Micholien

".....its just the way the math works out to be in statistics."

Sorry, studying hard right now (procrastinator) or I would expand on this topic a lot more. Implicit in the calculation above is the a priori equal weighting of each year in contribution to the sample or population covariance. 5 data points of equal value, so in a popluation sense, each contributes 1/5 to the covariance (this is not mathematically rigorous but it will do). Since you can factor out 1/5 from each term, the sum of pairs of products becomes the product of a scalar with a sum. In Portfolio Theory, returns are assigned a probability (and thereby a weighting towards the covariance - again not rigorous, really a joint probability functoin P(x,y) which simplifies in our case to the weights), since the probability weights (all less than or equal to 1) are multiplied by each corresponding return rather than factored out, there is no scalar fraction that divides the resulting sum - it has already been distributed among the addends. And just like in the first example, the sum of the weights = 1 (this is mandated by a bigger topic about probability measures having p(omega) = 1 where omega is the probability space - i think this was briefly discussed in book.) This a rather crude explanation but I hope it helps. Best of luck to you on Saturday.