Stochastic multifactor modeling of spot electricity prices

Date

2014-03-15

Author

Hayfavi, Azize

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

190
views

0
downloads

In this paper, a stochastic multifactor model is proposed for modeling of the daily spot market electricity prices. Stochastic part of the model is composed of three jump processes and a Brownian motion where two of the jump processes are assumed to be mean reverting with different mean reversion rates. The multistep algorithm proposed for model estimation utilizes an iterative threshold function (constructed on GARCH(1,1) volatility estimates) in separation of the jumps. The factor model is applied to Turkish day ahead electricity market. In order to evaluate the performance of the proposed multifactor model, estimation results are also compared to the results acquired by application of mean reverting jump diffusion model of Cartea and Figueroa (2005) and Markov regime switching model of Janczura and Weron (2010) to the same data set.

Subject Keywords

GARCH(1.1), Threshold, Jump process, Stochastic multifactor model, Electricity spot price

URI

https://hdl.handle.net/11511/30880

Journal

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

DOI

https://doi.org/10.1016/j.cam.2013.10.008

Collections

Graduate School of Applied Mathematics, Article

Suggestions

OpenMETU
Core

Hydro-Optimization-Based Medium-Term Price Forecasting Considering Demand and Supply Uncertainty İLSEVEN, Engin; Göl, Murat (2018-07-01) This paper proposes an electricity market model of Turkish electricity market for monthly and yearly electricity price forecasting in medium-term by means of supply and demand dynamics formed via a theoretical approach. The electricity market model created within this scope consists of three main components related to electricity demand, supply, and price segments along with hydro optimization submodel, which takes into account the nonlinear relation between supply and price. Electricity price is determined...
Stochastic volatility and stochastic interest rate model with jump and its application on General Electric data Celep, Betül; Hayfavi, Azize; Department of Financial Mathematics (2011) In this thesis, we present two different approaches for the stochastic volatility and stochastic interest rate model with jump and analyze the performance of four alternative models. In the first approach, suggested by Scott, the closed form solution for prices on European call stock options are developed by deriving characteristic functions with the help of martingale methods. Here, we study the asset price process and give in detail the derivation of the European call option price process. The second appr...
Stochastic approach in reserve estimation Ülker, Emine Buket; Kök, Mustafa Verşan; Department of Petroleum and Natural Gas Engineering (2004) Geostatistics and more specifically stochastic modeling of reservoir heterogeneities are being increasingly considered by reservoir analysts and engineers for their potential in generating more accurate reservoir models together with usable measures of spatial uncertainty. Geostatistics provides a probabilistic framework and a toolbox for data analysis with early integration of information. The uncertainty about the spatial distribution of critical reservoir parameters is modeled and transferred all the way...
Optimal bidding strategies for day ahead electricity market by risk constrained stochastic price based unit commitment Shileh Baf, Amir; Ulusoy, İlkay; Tör, Osman Bülent; Department of Electrical and Electronics Engineering (2014) Optimum bidding curves for a generating company to take part in the day ahead energy market are developed throughout this thesis. Continuous aim of the generating company to maximize its profit will be partly fulfilled by optimizing its bidding in the market. Price uncertainty has always been a major issue for proper bidding and maximizing the payoff. In contrast with traditional Price Based Unit Commitment which is only dependent on a good forecast of energy prices, stochastic programming takes care of the...
An empirical evidence for generalized shrinkage methods: application of bagging in day-ahead electricity price forecasting and factor augmentation . Özen, Kadir; Yıldırım Kasap, Dilem; Department of Economics (2020) Fundamental dynamics behind electricity prices are multi-dimensional and elaborate. A popular approach to forecasting electricity price is to utilize large number of predictors. In this study, using the day-ahead electricity price data from commonly studied markets of five major series and GEFCom2014 data, a variant of shrinkage method, Bootstrap Aggregation (bagging) is proposed to incorporate information from available predictors. Bagging manifests itself as a computationally simpler alternative to common...

Citation Formats

A. Hayfavi, “Stochastic multifactor modeling of spot electricity prices,” JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, pp. 434–442, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30880.