Hedging Electricity Price Volatility Applying Seasonal and Trend Decomposition
The Wholesale Electricity Market (MEM) has allowed participants to trade electricity at Local Marginal Price (LMP); therefore, developing hedging models to face high volatility electricity prices and avoid financial losses has become essential. This work proposes a methodology based on the Seasonal...
| Authors: | ; |
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| Format: | Article |
| Status: | Published version |
| Publication date: | 2022 |
| Country: | México |
| Institution: | ITESM |
| Repository: | Redalyc-ITESM |
| OAI Identifier: | oai:redalyc.org:41370350009 |
| Online Access: | https://www.redalyc.org/articulo.oa?id=41370350009 https://www.redalyc.org/journal/413/41370350009/ https://www.redalyc.org/journal/413/41370350009/html/ https://www.redalyc.org/journal/413/41370350009/41370350009.epub https://www.redalyc.org/journal/413/41370350009/movil |
| Access Level: | Open access |
| Keyword: | Economía y Finanzas C15 G10 O13 P18 Q47 |
| Summary: | The Wholesale Electricity Market (MEM) has allowed participants to trade electricity at Local Marginal Price (LMP); therefore, developing hedging models to face high volatility electricity prices and avoid financial losses has become essential. This work proposes a methodology based on the Seasonal and Trend Decomposition Model (STL) to the LMP returns series, which is fitted into NIG distribution by obtaining empirical NIG parameters from LMP returns using Maximum Likelihood Estimation (MLE) to generate a simulated NIG distributed series. Finally, the goodness-of-fit test is estimated to demonstrate that empirical data can be fitted into NIG Distribution. This work should be considered the first Electricity Hedging Valuation Methodology for the MEM. Results obtained show that electricity price returns can be fitted and simulated by NIG distribution even through economic crisis periods. The analysis period is from 29/01/2016 to 09/07/2021. |
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