I have been trading for multiple years now with mixed success. I have taken the time to educated myself on different strategies and have found trading index options to be the most comfortable market for me. I would consider myself fairly educated on relating (retail) topics with the exception of some of the more complex topics like options pricing models and some topics in financial mathematics. Now, with my limited knowledge of coding and backtesting capabilities I have tried my best to find a system that will yield a positive expectancy over long term. This system has been working for me in the short term, but I imagine it is what I don't know about probabilities and options pricing that will end up biting me in the a**. Im looking for somebody with a high knowledge level of mathematics/probabilities to give me more of a mathematical answer.
So here is my questions; my system in simple terms, uses daily support and resistance levels to find high prob setups, and a favorable risk reward in order to yield a positive expectancy over many trades. So just using a mean reversion strategy for example; after a decline, I might look for a reversion to the mean, and ALWAYS have a risk reward ratio of 1:2. If my stop is $1 away, my profit target is $2 away. I do not close my trade until one of those levels are hit (stop or sell limit). The most important part of my strategy, is that once the trade is open, I do not close it manually. Either a stop or profit target is hit, and once it happens I am out.
Using this logic, if I can achieve a prob of success of 50%, over 100 trades I should make 50 x $2 = $100, and lose 50 x $1 = $50 for a net gain of $50. Now I know this sounds great to me, but I understand there might be something deeper I am missing, so I am looking for some members with very advanced knowledge of mathematics/probabilities and stock/options pricing to fill me in about what I might be missing. The first thing that comes to mind, is that since my target price is twice as far away as my stop loss, I will have a higher prob of being stopped out more often. BUT, by using moving averages, BB, or other types of support/resistance, I am actually able to predict intra day movements in indices with decent precision.
My question is essentially; Will these predictions be enough to combat the difference in prob of getting stopped out vs prob of hitting profit target? Are stocks and options priced to have a zero expectancy even when using psychological levels of support and resistance, regardless of how well you can predict reversals? Is what I am doing in essence like selling options, where your prob of success might be higher but you will eventually have a zero expectancy? Or does predicting reversals in price action give me an actual EDGE.
Part of me almost thinks of it as scalping, where predicting short term movement seems easier to do, but a few losses end up wiping out your gains for a zero expectancy. But then my risk/reward ratio tells me otherwise. Is anyone able to answer these questions mathematically?
Sorry for the long post.
Thanks in advance.
So here is my questions; my system in simple terms, uses daily support and resistance levels to find high prob setups, and a favorable risk reward in order to yield a positive expectancy over many trades. So just using a mean reversion strategy for example; after a decline, I might look for a reversion to the mean, and ALWAYS have a risk reward ratio of 1:2. If my stop is $1 away, my profit target is $2 away. I do not close my trade until one of those levels are hit (stop or sell limit). The most important part of my strategy, is that once the trade is open, I do not close it manually. Either a stop or profit target is hit, and once it happens I am out.
Using this logic, if I can achieve a prob of success of 50%, over 100 trades I should make 50 x $2 = $100, and lose 50 x $1 = $50 for a net gain of $50. Now I know this sounds great to me, but I understand there might be something deeper I am missing, so I am looking for some members with very advanced knowledge of mathematics/probabilities and stock/options pricing to fill me in about what I might be missing. The first thing that comes to mind, is that since my target price is twice as far away as my stop loss, I will have a higher prob of being stopped out more often. BUT, by using moving averages, BB, or other types of support/resistance, I am actually able to predict intra day movements in indices with decent precision.
My question is essentially; Will these predictions be enough to combat the difference in prob of getting stopped out vs prob of hitting profit target? Are stocks and options priced to have a zero expectancy even when using psychological levels of support and resistance, regardless of how well you can predict reversals? Is what I am doing in essence like selling options, where your prob of success might be higher but you will eventually have a zero expectancy? Or does predicting reversals in price action give me an actual EDGE.
Part of me almost thinks of it as scalping, where predicting short term movement seems easier to do, but a few losses end up wiping out your gains for a zero expectancy. But then my risk/reward ratio tells me otherwise. Is anyone able to answer these questions mathematically?
Sorry for the long post.
Thanks in advance.
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Do you have any recommendations for running the exact numbers?