I understand that a non-stationary time series have fluctuating mean and variance (and ACF) over time. In my case for stock prices, it is leaning towards having cyclic pattern rather than seasonal pattern, since we cannot determine when are the rise and fall of stocks on a fixed time period. I would like to ask what other reasons are there in forecasting asset prices, and also what adjustments can be made so that it can be forecasted?

  • $\begingroup$ A decent benchmark model for stock prices is that they are random walks. The forecast for any future period based on such a model is simply the last observed value. Normally you cannot beat such a forecast systematically. $\endgroup$ – Richard Hardy Feb 1 at 9:32

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