Dünya Ham Petrol ve Seçilmiş Gıda Ürünlerin Arasındaki Fiyat Oynaklığın Tahmini: Bir BEKK-GARCH Yaklaşımı
Abstract
Bu çalışma, 1990-2015 yılları arasında dünya ham petrol ve bazı
temel gıda fiyatları arasındaki geçişkenliği analiz etmek amacıyla, çok
değişkenli-BEKK GARCH modeli kullanarak petrol fiyatının ve seçilen gıda ürünlerin
fiyat oynaklığının hareketi ve boyutunu ortaya koymayı amaçlamıştır. Bu çalışma
dünya ham petrol fiyatındaki değişme ile tarımsal gıda piyasaları arasındaki
fiyat oynaklığının kaynağını anlamak, oynaklığı azaltma arayışlarını artırmak, oynaklıktan
gıda güvencesini kontrol altına almak ve gelecekte planlamada istikrarı
sağlamak amacı büyük önem taşımaktadır. Makalede ayrıca, çalışmada gerçek
(reel) fiyat getirileri uygulanmış ve seri normalleştirilmiştir. Ampirik
sonuçlar, ham petrol ile mandıra ürünleri hariç diğer gıda ürünlerinin fiyat
getirileri arasında belirgin bir oynaklık geçişkenliği etkisinin olduğunu
göstermiştir. Ham petrol fiyatı getirisi ile et, tahıl, yenilebilir yağlar ve
şekerler arasında kuvvetli ikili çapraz korelasyon ilişkisi mevcuttur. Ayrıca şoklar
gıda ürünlerin fiyatlarında ve ilk gecikmelerinde gözlenmiştir.
Keywords
References
- Abdelradi, F., Serra, T., 2015. “Asymmetric price volatility transmission between food and energy markets: The case of Spain”. Agricultural Economics 46(4): 503-513.
- Bollerslev, T., 1986. Generalized autoregressive conditional heteroscedasticity. Econometrica, 31: 307–327.
- Bollerslev, T., Engle, R., Wooldridge, J. 1988. “A Capital Asset Pricing Model with Time-Varying Covariances”. Political Economy, 96(1): 116-197.
- Busse, S., Brümmer, B., Ihle, R. 2011. “Emerging Linkages between Price Volatilities in Energy and Agricultural Markets”. In Safeguarding Food Security in Volatile Global Markets Rome: FAO: Food and Agricultural Organization 111-125.
- Engle, R.F. 1982. Autoregressive condition heteroscedasticity with estimates of variance of United Kingdom inflation. Econometrica, 50(4): 987 – 1007.
- Engle, R., Kroner, K. F. 1995. Multivariate Simultaneous Generalized ARCH. Econ. Theory 11(01): 122-150.
- Engle, R., 2001. GARCH 101: The use of ARCH/GARCH models in applied econometrics. Econ. Perspect. 15: 157–168.
- Engle, R., Granger, C., (1987). Cointegration and error correction representation, estimation and testing. Econometrica 55: 251–276.
- Ewing, B., Malik, F. 2005. “Re-examining the asymmetric predictability of conditional variances: The role of sudden changes in variance”. Banking & Finance, 29(10): 2655-2673.
- FAO-OECD. 2011. Price Volatility in Food and Agricultural Markets. Policy Responses, Report including contributions by FAO, IFAD, IMF, OECD, UNCTAD, WFP, the World Bank, the WTO, IFPRI and the UN HLTF.
- Hafner, C., Herwartz, H. 2006. Volatility impulse responses for multivariate GARCH models: An exchange rate illustration. International Money and Finance, 25(5): 719-740.
- Li, H., Majerowska, E. 2008. Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach. Research in International Business and Finance, 22(3): 247-266.
- Hosking, J. 1981. Lagrange multiplier tests of multivariate time series models. The Royal Statistical Society Series, 43: 219–230.
- AbdElaal, M. A. 2011. Modeling and forecasting time varying stock return volatility in the Egyptian stock market. International Research Journal of Finance and Economics, 78: 96- 113.
- Nazlioglu, S., Erdem, C., Soytas, U. 2013. Volatility spillover between oil and agricultural commodity markets. Energy Economics. 36: 658-665.
- Sattary, A., Temurlenk, M. S., Bilgic, A., Celik, A. K. 2014. Volatility Spillovers between World Oil Markets and Sectors of BIST. Canadian Center of Science and Education, Asian Social Science, 10(8):1911-2025.
- Serra, T. 2015. Price volatility in Niger millet markets. Agricultural Economics 46(4): 489-502.
- García-Germán, S., Bardají, I., Garrido, A. 2015. Evaluating price transmission between global agricultural markets and consumer food price indices in the European Union. Agricultural Economics 47 (1): 59-70.
Estimating Price Volatility Transmission between World Crude Oil and Selected Food Commodities: A BEKK Approach
Abstract
This paper quantified the behaviour and extent of oil
price and selected food commodity price volatilities using a multivariate-BEKK GARCH
model to analyse the shocks and volatility transmission effect between crude
oil and these commodities prices during 1990-2015. In line with the properties
of time series data, a series of test such as collinearity, unit root as well
as the presence of ARCH effects were conducted. The objective of this paper was
to understand the most volatile commodity due to changes in world crude oil
price returns and explore ways to reduce volatility relevant to food security and
its stability for future planning purposes. The paper further used real price
returns and demeans for normalization. Empirical results showed significant
volatility transmission effects between crude oil and the all the food
commodity except for dairy. Strong correlations existed between crude oil price
returns and meat, cereal, edible oils and sugars. Shocks were also observed
food commodity prices and its first lags.
Keywords
References
- Abdelradi, F., Serra, T., 2015. “Asymmetric price volatility transmission between food and energy markets: The case of Spain”. Agricultural Economics 46(4): 503-513.
- Bollerslev, T., 1986. Generalized autoregressive conditional heteroscedasticity. Econometrica, 31: 307–327.
- Bollerslev, T., Engle, R., Wooldridge, J. 1988. “A Capital Asset Pricing Model with Time-Varying Covariances”. Political Economy, 96(1): 116-197.
- Busse, S., Brümmer, B., Ihle, R. 2011. “Emerging Linkages between Price Volatilities in Energy and Agricultural Markets”. In Safeguarding Food Security in Volatile Global Markets Rome: FAO: Food and Agricultural Organization 111-125.
- Engle, R.F. 1982. Autoregressive condition heteroscedasticity with estimates of variance of United Kingdom inflation. Econometrica, 50(4): 987 – 1007.
- Engle, R., Kroner, K. F. 1995. Multivariate Simultaneous Generalized ARCH. Econ. Theory 11(01): 122-150.
- Engle, R., 2001. GARCH 101: The use of ARCH/GARCH models in applied econometrics. Econ. Perspect. 15: 157–168.
- Engle, R., Granger, C., (1987). Cointegration and error correction representation, estimation and testing. Econometrica 55: 251–276.
- Ewing, B., Malik, F. 2005. “Re-examining the asymmetric predictability of conditional variances: The role of sudden changes in variance”. Banking & Finance, 29(10): 2655-2673.
- FAO-OECD. 2011. Price Volatility in Food and Agricultural Markets. Policy Responses, Report including contributions by FAO, IFAD, IMF, OECD, UNCTAD, WFP, the World Bank, the WTO, IFPRI and the UN HLTF.
- Hafner, C., Herwartz, H. 2006. Volatility impulse responses for multivariate GARCH models: An exchange rate illustration. International Money and Finance, 25(5): 719-740.
- Li, H., Majerowska, E. 2008. Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach. Research in International Business and Finance, 22(3): 247-266.
- Hosking, J. 1981. Lagrange multiplier tests of multivariate time series models. The Royal Statistical Society Series, 43: 219–230.
- AbdElaal, M. A. 2011. Modeling and forecasting time varying stock return volatility in the Egyptian stock market. International Research Journal of Finance and Economics, 78: 96- 113.
- Nazlioglu, S., Erdem, C., Soytas, U. 2013. Volatility spillover between oil and agricultural commodity markets. Energy Economics. 36: 658-665.
- Sattary, A., Temurlenk, M. S., Bilgic, A., Celik, A. K. 2014. Volatility Spillovers between World Oil Markets and Sectors of BIST. Canadian Center of Science and Education, Asian Social Science, 10(8):1911-2025.
- Serra, T. 2015. Price volatility in Niger millet markets. Agricultural Economics 46(4): 489-502.
- García-Germán, S., Bardají, I., Garrido, A. 2015. Evaluating price transmission between global agricultural markets and consumer food price indices in the European Union. Agricultural Economics 47 (1): 59-70.
Details
| Journal Section | Makaleler |
|---|---|
| Authors | |
| Publication Date | June 9, 2017 |
| Published in Issue | Year 2017 Volume: 48 Issue: 1 |
Cite
Cited By
Red Meat Price Volatility and Its Relationship with Crude Oil and Exchange Rates in Turkey with the Approach of GARCH (p, q) Model
Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi
https://doi.org/10.29133/yyutbd.984277
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