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Oil & Gas

Featured courses

AI provides a machine learning with the ability to learn and make decisions to solve problems or optimize results to meet a goal. There are many decisions to be made in the energy sector that need an early response and to handle a significant volume of data. Artificial intelligence can optimally perform these important decisions that require instantaneous collection and analysis of these large volumes of data while processing as fast and efficiently as possible.

Artificial Intelligence becomes more important in the energy industry and is having great potential for the future. Typical areas of application AI are electricity trading, smart grids, heat and transport. Prerequisites for an increased use of AI in the energy system are the digitalization of the energy sector and a correspondingly big data that is evaluable. AI helps make the energy industry more efficient and secure by analyzing and evaluating the data volumes.


Curso Intensivo y avanzado de valoración de productos derivados de renta variable, renta fija, tipo de cambio y crédito usando modelos tradicionales, inteligencia artificial y computación cuántica .


En el curso se muestran estrategias y coberturas con opciones, modelos avanzados de pricing para opciones de tipo de interés, modelos de volatilidad implícita, local, estocástica y Jump Difussion Model.


Para la valoración de las opciones de tipo de interés, hay un módulo que aborda la construcción de la Yield Curve porque es sumamente importante para la valoración de modelos de derivados de tipo de interés. Se ha actualizado la transición de Libor y la creación del SOFR yield curve que impactará el pricing de derivados y los XVA.  

Innovadoramente, se expone el uso de potentes herramientas de machine learning, particularmente las redes neuronales y el deep learning, para la valoración de derivados, calibración de ecuaciones diferenciales estocásticas, estimación de la volatilidad implícita y creación de la curva yield.

AI in Oil & Gas

Artificial Intelligence in trading helps improve forecasts. With AI, it is possible to evaluate systematically the Big data in electricity trading, such as weather data or prices. Better forecasts also increase grid stability and thus supply security. Especially in the field of forecasts, AI can help facilitate and speed up the integration of renewables. Machine Learning and specially Deep Learning play an important role in improving forecasts in the energy industry. Recently developments in forecasting quality have shown the potential of AI in this area: There is already a reduction in the demand for control reserve, even though the share of volatile power generators in the market has increased a lot.

Fermac Risk

At Fermac Risk we apply market risk and pricing methodologies for energy companies using advanced machine learning and quantum computing algorithms for forecasting energy consumption, we applied stochastic models to simulate scenarios, pricing energy derivatives, using powerful Python and R exercises.

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