Forecasting volatility in sub-Saharan Africa’s commodity markets

Simple item page
dc.contributor.authorOcran, Matthew Kofi
dc.contributor.authorBiekpe, Nicholas
dc.date.accessioned2021-04-16T12:23:52Z
dc.date.available2021-04-16T12:23:52Z
dc.date.issued2007
dc.description.abstractUsing spot prices from eighteen commodities traded by most Sub-Saharan African countries, this paper evaluates the out-of-sample volatility forecasting efficiency of seven models. The models evaluated included random walk, simple regression and five models from the ARCH family of models. Standard loss functions are used to examine the relative performance of the competiting models. The non-ARCH family of models consistently outperformed the ARCH family of models on all the evaluation criteria. Of the two non-ARCH family of models, the autoregressive model was superior. The results of the study suggest that government agencies in Sub-Saharan Africa that manage inflows from commodity markets can use autoregressive models in predicting volatility of inflows. Again, risk management strategies will be best served with autoregressive models.en_US
dc.identifier.citationOcran, M. K., & Biekpe, N. (2007). Forecasting volatility in sub-Saharan Africa’s commodity markets. Investment Management and Financial Innovations 4(2), 91-102en_US
dc.identifier.other0000 0004 6439 8257
dc.identifier.urihttp://hdl.handle.net/10566/6071
dc.language.isoenen_US
dc.publisherBusiness Perspectivesen_US
dc.subjectsub-Saharan Africaen_US
dc.subjectVolatility forecasten_US
dc.subjectModel evaluationen_US
dc.subjectCommodity spot pricesen_US
dc.subjectMarketsen_US
dc.titleForecasting volatility in sub-Saharan Africa’s commodity marketsen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Ocran, M.K_Forecasting volatility in Sub-Saharan Africas commodity markets_2007.pdf
Size:
160.46 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Research Articles (Economics)