The Option Profit Calculator estimates
- the percentage of success
- the average, median and standard deviation of the net result of your options positions
And all this at the exit date.
Data input
- Choose the stock on which you want to create the option strategy.
- Pick the options according to the logics of your strategy.
- Fill out the data in the cells in light yellow of the Dashboard.
- “Vol” is the current volatility of the stock, reported in the various web sites together with the quotes of the options; the file uses the “Vol” to calculate the value of the Implied Volatility (“IV”).
- You can find the current Volatility values in many websites, where you can also check the values of the highest and lowest of the recent period. Knowing the values of the current volatility “Vol” and those of the implied volatility (IV), you can set the mininum and maximum volatility and fill out the boxes Min Vol and Max Vol accordingly.
- Section “Entries“. The legs “Adj” are to be filled out only in case of adjustments being made to the options strategy.
- When a leg is closed, remember to classify the line as “C” in the “Open/Closed” column, and to manually book the closing price.
Data output
When all the data input is done, it is time to run the calculations: menu “Formulas”, command “Recalculate now“, and you can see the results in the “Probabilities & Results” box:
- the probability of success (%)
- the average, the median and the standard deviation of the profit or loss of the whole strategy, inclusive of all legs involved ($)
Simulating Option Strategies with Monte Carlo Analysis
Options trading is full of uncertainty. A strategy that looks good on paper can unravel the moment markets behave differently than expected. To deal with this, traders often turn to simulations that model thousands of possible future outcomes.
One powerful method for this is Monte Carlo analysis.
Monte Carlo simulation offers a practical way to estimate profits in options trading by running a large number of simulated price scenarios.
Instead of relying on a single “best guess” of the market, it creates a probability distribution of possible outcomes. This allows investors to estimate not just the average expected return, but also the likelihood of extreme gains or losses.
The method is particularly useful when strategies involve complex instruments, like options, where traditional models fail.
Profit potential is assessed by calculating the payoffs across many simulated price paths, and summarizing the results as expected profit, risk ranges, and worst-case scenarios.
The strength of the approach lies in its flexibility: it can handle any payoff structure.
Its weakness is that the results are only as reliable as the input assumptions about volatility, correlations, and interest rates.
Still, for decision-makers, Monte Carlo outputs provide a risk-adjusted perspective on profit potential that is far more realistic than relying on a single forecast.
I have developed an Excel-based tool that uses Monte Carlo simulations to evaluate the performance of various option strategies, including call and put spreads, iron condors, butterflies, strangles, straddles, Christmas trees, skip-strikes and 1-to-2 ratio spreads.
The idea is simple: instead of relying on a single forecast for the underlying asset, the tool generates over 20,000 random calculation for three different scenarios. Each scenario represents a possible market path, and the results of the strategy are calculated under those conditions.
This approach allows traders to see a wide range of possible outcomes—profits, losses, and everything in between. It highlights not just the “expected” payoff, but also the risk of extreme events, which are easy to ignore when looking only at static payoff diagrams.
By running thousands of random simulations, the tool builds a distribution of potential results, offering a clearer picture of both the strategy’s strengths and its vulnerabilities.
Why Monte Carlo is valuable for options:
- It accounts for randomness in price movements, rather than assuming a single outcome.
- It reveals the probability of different profit and loss levels.
- It helps traders compare strategies not just on average return, but also on risk profile.
- It provides insight into how strategies might perform in volatile or unusual markets.
In short, Monte Carlo simulation doesn’t predict the future, it acknowledges uncertainty and measures how a strategy could behave across thousands of possible futures.
For options traders, that shift in perspective can mean the difference between relying on neat theoretical payoffs and actually preparing for the messy reality of markets.
How all this is calculated
These calculations are performed using a special version of the Montecarlo theory.
To estimate the “Probabilities & Results”, the file generates sixty thousand calculations through sixty thousand different casual prices of the underline stock within the minimum and maximum price calculated according to the volatilty of the stock.
Within the logics of your Option strategy, you have the possibilty to compare different underlying stocks, different strike prices, different expiry dates, and then to pick the best for your strategy.
What the Options Profit Calculator does not give you
Remember: this file does not predict the movement of the stock nor the movement of the stock options.
Purchase the Options Profit Probability Calculator
You can buy the Option Profit Probability Calculator for a group of options strategies or all together.