Resumen

RAMIREZ-GARCIA, Alfredo  y  SAUCEDO, Eduardo. Hedging Electricity Price Volatility Applying Seasonal and Trend Decomposition. Anál. econ. [online]. 2022, vol.37, n.94, pp.143-166.  Epub 08-Abr-2022. ISSN 2448-6655.  https://doi.org/10.24275/uam/azc/dcsh/ae/2022v37n94/ramirez.

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.

Palabras llave : Seasonal and Trend decomposition using Loess (STL); Normal Inverse Gaussian Distribution (NIG); Electricity Price Forecasting (EPF); Wholesale Electricity Market (MEM); Electricity Hedging Valuation; C15; G10; O13; P18; Q47.

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