Application of Information Theoretic Divergence Measures- Forecasting Profit Maximation in Share Market

Abstract

In the present communication, we have discussed
Weighted Non- Symmetric JS-AG Divergence Measures of
type s,∀s ∈ R . Some bounds have been obtained for this
Weighted Non- Symmetric JS-AG Divergence Measures
and its particular cases for s=-1, 0, 1/2, 1, 2.Weighted Non-
Symmetric Relative J-Divergence of type s, ∀s ∈ R has
also been considered for its particular cases for s=0, 1, 2 in
section-2. Some mixed bounds- Non-Symmetric and
Symmetric have also been presented. “Application in
business – Share Market,” to switch over from one share to
another share utilizing Weighted Divergence Measure in
decision making process, has been exemplified in section-3
via weighted χ 2 -divergence and its adjoint. Analysis for
profit maximization has been presented numerically and
graphically. Section-4 presents the study of profit
maximization through weighted Kullback-Leibler
divergence, K(P//Q;W) and its adjoint.