Performance and functionality of the DAX formula

Good afternoon, I have the following problem.

I have the following data model

The Price List table is a table with approximately 12 million records, since they are sku codes and dates, while the SKC IPC table has a subset of codes that want to evaluate the evolution of prices over time.

For this I made the following table (as a visualization)

The last 2 forimulas what they are looking for is the variation of the column Price LP respcto of the previous one, is constructed in the following way:

Variation (%) Prices =

where _pre=

CALCULATE(

.MAX('Price Lists'[fecha_creacion_lp]),

FILTER(ALL('Price Lists'),

'Price Lists'[Key 1] =MIN('Price Lists'[Key 1]) &&

'Price Lists'[fecha_creacion_lp]<MIN('Price Lists'[fecha_creacion_lp])

)

)

where _preRES=

CALCULATE(

.MAX('Price Lists'[LP Price]),

FILTER(

ALL('Price Lists'),'Price Lists'[Key 1]=MIN('Price Lists'[Key 1]) &&

'Price Lists'[fecha_creacion_lp]=_pre))

return

IF(

ISBLANK( _preRES),

BLANK(),

DIVIDE( MIN('Price Lists'[LP Price]),_preRES)-1)

The results are correct, as seen in the resulting table, however when adding these two 2 measures the performance is significantly slower, either when filtering something, when expanding or contracting the visualization etc. and the second problem I present is that when you collapse the table, the results are wrong.

Then I would like help in 2 topics (sorted by priority)

1.- Improve the performance of the measure created
2.- Correct the measure so that when grouping / contracting the visualization correctly calculates the variation in $ and %

From already thank you very much!