stochdom2: Compute vectors measuring stochastic dominance of four orders.

Description

Stochastic dominance originated as a sophisticated comparison of two distributions of stock market returns. The dominating distribution is superior in terms of local mean, variance, skewness and kurtosis respectively, representing dominance orders 1 to 4, without simply computing the four moment summary measures for the entire data. Vinod (2008, sec. 4.3) explains the details. This function uses the output of `wtdpapb'.

Usage

stochdom2(dj, wpa, wpb)

Arguments

Vector of (unequal) distances of consecutive intervals defined on common support of two probability distributions being compared

wpa

Vector of the first set of (weighted) probabilities

wpb

Vector of the second set of (weighted) probabilities

Value

sd1b

Vector measuring stochastic dominance of order 1, SD1

sd2b

Vector measuring stochastic dominance of order 2, SD2

sd3b

Vector measuring stochastic dominance of order 3, SD3

sd4b

Vector measuring stochastic dominance of order 4, SD4

References

Vinod, H. D.', 'Hands-On Intermediate Econometrics Using R' (2008) World Scientific Publishers: Hackensack, NJ. https://www.worldscientific.com/worldscibooks/10.1142/6895

Vinod, H. D. 'Ranking Mutual Funds Using Unconventional Utility Theory and Stochastic Dominance,' Journal of Empirical Finance Vol. 11(3) 2004, pp. 353-377.

Examples

Run this code

# NOT RUN {
 
# }
# NOT RUN {
 set.seed(234);x=sample(1:30);y=sample(5:34)
 w1=wtdpapb(x,y) #y should dominate x with mostly positive SDs
 stochdom2(w1$dj, w1$wpa, w1$wpb) 
# }
# NOT RUN {
# }