scholarly journals Analisis Volatilitas Harga Daging Sapi Sebelum Sampai Dengan Sesudah Hari Besar Agama di Kota Jambi

2021 ◽  
Vol 21 (1) ◽  
pp. 365
Author(s):  
Firmansyah Firmansyah ◽  
Afriani H ◽  
Wahyu Aji Paiso
Keyword(s):  
Price Volatility ◽  
Forecast Model ◽  
Model Analysis ◽  
Survey Method ◽  
Garch Models ◽  
Average Price ◽  
Future Value ◽  
Heteroscedastic Model ◽  
Beef Prices ◽  
Autoregressive Conditional Heteroscedasticity

This study aims to analyze the level of beef price volatility before fasting (D-7) to after Eid (H + 7) in Jambi City, and compile a forecast model. This study used a survey method for beef traders in the Angso Duo market, Jambi City. The analysis used to calculate the volatility of beef prices is the ARCH (Autoregressive Conditional Heteroscedastic) model analysis and the GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model analysis. The average price of beef during the period before fasting (D-7) to after Eid (H + 7) in Jambi City was IDR 124,147 per kg with the highest price of IDR 150,000 and the lowest was 110,000 per kg. The volatility of beef prices during the period before fasting (D-7) to after Eid (H + 7) in Jambi City is the highest before Eid al-Fitr (Eid). ARCH and GARCH models can predict the future value of beef prices.

scholarly journals RESIDUAL-BASED GARCH BOOTSTRAP AND SECOND ORDER ASYMPTOTIC REFINEMENT

2016 ◽  
Vol 33 (3) ◽  
pp. 779-790 ◽  
Author(s):  
Minsoo Jeong
Keyword(s):  
Second Order ◽  
Moment Condition ◽  
Garch Models ◽  
Exact Order ◽  
Block Bootstrap ◽  
Edgeworth Expansions ◽  
Coverage Probabilities ◽  
The Moment ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Reliable Methods

The residual-based bootstrap is considered one of the most reliable methods for bootstrapping generalized autoregressive conditional heteroscedasticity (GARCH) models. However, in terms of theoretical aspects, only the consistency of the bootstrap has been established, while the higher order asymptotic refinement remains unproven. For example, Corradi and Iglesias (2008) demonstrate the asymptotic refinement of the block bootstrap for GARCH models but leave the results of the residual-based bootstrap as a conjecture. To derive the second order asymptotic refinement of the residual-based GARCH bootstrap, we utilize the analysis in Andrews (2001, 2002) and establish the Edgeworth expansions of the t-statistics, as well as the convergence of their moments. As expected, we show that the bootstrap error in the coverage probabilities of the equal-tailed t-statistic and the corresponding test-inversion confidence intervals are at most of the order of O(n−1), where the exact order depends on the moment condition of the process. This convergence rate is faster than that of the block bootstrap, as well as that of the first order asymptotic test.

scholarly journals A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 1001 ◽  
Author(s):  
Oscar V. De la Torre-Torres ◽  
Dora Aguilasocho-Montoya ◽  
María de la Cruz del Río-Rama
Keyword(s):  
Markov Switching ◽  
Garch Models ◽  
Arch Model ◽  
Conditional Heteroscedasticity ◽  
Arch Models ◽  
Trading Decisions ◽  
Portfolio Managers ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Potential Use ◽  
The U.S

In the present paper we tested the use of Markov-switching Generalized AutoRegressive Conditional Heteroscedasticity (MS-GARCH) models and their not generalized (MS-ARCH) version. This, for active trading decisions in the coffee, cocoa, and sugar future markets. With weekly data from 7 January 2000 to 3 April 2020, we simulated the performance that a futures’ trader would have had, had she used the next trading algorithm: To invest in the security if the probability of being in a distress regime is less or equal to 50% or to invest in the U.S. three-month Treasury bill otherwise. Our results suggest that the use of t-student Markov Switching Component ARCH Model (MS-ARCH) models is appropriate for active trading in the cocoa futures and the Gaussian MS-GARCH is appropriate for sugar. For the specific case of the coffee market, we did not find evidence in favor of the use of MS-GARCH models. This is so by the fact that the trading algorithm led to inaccurate trading signs. Our results are of potential use for futures’ position traders or portfolio managers who want a quantitative trading algorithm for active trading in these commodity futures.

Macroeconomic Determinants of Volatility for the Gold Price in Ethiopia: The Application of GARCH and EWMA Volatility Models

2017 ◽  
Vol 18 (2) ◽  
pp. 308-326 ◽  
Author(s):  
Amare Wubishet Ayele ◽  
Emmanuel Gabreyohannes ◽  
Yohannes Yebabe Tesfay
Keyword(s):  
Interest Rates ◽  
Risk Premium ◽  
Asset Management ◽  
Mean Squared Error ◽  
Price Volatility ◽  
Absolute Error ◽  
Gold Price ◽  
Garch Models ◽  
Simple Fact ◽  
T Distribution

Modelling and forecasting of commodity price volatility has important applications for asset management, portfolio analysis and risk assessment due to the simple fact that volatility has informational content and contains signals of the market information flow. This article models and forecasts the gold price volatility using the exponentially weighted moving average (EWMA) and the generalized autoregressive conditional heteroscedasticity (GARCH) models for the period from 1998 to 2014. The gold series shows the classical characteristics of financial time series, such as leptokurtic distributions, data dependence and strong serial correlation in squared returns. Hence, the series can be modelled using both EWMA and GARCH-type models. Among the GARCH-type models, GARCH-M(2,2) with Student’s t distribution for the residuals was found to be the best-fit model. Moreover, the manuscript finds that interest rates, exchange rates and crude oil prices have a significant impact on gold volatility. The risk premium effect is found to be positive and statistically significant, suggesting increased volatility is followed by a higher mean. Finally, a comparison is made between the GARCH and the EWMA models. Using the relative mean squared error and mean absolute error measures, the empirical result suggests that GARCH models with explanatory variables are superior for volatility forecasting.

scholarly journals Modeling Pork Supply Response and Price Volatility: The Case of Greece

2009 ◽  
Vol 41 (1) ◽  
pp. 145-162 ◽  
Author(s):  
Anthony N. Rezitis ◽  
Konstantinos S. Stavropoulos
Keyword(s):  
Risk Factor ◽  
Response Function ◽  
Price Volatility ◽  
Important Risk Factor ◽  
Garch Models ◽  
Cost Factor ◽  
Supply Response ◽  
Empirical Results ◽  
Of Greece ◽  
High Uncertainty

This paper examines the supply response of the Greek pork market. A GARCH process is used to estimate expected price and price volatility, while price and supply equations are estimated jointly. In addition to the standard GARCH model, several different symmetric, asymmetric, and nonlinear GARCH models are estimated. The empirical results indicate that among the estimated GARCH models, the quadratic NAGARCH model seems to better describe producers' price volatility, which was found to be an important risk factor of the supply response function of the Greek pork market. Furthermore, the empirical findings show that feed price is an important cost factor of the supply response function and that high uncertainty restricts the expansion of the Greek pork sector. Finally, the model provides forecasts for quantity supplied, producers' price, and price volatility.

scholarly journals Human-Oriented Leadership and Organizational Commitment in US Subsidiary Company Based in Sarawak

2016 ◽  
Vol 7 (3) ◽  
pp. 233
Author(s):  
Azman Ismail ◽  
Yusniati Ishak ◽  
Munirah Hanim Yusuf
Keyword(s):  
Organizational Commitment ◽  
Least Squares ◽  
Partial Least Squares ◽  
Model Analysis ◽  
Survey Method ◽  
Participative Leadership ◽  
Supportive Leadership ◽  
The Relationship

This article was conducted to examine the relationship between human-oriented leadership (HOL) and organizational commitment. A survey method was employed to obtain data from the employees of one US subsidiary companybased in Sarawak. Results of the Partial Least Squares (SmartPLS) model analysis confirmed that participative leadership, supportive leadership, and empowerment act as important antecedents of organizational commitment.These findings reveal that the capability of managers practicing HOL styles (supportive, participative, and empowerment) has enhanced employees’ commitment to the organization.

scholarly journals ARCH and GARCH Models: Quasi-Likelihood and Asymptotic Quasi-Likelihood Approaches

2020 ◽  
Author(s):  
Raed Alzghool
Keyword(s):  
Exchange Rate ◽  
Kernel Estimation ◽  
Estimation Procedure ◽  
Conditional Variance ◽  
Estimation Methods ◽  
Garch Models ◽  
Unknown Parameters ◽  
Conditional Heteroscedasticity ◽  
Garch Processes ◽  
Autoregressive Conditional Heteroscedasticity

This chapter considers estimation of autoregressive conditional heteroscedasticity (ARCH) and the generalized autoregressive conditional heteroscedasticity (GARCH) models using quasi-likelihood (QL) and asymptotic quasi-likelihood (AQL) approaches. The QL and AQL estimation methods for the estimation of unknown parameters in ARCH and GARCH models are developed. Distribution assumptions are not required of ARCH and GARCH processes by QL method. Nevertheless, the QL technique assumes knowing the first two moments of the process. However, the AQL estimation procedure is suggested when the conditional variance of process is unknown. The AQL estimation substitutes the variance and covariance by kernel estimation in QL. Reports of simulation outcomes, numerical cases, and applications of the methods to daily exchange rate series and weekly prices’ changes of crude oil are presented.

scholarly journals Volatility clustering, risk-return relationship and asymmetric adjustment in the Finnish housing market

2020 ◽  
Vol 13 (4) ◽  
pp. 661-688 ◽  
Author(s):  
Josephine Dufitinema
Keyword(s):  
Housing Market ◽  
Portfolio Management ◽  
House Price ◽  
Significant Risk ◽  
Price Volatility ◽  
Asymmetric Adjustment ◽  
Conditional Heteroscedasticity ◽  
Content Type ◽  
Risk Return ◽  
Autoregressive Conditional Heteroscedasticity

Purpose The purpose of this paper is to examine whether the house prices in Finland share financial characteristics with assets such as stocks. The studied regions are 15 main regions in Finland over the period of 1988:Q1-2018:Q4. These regions are divided geographically into 45 cities and sub-areas according to their postcode numbers. The studied type of dwellings is apartments (block of flats) divided into one-room, two rooms and more than three rooms apartment types. Design/methodology/approach Both Ljung–Box and Lagrange multiplier tests are used to test for clustering effects (autoregressive conditional heteroscedasticity effects). For cities and sub-areas with significant clustering effects, the generalized autoregressive conditional heteroscedasticity (GARCH)-in-mean model is used to determine the potential impact that the conditional variance may have on returns. Moreover, the exponential GARCH model is used to examine the possibility of asymmetric effects of shocks on house price volatility. For each apartment type, individual models are estimated; enabling different house price dynamics, and variation of signs and magnitude of different effects across cities and sub-areas. Findings Results reveal that clustering effects exist in over half of the cities and sub-areas in all studied types of apartments. Moreover, mixed results on the sign of the significant risk-return relationship are observed across cities and sub-areas in all three apartment types. Furthermore, the evidence of the asymmetric impact of shocks on housing volatility is noted in almost all the cities and sub-areas housing markets. These studied volatility properties are further found to differ across cities and sub-areas, and by apartment types. Research limitations/implications The existence of these volatility patterns has essential implications, such as investment decision-making and portfolio management. The study outcomes will be used in a forecasting procedure of the volatility dynamics of the studied types of dwellings. The quality of the data limits the analysis and the results of the study. Originality/value To the best of the author’s knowledge, this is the first study that evaluates the volatility of the Finnish housing market in general, and by using data on both municipal and geographical level, particularly.

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