I would like to do a linear regression of daily stock price returns, vs the price as a percentage of the 52 week high.
i.e. [next week return] = A * [Price / 52 Week High ] + B
where A and B are constants.
[Price / 52 Week High] will not be normally distributed, so the previous regression will not be very valid.
How can I normalise it to make it more valid?
Is there a better way for me to see how [Price / 52 Week High] affects the future return?