how does arima forecasting work 
arima forecasting is achieved by plugging in time series data for the variable of interest statistical software will identify the appropriate number of lags or amount of differencing to be applied to the data and check for stationarity it will then output the results which are often interpreted similarly to that of a multiple linear regression model the bottom linethe arima model is used as a forecasting tool to predict how something will act in the future based on past performance it is used in technical analysis to predict an asset s future performance arima modeling is generally inadequate for long term forecastings such as more than six months ahead because it uses past data and parameters that are influenced by human thinking for this reason it is best used with other technical analysis tools to get a clearer picture of an asset s performance 