A note on GARCH model identification

Ghahramani, M.; Thavaneswaran, A.

doi:10.1016/j.camwa.2007.10.001

Cited by 10 publications

(5 citation statements)

References 5 publications

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“…Table 5 presents maximum likelihood estimates for the GARCH model. This model was widely used in the international literature, mainly to analyse financial and economic time series (Ghahramani and Thavanewaran 2008). It is used to model the dynamic nature of volatility by specifying the conditional mean and variance (Kumar and Moheswaran 2012).…”

Section: Resultsmentioning

confidence: 99%

Price changes of dairy products in the European Union

Bełdycka-Bórawska¹,

Bórawski²,

Guth³

et al. 2021

Agric. Econ. - Czech

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This article presents changes in the prices of milk and other dairy products in the European Union (EU). First, the descriptive statistics of the prices of milk and dairy products are presented, and then correlation and regression analyses were conducted to measure the relationships between the prices. We used the augmented Dickey-Fuller (ADF) test and generalised autoregressive conditional heteroscedasticity (GARCH) model to measure the stationarity and changes in dairy product prices in the EU. At the EU level, we checked the changes in prices of butter, skim milk powder, whole milk powder, Cheddar, Edam, Gouda, Emmental and whey powder. Our analysis confirmed that the butter, skim milk powder, whole milk powder, Cheddar, Edam and Gouda processes depend on previous values. The biggest price changes were observed in whey powder (34.12%), butter (24.46%) and skim milk powder (21.78%).

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Section: Resultsmentioning

confidence: 99%

Price changes of dairy products in the European Union

Bełdycka-Bórawska¹,

Bórawski²,

Guth³

et al. 2021

Agric. Econ. - Czech

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“…The conditional variance is independent from previous observations. Based on the obtained results, it can be concluded that modeling the series of pellet production by means of models is entirely sufficient AR (1)-GARCH (1,1) with conditional normal distribution [118][119][120].…”

Section: Discussionmentioning

confidence: 99%

Development of Solid Biomass Production in Poland, Especially Pellet, in the Context of the World’s and the European Union’s Climate and Energy Policies

et al. 2021

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The aim of this research was to present the changes in biomass production, especially pellets in Poland, in the context of world’s and European Union’s (EU) climate and energy policy, compared to other renewable energy sources. We also analyzed the law concerning the biomass production in the EU. Finally, we have elaborated the prognosis of the pellet production on the world scale. We have used different methods to achieve the goals, among which the most important are the Generalized Autoregressive Conditional Heteroscedasticity (GARCH model) and prognosis. We also compared the results of pellet production in different countries in the European Union. The results were presented in tabular and graphic form. We have received the data from Eurostat and the Main Statistical Office (MSO) in Poland. Our research proves the increase of biomass and pellet production on the global scale. Moreover, global wood pellet production increased by 972% in the years 2005–18. We can conclude that this increase was the result of increasing demand for renewable energy sources. The first research hypothesis assumed that the changes in the European Union Policy have impacted the increase of biomass production in the world. Our prognosis confirmed the second hypothesis that the development of pellets will increase as the result of increasing global demand. The use of more renewable energy sources is necessary to decrease the degradation of the environment.

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“…So, this paper will use the GARCH model to give a more accurate estimation of volatility. The GARCH model ensures that the return series is normally and conditionally distributed, and the error distrib ution is unsymmetric [4]. In the GARCH Model, the author assumes that the asset price is a discrete-time stochastic process.…”

Section: Garch Modelmentioning

confidence: 99%

Comparison of Least Square Monte Carlo Algorithm and Binomial Tree Model for Pricing American Options

Meng¹

2023

Advances in Economics, Business and Management Research

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The financial market is a rapidly growing industry where derivatives are popular among investors. The rapid growth of options trading leads to the development of various option pricing theories and models. Through them, Longstaff and Schwartz improved the Monte Carlo model in 2001. The improved least square Monte Carlo simulation (LSM) is widely used in pricing American options. This paper aims to compare two estimation methods in pricing American options, namely the Least Square Monte Carlo Algorithm and the Binomial Tree Model, and detect which model better estimates the accuracy of the operation. In a refinement of using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to measure the volatility, an empirical comparison of the models using the Copper future contract is conducted. It is found that the binomial tree method can more accurately predict the American options prediction problem, and applying it to the pricing of copper can not only improve the market but also provide a more reasonable and rapid pricing basis for its subsequent development.

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A note on GARCH model identification

Cited by 10 publications

References 5 publications

Price changes of dairy products in the European Union

Price changes of dairy products in the European Union

Development of Solid Biomass Production in Poland, Especially Pellet, in the Context of the World’s and the European Union’s Climate and Energy Policies

Comparison of Least Square Monte Carlo Algorithm and Binomial Tree Model for Pricing American Options

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