Electricity Market Liquidity and Price Spikes: Evidence from Hungary

This article examines how electricity market liquidity, renewable production and cross-border activity together in combination explain price spikes the Hungarian Power Exchange day-ahead auctions. In applied logit model, dependent variable representing spike is binary, key explanatory a modified bid-ask spread depicting liquidity. Weather-dependent difference between exports imports appear as control variables model. The empirical analysis was based on data from 2017 2018. results show that have no effect model explains 96 per cent of well, with an AUC-ROC 0.75 Gini coefficient 0.5. Based results, it may be worthwhile for traders to incorporate their sales purchase curves into forecasts, this will improve chances successfully predicting extreme prices.