Automated Author ProfileJovani Patias
Jovani Patias
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract Recent work has shown a lack of integration between the producer and retail markets in the pork production chain. A solution to alleviate this obstacle could be performed through the dynamic hedging strategy with the Garch-DCC model, which would allow the management of daily buying and selling decisions. In this sense, the objective of the study was to verify if the model contributes efficiently to the daily price adjustments between the markets in comparison to the linear regression model, providing subsidies to producers to protect themselves from the price oscillations in the chain, reducing the risk against significant changes in prices. In order to do that, the period from 01/03/2011 to 08/27/2015 was analyzed, in which 1,156 observations were extracted for analysis. As a result, the hedge strategy for the Garch-DCC model presents better performance in comparison to the one performed by Linear Regression in reducing market oscillations. With this, this paper found an opening for the integration in the perceptions and the negotiation processes of this market in analysis.
Authors
- Jovani Patias ;
- Schlender, Sergio Guilherme ;
- Höfler, Claudio Edilberto ;
- Malheiros, Marco Antonio Da Costa ;
- Godoy, Leoni Pentiado
Abstract Recent work has shown a lack of integration between the producer and retail markets in the pork production chain. A solution to alleviate this obstacle could be performed through the dynamic hedging strategy with the Garch-DCC model, which would allow the management of daily buying and selling decisions. In this sense, the objective of the study was to verify if the model contributes efficiently to the daily price adjustments between the markets in comparison to the linear regression model, providing subsidies to producers to protect themselves from the price oscillations in the chain, reducing the risk against significant changes in prices. In order to do that, the period from 01/03/2011 to 08/27/2015 was analyzed, in which 1,156 observations were extracted for analysis. As a result, the hedge strategy for the Garch-DCC model presents better performance in comparison to the one performed by Linear Regression in reducing market oscillations. With this, this paper found an opening for the integration in the perceptions and the negotiation processes of this market in analysis.
Authors
- Jovani Patias ;
- Schlender, Sergio Guilherme ;
- Höfler, Claudio Edilberto ;
- Malheiros, Marco Antonio Da Costa ;
- Godoy, Leoni Pentiado