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Subject: Statistics × Author: Pushpa × End date: 2023 × Start date: 2023 × Type: Thesis × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    Volatility forecast models of prices and arrivals of tomato in APMC markets of Haryana
    (CCSHAU, Hisar, 2023-01) Pushpa; Joginder
    The majority of agricultural time series data are nonlinear, nonstationary and leptokurtic in nature. Thus, one of the most difficult areas of time series forecasting is agricultural price forecasting. Accurate forecasting assists both farmers and policymakers in making good decisions. According to the literature, each of the forecasting models has its own set of limitations. In the current study, forecasting performance of SARIMA, GARCH, ANN, Hybrid (SARIMA-GARCH and SARIMA-ANN) and multivariate time series (VAR and VARMA) models has been compared for monthly prices and arrivals of tomato in selected markets of Haryana. The purpose of the study is to give short term forecast of prices and arrivals of tomato with various forecast horizons such as one, three, six, nine and twelve months. Based on empirical results of the study, it is found that ANN models outperformed the others models for all horizon except one month ahead based on performance measures like MAPE and SEP. It is observed that Hybrid (SARIAM-ANN) models do not enhance the forecasting performance. The hybrid (SARIMA-GARCH) model outperforms the individual SARIMA and GARCH models in forecasting the prices and arrivals of tomato. It can be seen that the residuals obtained from linear SARIMA models contain the appropriate ARCH effect. The results of multivariate time series reveal that VARMA model outperforms the VAR model based on minimum values of forecasting performance measures such as MAPE and SEP.