TradingSimuLab’s Risk Simulation is the downside-path layer of the five-model framework.
It uses simulated future price paths to help answer:
Is the potential reward attractive enough relative to the modeled downside?
Instead of focusing only on upside, Risk Simulation examines:
- Expected Return;
- Probability of Gain;
- simulated price ranges;
- VaR;
- CVaR;
- Average Max Drawdown;
- Worst Max Drawdown;
- and risk-reward quality.
The goal is not to predict one exact future price.
It is to understand how wide the range of possible outcomes may be, how severe adverse paths can become, and whether the potential reward justifies that uncertainty.
Educational disclaimer: TradingSimuLab is an educational research platform. Simulation results are estimates under model assumptions, not financial advice, guaranteed probabilities, price targets, or maximum-loss limits.
What Is Risk Simulation?
Risk Simulation generates many possible future price paths rather than assuming one forecast will occur.
Some simulated paths may:
- finish strongly positive;
- produce modest gains;
- decline;
- recover after large drawdowns;
- or finish deep in the downside tail.
Studying the distribution of those paths provides more information than looking at one expected return.
That is why Risk Simulation is designed to answer:
What could the downside path look like if the setup does not develop cleanly?
The Main Risk Simulation Metrics
| Metric | What it tells you |
|---|---|
| Expected Return | Central expected outcome from the simulation |
| Expected Price | Price-level reference implied by the expected outcome |
| Probability of Gain | Percentage of simulated paths finishing above the starting price |
| 5th–95th Percentile Range | Lower and upper simulated scenario references |
| VaR 95% | A severe downside threshold in the modeled distribution |
| CVaR 95% | Average loss in the adverse tail beyond VaR |
| Average Max Drawdown | Typical worst peak-to-trough decline across paths |
| Worst Max Drawdown | Most severe simulated peak-to-trough decline |
| Risk-Reward Factor | Comparison of expected reward with modeled downside risk |
These metrics answer different questions.
The strongest interpretation comes from reading them together.
Expected Return: Start With the Reward, Not the Conclusion
Expected Return is the simulation’s central expected outcome.
Suppose Risk Simulation shows:
Expected Return: +10%
That does not mean the asset is predicted to rise exactly 10%.
Some paths may finish far above that level.
Others may finish below the starting price.
Expected Return is therefore a summary of the modeled distribution—not a guaranteed future return.
Probability of Gain: How Often Did Paths Finish Positive?
Probability of Gain shows the percentage of simulated paths that ended above the starting price.
For example:
Probability of Gain: 65%
means 65% of the simulated paths finished positively.
It does not mean there is a guaranteed 65% real-world probability of profit.
It simply describes the simulation results under the model’s assumptions.
This metric should always be compared with the size of potential losses.
A high percentage of positive paths can still coexist with a few severe negative outcomes.
VaR: Where Does Significant Downside Begin?
Value at Risk (VaR) provides a downside-threshold estimate from the simulated return distribution.
At a 95% confidence level, VaR helps identify the loss threshold associated with the adverse portion of the modeled distribution.
The important limitation is:
VaR is not the maximum possible loss.
Losses can exceed the VaR threshold.
This is why VaR should be paired with CVaR.
CVaR: How Bad Is the Tail Beyond VaR?
Conditional Value at Risk (CVaR) goes one step further.
Instead of only identifying a downside threshold, it examines the average severity of losses beyond that threshold.
A simple way to remember the distinction is:
VaR = where the bad tail begins.
CVaR = how severe that bad tail becomes on average.
This makes CVaR particularly useful when the worst outcomes are much more severe than the central simulation suggests.
Maximum Drawdown: What Happens Along the Way?
Final returns can hide substantial path stress.
Imagine a simulated path:
$100 → $125 → $78 → $92 → $110
The path eventually finishes higher than it started.
But it experienced a major peak-to-trough decline before recovering.
That is why TradingSimuLab also shows drawdown metrics.
Average Max Drawdown
The average worst peak-to-trough decline across simulated paths.
It helps describe a typical difficult path.
Worst Max Drawdown
The most severe peak-to-trough decline generated by the simulation.
It provides context around extreme simulated path stress.
Neither is a guaranteed future limit.
Why Positive Expected Return Can Still Be Risky
Consider:
Expected Return: +12%
Probability of Gain: 67%
Average Max Drawdown: -22%
Worst Max Drawdown: -43%
CVaR: Severe
The headline return appears attractive.
But the downside metrics tell a more complicated story.
A more accurate interpretation is:
The center of the simulation is positive, but adverse paths remain significant.
That is exactly why Risk Simulation should not be reduced to Expected Return.
High Probability of Gain Can Still Hide Tail Risk
Now imagine:
Probability of Gain: 75%
That sounds strong.
But suppose the remaining 25% of paths contain very large losses.
The high positive-path frequency does not eliminate those losses.
Probability tells you how often.
CVaR and drawdown tell you how severe.
Both matter.
What Do the 5th and 95th Percentile Prices Mean?
Risk Simulation can also show lower and upper scenario references.
The 5th percentile price represents a lower simulated outcome reference.
The 95th percentile price represents an upper simulated outcome reference.
These help show how wide the outcome distribution may be.
They should not be interpreted as:
- a guaranteed floor;
- a guaranteed ceiling;
- or exact price targets.
Real markets can move outside simulated ranges.
Risk-Reward Factor
The Risk-Reward Factor compares expected reward with modeled downside risk.
Its purpose is to help answer:
Does the potential return appear attractive enough given the risk required to pursue it?
A positive expected return does not automatically produce attractive risk-reward.
If downside risk is severe, the overall Risk-Reward Factor can remain defensive.
The model may also provide a confidence range around that estimate.
A wider range suggests greater uncertainty around the reward-to-risk assessment.
A Simple Risk Simulation Example
Suppose two assets show the same Expected Return:
| Metric | Asset A | Asset B |
|---|---|---|
| Expected Return | +10% | +10% |
| Probability of Gain | 70% | 55% |
| Average Max Drawdown | -10% | -24% |
| Worst Max Drawdown | -20% | -45% |
| CVaR | Moderate | Severe |
The expected return is identical.
The quality of the risk profile is not.
Asset B produces far more simulated path stress.
This is why downside metrics should come before excitement about the average return.
How to Read Risk Simulation
A useful sequence is:
1. Check Expected Return
What does the center of the simulation look like?
2. Check Probability of Gain
How often did paths finish positively?
3. Review the 5th–95th Percentile Range
How wide is the outcome distribution?
4. Inspect Average and Worst Max Drawdown
How stressful are typical and extreme simulated paths?
5. Compare VaR and CVaR
Where does severe downside begin, and how bad is the tail beyond it?
6. Review Risk-Reward
Does potential reward appear reasonable relative to modeled downside?
Then compare the risk picture with the other TradingSimuLab models.
How Risk Simulation Fits the Five-Model Framework
Each model answers a different question:
Trend Detector: Is the current trend healthy?
Trend Persistence: Is the trend durable?
Timing Model: Is the immediate setup confirming or vulnerable to failure?
Macro Model: What does the broader 12-month environment look like?
Risk Simulation: Can the downside be tolerated relative to the potential reward?
These layers can disagree.
For example:
Trend: Strong
Timing: Constructive
Risk Simulation: Defensive
The current market structure may look attractive while future path uncertainty remains uncomfortable.
That disagreement is useful information.
What Risk Simulation Does Not Do
Risk Simulation does not:
- predict an exact future path;
- guarantee Expected Return;
- establish a maximum possible loss;
- guarantee losses remain inside VaR or CVaR;
- remove model risk;
- replace trend, timing, persistence, or macro analysis.
TradingSimuLab also does not expose its proprietary internal simulation configuration or model assumptions.
The user-facing purpose is risk interpretation, not model replication.
Frequently Asked Questions
What is Monte Carlo risk simulation?
It generates many possible future paths to estimate return ranges, probability of gain, drawdown and downside risk.
What is VaR?
VaR is a downside threshold from the modeled return distribution. It is not a maximum possible loss.
What is CVaR?
CVaR measures the average severity of losses in the adverse tail beyond the VaR threshold.
What is Probability of Gain?
It is the percentage of simulated paths that finish above the starting price.
What is maximum drawdown?
It measures the largest peak-to-trough decline experienced along a path.
Can simulated losses be exceeded in real markets?
Yes. Simulation results are model-based estimates, not guaranteed limits.
Final Takeaway
Risk Simulation is designed to keep downside visible before expected upside becomes too persuasive.
The most useful sequence is:
Expected Return → Probability of Gain → Outcome Range → Drawdown → VaR → CVaR → Risk-Reward
Expected Return tells you about the center of the distribution.
Probability of Gain tells you how often paths finished positively.
Drawdown tells you how difficult the journey can become.
VaR and CVaR reveal downside and tail-loss severity.
Together, these metrics provide a much stronger picture than any one headline return.
That is the purpose of Risk Simulation:
not to predict the future perfectly, but to make uncertainty and downside risk harder to ignore.