Dear all, I saw a lot of backtest of last 5 or even more years. And many of them are doing well years before but not so well this year.

In my test, I used 18 month to train (6 month for a WFT loop), and rencent 2 month as out of sample test. The result is better than train 5 years (1 year for a WFT loop), and it passed the reality check.
The problem is, the optimized parameter only work for latest months. And it will fail for data from 2 years ago.

So based on above test result, and since this year's data pattern changed a lot:
1. Is it a good idea to only use 1-2 years data to train and only latest 2 month to test?
2. Is it a good idea to retrain monthly to include latest data patterns?