• Are day-ahead prices enough to explain and predict the next day’s natural gas demand? Evidences from the French case, with Olivier Massol and Benoît Sévi (2020) accepted for publication in The Energy Journal. (Link to article)
    The purpose of this paper is to investigate, for the first time, whether the next day’sconsumption of natural gas can be accurately forecast using a simple model that solely incorporates theinformation contained in day-ahead market data. Hence, unlike standard models that use a numberof meteorological variables, we only consider two predictors: the price of natural gas and the sparkratio measuring the relative price of electricity to gas. We develop a suitable modeling approach thatcaptures the essential features of daily gas consumption and, in particular, the nonlinearities resultingfrom power dispatching and apply it to the case of France. Our results document the existence of along-run relation between demand and spot prices and provide estimates of the marginal impacts thatthese price variables have on observed demand levels. We also provide evidence of the pivotal role ofthe spark ratio in the short run which is found to have an asymmetric and highly nonlinear impact ondemand variations. Lastly, we show that our simple model is sufficient to generate predictions thatare considerably more accurate than the forecasts published by infrastructure operators

Working papers

  • Machine learning approach in predicting α-stable noncausal processes with Fréderic Logé (2021)
  • Identifying oil supply news shocks and their effects on the global oil market with Zakaria Moussa (2021) (Link to article)
    This paper uses a new empirical strategy to identify oil supply news shocks within a Non-Causal VAR model of standard global oil market variables. These shocks explain most of the movements in oil production over a long but finite time horizon. Our findings highlight the prominent role of expectations in propagating shocks. Negative oil supply news shocks cause abrupt and permanent reactions in global oil production, global economic activity and in oil inventory. However, an oil supply shock has only a limited effect on oil price. Finally, a news shock regarding oil supply shortfalls has macroeconomic consequences, causing a substantial decline in US industrial production..
  • Real-time demand in U.S. natural gas price forecasting: the role of temperature data, with Benoît Sévi and Zakaria Moussa (2020) (Link to article)
    This paper provides evidence of the pivotal role temperature data can play in forecasting natural gas prices at the Henry Hub in real time. Considering a newly constructed temperature index as an additional exogenous variable in a Bayesian vector autoregressive (BVAR) framework significantly increases forecast accuracy at horizons of up to 12 months. Our novel approach to energy price forecasting simultaneously considers both supply and demand and incorporates temperature data as a proxy of real-time demand for natural gas.
  • Production intermittence in spot electricity markets: a behavioral simulations approach, with Albert Banal-Estanol, Olivier Massol and Augusto Ruperez Micola (2020). (DRAFT AVAILABLE)
    This paper analyzes the influence of production intermittence on spot electricity markets. More specifically, we examine how the presence of a competitive fringe operating low-cost intermittent generation assets modifies the bidding behavior of the strategic players who own the conventional (reliable) power plants. We first use game theory to derive the market outcomes obtained with perfectly rational players. We then compare them with the ones obtained when the players behave as adaptative traders who follow the Camerer and Ho (1999) behavioral model. The simulation results show that, compared to the theoretical benchmark, intermittent technologies yield lower prices when incumbents have individual market power, but are higher when they do not have it. We also run the simulations for a series of alternative specifications. The results indicate that this finding happens under different intermittency and ownership configurations. We also observe that replacing high-cost assets with low-cost ones results in prices that are higher than when they are left to co-exist
  • The role of expectations in predicting the real prices of oil: a non-causal analysis (2021). (DRAFT AVAILABLE)
    This paper revisits the predictive power of convenience yield for oil by incorporating expectations into an empirical specification through the estimation of Bayesian non-causal VAR. We empirically show that expectations play a significant role in the determination of oil prices. Second, we provide empirical evidence that real-time forecasts of real oil prices can be remarkably more accurate than the no-change forecast and significantly more accurate than real-time forecasts generated by existing structural models relying on Bayesian VAR. Beyond the traditional analysis at the monthly frequency, we further investigate the forecasting accuracy of our empirical specification at the daily and weekly frequency, resulting in interesting findings for potential investment purpose.

Academic conferences

  • 7th RCEA Times series workshop, University of Milano-Bicocca.
  • Thé des économètres, Paris, France.
  • 37th International Conference of the French Finance Association (AFFI), Nantes, France.
  • 19èmeJournée d’Économétrie, Développements Récents de l’Econométrie Appliquée àla Finance, EconomiX, Nanterre, France.
  • 2nd International Conference Environmental Economics: A Focus on Natural Re-sources,University of Orleans.
  • 13th International Conference on Computational and Financial Econometrics, London, UK
  • INFORMS Annual meeting 2019, Seattle, USA
  • 13th Annual Trans-Atlantic Infraday Conference, Washington, USA
  • 18ème Journée d’Économétrie, Développements Récents de l’Econométrie Appliquée à la Finance, EconomiX, Nanterre, France.
  • Séminaire CREST-ENSAI 2019, Rennes, France.
  • Thé des économètres, Orléans, France.
  • Workshop in Financial Econometrics, Nantes, France.
  • The 3rd Commodity Markets Winter Workshop-Leibniz University, Hannover, Germany
  • Workshop EDGE 2019, Rennes, France
  • The 2nd International Conference The Economics of Natural Gas, University Paris-Dauphine, Paris, France.
  • 12th International Conference on Computational and Financial Econometrics, Pisa, Italy
  • 41st edition of the IAEE international conference, Groningen, Netherland
  • FAEE summer workshop, Mines ParisTech, Paris, France
  • 29th European Conference On Operational Research. Valencia, Spain
  • INFORMS 2018 Annual Meeting Phoenix, USA
  • 11thAnnual Trans-Atlantic Infraday Conference, Washington, USA
  • Commodities and Energy Market Organization in the Energy Transition Context, IFP Energies nouvelles, Reuil-Malmaison, France

Other research activities

Refereeing activities

Annals of economics and statistics , Energy Journal, Energy Economics.

Conference organization
  • 43rd IAEE International Conference, Paris, France.
  • 37th International Conference of the French Finance Association (AFFI), Nantes, France