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Qureshi0040.pdf

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https://ir.library.oregonstate.edu/concern/conference_proceedings_or_journals/cz30pv759

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  • This study was conducted with the aim of modeling and forecasting the Indian shrimp export prices to the USA. Two major species mainly Black tiger (Penaeus monodon), white legged shrimp (Litopenaeus Vannmei) headless, shell on form, grade 16/20 were considered for the study. Published data on weekly price indicators of marine products exports (PRIME) of Marine products Exports Development Authority of India (MPEDA) for 204 weeks were collected. Multiple models were used for modeling and forecasting the price series. The results of Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model gave the best results. The other models used in this analysis and which gave higher RMSE values where ARIMA, ANN, GARCH and EGARCH. The empirical results have supported the theory that the EGARCH model can capture asymmetric volatility. Value at risk (VAR) is a widely used measure of risk and measures the maximum loss that can be incurred. However, GARCH provides a methodology to calculate the future values of standard deviation from which the VAR is derived. Thus, suitable GARCH model can produce forecasted standard deviation and also the future values of the VAR. In order to validate the predicted standard deviation from a GARCH model these predicted values were compared with the standard deviation calculated from out of sample data which became available subsequently. The results of the calculated standard deviation and the standard deviation estimated by the VAR indicated similar result. Hence GARCH can be used to forecast volatility effectively.
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file details Qureshi0040.pdf 2017-07-28 Pubblico Scaricare