To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

Nonlinear autoregressive Markov regime-switching models are intuitive and frequently proposed time series approaches for the modelling of electricity spot prices. In this paper such models are compared to an ordinary linear autoregressive model with regard to their forecast performance. The...

Statistical learning models are proposed for the prediction of the probability of a spike in the electricity DART (day-ahead minus real-time price) spread. Assessing the likelihood of DART spikes is of paramount importance for virtual bidders, among others. The model's performance is evaluated...

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study...

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study...

In this paper, we study the methods of combining different volatility forecasts using various GARCH models. Given that the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from the fact that there is no single best model for...

Using hourly metered load and weather data, this article shows that PJM electricity consumption during the COVID-19 period declined 10.6%, leading to poor-performance of load forecasts. The costs of over-purchasing day-ahead generation were likely low in March 2020 due to mild temperatures;...

This paper uses high-frequency real-time spot prices and day-ahead forward prices from the eastern hub of the Pennsylvania-New Jersey-Maryland (PJM) electricity market to calculate, describe, and forecast realized spot price volatility. Using Heterogeneous Autoregressive models of realized...

Modelling price formation in electricity markets is a notoriously difficult process, due to physical constraints on electricity generation and flow. This difficulty has inspired the recent development of bottom-up agent-based models of electricity markets. While these have proven quite...

We examine the information content of the CBOE Crude Oil Volatility Index (OVX) when forecasting realized volatility in the WTI futures market. Additionally, we study whether other market variables, such as volume, open interest, daily returns, bid-ask spread and the slope of the futures curve,...