# how can I make ARIMA more robust to outliers?

I have a very noisy time series like this and I forcast future values with auto.arima from the forecast package in R:

set.seed(123)
y <- diffinv(rnorm(100))

plot(forecast(auto.arima(ts(y))))


I am quite happy with this forecast. However, in my data, sometimes extreme outliers can happen, for example:

y[100] <- -10

plot(forecast(auto.arima(ts(y))))


These completely destroy my forecast. How can I make it so that ARIMA is robust to those outliers or would I have to detect and remove these outliers separetly?