The goal of AMIM is to provide an easy function to compute the rolling window AMIM following the paper of Tran & Leirvik (2019), “A simple but powerful measure of market efficiency”. Finance Research Letters, 29, pp.141-151.
Example
This is a basic example which shows you how to solve a common problem:
library(AMIM)
library(data.table)
data <- AMIM::exampledata # load the example data
AMIM <- AMIM.roll(data.table = data, identity.col = "ticker", rollWindow = 60, Date.col = "Date", return.col = "RET", min.obs = 30, max.lag = 10)
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AMIM[, .SD[(.N - 5):(.N), ], by = ticker] # show the last 5 observations for each ticker
#> ticker N Date MIM CI AMIM
#> 1: A 1 2021-07-06 0.5886046 0.6618747 -0.216695239
#> 2: A 1 2021-07-07 0.5886046 0.6618747 -0.216695239
#> 3: A 1 2021-07-08 0.5886046 0.6618747 -0.216695239
#> 4: A 1 2021-07-09 0.5886046 0.6618747 -0.216695239
#> 5: A 1 2021-07-10 0.5886046 0.6618747 -0.216695239
#> 6: A 1 2021-07-11 0.5886046 0.6618747 -0.216695239
#> 7: B 2 2021-07-06 0.7622182 0.7604725 0.007287748
#> 8: B 2 2021-07-07 0.7622182 0.7604725 0.007287748
#> 9: B 2 2021-07-08 0.7622182 0.7604725 0.007287748
#> 10: B 2 2021-07-09 0.7622182 0.7604725 0.007287748
#> 11: B 2 2021-07-10 0.7622182 0.7604725 0.007287748
#> 12: B 2 2021-07-11 0.7622182 0.7604725 0.007287748