Abstract
In the dynamic landscape of stock market investments, decision-making processes are often challenged by uncertainty and imprecision inherent in the financial data. It is important to evaluate the suitability of each stock based on multiple criteria, including market trends, financial indicators, and risk factors. Various approaches can be utilized to determine best option based on different parameters. The ambiguity and uncertainty around a phenomena are handled by fuzzy sets. Intuitionistic fuzzy (IF) set is an extension of fuzzy set used for managing uncertainty in more complex situations when fuzzy sets are unable to produce reliable results. This paper outlines a technique in IF environment to solve the problem of selection of stocks based on financial and other factors. A new IF knowledge measure (IFKM) is proposed to measure the amount of knowledge linked to IF sets. Reliability and utility of introduced knowledge measure is tested using some numerical examples. A new IF accuracy measure (IFAM) is proposed based on the suggested knowledge measure. Proposed IFAM is used to find the patterns similarity of unknown pattern with given pattern. Besides this, a new score function is proposed to compare the IF numbers which can get around the drawbacks of the current scoring functions. A modified Combined compromise solution (CoCoSo) technique is provided to choose the best stock by using the suggested scoring function and the IF accuracy measure. Lastly, to prove the effectiveness of the suggested method, a comparative analysis carries out with the other existing methods.
Published Version
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