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Research Paper | Statistics | Kenya | Volume 3 Issue 11, November 2014
Statistical Modeling of Electricity Prices using Time Series Model
Mwangi Charles [2] | Prof. Ali Islam | Dr Luke Orawo | Olivia Wanjeri
Abstract: Forecasting electric power prices of a competitive market is important to providing estimates of electricity prices for future days. Forecasting results can be used by generation companies for bidding in the market strategically. The forecast can also be used by the transmission companies can plan a head for scheduling short-term generator outages and design load response programs. The aim of this study is to determine the best model for forecasting the prices of electricity in a competitive market. Thus, we will compare the AR, MA, GARCH, and ARCH model. The study also aims at providing the estimates of electricity prices based on the best model. Other variables that provide energy in the industries will be used to test on the validity of the model. The ARMAX model indicated to be the better than the GARCH model in modeling the electricity prices.
Keywords: AR-model, MA-model, GARCH-model, ARCH-model, stationary,
Edition: Volume 3 Issue 11, November 2014,
Pages: 1405 - 1409
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Research Paper, Statistics, Nigeria, Volume 10 Issue 11, November 2021
Pages: 507 - 510Modelling Auto - Crash Cases in Osun State, Nigeria
Salami Taofeek A | Adeyemi Adekunle M | Yusuf Jamal .A
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Research Paper, Statistics, Nigeria, Volume 10 Issue 8, August 2021
Pages: 734 - 744Application of Autoregressive Integrated Moving Average Intervention Model for Corruption Index in Nigeria
Sadiq Nafisatu | Nweze N. O. [2] | Ibrahim Ahmed [4] | Mohammed Rilwan [2]