Mean-value at risk portfolio selection problem using clustering technique : A case study

Each financial investment refers to a highly volatile environment in the global market, thus adding uncertainties in the financial market makes an optimal portfolio selection problem a major disadvantage in the market scenario. In this paper, we present an integrated approach to a portfolio selectio...

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Hauptverfasser:	Kumari, Sheshma Kiran, Kumar, P., Priya, J., Surya, S., Bhurjee, A. K.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Case studies Clustering Convexity Global marketing Markets Optimization Portfolio management Stock exchanges
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creator	Kumari, Sheshma Kiran Kumar, P. Priya, J. Surya, S. Bhurjee, A. K.
description	Each financial investment refers to a highly volatile environment in the global market, thus adding uncertainties in the financial market makes an optimal portfolio selection problem a major disadvantage in the market scenario. In this paper, we present an integrated approach to a portfolio selection problem using clustering technique. A classification of historical stock data from the Sensex Bombay Stock Exchange into a cluster is presented using the K-Mean technique. Also, the Mean-Value-at-Risk model is used to select the optimum portfolio using non-convex programming problems. Finally, the analytical findings are supported by a case study.
doi_str_mv	10.1063/1.5112363
format	Conference Proceeding
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subjects	Case studies Clustering Convexity Global marketing Markets Optimization Portfolio management Stock exchanges
title	Mean-value at risk portfolio selection problem using clustering technique : A case study
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