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Forecasting wholesale electricity prices: A review of time series models, in "Financial Markets: Principles of Modelling, Forecasting and Decision-Making", eds. Abstract. In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. We calibrate autoregression (AR) models, including specifications(More)
A simple Ising spin model, which can describe the mechanism of price formation in financial markets is proposed. In contrast to other agent-based models, the influence does not flow inward from the surrounding neighbors to the center site, but spreads outward from the center to the neighbors. The model thus describes the spread of opinions among traders. It(More)
In this paper we study two statistical approaches to load forecasting. Both of them model electricity load as a sum of two components – a deterministic (representing seasonalities) and a stochastic (representing noise). They differ in the choice of the seasonality reduction method. Model A utilizes differencing, while Model B uses a recently developed(More)
In this paper, we present a procedure for consistent estimation of the severity and frequency distributions based on incomplete insurance data and demonstrate that ignoring the thresholds leads to a serious underestimation of the ruin probabilities. The event frequency is modelled with a non-homogeneous Poisson process with a sinusoidal intensity rate(More)
Using an agent-based modeling approach we show how personal attributes, like conformity or indifference, impact the opinions of individual electricity consumers regarding switching to innovative dynamic tariff programs. We also examine the influence of advertising, discomfort of usage and the expectations of financial savings on opinion dynamics. Our main(More)
Power-law tail behavior and the summation scheme of Levy-stable distributions is the basis for their frequent use as models when fat tails above a Gaussian distribution are observed. However, recent studies suggest that financial asset returns exhibit tail exponents well above the Levy-stable regime (0 < α ≤ 2). In this paper we illustrate that widely used(More)
In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. However, instead of evaluating point predictions we concentrate on interval forecasts. The latter are specifically important for risk management purposes where one is more interested in predicting intervals for future price movements than(More)