I have 4 years of daily data. there is a decreasing trend for the data for the first 3 years but the trend increase for the 4th year. I wanted to find a fitted model using the first 3 years and then test the model for 4th year but I think I can not do so as the best fitted model shows a decreasing trend and predicts the 4th year to have lower values but the actual data shows a different trend. How can I treat these kinds of data? I can not use 4 full years as I dont have the data for the 5th year to test my model so I had to use the first 3 years as the historic data and the fourth year as the test data.
"A trend is a trend is a trend, But the question is, will it bend? Will it alter its course through some unforeseen force And come to a premature end ? - Cairncross (1969)
This is quote that I got from the book principles of forecasting by J Scott Armstrong. Following the above quote Armstrong writes:
Will the trend bend ? Some statisticians believe that the data can reveal this. In my judgement, this question can be best answered by domain knowledge. Experts often have a good knowledge of the series and what causes it to vary. - J Scott Armstrong, Principles of forecasting (2002)
Forecasting trend is very hard, unless you have domain knowledge and expertise to know on what causes trend to increase/decrease/stay the same it is going to very difficult to forecast the trend irrespective of using any algorithms.