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          <name>Title</name>
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              <text>Identifying explosive behavioral trace in the CNX nifty index: A quantum finance approach</text>
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          <name>Subject</name>
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              <text>Artifcial neural network; Econophysics; Heuristics; Hilbert space; Reynolds number</text>
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              <text>The fnancial markets are found to be fnite Hilbert space, inside which the stocks are displaying their wave-particle duality. Te Reynolds number, an age old fluid mechanics theory, has been redefned in investment fnance domain to identify possible explosive moments in the stock exchange. CNX Nify Index, a known index on the National Stock Exchange of India Ltd., has been put to the test under this situation. Te Reynolds number (its fnancial version) has been predicted, as well as connected with plausible behavioral rationale. While predicting, both econometric and machinelearning approaches have been put into use. Te primary objective of this paper is to set up an efcient econophysics' proxy for stock exchange explosion. Te secondary objective of the paper is to predict the Reynolds number for the future. Last but not least, this paper aims to trace back the behavioral links as well.  2018 Bikramaditya Ghosh, Emira Kozarevic.</text>
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              <text>Ghosh B.; Kozarevic E.</text>
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              <text>Investment Management and Financial Innovations, Vol-15, No. 1, pp. 208-223.</text>
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              <text>LLC CPC Business Perspectives</text>
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          <name>Date</name>
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              <text>2018-01-01</text>
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              <text>&lt;a href="https://doi.org/10.21511/imfi.15(1).2018.18" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.21511/imfi.15(1).2018.18&lt;/a&gt;
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              <text>All Open Access; Gold Open Access</text>
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              <text>ISSN: 18104967</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Ghosh B., Institute of Management, Christ University, India; Kozarevic E., Faculty of Economics, University of Tuzla, Bosnia and Herzegovina</text>
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