Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]

A key element that must consider the electricity generators in their operation planning process is the electricity price forecasting. Thus, for this task it is fundamental to identify a forecasting tool. In this direction, this paper presents forecast models for the price of electricity in the Colom...

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Fecha de publicación:: 2018

Institución:: Universidad de Medellín

Repositorio:: Repositorio UDEM

Idioma:: spa

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network_acronym_str	REPOUDEM2
network_name_str	Repositorio UDEM
repository_id_str
dc.title.spa.fl_str_mv	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
title	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
spellingShingle	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot] Efficiency hypothesis Electricity markets Market anomalies SARIMA-GARCH Seasonality Commerce Costs Efficiency Financial data processing Forecasting Information systems Information use Asymmetric volatility Conditional autoregressive Electricity generators Electricity price forecasting Empirical analysis SARIMA-GARCH Seasonal autoregressive models Seasonality Power markets
title_short	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
title_full	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
title_fullStr	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
title_full_unstemmed	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
title_sort	Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]
dc.contributor.affiliation.spa.fl_str_mv	Monica, A.A.A., Universidad de Medellín; Universidad Nacional de Colombia;Botero, S.B., Universidad Nacional de Colombia;Jaime, H.H.B., Universidad de Medellín
dc.subject.spa.fl_str_mv	Efficiency hypothesis Electricity markets Market anomalies SARIMA-GARCH Seasonality Commerce Costs Efficiency Financial data processing Forecasting Information systems Information use Asymmetric volatility Conditional autoregressive Electricity generators Electricity price forecasting Empirical analysis SARIMA-GARCH Seasonal autoregressive models Seasonality Power markets
topic	Efficiency hypothesis Electricity markets Market anomalies SARIMA-GARCH Seasonality Commerce Costs Efficiency Financial data processing Forecasting Information systems Information use Asymmetric volatility Conditional autoregressive Electricity generators Electricity price forecasting Empirical analysis SARIMA-GARCH Seasonal autoregressive models Seasonality Power markets
description	A key element that must consider the electricity generators in their operation planning process is the electricity price forecasting. Thus, for this task it is fundamental to identify a forecasting tool. In this direction, this paper presents forecast models for the price of electricity in the Colombian market. The different models are based in different schemes such as: autoregressive mobile media, generalized processes of conditional autoregressive heteroscedasticity (ARMA-GARCH), seasonal autoregressive models with mobile average and exogenous regressors (SARIMAX-GARCH). Likewise, using the theory of markets efficiency hypothesis the results show the presence of monthly calendar effects and the presence of nonlinear and asymmetric volatility which changes over time together with an inverse leverage effect. © 2018 AISTI.
publishDate	2018
dc.date.accessioned.none.fl_str_mv	2018-10-31T13:44:18Z
dc.date.available.none.fl_str_mv	2018-10-31T13:44:18Z
dc.date.created.none.fl_str_mv	2018
dc.type.eng.fl_str_mv	Conference Paper
dc.type.coarversion.fl_str_mv	http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_c94f
dc.type.driver.none.fl_str_mv	info:eu-repo/semantics/conferenceObject
dc.identifier.isbn.none.fl_str_mv	9789899843486
dc.identifier.issn.none.fl_str_mv	21660727
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11407/4860
dc.identifier.doi.none.fl_str_mv	10.23919/CISTI.2018.8398640
identifier_str_mv	9789899843486 21660727 10.23919/CISTI.2018.8398640
url	http://hdl.handle.net/11407/4860
dc.language.iso.none.fl_str_mv	spa
language	spa
dc.relation.isversionof.spa.fl_str_mv	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049904209&doi=10.23919%2fCISTI.2018.8398640&partnerID=40&md5=0471dfa9e306cb7ac14511098248de5c
dc.relation.citationvolume.spa.fl_str_mv	2018-June
dc.relation.citationstartpage.spa.fl_str_mv	1
dc.relation.citationendpage.spa.fl_str_mv	7
dc.relation.ispartofes.spa.fl_str_mv	Iberian Conference on Information Systems and Technologies, CISTI
dc.relation.references.spa.fl_str_mv	Weron, R., Misiorek, A., Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models (2008) Int. J. Forecast., 24 (4), pp. 744-763. , Oct;Haugom, E., Ullrich, C.J., Market efficiency and risk premia in short-term forward prices (2012) Energy Econ., 34 (6), pp. 1931-1941. , Nov;Cifter, A., Forecasting electricity price volatility with the Markovswitching GARCH model: Evidence from the Nordic electric power market (2013) Electr. Power Syst. Res., 102, pp. 61-67. , Sep;Luo, C., Seco, L., Wu, L.-L.B., Portfolio optimization in hedge funds by OGARCH and Markov Switching Model (2015) Omega, 57, pp. 34-39. , Dec;Manera, M., Nicolini, M., Vignati, I., Modelling futures price volatility in energy markets: Is there a role for financial speculation (2014) Energy Econ., , Jul;Charfeddine, L., True or spurious long memory in volatility: Further evidence on the energy futures markets (2014) Energy Policy, 71, pp. 76-93. , Aug;Wang, Y., Wu, C., Yang, L., Forecasting crude oil market volatility: A Markov switching multifractal volatility approach (2016) Int. J. Forecast., 32 (1), pp. 1-9. , Jan;Nowotarski, J., Raviv, E., Trück, S., Weron, R., An empirical comparison of alternative schemes for combining electricity spot price forecasts (2014) Energy Econ., 46, pp. 395-412. , Nov;Shrivastava, N.A., Panigrahi, B.K., A hybrid wavelet-ELM based short term price forecasting for electricity markets (2014) Int. J. Electr. Power Energy Syst., 55, pp. 41-50. , Feb;Nojavan, S., Zare, K., Ashpazi, M.A., A hybrid approach based on IGDT-MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market (2015) Int. J. Electr. Power Energy Syst., 69, pp. 335-343. , Jul;Yang, Z., Ce, L., Lian, L., Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernelbased extreme learning machine methods (2017) Appl. Energy, 190, pp. 291-305;Kriechbaumer, T., Angus, A., Parsons, D., Rivas Casado, M., An improved wavelet-ARIMA approach for forecasting metal prices (2014) Resour. Policy, 39, pp. 32-41. , Mar;Raviv, E., Bouwman, K.E., Van Dijk, D., Forecasting day-ahead electricity prices: Utilizing hourly prices (2015) Energy Econ., 50, pp. 227-239. , Jul;Hamzacebi, C., Es, H.A., Forecasting the annual electricity consumption of Turkey using an optimized grey model (2014) Energy, 70, pp. 165-171. , Jun;Nowotarski, J., Tomczyk, J., Weron, R., Robust estimation and forecasting of the long-term seasonal component of electricity spot prices (2013) Energy Econ., 39, pp. 13-27. , Sep;Anderson, E.J., Cau, T.D.H., Implicit collusion and individual market power in electricity markets (2011) Eur. J. Oper. Res., 211 (2), pp. 403-414. , Jun;Hickey, E., Loomis, D.G., Mohammadi, H., Forecasting hourly electricity prices using ARMAX-GARCH models: An application to MISO hubs (2012) Energy Econ., 34 (1), pp. 307-315. , Jan;Islyaev, S., Date, P., Electricity futures price models: Calibration and forecasting (2015) Eur. J. Oper. Res., , May;Liu, H., Shi, J., Applying ARMA-GARCH approaches to forecasting short-term electricity prices (2013) Energy Econ., 37, pp. 152-166. , May;Lund, P.D., Lindgren, J., Mikkola, J., Salpakari, J., Review of energy system flexibility measures to enable high levels of variable renewable electricity (2015) Renew. Sustain. Energy Rev., 45, pp. 785-807. , May;Paraschiv, F., Fleten, S.-E., Schürle, M., A spot-forward model for electricity prices with regime shifts (2015) Energy Econ., 47, pp. 142-153. , Jan;Sigauke, C., Chikobvu, D., Prediction of daily peak electricity demand in South Africa using volatility forecasting models (2011) Energy Econ., 33 (5), pp. 882-888. , Sep;Suganthi, L., Samuel, A.A., Energy models for demand forecasting-A review (2012) Renew. Sustain. Energy Rev., 16 (2), pp. 1223-1240. , Feb;Tan, Z., Zhang, J., Wang, J., Xu, J., Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models (2010) Appl. Energy, 87 (11), pp. 3606-3610. , Nov;Ziel, F., Steinert, R., Husmann, S., Efficient modeling and forecasting of electricity spot prices (2015) Energy Econ., 47, pp. 98-111. , Jan;Uritskaya, O.Y., Uritsky, V.M., Predictability of price movements in deregulated electricity markets (2015) Energy Econ., 49, pp. 72-81. , May;Efimova, O., Serletis, A., Energy markets volatility modelling using GARCH (2014) Energy Econ., 43, pp. 264-273. , May;Engle, R., Bollerslev, T., Modelling the persistence of conditional variances (1986) Econometric Reviews, 5 (1), pp. 1-50
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_16ec
rights_invalid_str_mv	http://purl.org/coar/access_right/c_16ec
dc.publisher.spa.fl_str_mv	IEEE Computer Society
dc.publisher.program.spa.fl_str_mv	Ingeniería Financiera;Ciencias Básicas
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ingenierías;Facultad de Ciencias Básicas
dc.source.spa.fl_str_mv	Scopus
institution	Universidad de Medellín
repository.name.fl_str_mv	Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv	repositorio@udem.edu.co
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spelling	2018-10-31T13:44:18Z2018-10-31T13:44:18Z2018978989984348621660727http://hdl.handle.net/11407/486010.23919/CISTI.2018.8398640A key element that must consider the electricity generators in their operation planning process is the electricity price forecasting. Thus, for this task it is fundamental to identify a forecasting tool. In this direction, this paper presents forecast models for the price of electricity in the Colombian market. The different models are based in different schemes such as: autoregressive mobile media, generalized processes of conditional autoregressive heteroscedasticity (ARMA-GARCH), seasonal autoregressive models with mobile average and exogenous regressors (SARIMAX-GARCH). Likewise, using the theory of markets efficiency hypothesis the results show the presence of monthly calendar effects and the presence of nonlinear and asymmetric volatility which changes over time together with an inverse leverage effect. © 2018 AISTI.spaIEEE Computer SocietyIngeniería Financiera;Ciencias BásicasFacultad de Ingenierías;Facultad de Ciencias Básicashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85049904209&doi=10.23919%2fCISTI.2018.8398640&partnerID=40&md5=0471dfa9e306cb7ac14511098248de5c2018-June17Iberian Conference on Information Systems and Technologies, CISTIWeron, R., Misiorek, A., Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models (2008) Int. J. Forecast., 24 (4), pp. 744-763. , Oct;Haugom, E., Ullrich, C.J., Market efficiency and risk premia in short-term forward prices (2012) Energy Econ., 34 (6), pp. 1931-1941. , Nov;Cifter, A., Forecasting electricity price volatility with the Markovswitching GARCH model: Evidence from the Nordic electric power market (2013) Electr. Power Syst. Res., 102, pp. 61-67. , Sep;Luo, C., Seco, L., Wu, L.-L.B., Portfolio optimization in hedge funds by OGARCH and Markov Switching Model (2015) Omega, 57, pp. 34-39. , Dec;Manera, M., Nicolini, M., Vignati, I., Modelling futures price volatility in energy markets: Is there a role for financial speculation (2014) Energy Econ., , Jul;Charfeddine, L., True or spurious long memory in volatility: Further evidence on the energy futures markets (2014) Energy Policy, 71, pp. 76-93. , Aug;Wang, Y., Wu, C., Yang, L., Forecasting crude oil market volatility: A Markov switching multifractal volatility approach (2016) Int. J. Forecast., 32 (1), pp. 1-9. , Jan;Nowotarski, J., Raviv, E., Trück, S., Weron, R., An empirical comparison of alternative schemes for combining electricity spot price forecasts (2014) Energy Econ., 46, pp. 395-412. , Nov;Shrivastava, N.A., Panigrahi, B.K., A hybrid wavelet-ELM based short term price forecasting for electricity markets (2014) Int. J. Electr. Power Energy Syst., 55, pp. 41-50. , Feb;Nojavan, S., Zare, K., Ashpazi, M.A., A hybrid approach based on IGDT-MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market (2015) Int. J. Electr. Power Energy Syst., 69, pp. 335-343. , Jul;Yang, Z., Ce, L., Lian, L., Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernelbased extreme learning machine methods (2017) Appl. Energy, 190, pp. 291-305;Kriechbaumer, T., Angus, A., Parsons, D., Rivas Casado, M., An improved wavelet-ARIMA approach for forecasting metal prices (2014) Resour. Policy, 39, pp. 32-41. , Mar;Raviv, E., Bouwman, K.E., Van Dijk, D., Forecasting day-ahead electricity prices: Utilizing hourly prices (2015) Energy Econ., 50, pp. 227-239. , Jul;Hamzacebi, C., Es, H.A., Forecasting the annual electricity consumption of Turkey using an optimized grey model (2014) Energy, 70, pp. 165-171. , Jun;Nowotarski, J., Tomczyk, J., Weron, R., Robust estimation and forecasting of the long-term seasonal component of electricity spot prices (2013) Energy Econ., 39, pp. 13-27. , Sep;Anderson, E.J., Cau, T.D.H., Implicit collusion and individual market power in electricity markets (2011) Eur. J. Oper. Res., 211 (2), pp. 403-414. , Jun;Hickey, E., Loomis, D.G., Mohammadi, H., Forecasting hourly electricity prices using ARMAX-GARCH models: An application to MISO hubs (2012) Energy Econ., 34 (1), pp. 307-315. , Jan;Islyaev, S., Date, P., Electricity futures price models: Calibration and forecasting (2015) Eur. J. Oper. Res., , May;Liu, H., Shi, J., Applying ARMA-GARCH approaches to forecasting short-term electricity prices (2013) Energy Econ., 37, pp. 152-166. , May;Lund, P.D., Lindgren, J., Mikkola, J., Salpakari, J., Review of energy system flexibility measures to enable high levels of variable renewable electricity (2015) Renew. Sustain. Energy Rev., 45, pp. 785-807. , May;Paraschiv, F., Fleten, S.-E., Schürle, M., A spot-forward model for electricity prices with regime shifts (2015) Energy Econ., 47, pp. 142-153. , Jan;Sigauke, C., Chikobvu, D., Prediction of daily peak electricity demand in South Africa using volatility forecasting models (2011) Energy Econ., 33 (5), pp. 882-888. , Sep;Suganthi, L., Samuel, A.A., Energy models for demand forecasting-A review (2012) Renew. Sustain. Energy Rev., 16 (2), pp. 1223-1240. , Feb;Tan, Z., Zhang, J., Wang, J., Xu, J., Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models (2010) Appl. Energy, 87 (11), pp. 3606-3610. , Nov;Ziel, F., Steinert, R., Husmann, S., Efficient modeling and forecasting of electricity spot prices (2015) Energy Econ., 47, pp. 98-111. , Jan;Uritskaya, O.Y., Uritsky, V.M., Predictability of price movements in deregulated electricity markets (2015) Energy Econ., 49, pp. 72-81. , May;Efimova, O., Serletis, A., Energy markets volatility modelling using GARCH (2014) Energy Econ., 43, pp. 264-273. , May;Engle, R., Bollerslev, T., Modelling the persistence of conditional variances (1986) Econometric Reviews, 5 (1), pp. 1-50ScopusEfficiency hypothesisElectricity marketsMarket anomaliesSARIMA-GARCHSeasonalityCommerceCostsEfficiencyFinancial data processingForecastingInformation systemsInformation useAsymmetric volatilityConditional autoregressiveElectricity generatorsElectricity price forecastingEmpirical analysisSARIMA-GARCHSeasonal autoregressive modelsSeasonalityPower marketsFinancial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]Conference Paperinfo:eu-repo/semantics/conferenceObjecthttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fMonica, A.A.A., Universidad de Medellín; Universidad Nacional de Colombia;Botero, S.B., Universidad Nacional de Colombia;Jaime, H.H.B., Universidad de MedellínMonica A.A.A.Botero S.B.Jaime H.H.B.http://purl.org/coar/access_right/c_16ec11407/4860oai:repository.udem.edu.co:11407/48602020-05-27 17:45:28.714Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

Financial anomalies in the electricity market: Empirical analysis of spot prices [Anomalías Financieras en el Mercado de Electricidad: Análisis empririco de los precios spot]

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