# Value of alpha and beta in Holt's exponential smoothing method

How to choose the best values of alpha and beta in Holt's exponential smoothing? Leaving it upon R gives me $\alpha$ =1. Is this appropriate?

Entering different values of alpha and then comparing with the real data shows best result for $\alpha$ = 0.45. But then R calculates $\beta$=0.99. Is this fine?

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Values of $\alpha$ and $\beta$ close to one suggest the model is mis-specified.

Try using the ets() function in the forecast package instead. It will choose the model for you, and select the best values of the smoothing parameters.

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Used ets(). There is a slight improvement. Alpha=0.9999 while beta is close to 0.02. I am using daily data for one year for short-term forecasting. using six month data gives alpha=0.9996 with beta in the same range. –  Leo Nov 12 '12 at 6:29
I think a value of alpha close to 1 means estimates are based on the recent observations while small beta implies that trend is not changing a lot. Correct me if I am wrong. –  Leo Nov 12 '12 at 8:56