Modelling and Forecasting Volatility on Electric Power Exchange SEEPEX

Research Question: The launch and the beginning of trade on South East Electric Power Exchange (SEEPEX) in Belgrade, early 2016, opened issue forecasting volatility price movements market. Motivation: is vital importance for all market actors purpose maximising profits, reducing risks, planning production making investment decisions. Forecasting electric power markets important traders with profit maximisation yield-to-risk ratio optimisation mind and, equally, producers, large industrial consumers, investors portfolio managers. Idea: Exploring models techniques to forecast electricity subsequently testing statistical methods based time series data, ARMA-GARCH being preferred model, a view identifying optimal this have been tested during given period. results can be used gauge parameters opportunities extrapolate future prices. Data: For purposes analysis, involving volumes were used, covering period between SEEPEX end 2019. Tools: In empirical part paper, "Stata 13" econometric software was explore stylised facts model returns. Findings: authors offer an overview different research, having selected specifications as most reliable predicting exponential GARCH student-t error distribution believed provided best overall performance modelling return volatility, well forecast. Contribution: This one first studies Serbian that deals risk modelling. time-varying exchange participants interested variance forecasts calculate hedging measures.