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EN
The subject of this paper is the forecast of prices and volatility on the Day Ahead Market (DAM). The analysis was made for two portfolios of four contracts from 30.03.2009 to 28.10.2011 for two fixings on DAM. Four out of 24 contracts noted on DAM were chosen by PCA. Prices were forecast by the SARIMA models incorporating autocorrelation and seasonality. Value-at-Risk calculated through the DCC model was used to forecast volatility. These models describe well the prices and volatility on the DAM and may be used for forecasting purposes. Prices on fixing 2 are characterized by higher volatility than prices on fixing 1.
PL
Celem pracy jest przeprowadzenie analizy porównawczej ryzyka zmiany ceny oraz wolumenu obrotu na rynku energii elektrycznej oraz rynku gazu prowadzonych przez Towarową Giełdę Energii. W pracy została przeprowadzona analiza rozkładów stóp zwrotu z omawianych rynków, na podstawie której zaproponowano miary estymacji ryzyka. Na bazie oszacowanego ryzyka zostanie przeprowadzona analiza porównawcza poziomu ryzyka na poszczególnych rynkach.
EN
The aim of this paper is to carry out a comparative risk analysis of price and volume changes between electric energy contract prices and natural gas contracts quoted on Polish Power Exchange. On both markets prices are quoted continuously, and in fixings. In this paper the distribution of rates of return from both markets is analyzed. Based on this analysis, measures for estimating risk of price changes are proposed.
EN
In this paper a comparison of risk level changes of exchange company of power sector is presented. The analysis is based on data from Polish Stock Exchange (GPW) for following companies: Tauron Polska Energia SA (TPE), Polska Grupa Energetyczna SA (PGE), Polish Energy Partners SA (PEP), Zespół Elektrociepłowni Wrocławskich Kogeneracja SA (KGN) Enea SA (ENA), CEZ SA (CEZ). For these companies the portfolio with minimum Conditional Value-at-Risk (CVaR) is proposed.
PL
Celem pracy jest przeprowadzenie analizy porównawczej metod estymacji ryzyka zmiany ceny gazu oszacowanego za pomocą Value-at-Risk (VaR). W pracy do porównania efektywności estymacji ryzyka zmiany ceny gazu wybrano metodę symula-cji Monte Carlo, w której VaR traktowany jest jako kwantyl rozkładu zmiennej losowej o rozkładzie normalnym, t-Studenta, GED oraz skośnym rozkładzie t-Studenta z VaR oszacowanym z uwzględnieniem dynamiki zmienności cen gazu za pomocą liniowych oraz nieliniowych modeli szeregów czasowych AR-GARCH. Analiza porównawcza została przeprowadzona w oparciu o wyniki testu przekroczeń Kupca na podstawie logarytmicznych stóp zwrotu wartości indeksu gas_ base notowanego na Rynku Dnia Następnego (RDN) TGE w okresie od 1 stycznia do 20 listopada 2014 roku.
EN
This work is aimed at comparing methods of Value-at-Risk (VaR) estimation on Polish natural gas market. Two methods of calculating VaR were examined. One of them uses a quantile of the normal, t-Student, skewed t-Student or GED distribution. Another method is based on AR-GARCH models. Empirical analysis was carried out for logarithmic rates of return of gas-base index noted on the Day Ahead Market from 1th January to 20th November 2014. Based on Kupiec test results one may say that on Polish natural gas market VaR estimates calculated by time series models are more appropriate than VaR estimates calculated as a quantile of distribution.
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EN
The aim of this paper is the analysis of risk on Scandinavian energy market: Nord Pool Spot. The analysis is based on Value-at-Risk and Expected Shortfall. As the normality assumption for linear returns of prices has been rejected, the alternative distribution has been proposed: the alpha-stable distribution. The results shown that there are some differences between risks among submarkets of Nord Pool Spot. Moreover, the alpha- stable distribution better approximate real Value-at-Risk than normal one only if quantiles of order 0,05 and 0,95 are considered.
EN
The aim of this paper is a comparative analysis of contracts on electric energy at Polish Power Exchange (POLPX) and European Energy Exchange (EEX) spot markets. The approach considered in this article is based on minimization of the Conditional Value at Risk and maximization of portfolio rates of return. The analyzed portfolios were constructed with contracts noted on POLEX and EEX from 1st January 2011 to 31st December 2012.
EN
The aim of this paper is a comparative analysis of contract electric energy portfolios at Polish Power Exchange (POLPX) and European Energy Exchange (EEX) spot markets. The multi-criteria approach proposed in this paper is based on minimization of the Conditional Value at Risk with the confidence level 0.95 and maximization of portfolio rates of return. The analyzed portfolios have been constructed independently for each power exchange (for investors who are interested to invest on one market only), as well as for POLEX and EEX together (for investors who invest on more than one market) with two criteria.
EN
The aim of this paper is to describe and measure risk on the Polish & German Energy Market. The risk was estimated with three types of Value-at-Risk measures: VaR, stress VaR and Incremental Risk Charge (IRC). These measures were calculated on time series of logarithmic daily rates of return of indexes from the Polish Power Exchange (POLPX) andthe European Energy Exchange (EEX) spot market. Based on time series from 01.2009 to 28.09.2012 we attempted to answer the two questions: which measure is more appropriate for risk estimation, and where the risk level is higher.
PL
W artykule dokonano analizy porównawczej modeli wyboru portfeli budowanych w oparciu o miarę ryzyka CVaR (warunkowaną wartość zagrożoną). Zbadano portfele na rynkach kontraktów krótkoterminowych energii elektrycznej z wykorzystaniem liniowych dziennych stóp zwrotu cen notowanych na Towarowej Giełdzie Energii (POLPX) i Europejskiej Giełdzie Energii EEX.
EN
The aim of this paper is to show and compare different levels of risk during a day and during a week on spot markets from the Polish Power Exchange (POLPX) and the European Energy Exchange (EEX). Based on Principal Component Analysis (PCA) the classification of contracts from the two power exchanges was made. The classification was made for linear rates of return of 24 contracts listed on the power exchanges from 01.2009 to 24.10.2012. Additionally, the 24 contracts were divided into seven groups dependent on the day of a week. Based on these data sets the classification of risk during a week was made.
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