EWMA volatility (RiskMetrics 1996)
Value
Named list with \(conditional_variance, conditional_volatility, lambda, n, last_variance, last_volatility, method\).
Examples
set.seed(1)
morie_ewma_volatility(x = rnorm(50))
#> $conditional_variance
#> [1] 0.3924444 0.3924444 0.3709212 0.3905624 0.5198239 0.4951490 0.5058302
#> [8] 0.4897356 0.4930589 0.4833668 0.4599605 0.5694918 0.5444410 0.5349309
#> [15] 0.7971288 0.8252292 0.7758366 0.7293022 0.7389936 0.7351183 0.7121743
#> [22] 0.7201150 0.7136123 0.6711292 0.8683126 0.8392649 0.7890981 0.7432085
#> [29] 0.8284028 0.7924162 0.7553518 0.8207913 0.7721777 0.7348644 0.6909462
#> [36] 0.7632671 0.7278043 0.6934639 0.6520671 0.6855464 0.6793599 0.6402224
#> [43] 0.6056606 0.5984664 0.5811509 0.5747449 0.5702931 0.5440508 0.5468463
#> [50] 0.5147928
#>
#> $conditional_volatility
#> [1] 0.6264538 0.6264538 0.6090330 0.6249500 0.7209882 0.7036683 0.7112174
#> [8] 0.6998111 0.7021815 0.6952458 0.6782039 0.7546468 0.7378624 0.7313897
#> [15] 0.8928207 0.9084213 0.8808159 0.8539919 0.8596474 0.8573904 0.8439042
#> [22] 0.8485959 0.8447558 0.8192248 0.9318330 0.9161140 0.8883119 0.8620954
#> [29] 0.9101663 0.8901776 0.8691098 0.9059753 0.8787364 0.8572423 0.8312318
#> [36] 0.8736516 0.8531144 0.8327448 0.8075067 0.8279773 0.8242329 0.8001390
#> [43] 0.7782420 0.7736061 0.7623325 0.7581193 0.7551776 0.7375980 0.7394906
#> [50] 0.7174906
#>
#> $lambda
#> [1] 0.94
#>
#> $n
#> [1] 50
#>
#> $last_variance
#> [1] 0.5147928
#>
#> $last_volatility
#> [1] 0.7174906
#>
#> $method
#> [1] "EWMA RiskMetrics"
#>