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This study compares the macroeconomic impacts of China and the United States on international commodity markets using a factor-augmented vector auto-regression (FAVAR) model with latent factors extracted from a rich data set that includes various macroeconomic and financial indicators at monthly frequency. The main results suggest that whether or not the Chinese demand cause commodity prices to soar depends. Macroeconomic factors of China do have significant impact on commodity markets, but the impacts of the United States outperform those of China in terms of the size of coefficients and their level of significance, as well as the direction and magnitude of directional return spillovers. Moreover, the effects of these factors on individual commodity futures are not a universal phenomenon. Therefore, there is no systematic evidence of a relationship between strong growth in the emerging economy and the boom in commodity futures prices, either statistically or economically.

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The authors consider the problem of active international portfolio management with basket options to achieve optimal asset allocation and combined market risk and currency risk management via multi-stage stochastic programming (MSSP). The authors note particularly the novel consideration and significant benefit of basket options in the context of portfolio optimization and risk management. Extensive empirical tests strongly demonstrate that basket options consistently have more clearly improvement on portfolio performances than a portfolio of vanilla options written on the same underlying assets. The authors further show that the MSSP model provides as a supportive tool for asset allocation, and a suitable test bed to empirically investigate the performance of alternative strategies.