This video on time series analysis in R using the AAPL data from Yahoo Finance will show you how to use both auto arimas and custom arimas to get 4 unique models from which to look at forecast trends. We will look at the accuracy of the models and project them in RStudio over a 50 day, 100 day and 200 day time period to see the difference.

We will also look at using the ACF and PACF to determine 2 custom arima models and then use a default 1,1,1 arima model for comparison. In the end we will use the 4 arima models to see whether a buy, stay or sell signal is projected by each and what the overall prognosis is for each time period.

This will help you to quickly be able to build arima models quickly in R using RStudio and learn to forecast on any stock market symbol through Yahoo Finance. Forecasting can be a lot of fun and this video shows you exactly how to do every part of it.

To learn more about forecasting, Data Science, Data Analytics, how to predict future trends in stock prices, time series analysis and more, subscribe to our YouTube channel:    / @techknowhow4802  

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Disclaimer: This time series in r tutorial video on How to forecast AAPL with auto arima in RStudio and predict future trends is meant for learning R, data science and forecasting techniques, but does not constitute financial advice nor should it be taken as such. There are so many factors that are at work in the makeup of the value of a stock that it is highly variable and this method with arimas is for learning and should be taken in a directional, not measurable manner. However, time series forecasting is a fun and interesting way to learn data science. This is not financial advice and it is recommended that a licensed financial advisor or similar be obtained for proper financial advice. The sole purpose here is for learning quick time series analysis and forecasting.