Why R^2 Is Low For A Good Trading Strategy
Posted: Mon Nov 04, 2019 10:43 pm
Hello,
I am reading David Aronson TSSB Manual and in the book he states(after creating a simple strategy that is profitable) - "The R^2 is extremely low, as is the rule in financial applications. In most situations, the best predictors (the most likely to result in winning trades) are in the tails of the models distribution of predictions, the most extreme large and small values."
David suggests breaking our data into percentiles. That way we can model the extremes separately, for example, what is our profit factor when our indicator is in the bottom 10% and top 90%.
I am hoping someone can take his statement one step further. How might we asses predictor variables and why do we see most of the profits in the tails? An example would also be helpful.
Thank you.
I am reading David Aronson TSSB Manual and in the book he states(after creating a simple strategy that is profitable) - "The R^2 is extremely low, as is the rule in financial applications. In most situations, the best predictors (the most likely to result in winning trades) are in the tails of the models distribution of predictions, the most extreme large and small values."
David suggests breaking our data into percentiles. That way we can model the extremes separately, for example, what is our profit factor when our indicator is in the bottom 10% and top 90%.
I am hoping someone can take his statement one step further. How might we asses predictor variables and why do we see most of the profits in the tails? An example would also be helpful.
Thank you.