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<p>The model considered in this article is a quadratic fractional programming problem with coefficients and the decision variables being in the entire closed interval. A solution approach has been invented for this model based on the parametric notion of the interval. Consequently, an <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40819_2025_1947_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="20" /> </InlineMediaObject> <EquationSource Format="TEX">\(t\mu\)</EquationSource> </InlineEquation>-efficient solution is defined. It is generated by changing the original structure into an analogous quadratic interval programming problem and then back into a deterministic problem with no interval uncertainty. The technique’s theoretical existence and justification are also investigated. To demonstrate the application of the proposed method in portfolio selection, a numerical example is presented using a dataset from the Indian stock market. The results showcase the entire process of maximizing the Sharpe ratio in the context of portfolio optimization.</p>

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Enhanced Interval Quadratic Fractional Programming for Maximizing Sharpe Ratio in Portfolio Optimization

  • 期刊论文

  • 发表日期：

    2025年6月18日

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  • Mridul Patel,
  • Jyotirmayee Behera,
  • Pankaj Kumar

摘要

The model considered in this article is a quadratic fractional programming problem with coefficients and the decision variables being in the entire closed interval. A solution approach has been invented for this model based on the parametric notion of the interval. Consequently, an \(t\mu\) -efficient solution is defined. It is generated by changing the original structure into an analogous quadratic interval programming problem and then back into a deterministic problem with no interval uncertainty. The technique’s theoretical existence and justification are also investigated. To demonstrate the application of the proposed method in portfolio selection, a numerical example is presented using a dataset from the Indian stock market. The results showcase the entire process of maximizing the Sharpe ratio in the context of portfolio optimization.