Short at 8:33, Short at 8:40, Long 8:48 and again at 9:03, now short from 9:37
Short at 8:33, Short at 8:40, Long 8:48 and again at 9:03, now short from 9:37
Actually, there is nothing stupid about this example. Over time, the only thing that matters is the statistical expectation. I have several strategies that buy under-priced convexity and the win rates per trades are as low as 10%. If your trade is positively convex you can get away with a pretty low win rate (though it feels very unpleasant at times and you want to pull the plug).I agree for 100%, but most people say then "winning rate is not important". They copy what they hear or read and think they look smart. They give examples like 90% winning rate with average 1$ profit per trade and 10% losing rate with $100 loss per trade, result in a loss. This kind of examples is stupid.
So it's not MC but re-sampling. Your inputs are not random, you just re-shuffling actual data to provide stress scenarios.I get what you are saying but a MC analysis actually assumes the same exact trades you enter in the analysis but assumes RANDOM trade wins and losses in the system. So it assumes you trade the system the same over the course of say 200 trades but it repeats that random wins vs losses 10,000 times.
Actually, there is nothing stupid about this example.
I don't agree. It is stupid as you can name any winning rate from 1% to 100%. And theoretically any of these percentages can be profitable or just the opposite. It just depends of how big the profits and losses are. So winning rate on itself says nothing.
This table shows that from 5% to 50% you always make money.
View attachment 175604
This table shows that from 5% to 50% you always lose money.
View attachment 175605
So winning rate on it's own says nothing.
And that's what you proof too with your 10% winning rate. So you did not understand my previous post.
Ok, what was the actual statement you where trying to make? I understood it as "high winning rate is the only way to go". My point (regardless of what you said) was that what really matters is the overall statistical expectation (which is not completely true either, since other risk metrics matter as much, especially in a stand-alone strategy).