I tried to get a result in regression on
LIBSVM, and I get the same problem on single feature data or multivariate data.
Suppose I try to find the price of something, and I have the data for $N$ days. I give the day ($1,2,\ldots,N-1$) price for $X$ as independent variables, and I train it with the day ($2,3,\ldots,N$) price as the dependent variable. So I try to get the next day's price always.
When I get the solution ($Y$) on test data, surely I expect the data price for the days ($2 \ldots N$ for the test data). But I realized that the $Y$ values are always seems like the X values. When comparing the solution $Y$ with $X$ values, ($1,2,\ldots,N-1$) days, results are more successful than ($2,3,\ldots,N$) days.
In other words I expect the next days values but the result is more successful on the same day again.
What is wrong with the approach?