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          <name>Title</name>
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              <text>A comprehensive LR model for predicting banks stock performance in Indian stock market</text>
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              <text>Key financial ratios; Logistic regression; Market rate of return; NIFTY; SENSEX; Stock performance</text>
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              <text>The study focusses on developing a Logistic Regression model to distinguish between Good and Poor Performance of Bank-stocks which are traded in Indian stock market with regard to the financial ratios. The study- sample comprises of financialratios of 40 nationalised and private banks, for a period of six years. The study ascertains and scrutinizes eleven financial ratios that can categorize the Banksbroadly into two categories as good or poor, up to the accuracy level of 78 percent, based on their rate of return. First, the study predicts the performance of banks by using financial ratios and tries to build the goodness of fit by using Logistic Regression approach. The study also emphasizes that this model can enrich an investors ability to forecast the price of various stocks. However, the paper confers the real-world implications of Logistic Regression model to envisage the performance of Banks in the stock market. The study reveals that the model could be useful to potential investors, fund managers, and investment companies to improve their strategies and to select the out-performing Bank-stocks.  Serials Publications Pvt. Ltd.</text>
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              <text>Nataraja N.S.; Chilale N.R.; Ganesh L.</text>
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              <text>International Journal of Applied Business and Economic Research, Vol-15, No. 21, pp. 155-164.</text>
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              <text>2017-01-01</text>
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              <text>&lt;a href="" target="_blank" rel="noreferrer noopener"&gt;&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039168946&amp;amp;partnerID=40&amp;amp;md5=bc40f1aaaeab3a83e0bd3ea703ebc726" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039168946&amp;amp;partnerID=40&amp;amp;md5=bc40f1aaaeab3a83e0bd3ea703ebc726&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 9727302</text>
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              <text>English</text>
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              <text>Nataraja N.S., Alliance University, Bangalore, India; Chilale N.R., Vijaya College, Bangalore University, Bangalore, India; Ganesh L., Christ University, Bangalore, India</text>
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