scholarly journals Modelling and Forecasting Volatility on Electric Power Exchange SEEPEX

2021 ◽  
Author(s):  
Ivica Terzić ◽  
Zoran Jeremić ◽  
Tatjana Latas
Keyword(s):  
Time Series ◽  
Electric Power ◽  
Time Series Data ◽  
Research Question ◽  
Garch Model ◽  
Power Market ◽  
Series Data ◽  
Power Exchange ◽  
Price Movements ◽  
Forecasting Volatility

Research Question: The launch and the beginning of trade on the South East Electric Power Exchange (SEEPEX) in Belgrade, early in 2016, opened the issue of forecasting volatility and price movements in the market. Motivation: The issue is of vital importance for all market actors for the purpose of maximising profits, reducing risks, planning production and making investment decisions. Forecasting volatility and price movements in electric power markets is important for traders with profit maximisation and yield-to-risk ratio optimisation in mind and, equally, for producers, large industrial consumers, investors and portfolio managers. Idea: Exploring models and techniques to forecast volatility in electricity markets and subsequently testing statistical methods based on time series data, the ARMA-GARCH being the preferred model, with a view to identifying optimal methods for this market. The volatility of the power market and price movements have been tested during a given period. The results can be used to gauge market parameters and opportunities to extrapolate future volatility and movements in electricity prices. Data: For the purposes of this analysis, a time series involving price movements and trade volumes were used, covering a period between the SEEPEX trade launch and the end of 2019. Tools: In the empirical part of the paper, "Stata 13" statistical and econometric software was used to explore stylised facts and model the volatility of SEEPEX electricity price returns. Findings: The authors offer an overview of different methods used in the research, having selected different specifications of the ARMA-GARCH model as the most reliable in predicting volatility in the given market. The exponential GARCH model with student-t error distribution is believed to have provided the best overall performance in modelling the SEEPEX return volatility, as well as the best volatility forecast. Contribution: This is one of the first empirical studies of the Serbian power market that deals with risk modelling. Forecasting time-varying electricity exchange volatility is important for all market participants interested in variance forecasts to be used to calculate risk and hedging measures.

scholarly journals Fuzzy Time-Series Model of Electric Power Consumption

2000 ◽  
Vol 4 (3) ◽  
pp. 188-194 ◽  
Author(s):  
Kazuhiro Ozawa ◽  
◽  
’Takahide Niimura ◽  
Tomoaki Nakashima ◽  
Keyword(s):  
Time Series ◽  
Power Consumption ◽  
Electric Power ◽  
Time Series Data ◽  
Simple Procedure ◽  
Estimation Procedure ◽  
Fuzzy Time Series ◽  
Ar Model ◽  
Electric Power Consumption ◽  
Series Data

In this paper, the authors present a data analysis and estimation procedure of electrical power consumption under uncertain conditions. Tiraditional methods are based on statistical and probabilistic approaches but it may not be quite suitable to apply purely stochastic models to the data generated by human activities such as the power consumption. The authors introduce a new approach based on possibility theory and fuzzy autoregression, and apply it to the analysis of time-series data of electric power consumption. Two models, which are different in complexity, are presented, and the performance of the models are evaluated by vagueness and α-cuts. The proposed fuzzy Auoregression model represents the rich information of uncertainty that the original data contain, and it can be a powerful tool for flexible decision-making with uncertainty. The fuzzy AR model can also be constructed in relatively simple procedure compared with the conventional approaches.

scholarly journals DAMPAK KEBIJAKAN EKSPANSIF PEMERINTAH MELALUI TUNJANGAN PRESTASI KERJA (TPK) TERHADAP PERMINTAAN AGREGAT DAN INFLASI

2017 ◽  
Vol 3 (1) ◽  
pp. 70-84
Author(s):  
Ery Jayanti
Keyword(s):  
Time Series ◽  
Work Performance ◽  
Time Series Data ◽  
Research Question ◽  
Aggregate Demand ◽  
Provincial Government ◽  
Least Square ◽  
Series Data ◽  
Monthly Data ◽  
The Government

The study aimed to investigate how the effects of expansionary policies of the government through the provision of work performance benefits in the provincial government of Aceh on Aggregate Demand and Inflation. This study was conducted by using time series data for the period Januari 2010- april 2016, which is implemented in the monthly data sourced from Aceh Province Budget (DKA - ACEH), the Central Statistics Agency of Aceh (BPS-Aceh) and Bank Indonesia in Regional Financial Statistics Indicators and other institutions related to the research question. The method used was descriptive quantitative method by using Multiple Linier Regresion analysis model (OLS). This study used secondary data from Januari 2010 to april 2016. The data used was monthly data by the number of samples as many as76 months. The Results showed that there was significant effect between the expansionary policies of the government and aggregate demand, but inflation, no significally meaning that work performance insentive of the staff of the local government in Aceh would not affect. Then Fiscal Ekspansive policy implementation to do.Penelitian ini ingin melihat bagaimana pengaruh kebijakan ekspansif pemerintah melalui pemberian tunjangan prestasi kerja di Lingkungan pemerintahan Provinsi Aceh terhadap Permintaan Agregat dan Inflasi. Penelitian ini dilakukan dengan menggunakan data time series pada periode Januari 2010- April 2015, diimplementasi dalam data bulanan bersumber dari Dana Keuangan Provinsi Aceh (DKA - ACEH), Badan Pusat Statistik (BPS-Aceh) dan Bank Indonesia dalam Indikator Statistik Keuangan Daerah . Metode yang digunakan adalah Metode kuantitatif deskriptif dengan menggunakan Ordinary Least Square (OLS). Penelitian ini menggunakan data sekunder dari tahun Januari 2010 – April 2015, dengan jumlah Sampel sebanyak 76 bulan. Hasil penelitian melalui uji estimasi menunjukkan permintaan agregat secara signifikan dipengaruhi oleh pengeluaran pemerintah melalui pemberian Tunjangan Prestasi Kerja (TPK),secara positif dalam jangka panjang, Untuk variabel pengeluaran pemerintah dalam hal ini tunjangan prestasi kerja tidak berpengaruh terhadap inflasi. kesimpulannya kebijakan ekspansif ini masih bisa dijalankan.

scholarly journals Equity Return Modeling and Prediction Using Hybrid ARIMA-GARCH Model

2017 ◽  
Vol 8 (3) ◽  
pp. 154
Author(s):  
Kaiying Sun
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Model Fitting ◽  
Garch Model ◽  
Information Criterion ◽  
Equity Returns ◽  
Series Data ◽  
Arima Models ◽  
Fitting Procedure

In this paper, a hybrid ARIMA-GARCH model is proposed to model and predict the equity returns for three US benchmark indices: Dow Transportation, S&P 500 and VIX. Equity returns are univariate time series data sets, one of the methods to predict them is using the Auto-Regressive Integrated Moving Average (ARIMA) models. Despite the fact that the ARIMA models are powerful and flexible, they are not be able to handle the volatility and nonlinearity that are present in the time series data. However, the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are designed to capture volatility clustering behavior in time series. In this paper, we provide motivations and descriptions of the hybrid ARIMA-GARCH model. A complete data analysis procedure that involves a series of hypothesis testings and a model fitting procedure using the Akaike Information Criterion (AIC) is provided in this paper as well. Simulation results of out of sample predictions are also provided in this paper as a reference.

scholarly journals GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics

2001 ◽  
Vol 15 (4) ◽  
pp. 157-168 ◽  
Author(s):  
Robert Engle
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Garch Model ◽  
Applied Econometrics ◽  
Series Data ◽  
Garch Models ◽  
Portfolio Risk ◽  
Financial Applications ◽  
Analysis Of Time Series

ARCH and GARCH models have become important tools in the analysis of time series data, particularly in financial applications. These models are especially useful when the goal of the study is to analyze and forecast volatility. This paper gives the motivation behind the simplest GARCH model and illustrates its usefulness in examining portfolio risk. Extensions are briefly discussed.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

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