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I have started trying to do some stock price forecasting, and would like to know what some accurate yet simple methods are. I've covered the basic methods (naive, seasonal naive, average, moving averages) and would like to take the next step. Any tutorials, videos, etc that would be good for beginners?

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You can try ARIMA model, which combines Auto-regressive and Moving Average model. If you also want seasonal prediction model, then you can use SARIMAX model. Both of this are easy as inbuilt libraries are available in Python and R. You can easily find some good tutorials on web.

For Python, the available library is

http://www.statsmodels.org/devel/generated/statsmodels.tsa.arima_model.ARIMA.html#statsmodels.tsa.arima_model.ARIMA

I find this website useful for learning ARIMA,

https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/

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