Description Usage Arguments Value References Examples
pnts
calculates cdf of the NTS distribution with parameters (α, θ, β, γ, μ).
If only three parameters are given, it calculates cdf of the standard NTS distribution with parameter (α, θ, β)
If a time parameter value is given, it calculates cdf of the profess
F(x)=P((X(t+s)-X(s))<x), where X is the NTS process generated
by the NTS distribution with parameters (α, θ, β, γ, μ).
1 |
xdata |
An array of x |
ntsparam |
A vector of the NTS parameters (α, θ, β, γ, μ). For the NTS process case it is a vector of parameters (α, θ, β, γ, μ, t). A vector of the standard NTS parameters (α, θ, β). |
Cumulative probability of the NTS distribution
Kim, Y. S. (2020) Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk https://arxiv.org/pdf/2007.13972.pdf
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | library("temStaR")
alpha <- 1.2
theta <- 1
beta <- -0.2
ntsparam <- c(alpha, theta, beta)
x <- seq(from = -6, to = 6, length.out = 101)
p <- pnts(x, ntsparam)
plot(x,p,type = 'l')
alpha <- 1.2
theta <- 1
beta <- -0.2
gamma <- 0.3
mu <- 0.1
ntsparam <- c(alpha, theta, beta, gamma, mu)
x <- seq(from = -2, to = 2, by = 0.01)
p <- pnts(x, ntsparam)
plot(x,p,type = 'l')
#Annual based parameters
alpha <- 1.2
theta <- 1
beta <- -0.2
gamma <- 0.3
mu <- 0.1
#scaling annual parameters to one day
dt <- 1/250 #one day
ntsparam <- c(alpha, theta, beta, gamma, mu, dt)
x <- seq(from = -0.02, to = 0.02, length.out = 101)
p <- pnts(x, ntsparam)
plot(x,p,type = 'l')
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