I'm trying to predict a time series using a model-tree (Cubist) and I'm getting a strange behavior, I think. This is a stock market data but I'm not using the raw level of the stock price but change in the trend of the stock price. I did expect the prediction accuracy to be poor but I didn't expect the forecast to be the actual values lagged. The reason I didn't expect this is that I'm not using lagged values of the dependent variable as features.
There are lot of questions here regarding the forecast just being a lag of the actual values and the remedy seems to be to not include lagged values of the dependent variable in your regression.
So my question is if it is normal to get a forecast that is just the actual values lagged even though I'm not using lags of the dependent variable as features?