Journal of Commerce and Accounting Research

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Synergy Valuation in Mergers and Acquisitions in the Steel Industry: An Indian Context


Affiliations
1 IIM Shillong, Meghalaya, India
2 Associate Professor, IIM Shillong, Meghalaya, India
     

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This study attempts to value synergy gains in the mergers and acquisitions in the Indian steel industry. To value synergy, a neural network model has been created, where the change in financial ratios are the independent variables the value of the target company is the dependent variable. Along with the neural network, event study has been carried out, where cumulative abnormal returns (CAR) has been calculated to see if the acquiring companies’ shareholders gain wealth post the M&A transaction. This helps in understanding if the shareholders see merit in the transaction. For creating the model and to calculate CAR, the data from 2000-2019 has been taken from the Bloomberg terminal. The data consists of 30 M&A transactions in the steel industry in India. The results of the neural network indicate that the acquiring companies end up over paying for the synergy gains and the results of the event study show that the acquiring companies’ shareholders do not gain any wealth post the M&A transaction. The results will help managers in valuing the target companies for M&A in the future.

Keywords

Mergers and Acquisitions, Steel Industry, Neural Network, Event Study, Cumulative Abnormal Returns
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  • Synergy Valuation in Mergers and Acquisitions in the Steel Industry: An Indian Context

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Authors

Summit Rajesh Gupta
IIM Shillong, Meghalaya, India
Mousumi Bhattacharya
Associate Professor, IIM Shillong, Meghalaya, India

Abstract


This study attempts to value synergy gains in the mergers and acquisitions in the Indian steel industry. To value synergy, a neural network model has been created, where the change in financial ratios are the independent variables the value of the target company is the dependent variable. Along with the neural network, event study has been carried out, where cumulative abnormal returns (CAR) has been calculated to see if the acquiring companies’ shareholders gain wealth post the M&A transaction. This helps in understanding if the shareholders see merit in the transaction. For creating the model and to calculate CAR, the data from 2000-2019 has been taken from the Bloomberg terminal. The data consists of 30 M&A transactions in the steel industry in India. The results of the neural network indicate that the acquiring companies end up over paying for the synergy gains and the results of the event study show that the acquiring companies’ shareholders do not gain any wealth post the M&A transaction. The results will help managers in valuing the target companies for M&A in the future.

Keywords


Mergers and Acquisitions, Steel Industry, Neural Network, Event Study, Cumulative Abnormal Returns

References