A Performance based Ranking of Initial Public Offerings (IPOs) in India

Abstract

In recent times, Indian Stock Market (ISM) has been witnessing a surge in the number of IPOs listed in stock exchanges. However, in many occasions it has been noticed that post-listing performance of several IPOs are below par to the expectations of the investors. IPO performance has been one of the major concerns. In this context, the present paper endeavours to carry out a comparative performance assessment of a list of IPOs. We consider a period of three years after listing. Our sample consists of a list of IPOs having heterogeneous nature of business operations and introduced in 2018. We consider two aspects of the performance such as market-based indicators and fundamental efficiency in terms of profitability, liquidity and risk. For comparison, LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW) is used. The study period is considered as Fy 2020-21. The results reflect that for IPOs, market performance does not necessarily because of the fundamental efficiency. Further, we notice that the nature of equity ownership does not influence the market performance significantly. We surmise that during initial years, the performance of the IPOs at the marketplace is more driven by speculations and short-term goals of the investors. The result of validation test indicates that the ranking using LOPCOW method is comparable and consistent with a widely used model like Entropy.

Selection of Suitable Cloud Vendors for Health Centre: A Personalized Decision Framework with Fermatean Fuzzy Set, LOPCOW, and CoCoSo

“…Nila and Roy (2023) introduced a hybrid multi-criteria decision-making model that combines LOPCOW, FUCOM, and DOBI ("Dombi Bonferroni") methods with triangular fuzzy numbers to objectively evaluate and select third-party logistics providers for food manufacturing companies. Biswas and Joshi (2023) analysed the performance of IPOs in the Indian Stock Market from 2018-2021, using the LOPCOW method to assess market-based indicators and fundamental efficiency, suggesting that post-listing IPO performance is not necessarily tied to fundamentals and is often influenced by investor speculation, with the LOPCOW ranking method proving consistent with the widely-used Entropy model. From this literature review, the following point can be made about the LOPCOW method: (i) LOPCOW addresses significant differences in weight values, negative values, criterion limitations, and data size discrepancies in real-life problems, ensuring a more balanced weight calculation capability and leading to more acceptable outcomes compared to other objective weighting methods.…”

A Multicriteria-Based Comparison of Electric Vehicles Using q-Rung Orthopair Fuzzy Numbers

“…The outcomes of MCDM models often become unstable because of sudden changes in the governing conditions, such as changes in the criteria set, variations in the weights, selection of the alternatives, and addition/removal of elements of the decision matrix [ 62 , 63 , 64 , 65 , 66 , 67 , 68 ]. Therefore, it is important to carry out a sensitivity analysis (SA) to examine the stability of the solution.…”

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

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