International Journal of Modern Science and Technology
August 2020, Vol. 5, No. 8, pp. 224-230.
Forecasting Volatility for Assessment of Yellow Split Peas Products: Analysis in the Frameworks of ARCH Model
Md. Anwar Hossain¹*, Kalipada Sen², Nitai Chakraborty²
¹BCSIR Laboratories, Dhaka, Bangladesh Council of Scientific and Industrial Research, Dr. Qudrat-I-Khuda Road, Dhanmondi, Dhaka-1205, Bangladesh.
²Department of Statistics, Qazi Motahar Hossain Building (3rd floor),) University of Dhaka, Dhaka 1000, Bangladesh.
*Corresponding author’s e-mail:email@example.com
Thirty analysed observations of yellow split peas products were collected from Institute of Food Science and Technology (IFST), BCSIR, Dhaka over the year 2007 to 2012 by Single Stage Cluster Sampling method. The work has explored the impact of type of Yellow Split Peas products on testing for ARCH effects and the estimation of ARCH models for analysis data. Our products comprise physiochemical analysis data for Yellow Split Peas. The corresponding p-value is >0.05, which is very high except Purity (%) and Insect damage (%) variables. So we have no difficulty to accept the null hypothesis of no ARCH error in the analysis series. The parameters of Yellow Split Peas analysis are insignificant that means no ARCH effects of the models. The estimation results are given in the Table 1. An outcome of Dickey–Fuller (DF) test confirms that the physiochemical analysis variables series is stationary except Insect damage (%). The results of Figure 1 to 9 indicate that the volatility in the Yellow split peas exhibits almost all of the variable highly volatile in this time period. Our results revealed that the ARCH model satisfactorily explains volatility and the most appropriate model for explaining volatility in the series under analysis.
Keywords: Physiochemical analysis; ARCH effects; Forecasted to Volatility; Dickey–Fuller test.
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