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Forecasting Electricity Prices in Deregulated Wholesale Spot Electricity Market: A Review
Murthy, Girish Godekere Panchakshara; Sedidi, Vijayalakshmi - In: International Journal of Energy Economics and Policy 4 (2014) 1, pp. 32-42
In the new framework of competitive electricity markets, all power market participants need accurate price forecasting … perspective. Short term spot electricity price forecasting techniques are either inspired from electrical engineering literature … tools. Electricity price forecasts characterize significant information that can help captive power producer, independent …
Persistent link: https://www.econbiz.de/10010734745
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Forecasting electricity prices in deregulated wholesale spot electricity market : a review
Girish, Godekere Panchakshara Murthy; Vijayalakshmi, Sedidi - In: International Journal of Energy Economics and Policy : IJEEP 4 (2014) 1, pp. 32-42
Persistent link: https://www.econbiz.de/10010234667
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Algunos tópicos econométricos de interés: Series de tiempo, pronósticos, no linealidad
Franco, Elsa M. Castro - In: REVISTA APUNTES DEL CENES (2001)
La relación entre la teoría y la políticaeconómica con la práctica y el modelamientoempírico cada día cobra másimportancia. El economista en susinvestigaciones teóricas y/o empíricasante todo debe clarificar y delimitar elcontexto específico de análisis en elcampo teórico económico...
Persistent link: https://www.econbiz.de/10010945886
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Machine-learning-based semiparametric time series conditional variance: Estimation and forecasting
Dang, Justin; Ullah, Aman - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-12
This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...
Persistent link: https://www.econbiz.de/10013201342
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Learning from Errors While Forecasting Inflation: A Case for Intercept Correction
Malik, Muhammad Jahanzeb; Hanif, Muhammad Nadim - In: International Econometric Review (IER) 11 (2019) 1, pp. 24-38
. Forecasting from such a model assuming 'no structural break' and 'correct model' is tantamount to ignoring important aspects of …) a random walk model. Optimal IC approach, though computational intensive, outperforms in forecasting next period …
Persistent link: https://www.econbiz.de/10012610973
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Machine-learning-based semiparametric time series conditional variance : estimation and forecasting
Dang, Justin; Ullah, Aman - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-12
This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...
Persistent link: https://www.econbiz.de/10012814196
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Learning from errors while forecasting inflation : a case for intercept correction
Malik, Muhammad Jahanzeb; Hanif, Muhammad Nadim - In: International econometric review 11 (2019) 1, pp. 24-38
. Forecasting from such a model assuming "no structural break" and "correct model" is tantamount to ignoring important aspects of …) a random walk model. Optimal IC approach, though computational intensive, outperforms in forecasting next period …
Persistent link: https://www.econbiz.de/10012040055
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Employing of extended characteristic surface model for forecasting of demand in tourism
Opiła, Janusz - In: Proceedings of the ENTRENOVA - ENTerprise REsearch … 6 (2020) 1, pp. 60-73
and forecasting as well as for "whatif" inferring suitable for entities of all sizes. In particular, it allows for …
Persistent link: https://www.econbiz.de/10012542166
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Forecast of facilities stock for the consequences elimination of the anthropogenic accidents
Mkhitaryan, Vladimir; Shishov, Vladimir; Kozlov, Andrey - In: Applied Econometrics 19 (2010) 3, pp. 91-100
Accidents forecast of various nature with sufficient economic damage, maximal loss enhancement, elimination of their consequences is a national wide problem It is an important concern of authorities and all levels management In order to solve this problem we need a forecast system for...
Persistent link: https://www.econbiz.de/10009291631
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MODELING & FORECASTING OF MACRO-ECONOMIC VARIABLES OF INDIA: BEFORE, DURING & AFTER RECESSION
SINHA, Pankaj; GUPTA, Sushant; RANDEV, Nakul - In: Journal of Applied Economic Sciences 6 (2011) 1(15)/ Spring 2011, pp. 43-60
This paper examines the state of the Indian economy pre, during and post-recession by analysing various macro-economic factors such as GDP, exchange rate, inflation, capital markets and fiscal deficit. We forecast some of the major economic variables using ARIMA modelling and present a picture...
Persistent link: https://www.econbiz.de/10009002541