After months of beating my head against the wall, I#8217;m giving up and asking for assistance. My guess is that somebody here (twoblink maybe?) Knows exactly how to solve the problem that I need an answer to.

I#8217;m trying to work out the mathematically expected maximum drawdown of the system. I have the stats derived from a statistically significant sample size, but that I can#8217;t work out how to convert that into a distribution of drawdown chances. Running thousands of Monte Carlo simulations, I have a general idea about what I#8217;m considering, but I had been hoping to get some concrete numbers like:

· X% chance of a whole drawdown of 10 percent over x transactions
· Xpercent chance of a entire drawdown of 25% over x transactions
· Xpercent chance of a entire drawdown of 50% over x transactions
· Xpercent chance of a entire drawdown of 100% over x transactions

I'd ultimately like to build a distribution curve incorporating the information, which I suppose is an entirely different issue, however I could #8217;t tackle it until I purchase the raw calculations to generate it. So the ask that is shortened is how do I compute the mathematically expected drawdown for any particular system?

For a side project, I would also like to work out how to calculate the percentage opportunity for any particular number consecutive losses to happen based on a proven win rate. We've got the following chart, which can be cool, but I'd love to comprehend the calculation. Does anyone know what calculations are used to generate this table?

Http://www.thetechdepartment.com/drawdown.gif

When the calculations are too complex or you just don#8217;t want to be bothered trying to describe it, even pointing me in the direction of what I need to research would be very much valued. Thanks in advance for your help.

NOTE:// I am mainly looking for the real world calculations. Something like plug x variables into a calculator and hit the X key or an excel formula to perform it. I get the impression it is going to be very abstract and or tedious to explain, although the theory behind it could be excellent.
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