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As a Co-founder of Clear Markets Ltd, I oversee operational and financial systems.
I am the Director/Owner of Excel Markets Inc. (Regulated by the US National Futures Association)
I am an NFA Associate Member with a Series 3 and 34 license.
Accomplished Broker Partnerships Manager and Customer Support Team Leader, I specialize in leveraging data-driven insights to enhance financial strategies and foster business growth, particularly within the retail sector. With a robust background as a Data Manager and Financial Analyst, my expertise lies in utilizing analytical approaches to optimize trading outcomes and investment strategies for clients.
Having previously worked with multiple CFD brokers in Cyprus, I maintain a strong commitment to staying current with industry trends. My analytical skills are pivotal in recommending tailored trading solutions that align with clients' specific needs and investor profiles.
Use this Risk of Ruin Calculator to estimate the probability of reaching a critical drawdown level and the likelihood of blowing a trading account based on win rate, risk per trade, and reward-to-risk ratio.
Risk of Ruin is one of the most overlooked concepts in trading, yet it is the main reason most traders eventually blow their accounts. Even a profitable trading strategy can fail if position sizing and risk control are not properly managed.
In leveraged markets such as forex, high win rate alone does not guarantee long-term survival. Risk of Ruin measures how likely a trading system is to reach an unrecoverable drawdown over time.
Risk of Ruin (RoR) is a probabilistic model used to estimate the likelihood that a trader will lose a significant portion of their trading capital and be unable to recover.
The Risk of Ruin Calculator uses key performance metrics — including win rate, average profit-to-loss ratio, and risk per trade — to simulate potential outcomes and assess the overall robustness of a trading system.
Enter the historical win rate percentage of your trading strategy.
Input the average profit of winning trades divided by the average loss of losing trades.
Professional traders typically risk no more than 1–2% of total account equity per trade. Higher risk per trade dramatically increases Risk of Ruin.
Enter the number of trades used for testing or simulation. More trades produce more reliable estimates.
Define the drawdown level at which you consider the account to be effectively ruined.
Click the Calculate button to view your estimated Risk of Ruin and peak-to-valley drawdown probability.
The calculator is based on a Monte Carlo simulation of 100,000 iterations, meaning results may vary slightly between calculations.
Most professional traders aim to keep Risk of Ruin below 1%, especially when trading forex or leveraged instruments.
Yes. Poor position sizing and excessive risk per trade can result in account failure even if a strategy has positive expectancy.
Leverage increases effective exposure per trade, which significantly raises the probability of large drawdowns and account ruin if risk is not carefully controlled.
Generally, at least 50–100 trades are recommended to produce meaningful and stable Risk of Ruin estimates.
This Risk of Ruin Calculator is provided for educational purposes only and does not constitute financial or investment advice. Trading forex and leveraged products involves significant risk and may not be suitable for all investors.
Most professional traders aim to keep their Risk of Ruin below 1%. A low Risk of Ruin ensures long-term survival, especially in leveraged markets like forex.
Yes. Even a strategy with positive expectancy can fail if risk per trade is too high. Poor position sizing is one of the main causes of account blow-ups.
Leverage increases a trader’s effective exposure per trade. If risk is not controlled, higher leverage can dramatically increase drawdowns and lead to a much higher Risk of Ruin.
In many cases, yes. A high win rate does not guarantee account survival. Risk of Ruin focuses on long-term capital preservation, which is more important than short-term performance.
Generally, 50–100 trades are recommended to produce stable and meaningful Risk of Ruin estimates. More data results in more reliable simulations.
