Monte Carlo Trading Simulation: How Traders Can Measure Risk, Ruin, and Time to Profit

Until now, we’ve mostly been thinking in terms of how much we can make — and only in a straight line. But in the real world — and in any Monte Carlo trading simulation — it’s never a straight line. And one of the most important jobs of a trader is to be prepared for negative curves.

These negative curves are what we call drawdowns — and in a trading simulation, they’re what determine your emotional and financial limits. If drawdowns go too deep, they can drain an account to zero — what we call ruin.

Some traders accept a degree of risk of ruin. Some don’t. Both are right — as long as they follow what they’ve calculated and are prepared for it.

Traders who accept a higher risk of ruin may reach their financial targets faster than those who don’t. But how much faster, and is it worth it — that’s for each trader to check and decide for themselves.

Thanks to ClockTrades’ Monte Carlo Trading Simulation tool —  Trading Strategy Performance Visualizer — we can explore four deeply human concepts hiding inside the math:

• Risk of Ruin

• Realistic Drawdowns

• Realistic Expected Returns

• Time to Target

These aren’t abstract ideas. They are the lived experience of any trader who puts money on the line.

With this Monte Carlo trading simulation, we can stress-test our system and obtain realistic performance metrics.

☠️ Risk of Ruin in Monte Carlo Trading Simulations

This is the dark side of compounding risk — the flipside of the growth simulations we explored in How Compound Interest Builds Trading Wealth Over Time . This is the part that hurts to understand. The part no one shows when they share a smooth equity curve.

Even a beautiful system with solid expectancy can blow up — if the position sizing is too aggressive. The math is unforgiving: the higher the risk per trade, the faster you may grow… or crash.

We discovered expected value in previous issues:

• Expected Value in Trading: Measuring Your Strategy’s Real Potential 

• Exploring Expected Value: The Psychology and Math of Big Wins vs. Frequent Wins 

Let’s work with our base system using the ClockTrades Monte Carlo Trading Simulator — Performance Visualizer. Input:

• Win-rate: 40%

• R-multiple: 2R

• Risk per trade: Full Kelly compounded Periodically

Run the simulation and observe how often your equity goes near zero.

With a Full Kelly, our results yielded that there is 19% chance of blowing out the account.

Now reduce the risk to Half-Kelly. Please run the Monte Carlo simulation now.

What’s the difference in the Risk of Ruin result? How does the result feel?

If you run the simulations, you might be quite surprised with what you see.

That is risk of ruin in motion. It’s not just a formula — it’s a feeling that comes alive in any realistic trading simulation.

What risk of ruin can you accept? Is 5% acceptable? Or is it 0% or nothing?

There’s nothing wrong with being cautious — it just means adjusting your expectations for returns and time to target. That’s the point: creating a mechanism that works for you.

And if you’re unsure what you can handle — you’ll learn by experience.

📉 Drawdown Simulator: What the Math Feels Like

This is the heart of it all.

What you really experience as a trader are constant fluctuations — on both your trades and your portfolio balance. The main job is to KEEP GOING, no matter what.

A trader loses only when they stop doing what provides their edge.

Drawdowns can be scary. That’s why adjusting position sizing to your emotional and financial comfort level is essential.

Once you find a tolerable level of risk of ruin, the next step is to simulate and study the drawdowns using a Monte Carlo-based drawdown simulator.

When R and win-rate are fixed, and risk is acceptable, the next question is: Are the drawdowns tolerable?

We will go along with the simulation of 2R, 40% win-rate system and Half-Kelly periodically compounded system.

Drawdowns can be still quite significant. There is a big chance on suffering 50-80% drawdown at any point in time.

If not ready for that, think of mitigating it or reduce your position size further — until the outcome feels realistic and sustainable.

The comfort of staying in the game must prevent one of the worst outcomes: quitting before your winners arrive.

📊 Expected Returns in Trading Simulations (And How to Stay Realistic)

With a risk profile and drawdown tolerance in place, a trader can finally build realistic expectations.

If the system performs, on average, with the calculated expectancy, your main focus becomes staying the course. Some months may perform better, others worse — but neither should come as a surprise.

The goal is to maintain discipline and take action only when truly necessary.

If your realistic expected return is much lower than you first imagined — good! It means your expectations are now based on reality, not hope.

Unrealistic expectations are a highway to burnout.

Math comes first. Performance comes second.

The result is a mechanism where math and performance work together.

With realistic expectations, you can begin planning for withdrawals or financial goals — and test those scenarios in the tool.

For our base system (2R, 40%, Half-Kelly adjusted periodically) in 10 cycles (years) the end balance of 76 out of 100 simulations hit the one million $ mark.

The average Return Per Period yielded 11408.1$.

I don’t know how about you but for me, it’s quite impressive.

All comes with a cost - willingness to suffering through quite large drawdowns, but without statistical risk of ruin.

⏳ Monte Carlo Time to Target: How Long Does It Really Take?

Everyone wants to know: How long will it take to hit your target? That’s exactly what Monte Carlo time-to-target simulations are for.

But markets don’t move in straight lines. And the number of trades you take, your win-rate, and your position size all stretch or compress the timeline.

Notice: more trades shorten the journey. More risk may shorten it too much — in the wrong direction.

Most people want the fastest road. But sometimes, the fastest road is also the most dangerous.

And most importantly — it’s often unnecessary.

Does it really matter if building wealth takes a little longer?

All of trading, investing, and business is about executing now — but waiting for the fruits until tomorrow.

And does it really matter if today lasts a little longer, if tomorrow is bright, clear, and full of promise?

In our simulation, our base system reached from one thousand to one million dollars in 76% of cases in maximum 10 years. The odds of success are quite significant!

Performance Visualiser from Clocktrades provides also information about distribution of time span in Cycles and Periods, so you know when approximately system can reach the targets.

💡 Lesson from the Monte Carlo Trading Simulator

If a trader designs a system without accounting for ruin, time, or drawdowns — they’re designing a fantasy.

The real preparation is building a machine that works with real life.

What the app shows you isn’t just numbers — it’s character.

It’s patience.

It’s resilience.

What correlations do you notice?

Does waiting slightly longer for results feel like a waste of time?

Or does it bring comfort — the security of a result you know will come?

What are your thoughts, trader?

Put them in your notebook — or share them in the comments!

🏁 Ending the Monte Carlo Journey — Without Ruin

Ruin isn’t just about blowing up an account.

It can also mean:

• Burning out

• Losing faith

• Quitting after a bad run

The hidden lesson is this:

You don’t win by being right all the time.

You win by staying in the game long enough to let your edge work.

If you’re just beginning this journey with us and enjoyed this issue, you might want to start with the Why I Write This (and for Whom) — or jump straight into the Expected Value in Trading: Measuring Your Strategy’s Real Potential where we break down the key concepts behind the tools we explore here.

Until next time,

Kamil — Markets & Manners