I'm trying to predict a current value of a variable based on the its previous 10 values. I tried multiple time series approaches including ARIMA, LSTM and linear regression... None of them really performed well, so I'm starting to think that the sequence of data I have is just random and not predictable.
Please if you have any advice, let me know. Or if you know of any metrics I can compute to make sure that the sequences of data I have are not just random.
for LSTM I'm trying to use the Window Method in to do my prediction in the following link: https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/
Here's the auto-correlation plot and the plot and a part of the data sequence I'm using: