stochdom2 | R Documentation |
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. However, stochastic dominance orders 1 to 4 are really not related to the four moments. Some details are in Vinod (2022, sec. 4.3) and vignettes. Nevertheless, this function uses the output of ‘wtdpapb.’ and Anderson's algorithm. Of course, Anderson's method remains subject to the trapezoidal approximation avoided by exact stochastic dominance methods.
stochdom2(dj, wpa, wpb)
dj |
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 |
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 |
The input to this function is the output of the function wtdpapb
.
Prof. H. D. Vinod, Economics Dept., Fordham University, NY
Vinod, H. D.', 'Hands-On Intermediate Econometrics Using R' (2008) World Scientific Publishers: Hackensack, NJ. https://www.worldscientific.com/worldscibooks/10.1142/12831
Vinod, H. D. 'Ranking Mutual Funds Using Unconventional Utility Theory and Stochastic Dominance,' Journal of Empirical Finance Vol. 11(3) 2004, pp. 353-377.
See Also wtdpapb
## 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)
## End(Not run)
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