse scenarios. A trader is not required to predict direction perfectly, but they are obligated to control the consequences of being wrong.
Every trade must be “paid for” in advance. The potential loss must be known and psychologically accepted before entry. For one trader, an acceptable risk may be one percent of capital; for another, five percent. These figures are not universal truths — they reflect individual tolerance for uncertainty, trading style, and time horizon. What matters is not the number itself, but strict adherence to it.
For a beginner trader, an acceptable risk per trade is typically a loss of no more than one to two percent of the account. This level of risk allows the trader to endure a series of losing trades without causing critical damage to capital and, just as importantly, to psychological stability. Under these conditions, the risk-to-reward ratio should be no less than 1:2 and, in more favorable setups, should approach 1:3. This means that the potential profit of a trade should be at least twice, and preferably three times, greater than the potential loss. With such an approach, a trader maintains a positive mathematical expectancy even when a portion of trades ends in losses.
No single trade is decisive. The market is a sequence of attempts, not a single trial. Focusing on the outcome of an individual trade undermines discipline and distorts risk perception.
Refusing to exit is also a decision — and it carries risk. Holding a losing position in the hope of a reversal is not a neutral action; it is an active choice to increase uncertainty.
Periods of growth require no less caution than periods of decline. Confidence reinforced by a streak of successful trades often becomes the source of the largest losses. Growth in capital is a reason to reduce risk, not to increase it.
The best kind of risk is one that allows for error. A strategy that leaves no room for mistakes is doomed in the long run. Resilience matters more than precision.
The goal of risk management is not to eliminate losses, but to preserve the ability to continue trading. A trader wins not when losses are avoided, but when losses do not deprive them of the ability to take the next step.
This post is based on our own experiences and research we've gathered from books and various platforms.
Enjoy!
