Journal of Commerce and Accounting Research

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

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
     

   Subscribe/Renew Journal


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
Subscription Login to verify subscription
User
Notifications
Font Size


  • An, S., He, Y., Zhao, Z., & Sun, J. (2006). Measurement of merger and acquisition performance based on artificial neural network. In 5th IEEE International Conference on Cognitive Informatics (pp. 502-506). New York, IEEE Press.

  • Banerjee, A. (2021). An empirical study on risk-return analysis to compute efficiency of Indian cement companies during pre- and post-recession periods. Journal of Commerce and Accounting Resarch, 10(1), 7-14.

  • Bradley, M., & Kim, E. H. (1988). Synergistic gains from corporate acquisitions and their division between the stockholders of target and acquiring firms. Journal of Financial Economics, 21(1), 3-40.

  • Chakraborty, S., & Chetan G. K. (2018). A study of quarterly earnings announcement and stock price reactions – With reference to nifty MIDCAP 150. Journal of Commerce and Accounting Research, 7(4), 1-12.

  • Chatarjee, S. (1986). Types of synergy and economic value: The impact of acquisitions on merging and rival firms. Strategic Management Journal, 7(2), 119-139.

  • Chavda, K., & Raval, K. (2019). A study on finanacial impact of merger and acquisition of selected steel companies in India. GAP Interdisciplinarities, 2(4).

  • Damodaran, A. (2005). The value of synergy. Stern School of Business.

  • Huh, K.-S. (2015). The performances of acquired firms in the steel industry: Do financial institutions cause bubbles? The Quarterly Review of Economics and Finance, 5(C), 143-153.

  • Kalsie, A., & Nagpal, A. (2017). Valuation of financial synergies in mergers and acquisitions: A case study of multiple Indian entities. Mudra Journal of Finance and Accounting, 4(2), 22-49.

  • Kohli, R., & Mann, B. J. (2012). Analyzing determinants of value creation in domestic and cross border acquisitions in India. International Business Review, 21(6), 998-1016.

  • Kumar, K., Bandi, J., & Tenneti, L. (2019). The Indian steel industry: Growth, challenges and digital disruption. PwC.

  • Kumar, S., & Bansal, L. (2008). The impact of mergers and acquisitions on corporate performance in India.

  • Management Decision, 46(10), 1531-1543.

  • Liu, H., & Ma, W. (2009). Price prediction of target of mergers and acquisitions based on genetic algorithm BP neural network. IEEE IEEM, 787-791.

  • Liu, Z.-B., & Shen, P. (2008). A novel neural network model of mergers and acquisitions performance measurement based on multistage dynamic fuzzy judgement. International Conference on Machine Learning and Cybernetics (pp. 1676-1680).

  • Lyons, P. J., & Persek, S. C. (1991). Integrating neural networks and expert systems for merger & acquisition analysis. First International Conference on Artificial Intelligence Applications on Wall Street (pp. 200-205).

  • Mal, P., & Gupta, K. (2020). Impact of merger and acquisition announcements on stock return, volatility and liquidity of acquirers: Evidence from the Indian banking sector. Management and Accounting Review, 19(1), 73-103.

  • Mall, P., & Gupta, K. (2019). Impact of merger announcements on stock returns of acquiring firms: Evidence from India. Journal of Commerce and Accouting Research, 8(1), 46-53.

  • Mishra, S., Vyas, V., & Meena, V. K. (2021). Abnormal returns and impact of information of natural disaster on the Indian stock market. Journal of Commerce and Accounting Research, 10(3), 25-35.

  • Nair, P. (2018, December 27). Finance@TAPMI. Retrieved from Finance@TAPMI: https://tapmi.finance/2019/01/12/mergers-and-acquisitions-the-game-of-consolidation-in-the-indian-steel-sector/#:~:text=Mergers%20and%20Acquisitions%2C%20The%20game%20of%20consolidation%20in%20the%20Indian%20steel%20sector,-January%2012%2C%202019&text=In%

  • Reddy, K. S., Nangia, V. K., & Aggarwal, R. (2013). Corporate mergers and financial performance: A new

  • assessment of Indian cases. Nankai Business Review International, 4(2), 107-129.

  • Slusky, A. R., & Caves, R. E. (1991). Synergy, agency, and the determinants of premia paid in mergers. The Journal of Industrial Economics, 39(3), 277-296.

  • Varghese, T., & Thaha, A. (2017). Impact of merger on acquiring bank performance: A case of Kotak Mahindra Bank. Journal of Commerce and Accounting Research, 6(3), 34-43.


Abstract Views: 159

PDF Views: 0




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

Abstract Views: 159  |  PDF Views: 0

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