MODELLING PRICE DYNAMICS IN TURKISH ELECTRICITY MARKET: LESSONS FROM GARCH ESTIMATES
Year 2017,
, 621 - 638, 24.12.2017
Talat Ulussever
,
Mehmet Ali Soytaş
,
Hasan Murat Ertuğrul
Abstract
In this paper, we estimate electricity market volatility in Turkey using various GARCH-class models. Spot price in Turkish electricity market exhibits significant variation and therefore, conditional modelling of the volatility can make us better understand the price dynamics of this important market. We estimate volatilities of weekly prices over the period of January 2010 to April 2017 and compare the performance of various GARCH models that take into account the asymmetric effects, possible mean effects of the volatility, fat-tails of the distribution and persistence of the volatility series. We found time varying volatility is an important feature of the price dynamics in Turkish electricity market and additionally, in modelling volatility, paying attention to the extreme price changes via heavy tailed distributions improves the model fit substantially.
References
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ARIMA-EGARCH Models.” Energy Economics, 30(6), 2008, pp: 3186–3197.
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ARCH-M Model.” Econometrica, 55, 1987, pp: 391-407.
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University, Ankara, 2012.
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Using Nonlinear Excess Demand Specification.”, Working Paper, Ozyegin University, 2017.
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paper, Universidad Carlos III de Madrid, 2002.
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Energy Economics, 34(6), 2012, pp: 2228-2239.
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the International Conference on Business Management & Information Systems, 2012.
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Volatility of the Nominal Excess Return on Stocks.” Journal of Finance, 48, 1993, pp: 1779–1801.
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in the US.” Energy Journal, 25(4), 2004, pp: 23-40.
- HICKEY, E., Loomisand, D.G., and Mohammadi, H., “Forecasting Hourly Electricity Prices Using ARMAX–
GARCH Models: An Application to MISO Hubs.” Energy Economics, 34(1), 2012, pp: 307-315
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Markets.” Energy Economics, 31, 2009, pp: 748–756.
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University of California Energy Institute Working Paper PWP-087, 2001.
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Economics 1123, 2011.
- LE PEN, Y., and Sevi, B., “Volatility Transmissions and Volatility Impulse Response Functions in European
Energy Forward Markets.” Energy Economics, 32, 2010, pp: 758-770.
- LIU, H.-H., and Chen, Y.-C., “A Study on the Volatility Spillovers, Long Memory Efects and Interactions
between Carbon and Energy Markets: The Impacts of Extreme Weather.” Economic Modelling, 35,
2013, pp: 840-855.
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pp: 43-56.
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Energy Economics, 34(4), 2012, pp: 899-904.
- LUCIA, J., and Schwartz, E.S., “Electricity Prices and Power Derivatives: Evidence from the Nordic Power
Exchange.” Review of Derivatives Research, 5(1), 2002, pp: 5-50.
- MUGELE, C., Rachev S., and Trueck, S., “Stable Modeling of Different European Power Markets.” Investment
Management and Financial Innovations, 2 (3), 2005, pp: 65–85.
- MURTHY, G.G.P., Sedidi, V., and Panda, A.K., “Forecasting Electricity Prices in Deregulated Wholesale
Spot Electricity Market: A Review.” International Journal of Energy Economics and Policy, 4(1),
2014, pp: 32-42.
- SADORSKY, P., “Modeling and Forecasting Petroleum Futures Volatility.” Energy Economics, 28(4), 2006,
pp: 467-488.
- THOMAS, S., and Mitchell, H., “GARCH Modeling of High-Frequency Volatility in Australia’s National
Electricity Market.” Working Paper, RMIT University, Melbourne (Australia), 2007.
- WANG, Y., and Wu, C., “Forecasting Energy Market Volatility Using GARCH Models: Can Multivariate
Models Beat Univariate Models?” Energy Economics, 34(6), 2012, pp: 2167-2181.
- WANG, K.L., Fawson, C., Barrett, C.B., and McDonald, J.B., “A Flexible Parametric GARCH Model with
an Application to Exchange Rates.” Journal of Applied Econometrics, 16(4), 2001, pp: 521–536.
- WERON, R., “Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach.” John Wiley
& Sons, 2006.
- WORTHINGTON, A.C., Kay-Spratley, A., and Higgs, H., “Transmission of Prices and Price Volatility in
Australian Electricity Spot Markets: A Multivariate GARCH Analysis.” Energy Economics, 27(2),
2005, pp: 337-350.
Year 2017,
, 621 - 638, 24.12.2017
Talat Ulussever
,
Mehmet Ali Soytaş
,
Hasan Murat Ertuğrul
References
- BOLLERSLEV, T., “Generalized Autoregressive Conditional Heteroscedasticity.” Journal of Econometrics,
31, 1986, pp: 307-327.
- BOWDEN, N., and Payne, J. E., “Short Term Forecasting of Electricity Prices for MISO Hubs: Evidence from
ARIMA-EGARCH Models.” Energy Economics, 30(6), 2008, pp: 3186–3197.
- BROOKS, C., “Introductory Econometrics for Finance.”, Cambridge University Press, 2002.
- CHAN, K.F., and Gray, P., “Using Extreme Value Theory to Measure Value at Risk for Daily Electricity Spot
Prices.” International Journal of Forecasting, 22(2), 2006, pp: 283-300.
- ENGLE, R. F., “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United
Kingdom Inflation.” Econometrica, 50(4), 1982, pp: 987-1008.
- ENGLE, R. F., Lilien, D., and Robins, R., “Estimating Time Varying Risk Premia in the Term Structure: The
ARCH-M Model.” Econometrica, 55, 1987, pp: 391-407.
- ERTUĞRUL, H.M., “Türkiye’de Döviz Kuru Volatilitesi Modellemesi.” Unpublished Manuscript,
Undersecretariat of Treasury, Republic of Turkey, Ankara, 2010.
- ERTUĞRUL, H.M., “Türkiye’de Döviz Kuru Volatilitesi ve Enflasyon İlişkisi.” PhD. Dissertation, Hacettepe
University, Ankara, 2012.
- ERTUĞRUL, H.M., Soytas, M.A., and Ulussever, T., “Short-term Price Prediction in Electricity Market
Using Nonlinear Excess Demand Specification.”, Working Paper, Ozyegin University, 2017.
- ESCRIBANO PEAEA, J., and Villaplana, P., “Modelling Electricity Prices: International Evidence.” Working
paper, Universidad Carlos III de Madrid, 2002.
- GIANFREDA, A., and Grossi, L., “Forecasting Italian Electricity Zonal Prices with Exogenous Variables.”
Energy Economics, 34(6), 2012, pp: 2228-2239.
- GIRISH, G.P., “Modeling and Forecasting Day-ahead Hourly Electricity Prices: A Review.” Proceedings of
the International Conference on Business Management & Information Systems, 2012.
- GLOSTEN, L.R., Jagannathan, R., and Runkle, D. E., “On the Relation between the Expected Value and the
Volatility of the Nominal Excess Return on Stocks.” Journal of Finance, 48, 1993, pp: 1779–1801.
- HADSELL, L., Marathe, A., and Shawky, H.A., “Estimating the Volatility of Wholesale Electricity Spot Prices
in the US.” Energy Journal, 25(4), 2004, pp: 23-40.
- HICKEY, E., Loomisand, D.G., and Mohammadi, H., “Forecasting Hourly Electricity Prices Using ARMAX–
GARCH Models: An Application to MISO Hubs.” Energy Economics, 34(1), 2012, pp: 307-315
- HIGGS, H., “Modelling Price and Volatility Inter-relationships in the Australian Wholesale Spot Electricity
Markets.” Energy Economics, 31, 2009, pp: 748–756.
- KNITTEL, C.R., and Roberts, M.R., “An Empirical Examination of Deregulated Electricity Prices.”
University of California Energy Institute Working Paper PWP-087, 2001.
- KOENIG, P., “Modelling correlation in carbon and energy markets.” Cambridge Working Paper in
Economics 1123, 2011.
- LE PEN, Y., and Sevi, B., “Volatility Transmissions and Volatility Impulse Response Functions in European
Energy Forward Markets.” Energy Economics, 32, 2010, pp: 758-770.
- LIU, H.-H., and Chen, Y.-C., “A Study on the Volatility Spillovers, Long Memory Efects and Interactions
between Carbon and Energy Markets: The Impacts of Extreme Weather.” Economic Modelling, 35,
2013, pp: 840-855.
- LIN, S.X., and Tamvakis, M.V., “Spillover Effects in Energy Futures Markets.” Energy Economics, 23, 2001,
pp: 43-56.
- LINDSTROM, E., and Regland, F., “Modeling Extreme Dependence between European Electricity Markets.”
Energy Economics, 34(4), 2012, pp: 899-904.
- LUCIA, J., and Schwartz, E.S., “Electricity Prices and Power Derivatives: Evidence from the Nordic Power
Exchange.” Review of Derivatives Research, 5(1), 2002, pp: 5-50.
- MUGELE, C., Rachev S., and Trueck, S., “Stable Modeling of Different European Power Markets.” Investment
Management and Financial Innovations, 2 (3), 2005, pp: 65–85.
- MURTHY, G.G.P., Sedidi, V., and Panda, A.K., “Forecasting Electricity Prices in Deregulated Wholesale
Spot Electricity Market: A Review.” International Journal of Energy Economics and Policy, 4(1),
2014, pp: 32-42.
- SADORSKY, P., “Modeling and Forecasting Petroleum Futures Volatility.” Energy Economics, 28(4), 2006,
pp: 467-488.
- THOMAS, S., and Mitchell, H., “GARCH Modeling of High-Frequency Volatility in Australia’s National
Electricity Market.” Working Paper, RMIT University, Melbourne (Australia), 2007.
- WANG, Y., and Wu, C., “Forecasting Energy Market Volatility Using GARCH Models: Can Multivariate
Models Beat Univariate Models?” Energy Economics, 34(6), 2012, pp: 2167-2181.
- WANG, K.L., Fawson, C., Barrett, C.B., and McDonald, J.B., “A Flexible Parametric GARCH Model with
an Application to Exchange Rates.” Journal of Applied Econometrics, 16(4), 2001, pp: 521–536.
- WERON, R., “Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach.” John Wiley
& Sons, 2006.
- WORTHINGTON, A.C., Kay-Spratley, A., and Higgs, H., “Transmission of Prices and Price Volatility in
Australian Electricity Spot Markets: A Multivariate GARCH Analysis.” Energy Economics, 27(2),
2005, pp: 337-350.