Soft Computing in Fuzzy Logic in Financial Engineering of Stock Market Decision Evaluation (original) (raw)

Soft computing is a collection of methodologies that aim to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost. Its principal constituents are fizzy logic, neurocomputing ,and probabilistic reasoning. Soft computing is likely to play an increasingly important role in many application areas, including financial engineering. The role model for soft computing is the human mind. The fuzzy set theory provides a guide to and techniques for forecasting, decision making, conclusions, and evaluations in an environment involving uncertainty, vagueness, and impression in business, finance, management, and socio-economic sciences. It encompasses applications in case studies including stock market strategy. The fuzzy membership function (unit share price) for low, medium and high and the corresponding Mumbai Stock Exchange Sensitive Index (BSE SENSEX), (BSE SENSEX) for low, medium and high are described. It has been shown that the unit share price in a dynamically stable market moves along with the sensitive index. The application of fuzzy control algorithms for market management may appear to be a promising domain for further investigation. Key words: fuzzy set theory, stock market strategy, membership function, relational matrices