Managing renewable energy production risk

Journal of Banking & Finance - Tập 97 - Trang 1-19 - 2018
Martin Hain1, Hans Schermeyer2, Marliese Uhrig-Homburg3, Wolf Fichtner2
1Martin Hain, BASF SE, Ludwigshafen am Rhein, Germany
2Institute for Industrial Production (IIP), Karlsruhe Institute of Technology (KIT), P.O. Box 6980, Karlsruhe D-76049, Germany
3Chair of Financial Engineering and Derivatives, Karlsruhe Institute of Technology (KIT), P.O. Box 6980, Karlsruhe D-76049, Germany

Tài liệu tham khảo

AEE, 2014, Stromgestehungskosten verschiedener erzeugungstechnologien: erneuerbare energien metaanalayse, Agentur für Erneuerbare Energien Aid, 2013, A structural risk-neutral model for pricing and hedging power derivatives, Math. Finance, 23, 387, 10.1111/j.1467-9965.2011.00507.x Alexandridis, 2013, Wind derivatives: modeling and pricing, Comput. Econ., 43, 299, 10.1007/s10614-012-9350-y Anemos, 2016 Bieger-König, 2013 Bloomberg, 2016. Bloomberg new energy finance: The global trends in renewable energy investment report (gtr) www.mmm.ucar.edu/mm5/overwiew.html. BMWi, 2016. Eeg 2016: Kernpunkte des kabinettbeschlusses vom 8.6.2016 https://www.bmwi.de/Redaktion/DE/Downloads/E/eeg-novelle-2016-kernpunkte-des-kabinettbeschlusses.pdf?__blob=publicationFile&v=4. Branger, 2011, Hedging under model misspecification: all risk factors are equal, but some are more equal than others ..., J. Futures Markets, 32, 397, 10.1002/fut.20530 Brown, 1984, Time series models to simulate and forecast wind speed and wind power, J. Clim. Appl. Meterol., 23, 1184, 10.1175/1520-0450(1984)023<1184:TSMTSA>2.0.CO;2 Brown, 2002, How firms should hedge, Rev. Financ. Stud., 15, 1283, 10.1093/rfs/15.4.1283 Bundeskartellamt, 2016. Monitoringbericht 2016 https://www.bundesnetzagentur.de/SharedDocs/Downloads/DE/Sachgebiete/Energie/Unternehmen_Institutionen/DatenaustauschUndMonitoring/Monitoring/Monitoringbericht2016.pdf?__blob=publicationFile&v=2. Bundesnetzagentur, 2015. Eeg in zahlen. https://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/ErneuerbareEnergien/ZahlenDatenInformationen/zahlenunddaten-node.html. Burger, 2004, A spot market model for pricing derivatives in electricity markets, Quant. Finance, 4, 109, 10.1088/1469-7688/4/1/010 Caporin, 2012, Modelling and forecasting wind speed intensity for weather risk management, Comput. Stat. Data Anal., 56, 3459, 10.1016/j.csda.2010.06.019 Cartea, 2005, Pricing in electricity markets: a mean-reverting jump diffusion model with seasonality, Appl. Math. Finance, 12, 313, 10.1080/13504860500117503 Cartea, 2009, Modelling electricity prices with forward looking capacity constraints, Appl. Math. Finance, 16, 103, 10.1080/13504860802351164 CBOE, 2017. Chicago board of options exchange (cboe): Volatility indices www.cboe.com/micro/volatility/. Cludius, 2014, The merit order effect of wind and photovoltaic electricity generation in germany 2008-2016: estimation and distributional implications, Energy Econ., 44, 302, 10.1016/j.eneco.2014.04.020 Cole, 2017, How does risk management influence production decisions? evidence from a field experiment, Rev. Financ. Stud, 30, 1935, 10.1093/rfs/hhw080 Cornaggia, 2013, Does risk management matter? evidence from the U.S. agricultural industry, J. Financ. Econ., 109, 419, 10.1016/j.jfineco.2013.03.004 Coulon, 2009, Stochastic behaviour of the electricity bid stack: from fundamental drivers to power price, J. Energy Markets, 2, 29, 10.21314/JEM.2009.032 Deng, 2000 Economist-Intelligence-Unit, 2011. Managing the risk in renewable energy http://digitalresearch.eiu.com/risksandrenewables/report. Ederington, 2008, Minimum variance hedging when spot price changes are partially predictable, J. Bank. Finance, 32, 654, 10.1016/j.jbankfin.2007.05.003 EEX, 2015. Eex wind power futures https://www.eex.com/en/products/weather. EEX, 2016. Eex-transparency https://www.eex-transparency.com/. EIA, 2016. Eia energy outlook 2016. https://www.iea.org. EnergyMap, 2016. Eeg-anlagenregister http://www.energymap.info/. Eydeland, 2003 Figlewski, 1984, Hedging performance and basis risk in stock index futures, J. Finance, 39, 657, 10.1111/j.1540-6261.1984.tb03654.x Füss, 2015, Electricity derivatives pricing with forward-Looking information, J. Econ. Dynam. Control, 58, 34, 10.1016/j.jedc.2015.05.016 Geman, 2006, Understanding the fine structure of electricity prices, J. Business, 79, 1225, 10.1086/500675 Grothe, 2011, Spatial dependence in wind and optimal wind power allocation: A Copula-Based analysis, Energy Policy, 39, 4742, 10.1016/j.enpol.2011.06.052 Hain, 2017 Hambly, 2009, Modelling spikes and pricing swing options in electricity markets, Quant. Finance, 9, 937, 10.1080/14697680802596856 Haushalter, 2000, Financing policy, basis risk, and corporate hedging: evidence from oil and gas producers, J. Finance, 55, 107, 10.1111/0022-1082.00202 Keles, 2013, A combined modeling approach for wind power feed-in and electricity spot prices, Energy Policy, 59, 213, 10.1016/j.enpol.2013.03.028 Ketterer, 2014, The impact of wind power generation on the electricity price in germany, Energy Econ., 44, 270, 10.1016/j.eneco.2014.04.003 Lucia, 2002, Electricity prices and power derivatives: evidence from the nordic power exchange, Review of Derivatives Research, 5, 5, 10.1023/A:1013846631785 Mora-Lopez, 1998, Multiplicative arma models to generate hourly series of global irradiation, Sol. Energy, 63, 283, 10.1016/S0038-092X(98)00078-4 Morales, 2009, A methodology to generate statistically dependent wind speed scenarios, Appl Energy, 87, 843, 10.1016/j.apenergy.2009.09.022 Papavasiliou, 2011, Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network, Oper. Res., 61, 578, 10.1287/opre.2013.1174 Perez-Gonzalez, 2013, Risk management and firm value: evidence from weather derivatives, J. Finance, 68, 2143, 10.1111/jofi.12061 PSU/NCAR, 2016 Seifert, 2007, Modelling jumps in electricity prices: theory and empirical evidence, Rev. Derivat. Res., 10, 59, 10.1007/s11147-007-9011-9 Stulec, 2017, Effectiveness of weather derivatives as a risk management tool in food retail: the case of croatia, Int. J. Financ. Stud., 5 Wagner, 2014, Residual demand modeling and application to electricity pricing, Energy J., 35, 10.5547/01956574.35.2.3 Woodard, 2008, Basis risk and weather hedging effectiveness, Agricult. Finance Rev., 68, 99, 10.1108/00214660880001221 Zhu, 2015 Ziel, 2016, Electricity price forecasting using sale and purchase curves: the x-model, Energy Econ., 59, 435, 10.1016/j.eneco.2016.08.008