ARIMA (auto.arima in R) forecasts 0 for high variance and large time series

Question

I'm noticing an issue with using auto.arima in R where if I input a series with large values and high variance, the forecast simply returns 0. Is this because the hyperparameters chosen are wrong? For example, see the simple example below:

library(forecast)

my_time_series = c(
  234829874, 
  293481040534,
  4087598324,
  20394823094324,
  234832948234,
  2034982034,
  2304984,
  2039483029481,
  20349812044,
  2034982094814
)
forecast(auto.arima(my_time_series))

>>>
  Point Forecast         Lo 80        Hi 80         Lo 95        Hi 95
11              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
12              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
13              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
14              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
15              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
16              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
17              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
18              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
19              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13
20              0 -8.348708e+12 8.348708e+12 -1.276825e+13 1.276825e+13

Why is this and how do I fix this? For example, in this fictional time series, I would have expected at least ARIMA to basically output the mean, but I don't understand why it's forecasting 0.