The accompanying data set provides the closing prices for fourstocks and the stock exchange over 12 days:

Date	A	B	C	D	Stock Exchange
9/3/10	127.37	18.34	21.03	15.51	10432.45
9/7/10	127.15	18.18	20.44	15.51	10334.67
9/8/10	124.92	17.88	20.57	15.82	10468.41
9/9/10	127.35	17.95	20.52	16.02	10498.61
9/10/10	128.37	17.82	20.42	15.98	10563.84
9/13/10	128.36	18.64	21.16	16.21	10616.07
9/14/10	128.61	18.83	21.29	16.22	10565.83
9/15/10	130.17	18.79	21.69	16.25	10627.97
9/16/10	130.34	19.16	21.76	16.36	10595.39
9/17/10	129.37	18.82	21.69	16.26	10517.99
9/20/10	130.97	19.12	21.75	16.41	10661.11
9/21/10	131.16	19.02	21.55	16.57	10687.95

With the help of the Excel Exponential Smoothing tool, I wasable to forecast each of the stock prices using simple exponentialsmoothing with a smoothing constant of 0.3 (ie, damping factor of0.7).

I was also able to calculate the Mean Absolute Deviation(MAD) of each of the stocks: MAD of Stock A = 1.32MAD of Stock B = 0.37 MAD of Stock C = 0.41 MAD of Stock D = 0.26MAD of Stock Exchange = 83.85.

The Mean Square Error (MSE) of the stocks: MSEof Stock A = 2.22, MSE of Stock B = 0.17, MSE of Stock C = 0.21,MSE of Stock D = 0.08, MSE of Stock Exchange = 7963.44.

Help me to understand the concept of Mean Absolute PercentageError (MAPE). I realize that MAPE is the averageof absolute errors divided by actual observation values. I'mwondering if this is just the MAD divided by the total observationvalues for a particular stock. For example, for Stock A, If myunderstanding is correct (which I don't think it is), theMAPE of Stock A would be 1.32 / each of the observation valuesindividually. Or, would it be [(127.15 - 127.37) / 127.15]. Or, doI need to add up all the absolute errors for Stock A and all theactual observation values for Stock A and divide the former by thelatter and then multiply by 100. As you can see, I'm confused.Please help.