Commodities, Volume 1, Issue 1 (September 2022) – 5 articles

This paper examines the relevancy of price measurement for characterizing the relation between real oil prices and real exchange rates. The current empirical literature shows a consensus on using the U.S. CPI to deflate the nominal oil price simply because of its numerous advantages. However, reliance on the U.S. CPI assumes that the worldwide alternative to a barrel of oil is the U.S. consumption basket. There are, however, alternative baskets, and I consider two: the price of gold and the IMF Global Commodity Price Index. Inspection of the results reveals that the relation between real oil prices and real exchange rates is sensitive to the choice of deflator for the price of oil and to the use of effective or bilateral exchange rates. Specifically, using the IMF’s Global Commodity Price Index as a deflator reveals that real oil prices and real exchange rates (effective or bilateral) are clustered along a long-run relation with unitary elasticity. Further, this choice of deflator has the lowest forecast errors. To be sure, much work remains to be completed along the lines of measurement and estimation methods. However, extending the results of this paper will emphasize its main point—namely, that measurement matters. Full article

We use a robust measure of non-linear dependence, the Gerber cross-correlation statistic, to study the cross-dependence between the returns on Bitcoin and a set of commodities, namely wheat, gold, platinum and crude oil WTI. The Gerber statistic enables us to obtain a more robust co-movement measure since it is neither affected by extremely large nor small movements that characterise financial time series; thus, it strips out noise from the data and allows us to capture effective co-movements between series when the movements are “substantial”. Focusing on the period 2014–2022, we construct the bootstrapped confidence intervals for the Gerber statistic and test the null that all the Gerber cross-correlations up to lag $k_{\max }$ are zero. Our results indicate a low degree of dependence between Bitcoin and commodities prices, both when we consider contemporaneous correlation and when we employ correlations between current Bitcoin and lagged (one day, one week, or one month) commodities returns. Further, the cross-correlation between Bitcoin and commodities’ returns, although scanty, shows an increasing trend during periods of economic, health and financial turbulence. This increased cross-correlation of returns during hectic market periods could be due to the contagion effect of some markets by others, which could also explain the strong dependence across volatilities we detected. Based on our results, Bitcoin cannot be considered the “new digital gold”. Full article

The present paper provides an empirical analysis of the relationship between shocks to commodity markets and stock markets. By employing a total volatility connectedness measure, we study the relationship between shocks to oil, gold, copper, and agricultural commodity markets and emerging and developed stock markets. We conduct a connectivity analysis in the time and frequency domain to quantify market linkages using volatility spillovers over the period from 2004 to 2021. In addition, we analyze the spillovers of returns in these markets over the same period. The results suggest that both on volatility and returns spillovers, slightly more than 35% of the total variance of forecast errors is explained by shocks to markets during the period January 2004 to June 2021. We also show that, in terms of both volatility and returns, the contribution of equity market shocks to other markets is substantially more important than that of commodities; however, our analysis reveals that the total link between market returns is larger in the short run than in the long run, while in the case of volatility, the long-run frequencies concentrate the market link. Additionally, we use dynamic analysis to assess both the time evolution of total connectivity and all directional partial connectivity between markets. Our results show that both volatility and return linkages change significantly over time and that a set of events has a significant impact on them. Full article

Utilizing the Commodity Futures Trading Commission’s Commitment of Traders report, we examine the behavior of traders in three large agricultural futures markets (corn, soybean, and wheat) when prices are at a key technical trading level—the 52-week high (the highest price during the past year). Our empirical results confirm that, consistent with hedging behavior, commercial traders tend to be negative feedback traders, while non-commercial traders tend to be momentum traders. In both cases, there is a moderating effect when the market is at the 52-week high. For non-commercial traders, this effect is concentrated in short positions. Although we find no evidence of a broad market timing ability from any trader type, trader positions appear to be more informative when the market is at the 52-week high. Our results have implications for traders attempting to time market entry. Full article