Hedging Commodity Price Risk Exposure and the Financial Performance of Manufacturing Companies in Kenya
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Abstract
This study sought to establish how the commodity price exposure faced by manufacturing companies in Kenya influence their financial performance focusing on the earnings before interest and tax (EBIT) and return on assets (ROA). The objective of the study focused on whether commodity price risk exposure should compel manufacturing entities to use hedging strategies based on the premise that commodity risk exposure affects the financial performance. The key theory upon which the research was grounded is the game theory given that irrespective of whether the players act independently or in a group and given that there is more than one course of action, the outcome of the “game” is dependent on the interface of pursued strategies. The researcher conducted a thorough literature review focusing on the key variables of the study. The literature reviewed was critical in providing different perspectives and aspects of commodity price risk exposure and its management strategies. The study adopted an analytical research design in order to get a better understanding of the impact of the independent variables on the dependent variable. The target population consisted of all manufacturing companies in Kenya from which a representative sample of two hundred and fifty five companies was selected through stratified sampling from the key sectors as classified by the Kenya Association of Manufacturers (KAM). The study used ten year panel data given that this period was deemed to be adequate for an objective analysis. Data was collected from archival financial statements to compute the key measures under the independent and dependent variables. Data analysis was done through a general linear model for panel data analysis. From the results obtained, it was observed that manufacturing firms do not disclose any derivative usage in their financial statements. Under the EBITS model, it was observed that TITS was statistically significant and points to the need to hedge commodity price risk in order to enhance financial performance. Under the ROA model, it was observed that Lnassets and CFTA were statistically significant and points to the need maintain adequate cash flows to hedge commodity price risk in order to enhance financial performance.
Keywords: Hedging, Commodity, Price Risk Exposure, Financial, Performance, Manufacturing Companies
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References
- Al Janabi, M. (2009). Commodity price risk management: Valuation of large trading portfolios under adverse and illiquid market settings. Journal of Derivatives & Hedge Funds, 15(1), 15–50.
- Ali, A., Namusonge, S., & Sakwa, M. (2016). Determinants of corporate hedging in Kenya listed companies. Journal of Business Management, 2(7), 65-80.
- Ayturk, Y., Gurbuz, A. O., & Yanik, S. (2016). Corporate derivatives use and firm value: Evidence from Turkey. Borsa Istanbul Review, 16(2), 108-120.
- Bartram, S. M., Brown, G. W., & Fehle, F. R. (2009). International evidence on financial derivatives usage. Financial management, 38(1), 185-206.
- Bartram, S. M., Gregory, W., Brown, G. W., & Conrad, J. (2011). The effects of derivatives on firm risk and value. Journal of Financial and Quantitative Analysis, 46(4), 967- 999.
- Capkun, V., Hameri A., & Weiss L. (2009). On the relationship between inventory and financial performance in manufacturing companies. International Journal of Operations & Production Management, 29(8), 789-806.
- Carfì, D. & Musolino, F. (2015). A competitive-dynamical game model for currency markets stabilization. AAPP | Atti della Accademia Peloritana dei Pericolanti Classe di Scienze Fisiche, Matematiche e Naturali, 93(1), C1.
- Carfí, D., & Musolino, F. (2014). Speculative and hedging interaction model in oil and US dollar markets with financial transaction taxes. Economic Modelling, 37, 306-319.
- Carr, G. (2012). Managing geopolitical risk in energy markets, retrieved from http://www.risk.net/energy-risk/feature/2144307/managing-geopolitical-risk-energy- markets.
- Chanzu, N., & Gekera, M. (2014). effects of use of derivatives on financial performance of companies listed in the Nairobi Security Exchange. International Journal of Academic Research in Accounting, Finance and Management Sciences. 4(4), 27–43.
- Clarvis, M., Halle, M., Mulder, I., & Yarime, M. (2014). Towards a new framework to account for environmental risk in sovereign credit risk analysis, Journal of Sustainable Finance & Investment, 4(2), 147-160.
- Ehrhart, H., & Guerineau, S. (2013). Commodity price volatility and tax revenues: Evidence from developing countries. Etudes et Documents, E 2011.31, CERDI.
- German, H. (2009). Commodities and Commodity Derivatives: Pricing and Modeling Agricultural, Metals and Energy. USA: John Wiley & Sons.
- Hatemi-J, A., & Roca, E. (2010). Estimating Optimal Hedge Ratio with Unknown Structural Breaks. Discussion papers, finance.
- Ithai, J. K. (2013). Factors leading to slow adoption of derivatives use in Kenya: A case study of commercial banks in Kenya. International Journal of Social Sciences and Entrepreneurship, 1(3), 454-468.
- Jorge, M. J. D. S., & Augusto, M. A. G. (2011). Financial risk exposures and risk management: evidence from European nonfinancial firms. RAM. Revista de Administração Mackenzie, 12(5), 65-97.
- Kozarevic, E., Jukan, M. K., & Civic, B. (2014). The use of financial derivatives in emerging market economies: An empirical evidence from Bosnia and Herzegovina's Non- Financial Firms. Research in World Economy 5(1), 39-48.
- Lynch, T. (2012). Derivatives: A twenty-first century understanding. Loyola University Chicago Law Journal, 43, 1-14.
- Martin, C., Carlos M., Omera K., & Oznur Y. (2011). Approaches to managing global sourcing risk, Supply Chain Management: An International Journal, 16(2), 67-81.
- Murungi, C. M., Murage, K. & Wanjau, K. (2014). Challenges facing nonfinancial firms in hedging financial risks using derivatives. International Journal of Social Sciences and Entrepreneurship, 1(10), 361-374.
- Musolino, F. (2012). Game theory for speculative derivatives: A possible stabilizing regulatory model. Atti della Accademia Peloritana dei Pericolanti, Classe di Scienze Fisiche, Matematiche e Naturali, 90(1), 99-107.
- Nguyen, H. V. (2011). Why do non-financial firms select one type of derivatives over others?
- Journal of Applied Business and Economics, 12(3), 91-109.
- Oum, Y., & Oren, S. (2010). Optimal static hedging of volumetric risk in a competitive wholesale electricity market. Decision Analysis, 7(1), 107-122.
- Pirrong, C. (2014). The economics of commodity trading firms, Bauer College of Business, University of Houston, White paper.
- Ravichandran, T., Yu Liu, Shu, H., & Iftekhar, H. (2009). Diversification and firm performance: Exploring the moderating effects of information technology spending. Journal of Management Information Systems, 25(4), 205-240.
- Tse, Y., & William, M. (2013). Does index speculation impact commodity prices? An intraday futures analysis, Financial Review, 48(3), 365–383.