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visualizing trade-offs between tight and wide stop and target
How would you incorporate those formulas into a linear regression of time and price to make it useful in a real world scenario?
Here is a daily chart of Nasdaq with a regression trend applied showing 2 deviations. You would need to take the coin toss scenario which you presented and somehow factor that into a joint or conditional probability calculation. The visual representation makes it easy to see where your odds lie but I'm interested to see how you would mathematically join stop/target odds with time/price probabilities.
This is still an active research area : )
Those calculations of mine were triggered by Timothy LuCarelli (ISBN: 9781626756335), with his pre-set wide stops and pre-set targets of sometimes 3pip. I wanted to quantify the downside of this method.
Cool, good work. Post when you figure it out, I think you have to use log scales to reduce it to a binary result but I haven't managed to work it out yet.
