International Journal of Advances in Science, Engineering and Technology(IJASEAT)
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Volume-7,Issue-3  ( Jul, 2019 )
Statistics report
Sep
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
  Journal Paper

Paper Title
Model for Choosing Best Stock among a Set of Stocks in Stock Market

Abstract
The million-dollar question for stock investors isif the price of a stock will rise or not. The fluctuation of stock market prices are violent and there are many complicated financial indicators. Only people with extensive experience and knowledge of the market can understand the meaning of these indicators. Most of other people can only rely on luck to earn money from stock trading. Price of shares of the companies are increasing or decreasing day by day and it is necessary to safeguard the money of the investors. In this paper we have focused on IT industry by selecting 10 companies within this field. In order to predict the best performing company, newly proposed MCDM called BWM is applied and hence the companies are ranked according to their performances. Inan MCDM problem, a number of alternatives are evaluated with respect to a number of criteria in order to select the best alternative. According to BWM, the best (e.g. Most desirable, most important) and the worst (e.g. least desirable, least important) criteria are identified first by the decision-maker. Pairwise comparisons are then conducted between each of these two criteria and the other criteria. A maximin problem is then formulated and solved to determine the weights of different criteria. The weights of the alternatives with respect to different criteria are obtained using the same process. The final scores of the alternatives are derived by aggregating the weights from different sets of criteria and alternatives to obtain optimal weights, based on which the best alternative is selected. Keywords - MCDM, BWM, pair-wise comparisons, optimal weights


Author - C. Sri Krishna, K. Niyas, P. Arun Raj Kumar

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| Published on 2018-03-30
   
   
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