Description

Applied Mathematics Techniques for Energy Markets in Transition

Scientific organizers:
Matthias Ehrhardt (Wuppertal, Germany)  
Karel In ’t Hout (Antwerp, Belgium)  
Cornelis Oosterlee (Amsterdam, The Netherlands)

Description and Aim

The world is witnessing a tremendous change in its energy supply mix, demand behavior and market dynamics. Pivotal developments include ambitious climate change and environmental policies, the progressive move to sustainable energy, the (at times sudden) abandonment of polluting electricity generation, the growing availability of liquefied natural gas and shale oil and gas. This all has a significant impact on the core business and risk exposures of energy companies, on commodity and energy prices, and also on the many financial energy derivative products traded. Changes in market mechanisms and products demand novel mathematical models, stochastic and deterministic, microscopic and macroscopic models, and changing pricing techniques, defining new research areas within the field of applied mathematics.

Energy markets present unique challenges given very specific, inherent features, like (practical) non-storability of electricity, seasonality trends and dramatic price spikes, complex (often embedded) financial derivative structures, and strong dependence on fundamental factors or political decision making. Furthermore, seasonal patterns exist in demand and across various exogenous and endogenous fundamental price drivers, e.g., fuel prices, emission prices, weather conditions, market coupling mechanisms. Finally, there are often strong regulations or subsidies by governmental authorities, driven by energy and climate control policies. All of these require specially tailored mathematical modelling and methods adapted to energy market applications, e.g., forward backward stochastic differential equations (FBSDEs), Monte Carlo (MC) methods, nonlinear partial (integro) differential equations (PDEs, PIDES), high-dimensionality, sparse grids, recombination techniques, agent-based models and mean field game models.

In this workshop we wish to focus on three relevant, contemporary mathematical themes to cover the different aspects. We envision ample, lively discussions between experts in the fields of applied mathematics, computer science (heuristic algorithms, big data and machine learning), as well as economics (the impact of a major transition). This makes our foreseen workshop highly interactive and a stimulating, challenging experience.

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• Email: Martijn Fritsen
• Phone: 071 527 5542
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PhD defense Alvaro Leitao (Scientific Computing)

You are all cordially invited to the public defense of Alvaro Leitao on his PhD thesis entitled: Hybrid Monte Carlo methods in computational finance.

Promotor: Prof.dr. Kees Oosterlee

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WakEUPCall Study Week with the Financial Industry

The goal of this initiative is to bring together scholars and practitioners to work on open financial problems, trying to find out a viable solution. The ESRs of the WakEUpCall European Industrial Doctorate, their supervisors, the industrial partners and a selected group of interested participants (please feel free to apply) will devote a full week to the study of cutting-edge topics like: machine learning with car insurance data, longevity risk modeling, long-term modeling of interest rates, propagation of perturbations in financial algorithms.
Inputs and suggestions from external scholars and practitioners, willing to take part in our study week, are very welcome.
Please contact us using the registration form.
The participation in the event is free of charge, but the available placed are limited.

We hope to meet you soon in a beautiful and sunny Madrid!

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PhD Defense Qian Feng (Scientific Computing)

Everyone is invited to atttend the public defense of Qian Feng of her PhD thesis:

Advanced Estimation of Credit Valuation Adjustment

Promotor: prof.dr. Kees Oosterlee

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PhD Defence Jesse Dorrestijn (Scientific Computing)

Everyone is welcome to attend the public defense of Jesse Dorrestijn of his thesis                

'Stochastic Convection Parameterization'

Promotors: prof.dr. A.P. Siebesma en prof.dr. D.T. Crommelin

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Intreerede Daan Crommelin (UvA)

Alle belangstellenden worden uitgenodigd tot het bijwonen van de openbare rede van Daan Crommelin.

Omgaan met onzekerheden bij het maken van simulaties

Dhr. prof. dr. D.T. Crommelin, bijzonder hoogleraar Numerieke analyse en dynamische systemen

Bij het maken van computersimulaties is het van belang om zicht te krijgen op de vaak inherente onzekerheden in de uitkomst. Het incorporeren van zulke onzekerheden in simulaties en het in kaart brengen van de bandbreedte aan mogelijke uitkomsten staan centraal in de oratie van Daan Crommelin.

Er kan sprake zijn van onzekerheden ten gevolge van chaotisch gedrag, benaderingen, micro-macro-interacties, fluctuerende modelinput, onzekere parameters, enzovoorts. De belangstelling voor onzekerheden in simulaties groeit sterk binnen de toegepaste wiskunde.

Een centraal element bij dit onderwerp is de uitdaging om algoritmes te ontwerpen waarbij de benodigde rekentijd binnen de perken blijft. De vraag naar onzekerheden in simulaties is relevant voor een breed scala aan toepassingen. Crommelin gaat vooral in op simulaties van het klimaatsysteem en van energienetwerken.

Bron: UvA Persvoorlichting

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