Abstract
For a regular investor, it is necessary to identify the stocks with the strong fundamentals that yield good returns. An individual can check few such stocks manually but cannot do so for whole of the stock market listing. Thus, it is desirable to devise a mechanism that is able to assess the intrinsic health of the stock, across the whole of stock market scenario, in an automated manner and provide credible advice(s). The proposed work is an effort in this direction wherein on the basis of expert advice; a regression based supervised learning model has been created using feature extraction from the raw data. The regressive output of the learning model provides a stock health index that has been classified into fuzzy sets. A fuzzy rule base was created that generates the requisite advice on the basis of stock health index. The paper concludes with the identification of some fundamentally good stocks and validates the results through their quantified performance.
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