The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling

Saâdaoui, Foued

doi:10.1007/s10614-012-9346-7

Cited by 22 publications

(24 citation statements)

References 20 publications

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“…Voronin et al have designed an ANN‐based hybrid methodology, which has the ability to predict the occurrence of normal range prices and price spikes in the electricity market. Other strategies have used preprocessing techniques to extract the smooth parts of the stochastic processes. Once extracted and modelled, smooth parts are exactly extrapolated on several temporal horizons before adding their corresponding forecast values.…”

Section: Previous Researchmentioning

confidence: 99%

“…They have demonstrated that the volume is confirmed to be always significant and positive in zones. Last but not least, Saâdaoui used wavelet–cross‐correlation tools to analyse the relationship between prices and trading volume at different frequency levels. The significant results led the author to define an efficient multiscale VAR model aiming to forecast both prices and volumes.…”

Section: Previous Researchmentioning

confidence: 99%

“…We can mention among the best known, the approach developed by Granger in 1969, which is the most commonly used in the empirical economics studies. The causality notion can be simply summarized in the fact that a variable Y 1 t causes another variable Y 2 t , if Y 1 t contains information to improve forecasting Y 2 t . When this relationship is also validated in the opposite direction, the causality is said bidirectional.…”

Section: Empirical Modellingmentioning

confidence: 99%

“…With the introduction of the competition and emergence of the electricity exchange, the level of risk borne by the electricity companies, electricity producers, and traders has increased considerably. As a result, consumers become free to choose their suppliers, and electricity is bought and sold at market prices like any other commodity . The liberalization of these markets has not only led to new challenges for market participants but also to create new fields of research.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, consumers become free to choose their suppliers, and electricity is bought and sold at market prices like any other commodity. [3][4][5] The liberalization of these markets has not only led to new challenges for market participants but also to create new fields of research. Today, many works are trying to understand the prices' dynamics, the stylized facts, and the coevolution with some other variables (volume of transactions, production, temperature, etc) in the most important markets.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic modelling of the price‐volume relationship in electricity markets: Evidence from the Nordic energy exchange

Saâdaoui

Mrad

2017

Int Trans Electr Energ Syst

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Summary The analysis of the interactions between price and transaction volume, conducted as part of a financial market, is one of the central themes of the financial theory. However, with the emergence of power exchanges and despite the expansion of the research sphere in this context, this issue had not been sufficiently addressed. This is due to not only the lack of concepts in theory but also to the peculiarity of price dynamics. The purpose of this paper is to shed light on the nature of the relationship between price changes and trading volume in the Nordic power market (Nord Pool), which is one of the largest energy markets worldwide. Through statistical timing analysis of the price‐volume covariation, we reconsider this joint modelling, but only settling for daily observations, which makes the specificity of this work. Contrary to most comparable works, which were based on high frequency data, we chose to omit intraday observations to circumvent the repercussion of the daily seasonality on one side and ensure more lucidity and clairvoyance to a wider horizon on the other. The empirical results go in line with our expectations and provide support for the claim that there exists a significant reciprocal causality between prices and trading volume.

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Section: Previous Researchmentioning

confidence: 99%

Section: Previous Researchmentioning

confidence: 99%

Section: Empirical Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stochastic modelling of the price‐volume relationship in electricity markets: Evidence from the Nordic energy exchange

Saâdaoui

Mrad

2017

Int Trans Electr Energ Syst

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Multiscaled causality of infections on viral testing volumes: The case of COVID‐19 in Tunisia

Saâdaoui

Rabbouch

Saadaoui

et al. 2022

Health Planning & Management

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Objectives Coronavirus disease (COVID‐19) is one of the most detrimental pandemics that affected the humanity throughout the ages. The irregular historical progression of the virus over the first year of the pandemic was accompanied with far‐reaching health and social damages. To prepare logistically against this worsening disaster, many public authorities around the world had set up screening and forecasting studies. This article aims to analyse the time‐frequency co‐evolution of the number of confirmed cases (NCC) in Tunisia and the related number of performed polymerase chain reaction (PCR) tests over the COVID‐19 first year. Accurately predicting such a relationship allows Tunisian authorities to set up an effective health prevention plan. Study Design In order to keep pace with the speed of evolution of the virus, we used uninterrupted daily time series from the Tunisian Ministry of Public Health (TMPH) recorded over the COVID‐19 first year. The objective is to: (1) analyse the time‐frequency progress of the NCC in relationship with the number of PCR tests, (2) identify a multi‐scale two‐factor stochastic model in order to develop a robust bivariate forecasting technique. Methods We assume a bivariate stochastic process which is projected onto a set of wavelet sub‐spaces to investigate the scale‐by‐scale co‐evolvement the NCC/PCR over the COVID‐19 first year. A wavelet‐based multiresolutional causality test is then performed. Results The main results recommend the rejection of the null hypothesis of no instantaneous causality in both directions, while the statistics of the Granger test suggest failing to reject the null hypothesis of non‐causality. However, by proceeding scale‐by‐scale, the Granger causality is proven significant in both directions over varying frequency bands. Conclusions It is important to include the NCC and PCR variables in any time series model intended to predict one of these variables. Such a bivariate and multi‐scale model is supposed to better predict the needs of the public health sector in screening tests. On this basis, testing campaigns with multiple periodicities can be planned by the Tunisian authorities.

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A seasonal feedforward neural network to forecast electricity prices

Saâdaoui

2016

Neural Comput & Applic

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The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling

Cited by 22 publications

References 20 publications

Stochastic modelling of the price‐volume relationship in electricity markets: Evidence from the Nordic energy exchange

Stochastic modelling of the price‐volume relationship in electricity markets: Evidence from the Nordic energy exchange

Multiscaled causality of infections on viral testing volumes: The case of COVID‐19 in Tunisia

A seasonal feedforward neural network to forecast electricity prices

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