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edit approved Aug 2, 2021 at 0:44
Peter Mortensen
edit approved Aug 2, 2021 at 0:44
Peter Mortensen
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How tocan I normalize price history between -1 and 1 while keeping the ratio of price differences to each other the same?

I want to normalize a series of numbers to all be between -1 and 1, but I would like to do it in a way where the relative difference between price elements stays the same, if possible.

Example list of price series
  price_list = np.array([4.8, 7.2, 5.0, 8.1])

I use this equation to normalize between -1 and 1.
  (2*(price_list - min(price_list)) / (max(price_list) - min(price_list)))-1
  This returns
  array([-1. , 0.45454545, -0.87878788, 1. ])

Let's take the ratio between the 0th and 1st non-normalized values.
  4.8 / 7.2 = 0.6666666666666666
  But the ratio of the 0th and 1st elements in the normalized list is -1 / 0.45454545 = -2.200000022

I would like the data normalized between -1 and 1 in a way that the ratio is also 0.6666666666666666.

How to normalize price history between -1 and 1 while keeping the ratio of price differences to each other the same?

I want to normalize a series of numbers to all be between -1 and 1 but I would like to do it in a way where the relative difference between price elements stays the same, if possible.

Example list of price series
  price_list = np.array([4.8, 7.2, 5.0, 8.1])

I use this equation to normalize between -1 and 1.
  (2*(price_list - min(price_list)) / (max(price_list) - min(price_list)))-1
  This returns
  array([-1. , 0.45454545, -0.87878788, 1. ])

Let's take the ratio between the 0th and 1st non-normalized values.
  4.8 / 7.2 = 0.6666666666666666
  But the ratio of the 0th and 1st elements in the normalized list is -1 / 0.45454545 = -2.200000022

I would like the data normalized between -1 and 1 in a way that the ratio is also 0.6666666666666666.

How can I normalize price history between -1 and 1 while keeping the ratio of price differences to each other the same?

I want to normalize a series of numbers to all be between -1 and 1, but I would like to do it in a way where the relative difference between price elements stays the same, if possible.

Example list of price series price_list = np.array([4.8, 7.2, 5.0, 8.1])

I use this equation to normalize between -1 and 1. (2*(price_list - min(price_list)) / (max(price_list) - min(price_list)))-1 This returns array([-1. , 0.45454545, -0.87878788, 1. ])

Let's take the ratio between the 0th and 1st non-normalized values. 4.8 / 7.2 = 0.6666666666666666 But the ratio of the 0th and 1st elements in the normalized list is -1 / 0.45454545 = -2.200000022

I would like the data normalized between -1 and 1 in a way that the ratio is also 0.6666666666666666.

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Renoldus
Renoldus
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How to normalize price history between -1 and 1 while keeping the ratio of price differences to each other the same?

I want to normalize a series of numbers to all be between -1 and 1 but I would like to do it in a way where the relative difference between price elements stays the same, if possible.

Example list of price series
price_list = np.array([4.8, 7.2, 5.0, 8.1])

I use this equation to normalize between -1 and 1.
(2*(price_list - min(price_list)) / (max(price_list) - min(price_list)))-1
This returns
array([-1. , 0.45454545, -0.87878788, 1. ])

Let's take the ratio between the 0th and 1st non-normalized values.
4.8 / 7.2 = 0.6666666666666666
But the ratio of the 0th and 1st elements in the normalized list is -1 / 0.45454545 = -2.200000022

I would like the data normalized between -1 and 1 in a way that the ratio is also 0.6666666666666666.