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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.
You can install the released version of AMIM from CRAN with:
install.packages("AMIM")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 2 2021-07-06 0.7044131 0.7604725 -0.23404162
#> 2: A 2 2021-07-07 0.7044131 0.7604725 -0.23404162
#> 3: A 3 2021-07-08 0.8058670 0.8110500 -0.02743054
#> 4: A 3 2021-07-09 0.8017444 0.8110500 -0.04924920
#> 5: A 3 2021-07-10 0.8017444 0.8110500 -0.04924920
#> 6: A 3 2021-07-11 0.8017444 0.8110500 -0.04924920
#> 7: B NA 2021-07-06 NA NA NA
#> 8: B NA 2021-07-07 NA NA NA
#> 9: B NA 2021-07-08 NA NA NA
#> 10: B NA 2021-07-09 NA NA NA
#> 11: B NA 2021-07-10 NA NA NA
#> 12: B NA 2021-07-11 NA NA NAThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.