Risk of Ruin — How It Is Calculated
The Pillinger Trader UI Risk of Ruin analysis uses Monte Carlo simulation to estimate the probability that a simulated equity path reaches a defined loss threshold within a selected number of future trades.
The calculation is based on the trader’s actual historical closed trades rather than on a theoretical win rate or a simplified Risk of Ruin formula.
1. What data is used?
The calculation starts by determining the starting equity of the analyzed period.
For each closed trade, the system then calculates its historical trade return relative to that starting equity:
Trade Return = Trade P&L / Starting Equity
For example, if:
- Starting Equity = 1,000,000 HUF
- Trade P&L = +20,000 HUF
the historical trade return is:
+2.0%
If another trade produced:
- Trade P&L = −15,000 HUF
its historical trade return is:
−1.5%
The Monte Carlo model therefore works with the historical trade-return distribution, rather than simply treating all trades as identical wins or losses.
2. What happens during a Monte Carlo simulation?
Pillinger Trader UI performs 10,000 independent simulations.
Each simulation starts with an equity level of 100%.
The system then randomly selects trade returns from the historical trade-return dataset and applies them sequentially to create a possible future equity path.
For example, one simulated path might contain:
+2.1% → −1.4% → +0.7% → −3.2% → +4.0% → ...
Another simulation may use a completely different sequence from exactly the same historical dataset:
−3.2% → +0.7% → −0.8% → +2.1% → −1.4% → ...
The historical trades therefore provide the observed distribution of outcomes, while Monte Carlo randomization creates many different possible sequences of those outcomes.
This allows the system to examine how frequently a defined loss threshold would be reached under many different possible trade sequences.
3. What is the Ruin Threshold?
The Ruin Threshold defines the maximum equity decline that counts as a ruin event for the simulation.
The available thresholds are:
- −10%
- −20%
- −30%
- −50%
- −100%
For example, with a −20% threshold:
- Starting equity = 100%
- Ruin threshold = 80%
If a simulated equity path reaches or crosses 80%, that simulation is classified as having experienced a ruin event.
Importantly, the simulation remains a ruin event even if the path would subsequently recover.
For example:
100% → 93% → 86% → 79% → 95% → 110%
is still counted as a ruin event for a −20% threshold because the equity reached 79%, which is below the 80% threshold.
In the chart, the ruined path is stopped at the selected threshold rather than being allowed to continue below it.
4. How is Risk of Ruin calculated?
After all 10,000 simulations have been completed, the system counts how many simulations reached the selected Ruin Threshold.
For example:
- Total simulations: 10,000
- Simulations reaching the threshold: 6,114
- Simulations surviving the entire horizon: 3,886
The Risk of Ruin is therefore:
Risk of Ruin = Ruined Simulations / Total Simulations
In this example:
6,114 / 10,000 = 61.14%
The complementary value is the Survival Probability:
Survival Probability = 100% − Risk of Ruin
Therefore:
100% − 61.14% = 38.86%
The two values always add up to 100%.
5. What does the Trade Horizon mean?
The Trade Horizon determines how many future simulated trades are considered in the analysis.
The available horizons are:
- 100 trades
- 250 trades
- 500 trades
- 1,000 trades
For example:
−20% / 500 trades
means:
The system estimates the probability that a simulated equity path will reach or cross a 20% loss at least once during the first 500 simulated trades.
This is an important part of the interpretation because Risk of Ruin is not a single universal percentage.
The result always depends on both:
Ruin Threshold + Trade Horizon
A −20% threshold over 100 trades is therefore a different question from a −20% threshold over 1,000 trades.
6. Portfolio and Strategy analysis
Risk of Ruin can be analyzed at two levels.
Portfolio
The Portfolio calculation uses the historical closed trades included in the overall analysis.
The complete historical trade-return distribution is used as the source for the Monte Carlo resampling.
The result therefore answers the question:
Based on the observed historical trade-return distribution, how frequently would simulated portfolio equity reach the selected loss threshold within the selected number of trades?
Strategy
The Strategy calculation uses only the closed trades belonging to the selected strategy.
The same Monte Carlo methodology is then applied to that strategy-specific trade-return distribution.
This allows the trader to examine whether different strategies produce different simulated probabilities of reaching the selected loss threshold.
A minimum of 30 historical trades is required for a strategy-level Monte Carlo calculation. If fewer than 30 trades are available, the system displays Insufficient sample rather than producing a potentially misleading percentage from a very small sample.
7. What does the Monte Carlo chart show?
The Risk of Ruin chart is a Monte Carlo equity-path visualization, sometimes referred to as a spaghetti chart.
The calculation runs 10,000 simulations, but displaying all 10,000 paths would make the chart unreadable. The chart therefore displays a representative subset of the simulated paths.
The chart uses:
- 100% as the starting equity level;
- grey paths for simulations that remain above the Ruin Threshold;
- red paths for simulations that reach the Ruin Threshold;
- a red dashed horizontal line representing the selected Ruin Threshold;
- the selected Trade Horizon as the simulation endpoint.
The chart is therefore a visual representation of the Monte Carlo process, rather than the source of the Risk of Ruin percentage itself.
The Risk of Ruin percentage is calculated from all 10,000 simulations, not from the number of paths visually displayed on the chart.
8. What does a Ruin event actually mean?
A ruin event does not necessarily mean that the trader’s account has literally gone bankrupt.
The word “Ruin” refers to the user-selected loss threshold.
For example:
−10%
means reaching a 10% equity decline.
−20%
means reaching a 20% equity decline.
−50%
means reaching a 50% equity decline.
−100%
represents complete loss of the starting equity.
Therefore, when Risk of Ruin shows:
Risk of Ruin = 25%
with:
Ruin Threshold = −20%
Trade Horizon = 500
this means that approximately 25% of the Monte Carlo simulations reached a 20% equity loss at some point during the first 500 simulated trades.
It does not mean that the trader has a 25% guaranteed probability of permanently losing 20% of their account in real trading.
9. Why does Pillinger Trader UI use historical trade outcomes?
Traditional Risk of Ruin calculations can use simplified assumptions such as:
- win rate;
- loss rate;
- fixed risk per trade;
- fixed win/loss ratios.
Those approaches can be useful under the assumptions they require, but they simplify the actual distribution of trading results.
Pillinger Trader UI instead uses the trader’s observed historical trade-return distribution.
This means the Monte Carlo sample can contain the actual variation present in the historical results:
- smaller winning trades;
- larger winning trades;
- smaller losing trades;
- larger losing trades.
The model does not reduce the trader’s history to a simple statement such as:
“The strategy wins 75% of the time.”
Instead, it asks:
What happens if the observed historical trade-return distribution occurs again in many different random sequences?
This makes the analysis directly connected to the trader’s recorded trading history.
10. Why can the Risk of Ruin value change between calculations?
The Monte Carlo simulation uses random resampling.
Therefore, even when the following settings remain unchanged:
- same historical trades;
- 10,000 simulations;
- same Ruin Threshold;
- same Trade Horizon;
two separate Monte Carlo runs can produce slightly different estimates.
For example, one run might produce:
61.14%
while another might produce:
60.87%
and another:
61.32%
This variation is a normal characteristic of Monte Carlo estimation.
The purpose of the simulation is not to produce a mathematically fixed number from a deterministic formula. Its purpose is to estimate a probability by repeatedly sampling possible outcomes.
For this reason, Pillinger Trader UI intentionally uses fresh random sampling rather than forcing a deterministic result through a fixed random seed.
11. What the Risk of Ruin calculation does NOT assume
The current Risk of Ruin implementation does not assume that every future trade will have:
- the same profit;
- the same loss;
- the same win rate;
- the same fixed reward/risk ratio.
It also does not attempt to predict the actual sequence of future trades.
Instead, it uses the historical trade-return distribution as the empirical basis for generating many possible future sequences.
The resulting Risk of Ruin is therefore a statistical estimate based on historical behavior, not a prediction of a specific future outcome.
12. Important limitations
Risk of Ruin is inherently dependent on the quality and representativeness of the historical data.
The calculation assumes that the historical trade-return distribution provides useful information about the range of outcomes that could occur in future trading.
The actual future distribution may change because of factors such as:
- changes in market conditions;
- changes in strategy execution;
- changes in position sizing;
- changes in trading behavior;
- changes in instruments traded;
- changes in volatility;
- changes in transaction costs or execution conditions.
Consequently, the Risk of Ruin figure should be interpreted as:
An empirical Monte Carlo estimate based on the observed historical trade-return distribution, not a guarantee or forecast of future account behavior.
13. The complete calculation in one example
Suppose a trader selects:
Ruin Threshold: −20%
Trade Horizon: 500 trades
Simulations: 10,000
The system:
- determines the starting equity;
- collects the eligible historical closed trades;
- converts each trade’s P&L into a return relative to starting equity;
- randomly resamples those historical trade returns;
- constructs 10,000 simulated equity paths;
- runs each path for up to 500 trades;
- checks each path for a −20% equity decline;
- marks a path as ruined if it reaches or crosses the threshold;
- counts all ruined paths;
- divides the number of ruined paths by 10,000.
If 6,114 simulations reach the threshold:
Risk of Ruin = 61.14%
and:
Survival Probability = 38.86%
The same process is then repeated using the trade subset belonging to an individual strategy when the user views Strategy-level Risk of Ruin.
In short
Pillinger Trader UI Risk of Ruin is an empirical Monte Carlo estimate of threshold-crossing probability.
It takes the trader’s historical trade P&L distribution, converts it into trade returns relative to the analyzed starting equity, randomly resamples those outcomes thousands of times, constructs possible future equity paths, and measures how often those paths reach the selected loss threshold within the selected trade horizon.
The result answers a specific statistical question:
“If future trade outcomes were repeatedly drawn from the observed historical trade-return distribution, how often would the simulated equity reach the selected loss threshold within the selected number of trades?”
That is what the Risk of Ruin % represents in Pillinger Trader UI.
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