Commodity and energy markets break the assumptions that equity research takes for granted: the underlying is physical, storage and delivery matter, prices spike and mean-revert on seasonal and weather cycles, and in electricity the asset cannot be stored at all. That is why this literature has its own models — futures-curve dynamics, storage-constrained pricing, spike-jump processes for power, and the carbon-market mechanics of emission allowances — and why volatility and forecasting results from equities rarely transfer.
The rigor split here is stark. Forecasting papers (oil, gas, power prices) often test against naïve and seasonal baselines on real data and score well. Pricing and hedging papers for structured energy contracts tend to be theory-first. When a paper claims a trading result, check whether it uses tradable front-month contracts with roll costs or a spliced continuous series that never existed, and whether the sample includes 2020–2022, the stress test nothing in this market escaped.
Related hubs: Volatility, Options & Derivatives, Machine Learning for Forecasting, Risk Management.
Agricultural products play a critical role in human development. With economic globalization and the financialization of agricultural products continuing to advance, the interconnections between different agricultural futures have become closer. We utilize a TVP-VAR-DY model combined with the quanti
Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue tha
In this work, we study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering the two benchmark crude oil futures (Brent and WTI) together with the newly introduced Shanghai crude oil futures. We
The Nelson-Siegel framework is employed to model the term structure of commodity futures prices. Exploiting the information embedded in the level, slope and curvature parameters, we develop novel investment strategies that assume short-term continuation of recent parallel, slope or butterfly movemen
Aggregated curves are common structures in economics and finance, and the most prominent examples are supply and demand curves. In this study, we exploit the fact that all aggregated curves have an intrinsic hierarchical structure, and thus hierarchical reconciliation methods can be used to improve
In this study the cross-correlations between the cryptocurrency market represented by the two most liquid and highest-capitalized cryptocurrencies: bitcoin and ethereum, on the one side, and the instruments representing the traditional financial markets: stock indices, Forex, commodities, on the oth
In this paper, we discuss the Dutch power market, which is comprised of a day-ahead market and an intraday balancing market that operates like an auction. Due to fluctuations in power supply and demand, there is often an imbalance that leads to different prices in the two markets, providing an oppor
The twenty-first century’s transformative technology, artificial intelligence, is increasingly constrained by the twentieth century’s transformative technology, the electricity grid. Rapid growth in electricity demand from data centers is leading to higher electricity prices, without a compensating
Accurate and efficient imbalance electricity price forecasting is critical for industrial energy trading systems, especially as battery assets and automated bidding pipelines increasingly participate in balancing markets. However, real-time forecasting is complicated by nonlinear market-rule-based p
In recent years, a rapid development of forecasting methods has led to an increase in the accuracy of predictions. In the literature, forecasts are typically evaluated using metrics such as Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). While appropriate for statistical assessment, th
We study the price impact of storage facilities in electricity markets and analyze the long-term profitability of these facilities in prospective scenarios of energy transition. To this end, we begin by characterizing the optimal operating strategy for a stylized storage system, assuming an arbitrar
This study focuses on the application of the Heston model to option pricing, employing both theoretical derivations and empirical validations. The Heston model, known for its ability to incorporate stochastic volatility, is derived and analyzed to evaluate its effectiveness in pricing options. For p
Battery energy storage systems (BESS) participating in multi-market electricity trading require price forecasts to optimize dispatch decisions. A widely held assumption is that forecast accuracy, measured by standard metrics such as mean absolute error (MAE), drives trading performance. We challenge
Mobilising private capital is a critical bottleneck of the energy transition, yet recent crisis-driven windfall profits for fossil power firms suggest that market signals may still favour carbon-intensive assets. Here we analyse a panel of 900 European power firms (2001-2023) to resolve whether thes
Accurate mid-term (weeks to one year) hourly electricity load forecasts are essential for strategic decision-making in power plant operation, ensuring supply security and grid stability, planning and building energy storage systems, and energy trading. While numerous models effectively predict short
This paper develops a coupled model for day-ahead electricity prices and average daily temperature which allows to model quanto weather and energy derivatives. These products have gained on popularity as they enable to hedge against both volumetric and price risks. Electricity day-ahead prices and a
Carbon futures has recently emerged as a novel financial asset in the trading markets such as the European Union and China. Monitoring the trend of the carbon price has become critical for both national policy-making as well as industrial manufacturing planning. However, various geopolitical, social
On April 20, 2020, the May front-month WTI oil futures contract, one day before its expiration date, opened near $$17/$barrel and dropped far below zero in a single trading day, reaching an intraday low of $-$40.32$ and settling at $-$37.63$. Such market behavior was unforeseen at the time. This
We present an approximate dynamic programming framework for designing degradation-aware market participation policies for battery energy storage systems. The approach employs a tailored value function approximation that reduces the state space to state of charge and battery health, while performing
Energy storage promotes the integration of renewables by operating with charge and discharge policies that balance an intermittent power supply. A key challenge in this emerging sector is how to optimize the operation of storage assets given future price uncertainties and the need to recover the cos