I hope this is an appropriate question for this forum... for me it is an obvious query since it intrigues me for a long time.
Ok, assume there are 2 distinct classes of models: econometric (AR, MA, ARIMA, ARCH, GARCH, EGARCH, TGARCH, ...) and neural networks (MLP, RBF, BPTT, TDNN, Elman, NARX, ..., I'm putting even SVM and SVR into this group).
I know it is a broad subject - depends on the market, assets, for a start... but under what conditions one is better than the other? Is there a general consensus over this? In terms of MSE, R2, accuracy and so on? Is it fare to compare them? Does it make sense?
I've seen many studies doing this kind of comparison, here is an example (sorry for this being biased towards one side). But none summarizing previous conclusions on this topic.
Finally, what is your experience with both of them? Do you have other articles running this kind of test (even if not published)?
Thanks in advance, DBS.