English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper we aim to obtain forecasts of commodity,price movements,that can system- atically improve,upon,naive statistical benchmarks.,In doing this we revisit the forecasting performance of changes in commodity currencies as e¢ cient commodity price predictors, as emphasized in the recent literature. In addition, we consider di¤erent types of factor- augmented,models,that make,use of information,from a large dataset containing a variety of indicators of supply,and demand,conditions,across major,developed,and developing,coun- tries. These factor-augmented models either use standard principal components or, the more novel, partial least squares (PLS) regression to extract dynamic factors from the dataset. The forecasting analysis considers ten alternative indices and sub-indices of spot prices for three di¤erent commodity,classes across di¤erent periods. Of the three aforementioned,ap- proaches, the exchange rate-based model and the PLS factor-augmented model are more prone to outperform the naive statistical benchmarks, and PLS factor-augmented models usually have a slight edge over the exchange rates-based approach. However, across our range of commodity price indices we are not able to generate out-of-sample forecasts that, on average, are systematically more accurate than predictions based on a random walk or autoregressive speci…cations. Keywords: Commodity prices, forecasting, exchange rates, factor models, PLS regression.

Commodity Prices, Commodity Currencies, and Global Economic Developments