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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?

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