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)
<- AMIM::exampledata # load the example data
data
<- AMIM.roll(data.table = data, identity.col = "ticker", rollWindow = 60, Date.col = "Date", return.col = "RET", min.obs = 30, max.lag = 10)
AMIM #> | | | 0% | |=== | 4% | |====== | 8% | |========= | 12% | |============ | 17% | |=============== | 21% | |================== | 25% | |==================== | 29% | |======================= | 33% | |========================== | 38% | |============================= | 42% | |================================ | 46% | |=================================== | 50% | |====================================== | 54% | |========================================= | 58% | |============================================ | 62% | |=============================================== | 67% | |================================================== | 71% | |==================================================== | 75% | |======================================================= | 79% | |========================================================== | 83% | |============================================================= | 88% | |================================================================ | 92% | |=================================================================== | 96% | |======================================================================| 100%
- 5):(.N), ], by = ticker] # show the last 5 observations for each ticker
AMIM[, .SD[(.N #> 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 NA