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