A Comparative Study on Time-delay Neural Network and GARCH Models for Forecasting Agricultural Commodity Price Volatility
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Title |
A Comparative Study on Time-delay Neural Network and GARCH Models for Forecasting Agricultural Commodity Price Volatility
Not Available |
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Creator |
Achal Lama
Girish K. Jha Bishal Gurung Ranjit Kumar Paul Anshu Bharadwaj Rajender Parsad |
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Subject |
Time-delay neural network
GARCH Non-parametric Combining forecasts |
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Description |
Not Available
In this paper, forecasting performance of time-delay neural network and GARCH models for predicting the volatility using monthly price series of edible oils in domestic and international markets is evaluated. An attempt has also been made to investigate whether the forecasting performance of two competing models can be improved by combining their individual forecasts. For this purpose, the individual models were combined to produce improved forecasts using non-parametric approach through the use of kernel. Further, the models were evaluated on their ability to predict the correct change of direction (CCD) for future values. Not Available |
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Date |
2017-04-13T05:44:50Z
2017-04-13T05:44:50Z 2016-04-30 |
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Type |
Research Paper
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Identifier |
Achal Lama, Girish K Jha, Bishal Gurung, Ranjit Kumar Paul, Anshu Bharadwaj and Rajender Parsad (2016). A comparative study on time-delay neural network and GARCH models for forecasting agricultural commodity price volatility. Journal of the Indian Society of Agricultural Statistics, 70(1), 7-18.
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/3606 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Indian Society of Agricultural Statistics
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