I am building a machine learning model using historical prices and I am using data from yahoo finance. Currently yahoo finance data have two close prices one normal close price(close) and other adjusted close price(Adj close). My question is which close price should I take for teaching my ML model. Is there any (dis)advantage of using adjusted close price instead of close price?
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2 Answers
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You should use Adj close price
Using Adj close price gives you the adjusted values of close price, hence the fair picture in case of off-beat events like splits and dividends. Using close price instead of adj close price provides unrealistic and false values of metrics like returns, which could generate false signals in your ML model.
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Hmm I don't know if I agree that the adjusted price should be used. On the one hand the adjusted prices do help to avoid the impact of corporate actions like stock splits.
On the other hand using the adjusted price incorporates dividends into the price and that will cause a unpredictable shock to price. Lets take an example: you are making a prediction on each days move. On the 4th day a dividend is payed and there are capital gains. Your model wont be able to account for the dividend.
I think the best thing to do is to take the raw data, adjusted it for corporate actions, and not include dividend payments in the price.
