Has anyone attempted time series prediction using support vector regression?
I understand support vector machines and partially understand support vector regression, but I don't understand how they can be used to model time series, especially multivariate time series.
I've tried to read a few papers, but they are too high level. Can anyone explain in lay terms how they would work, especially in relation to multivariate time series?
Thanks in advance.
EDIT:To elaborate a bit, let me try to explain with a stock price example.
Say we have stock prices for N days. Then, for each day we could construct a feature vector, which, in a simple case, could be be the previous day's price and the current day's price. The response for each feature vector would be the next day's price. Thus, given yesterday's price and today's price the objective would be to predict the next days price. What I don't understand is, say we have six months training data, how would you give greater emphasis to the more recent feature vectors?