ASSESSMENT OF SECTOR BOND, EQUITY INDICES AND GREEN BOND INDEX USING INFORMATION THEORY QUANTIFIERS AND CLUSTERS TECHNIQUES

Green bonds are financial assets similar to classic debt securities used finance sustainable investments. Given this, they a long-term investment alternative that effectively contributes the planet’s future by preserving environment and encouraging development. This research encompasses rich dataset of equity bond sectors, general indices, S&P Bond Index. We estimate permutation entropy [Formula: see text], an appropriate statistical complexity measure Fisher Information text]. Therefore, we employ these measures construct two 2D maps, complexity-entropy causality plane ([Formula: text] ×[Formula: text]) Shannon–Fisher text]). Also, use information theory quantifiers rank indices’ efficiency analogous hierarchy. From mathematical point view, (CECP) is map considers global analysis, while SFCP simultaneously feels local analysis. Our findings reveal both maps indicated most efficient (b_info_tech) least (b_energy) assets. There peculiarities in ranking performed considering build each due distinction underlies construction map. Moreover, applied clustering approaches text]-means Hierarchical cluster) categorically converged indication four distinct groups, which allowed us verify that, overview, equities present unique dynamic when compared index.