# Does it make sense to interpret autocorrelation and box test on 5 data points?

I am trying to see if after I trade a stock the price movements at 2, 5, 7, 10, 30 and 60 seconds after exhibit any autocorrelation. Below I have the returns from my trade price to the trade 2,5,7,10 30 and 60 seconds after my trade.

Does it make sense to run and acf test in r to see if there is autocorrelation and the box test OR is 6 data points not enough data to run the test?

Does it also matter that my returns are not evenly spaced apart?

r<- c(.2,.3,.3,.5,1,1.1)
acf(r)
Box.test(r, lag = 1, type = c("Box-Pierce", "Ljung-Box"), fitdf = 0)


Thank you