Time series analysis and forecasting of the prices of Indian natural rubber (Record no. 157823)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04142nam a22001697a 4500 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 630.31 |
| Item number | VEL/TI |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Velpula Jhansi Rani |
| 245 ## - TITLE STATEMENT | |
| Title | Time series analysis and forecasting of the prices of Indian natural rubber |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Vellanikkara |
| Name of publisher, distributor, etc | Department of Agricultural Statistics, College of Horticulture |
| Date of publication, distribution, etc | 2017 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 84 |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | MSc |
| 520 3# - SUMMARY, ETC. | |
| Abstract | The study entitled “Time series analysis and forecasting of the prices of<br/>Indian Natural Rubber” is primarily intended to forecast the prices for Indian<br/>Natural Rubber (NR). For forecasting the prices, firstly, domestic NR price was<br/>decomposed it into time series components. Evaluation of growth, instability<br/>and relationship between the domestic and international prices in the pre WTO<br/>and post WTO periods were carried out in this study.<br/>For decomposition of domestic NR prices into time series components,<br/>additive decomposition was tried. The data were decomposed into trend,<br/>seasonal and cyclic components. The trend values proved that there was<br/>quadratic trend over the years. Seasonality indices revealed that the highest price<br/>was in June and lowest price in December. Cyclic components showed three<br/>cycles over a period of time under investigation.<br/>For evaluation of growth and instability, volatility and instability<br/>analyses were carried out for pre-WTO, post-WTO and overall periods in terms<br/>of rupees as well as dollars. Two types of volatility i.e., intra-annual volatility<br/>(within year dispersion) and inter annual volatility (between year dispersion)<br/>were calculated. Intra-annual and inter annual volatility were higher in post-<br/>WTO for international and domestic NR price series and the crude oil price<br/>showed higher volatility in pre-WTO period in terms of rupees as also in dollars.<br/>GARCH (1,1) model gave an additional evidence for persistence of volatility. It<br/>proved that the volatility persisted in the overall period in terms of rupees and<br/>dollars for domestic and international NR price. Instability analysis showed that<br/>the price instability in post-WTO period was almost double than that of pre-<br/>WTO period and it tripled in the overall period in terms of rupees. In terms of<br/>dollars, the instability in post-WTO and overall period was almost triple than<br/>pre-WTO period for domestic and international NR prices and crude oil prices<br/>showed almost double instability than pre-WTO period.<br/>iii<br/>The relationship between domestic and international NR prices were<br/>analysed through cointergration analysis and Vector error correction model<br/>(VECM). The direction of relation was drawn by Granger Causality test.<br/>Cointegration and Granger Causality test proved that there was at least<br/>unidirectional relationship among the variables. VECM analysis proved that<br/>there was long run relationship between domestic NR price, international NR<br/>price and crude oil price. It revealed that, a speed rate of adjustment 14.3 per<br/>cent was required for domestic NR price series to correct its previous period.<br/>There were many general factors affecting the prices of domestic NR like<br/>synthetic rubber production, crude oil prices, international rubber demand and<br/>supply, international transactions, exchange rates, natural factors and<br/>development of automobile industries. Stepwise regression analysis was used to<br/>sort out the factors affected in pre-WTO and post-WTO periods. In pre-WTO,<br/>domestic NR price was affected by international NR prices and in post-WTO by<br/>international NR prices and SR consumption.<br/>Domestic NR prices were forecasted with three different models like<br/>Stepwise regression method, ARIMA and SARIMA models. Stepwise<br/>regression method could be predicted when the variables like international NR<br/>prices and import value of NR were available. Among ARIMA and SARIMA<br/>models, ARIMA (4,1,4) and (4,1,4) (1,0,1) 12 was found to be best judged as per<br/>different statistical criteria for assessing the model fit and model adequacy.<br/> |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Agricultural Statistics |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Krishnan, S (Guide) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://krishikosh.egranth.ac.in/handle/1/5810138143 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Item type | Theses |
| Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|
| Not For Loan | Reference Book | KAU Central Library, Thrissur | KAU Central Library, Thrissur | Theses | 04/12/2017 | 630.31 VEL/TI | 173994 | 04/12/2017 | Theses |