jVaR: Value at Risk Function

Description

Compute VaR by many methods.

See the report: Value at Risk.

Usage

jVaR(type, Return, Alpha, N_th_day)

Arguments

type

Computing method. . 'non_adjust_hist': Historical method without any adjustment. . 'grch11_hist': Historical method with adjustment by Garch(1,1) method. . 'ewhv_hist': Exponential Weighted method. . 'ewma_hist': Historical method with adjustment by EWMA method. . 'kernel_hist': Estimating density function using kernel fitting method. . 'grch11_kernel_hist': Kernel fitting method apply on return adjusted by Garch(1,1). . 'ewma_kernel_hist': Kernel fitting method apply on return adjusted by EWMA. . 'garch11': Garch(1,1) method. . 'normal': Normal return method. . 'mle_normal': Normal return method (Estimating by maximum likelihood method). . 'monte_carlo': Simulation method.

Return

A return series that computed from price series.

Alpha

Given probability of the event that loss exceeds VaR.

N_th_day

Time point of VaR computing (...,-1,0,1,...)

. -1 : previous day . 0 : present . 1 : next day

Value

Value at Risk at the time point.

References

Value at Risk.(reserchgate.net)

Examples

Run this code

y <- c(11, 12, 10, 13, 12, 14, 13, 15, 13, 14, 12)
s <- jReturn(y)
alpha <- 0.2
h <- 0
v <- jVaR('non_adjust_hist',s,alpha,h)