# how to adjust very old stock price correctly

lets say that i have a file stating a stock and the price which someone paid for it and the date. for example: apple (AAPL) 422$15/11/2011. now apple have gone through many splits and possibly public offerings, or maybe increased their treasury stock numbers and any other activity which might affect the the number of stock available and the price of each stock. the problem that i have that historical data is adjusted for splits and all of the changes. and i wish to know the price that someone would pay with all the adjusting (something like 15$ in the apple example).

how can i convert that 422 dollars to the 15 dollars? i have many stocks, each one with different date and price. looking for a safe way to do those, and deviding by stock splits doesn't feel safe to me since stock splitting isn't the only option the change the price.

one idea i had is to use linear regression with x as the closing prices in the past (like 400) and y with the public adjusted data that i have (like 14.8) and use the result to convert 422 to 15. but i also can't find historical data with the 400 prices for 2011, all i find is adjusted. any idea how to convert?

• Are you asking how to adjust for corporate actions without having the corporate action data?
– will
Jan 2, 2022 at 15:29
• i ask first what kind of corporate action data do i need and how to get and adjust it. and if possible, just use linear regression without the actual data, just using the original open and close prices which i can't find. so how can i find it? Jan 2, 2022 at 15:31
• Here is a neat explanation of how historical stock price adjustments are done by one of the stock price data providers and which corporate actions they use. You can find more documents like this if you search for them on the Internet. However, it would not be possible to infer the adjustments made to a stock’s historical prices based only on the historical adjusted stock prices and figure out the historical unadjusted prices. Jan 4, 2022 at 12:18