Articles | 2024-08-03

Comparative Analysis of Hedging Effectiveness in Indonesia’s National Electrical Company: An Evaluation of Ordinary Least Square (OLS), General Autoregressive Conditional Heteroskedasticity (GARCH) and Naïve Dollar-Offset Models

Rudi Asrudin, Buddi Wibowo
Quantitative Economics and Management Studies, Vol. 5 No. 4 (2024), pp. 774-781 https://doi.org/10.35877/454RI.qems2697 Published: 2024-08-03
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Abstract

This study evaluates the hedging effectiveness of Indonesia’s national electrical company, PT PLN (Persero), by comparing Ordinary Least Squares (OLS), Generalized Autoregressive Conditional Heteroskedasticity (GARCH), and Dollar Offset models. Using transaction data from 2018-2023, the analysis shows that the OLS model explains 48.8% of the variance in forward rates, indicating high effectiveness. The GARCH model, while capturing dynamic volatility with an average effectiveness of 4.32%, demonstrates the need for advanced models in volatile conditions. The Dollar Offset method, despite its simplicity, shows a moderate effectiveness of 19.03%. Combining these methods can enhance hedging strategies, providing robust risk management. Future research should expand data sources and periods to further validate findings.

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References (27)

  1. Grady, J. S., Her, M., Moreno, G., Perez, C., & Yelinek, J. (2019). Emotions in storybooks: A comparison of storybooks that represent ethnic and racial groups in the United States. Psychology of Popular Media Culture, 8(3), 207–217. https://doi.org/10.1037/ppm0000185
  2. Adler, M., & Dumas, B. (1984). Exposure to Currency Risk: Definition and Measurement. Financial Management, 13(2), 41–50. https://doi.org/10.2307/3665446
  3. Aggarwal, R., & Harper, J. T. (2010). Foreign exchange exposure of domestic corporations. Journal of International Money and Finance, 29, 1619–1636.
  4. Bartov, E., & Bodnar, G. M. (1994). Firm Valuation, Earnings Expectations, and the Exchange-Rate Exposure Effect. The Journal of Finance, 49(5), 1755–1785. https://doi.org/10.2307/2329270
  5. Bodnar, G. M., and W. M. Gentry, 1993, Exchange-rate exposure and industry characteristics: Evidence from Canada, Japan and the U.S., Journal of International Money and Finance 12, 29-45.
  6. Bollerslev, T. (1986/04//). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307. Retrieved from https://www.proquest.com/scholarly-journals/generalized-autoregressive-conditional/docview/196704069/se-2
  7. Buddi Wibowo (2017). Uji Empirik Metode Pengukuran Hedging Ratio dan Efektifitas Hedging di Bursa Komoditas Berjangka Jakarta. Jurnal Manajemen & Agribisnis, Vol. 14 No. 3, November 2017.
  8. Buyukkara, G., Kucukozmen, C. C., Uysal, E. T. (2021). Optimal hedge ratios and hedging effectiveness: An analysis of the Turkish futures market. Borsa Istanbul Review 22-1 (2022) 92-102.
  9. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed.). Routledge.
  10. Cotter, J., & Hanly, J. (2012). Hedging effectiveness under conditions of asymmetry. The European Journal of Finance, 18(2), 135-147. https://doi.org/10.1080/1351847X.2011.574977

How to Cite

Asrudin, R., & Wibowo, B. (2024). Comparative Analysis of Hedging Effectiveness in Indonesia’s National Electrical Company: An Evaluation of Ordinary Least Square (OLS), General Autoregressive Conditional Heteroskedasticity (GARCH) and Naïve Dollar-Offset Models. Quantitative Economics and Management Studies, 5(4), 774–781. https://doi.org/10.35877/454RI.qems2697