# 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

## 1 Answer

You can do it with 6 data points. However two caveats:

1) With returns no evenly spaced apart you need some adjustments. This topic might help.

2) With only six data points you will get huge standard deviations, so almost sure your statistics will not be significant and you cannot do anything with them.