STAT3170 Stochastic Methods of Energy Markets (5 op)

Verkosto-opintojakso

Verkosto: Vaasan korkeakoulukonsortio

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Verkosto: Matematiikan ja tilastotieteen syventävien kurssien ristiinopiskelu

Tämä opintojakso on tarjolla Matematiikan syventävät opinnot -ristiinopiskeluverkostossa. Verkoston opinnot ovat tarjolla seuraaville opiskelijoille:

  • Matematiikan kandidaattiohjelma
  • Matematiikan maisteriohjelma
  • Matematiikan aineenopettajien kandidaattiohjelma
  • Matematiikan aineenopettajien maisteriohjelma
  • Matematiikan, kemian tai fysiikan aineenopettajan ja luokanopettajan kandidaattiohjelma (matematiikan opintosuunta)
  • Matematiikan, kemian tai fysiikan aineenopettajan ja luokanopettajan maisteriiohjelma (matematiikan opintosuunta)
  • Matematiikan ja tilastotieteen tohtoriohjelma
  • Matemaattisten tieteiden ja luonnontieteiden tohtoriohjelma (matematiikan opintosuunta)

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Arviointiasteikko:
0-5
Suorituskieli:
englanti

Kuvaus

5.1 1. Introduction to Energy Markets. 1.1 Stylized facts in energy markets, 1.2 Basic contracts (day-ahead prices, forward prices, swaps). 1.3 Derivative contracts for physical assets: calls/puts, Asians, spreads, power plants, swings, storages, weather derivatives. 2. Forward Models: Brownian Motion 2.1. Brief recap on Ito calculus. 2.2. Black-Scholes-Merton and Black 76 formulas. 2.3. Brownian motion and geometric Brownian notion. Multi- factor forward models. 3. Spot Models: Ornstein-Uhlenbeck Processes 5.1. Ornstein-Uhlenbeck processes, one-factor spot models. 5.2. Multi-factor spot models, regime-switching models. 4. Some Notes on Lévy and Jump-diffusion Processes 4.1. Jump-diffusion processes, e.g. compound Poisson, Kou model. 4.2. Pure jump processes, e.g. Gamma, IG, VG, and NIG. 5. Pricing Contracts in practice 5.1. Monte Carlo methods in Python. 5.2. Pricing spread options. 5.3. Pricing weather derivatives 4. Pricing Storages

Osaamistavoitteet

The liberalization of energy markets in many regions has led to new electricity and gas markets with increasing trading volumes. Producers have started trad- ing energy, and particularly after the 2007/2008 financial crisis, they are now subject to regulations similar to those in the banking industry. Consequently, the modeling of physical assets, like hydro power plants or gas-fired plants, is addressed using real option approaches from financial mathematics. Energy and commodity markets exhibit unique characteristics and are based on different fundamentals than pure financial markets. Energy and commodity prices often depend on physical constraints and are seen as volatile and erratic. These aspects require robust and complex mathematical modeling by risk man- agement units and trading desks. This course provides students with a solid foundation in stochastic methods for energy markets, equipping them with both theoretical and computational skills suited for careers as quantitative analysts, risk managers, or traders in commodity trading houses, energy companies, banks, insurance firms, and con- sulting companies.

Esitietojen kuvaus

(Recommended) • Probability • Stochastic Analysis • Basic Programming in Python