Rafal Weron
Associate Editor of Computational Statistics, Journal of Energy Markets, and Surveys in Mathematics and its Applications, his research focuses on risk management and forecasting in the power markets and computational statistics as applied to finance and insurance. His other interests include stochastic modeling, time series, heavy tailed distributions, and computer simulations of highly volatile phenomena.
Articles by this Author
Modeling highly volatile and seasonal markets: evidence from the Nord Pool electricity market
- By Rafal Weron
- Published 01/7/2008
- Price modeling
- Unrated
Keywords: electricity price, mean-reversion, Wavelet transform, Jump diffusion model
Published in: Applications of econophysics
Publication year: 2004
Co-author 1: Ingve Simonsen
Co-author 2: Piotr Wilman
In this paper we address the issue of modeling spot electricity prices. After analyzing factors leading to the unobservable in other financial or commodity markets price dynamics we propose a mean reverting jump diffusion model. We fit the model to data from the Nord Pool power exchange and find that it nearly duplicates the spot price’s main characteristics. The model can thus be used for risk management and pricing derivatives written on the spot electricity price.
Published in: Applications of econophysics
Publication year: 2004
Co-author 1: Ingve Simonsen
Co-author 2: Piotr Wilman
In this paper we address the issue of modeling spot electricity prices. After analyzing factors leading to the unobservable in other financial or commodity markets price dynamics we propose a mean reverting jump diffusion model. We fit the model to data from the Nord Pool power exchange and find that it nearly duplicates the spot price’s main characteristics. The model can thus be used for risk management and pricing derivatives written on the spot electricity price.
Forecasting spot electricity prices with time series models
- By Rafal Weron
- Published 01/28/2008
- Forecasting , Price modeling
- Unrated
Keywords:
Published in:
Publication year: 2005
Co-author 1: Adam Misiorek
In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period proceeding and including the market crash.
Published in:
Publication year: 2005
Co-author 1: Adam Misiorek
In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period proceeding and including the market crash.
Heavy tails and electricity prices
- By Rafal Weron
- Published 01/28/2008
- Price modeling
- Unrated
Keywords:
Published in:
Publication year: 2005
In the first years after the emergence of deregulated power markets it became apparent that for the valuation of electricity derivatives we cannot simply rely on models developed for financial or other commodity markets. However, before adequate models can be put forward the unique characteristics of electricity (spot) prices have to be thoroughly analyzed. In particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of returns. In this paper we first analyze the stylized facts of electricity prices, then present two modeling approaches: jump-diffusion and regime-switching, which to some extent address the pertinent issues.
Published in:
Publication year: 2005
In the first years after the emergence of deregulated power markets it became apparent that for the valuation of electricity derivatives we cannot simply rely on models developed for financial or other commodity markets. However, before adequate models can be put forward the unique characteristics of electricity (spot) prices have to be thoroughly analyzed. In particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of returns. In this paper we first analyze the stylized facts of electricity prices, then present two modeling approaches: jump-diffusion and regime-switching, which to some extent address the pertinent issues.
