Drives price-to-book I need to control for differences in return on equity right now here’s a trick you can pullout of your statistics book i went in and opened up to my multiple great chapter and remember in multiple regression you trying to explain dependent variable of the independent variables the dependent variable i have yours price-to-book and I chose to use two independent.
variables relating to bags to try to explain the price level the first was the return on equity my hypothesis being the higher the return on equity the higher the price about MONEY and second to measure the risk in bank rather than look at the bait of the standard deviation i looked at the bank’s tier capital capital ratio see what does that measure the higher this ratio the more regulatory.
capital bank has it the safer it is so you’re again I’d expect the higher this ratio the higher the price table so I ran the regression across banks the r-squared is not back it’s not great it’s not bust’s not bad twenty-four percent but this coefficients all have the rightsizes higher return on equity companies have higher priced about higher tier capital ratio companies of higher price to bug you notice the number instead in brackets below the below the coefficients those are mighty statistic sand they’re telling me that this is a statistically significant relationship.
I can use it in a prediction i plug in the numbers for daughter into that printer that regression the tier capital ratio for dona as well the .three percent hero capital ratio of the existing return on equity i get predicted price-to-book ratio forger . you see what does that tell me given daughters return.
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