Risk Simulation Explained: VaR, CVaR, Drawdown and Monte Carlo Paths

What Risk Simulation is

Risk Simulation is the TradingSimuLab layer focused on simulated outcome ranges. It uses Monte Carlo paths to stress-test future price possibilities and highlight downside exposure.

The goal is not to guarantee a future price. The goal is to understand the risk side of the model stack before interpreting a trend, timing, or macro read too aggressively.

Main Risk Simulation KPIs

The public KPIs include expected return, expected price, probability of gain, VaR, CVaR, average max drawdown, worst max drawdown, risk-reward factor, percentile price ranges, large-move probabilities, risk regime, and confidence bands.

Expected return and expected price

Expected return is the simulation central expected outcome. Expected price converts that return estimate into a price-level reference.

Neither should be described as guaranteed. They are simulation outputs and should be compared with probability of gain, drawdown, VaR, CVaR, and the broader five-model stack.

Probability of gain

Probability of gain shows how often the simulation paths ended above the starting price. It is not the same as the probability of a guaranteed profitable trade.

A high probability of gain may still come with poor tail-loss risk if the downside outcomes are severe. That is why probability of gain should be read with CVaR and drawdown.

VaR and CVaR

Horizon VaR at 95% marks a severe simulated downside threshold. It is a risk estimate, not a maximum possible loss.

CVaR, or tail-loss risk, shows the average loss inside the worst simulated outcomes beyond VaR. This often matters more than VaR because it describes the depth of the bad tail, not only the cutoff point.

Average and worst max drawdown

Average max drawdown shows the typical worst pullback across simulation paths. Worst max drawdown shows the most severe simulated peak-to-trough path in the run.

These drawdown metrics help users understand the emotional and risk-management side of a setup. A model read can look constructive but still require caution if simulated drawdowns are large.

Risk-reward factor and confidence range

Risk-reward factor compares expected return against simulated downside risk. In the current backend standardization, it uses expected value divided by absolute CVaR when CVaR is available, otherwise absolute VaR.

The RRF confidence range shows uncertainty around that reward-to-risk estimate. A weak or negative reading keeps the setup defensive.

Percentile prices and large-move probability

The 5th percentile price is a lower scenario reference. The 95th percentile price is an upper scenario reference. Neither is a floor or target.

Probability of +20%, -20%, or large move describes how often the simulation produced major upside, downside, or large dispersion.

How to read simulation risk

Risk Simulation should be read from the downside outward. Expected return and probability of gain are useful, but VaR, CVaR, drawdown, and scenario range explain how much stress the setup may carry if the path goes wrong.

A balanced risk read usually needs more than a positive expected return. It should also show tolerable tail-loss risk, reasonable drawdown behavior, and a risk-reward factor that does not fight the rest of the model stack.

Common Risk Simulation misreadings

The most dangerous mistake is treating VaR as the maximum possible loss. VaR marks a severe simulated downside threshold, but outcomes beyond that threshold can still be worse. CVaR helps describe that deeper tail.

Another mistake is focusing only on probability of gain. A setup can have many small positive simulated outcomes and still have a poor tail if the losing paths are severe.

Percentile prices are also often misread as targets. They are scenario references from the simulation distribution, not forecasts that price must reach.

How it appears in daily model reads

In daily TradingSimuLab articles, Risk Simulation often decides how aggressive or cautious the final tone should be. It can confirm that the reward-to-risk profile supports the setup, or it can keep the read defensive even when trend and macro look constructive.

A constructive daily read might say that simulated downside is manageable relative to expected return. A cautious read might say that tail-loss risk, drawdown, or wide scenario bands make the setup less clean.

This helps readers understand risk without exposing the private simulation configuration behind the tool.

Example interpretation scenarios

Positive expected return, poor tail risk: A simulation can show a constructive average outcome while CVaR remains unattractive. That means the center of the distribution looks useful, but the bad tail is still too severe to ignore.

High probability of gain, weak risk-reward: Many small positive paths can coexist with a few large downside paths. This is why the article should compare probability of gain with VaR, CVaR, drawdown, and risk-reward factor.

Wide percentile range: If the 5th and 95th percentile outcomes are far apart, the model is showing high dispersion. That can make the setup harder to interpret even when the expected outcome is positive.

Trend support, defensive simulation: A strong Trend Detector read can still be held back by simulated downside. In daily content, this is one of the clearest ways to show that TradingSimuLab values risk context, not just upside narratives.

Risk interpretation checklist

Risk Simulation is strongest when readers compare central outcomes with tail outcomes. That prevents the article from focusing only on expected return while ignoring downside quality.

• Expected outcome: Is expected return positive, negative, or too small to matter?
• Probability balance: Does probability of gain support the setup, or is it mixed?
• Tail risk: Are VaR and CVaR mild enough for the setup, or do they create a defensive read?
• Drawdown: Do average and worst max drawdown suggest tolerable stress or a difficult path?
• Scenario range: Are percentile prices tight and useful, or wide enough to signal uncertainty?

This gives the page a practical educational role without publishing the internal Monte Carlo configuration or proprietary simulation assumptions.

How it fits the five-model framework

Risk Simulation is often the main counterweight in a daily read. Even when trend, persistence, timing, or macro are constructive, simulated downside and tail-loss metrics can keep the final interpretation cautious.

A useful five-model read explains whether risk supports the setup or keeps it defensive.

FAQ

Is VaR the maximum possible loss?

No. VaR is a severe simulated downside threshold, not a maximum possible loss.

Why is CVaR important?

CVaR shows the average loss inside the worst simulated tail, which can be more informative than a single threshold.

Can Risk Simulation guarantee future outcomes?

No. It stress-tests possible paths and downside exposure, but it cannot guarantee future returns or losses.

Can probability of gain be high while risk is still unattractive?

Yes. If the downside tail or drawdown is severe, a high probability of gain can still come with poor overall risk quality.

Why does TradingSimuLab not publish the exact simulation settings?

The public page explains how to read the risk outputs. The exact simulation configuration and model implementation remain private.