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Robust estimation and forecasting of the long-term seasonal component of electricity spot prices
Nowotarski, Jakub; Tomczyk, Jakub; Weron, Rafał - In: Energy Economics 39 (2013) C, pp. 13-27
We present the results of an extensive study on estimation and forecasting of the long-term seasonal component (LTSC … are significantly better in terms of forecasting spot prices up to a year ahead than the commonly used monthly dummies and …
Persistent link: https://www.econbiz.de/10011039659
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Modelling and forecasting rig rates on the Norwegian Continental Shelf
Skjerpen, Terje; Storrøsten, Halvor Briseid; … - 2015
Knowledge about rig markets is crucial for understanding the global oil market. In this paper we first develop a simple bargaining model for rig markets. Then we examine empirically the most important drivers for rig rate formation of floaters operating at the Norwegian Continental Shelf in the...
Persistent link: https://www.econbiz.de/10011968602
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Electricity demand analysis and forecasting: A panel cointegration approach
El-Shazly, Alaa - In: Energy Economics 40 (2013) C, pp. 251-258
This article analyzes the demand for electricity and provides out-of-sample forecasting at the sectoral level using a … one would expect if the forecasting relationship is stationary. The long-run parameter estimates are then used to conduct … ex-ante forecasting under plausible assumptions for policy making. …
Persistent link: https://www.econbiz.de/10010718767
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Forecasting Implied Volatility Surfaces
Audrino, Francesco; Colagelo, Dominik - School of Economics and Political Science, Universität … - 2007
We propose a new semi-parametric model for the implied volatility surface, which incorporates machine learning algorithms. Given a starting model, a tree-boosting algorithm sequentially minimizes the residuals of observed and estimated implied volatility. To overcome the poor predicting power of...
Persistent link: https://www.econbiz.de/10005453978
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Predicting the global minimum variance portfolio
Reh, Laura; Krüger, Fabian; Liesenfeld, Roman - 2020
We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...
Persistent link: https://www.econbiz.de/10012243462
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Predicting the global minimum variance portfolio
Reh, Laura; Krüger, Fabian; Liesenfeld, Roman - 2020
We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...
Persistent link: https://www.econbiz.de/10012250683
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Biofuels and food prices: Searching for the causal link
Bastianin, Andrea; Galeotti, Marzio; Manera, Matteo - 2013
We analyze the relationship between the prices of ethanol, agricultural commodities and livestock in Nebraska, the U.S. second largest ethanol producer. The paper focuses on long-run relations and Granger causality linkages between ethanol and the other commodities. The analysis takes possible...
Persistent link: https://www.econbiz.de/10010294304
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Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices
Raviv, Eran; Bouwman, Kees E.; van Dijk, Dick - 2013
The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This...
Persistent link: https://www.econbiz.de/10010326529
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Forecasting daily electricity prices with monthly macroeconomic variables
Foroni, Claudia; Ravazzolo, Francesco; Rossini, Luca - 2019
forecasting daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed …-frequency models, introducing a Bayesian approach to reverse unrestricted MIDAS models (RU-MIDAS). We study the forecasting accuracy …
Persistent link: https://www.econbiz.de/10012142094
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What do market-calibrated stochastic processes indicate about the long-term price of crude oil?
Hahn, Warren J.; DiLellio, James A.; Dyer, James S. - In: Energy Economics 44 (2014) C, pp. 212-221
problems. In this paper, we focus on modeling and forecasting the long-term price level, since it is the dominant factor in …
Persistent link: https://www.econbiz.de/10011100087