![]() ![]() Generic metal futures returns are taken from the J.P. Some words about generic metal excess returns Put simply, reported excess demand, and opposing mood swings in manufacturing are expected to be negatively related to subsequent metal futures returns. The underlying materials are aluminum (ALM), copper (CPR), lead (LED), nickel (NIC), tin (TIN), and zinc (ZNC). We test these hypotheses for industrial or base metal futures returns. As sentiment is often affected by orders or order prospects, rather than production, it should on balance have some predictive power for physical consumption. Mood swings: If manufacturing business confidence has weakened in recent months, we expect all other things equal, that industrial commodity demand would slow or even decline accordingly.Conversely, if past industry growth has been unusually low or negative and inventories decreased, we can diagnose a temporary shortfall and a higher likelihood of acceleration in demand. Hence, if past manufacturing activity has expanded at an above-par rate and inventories increased, we can diagnose temporary excess demand and increased probability of negative payback. Excess demand: Since physical commodities require storage and neither shortages nor excesses of stocks are desirable, it is plausible that commodity demand, to some extent, rises and falls with industrial activity.In particular, this post focuses on predicting changes in the pace of physical commodity demand based on two effects: ![]() This is important for formulating hypotheses on the relationship between economic data and commodity returns. In other financial markets, economic information mostly affects subsequent demand and supply. Specifically, data on manufacturing orders, production, and inventories are related to the purchases of raw materials by industrial consumers. Unlike for bonds and equity, in the commodity futures markets, economic information effectively also informs on past flows of the underlying asset. Economic data and industrial commodity markets This post ties in with this site’s summary of trading strategies based on macro trends. The below post is based on proprietary research of Macrosynergy Ltd. Simple strategies based on a composite score of inventory dynamics, past industry growth, and industry mood swings would have consistently added value to a commodities portfolio over the past 28 years, without adding aggregate commodity exposure or correlation with the broader (equity) market. data and base metal futures returns confirms these effects. ![]() Empirical evidence based on real-time U.S. Moreover, changes in manufacturing sentiment should help predict turning points in demand. This helps to spot temporary price exaggerations. Data on industrial production and inventory build-ups indicate whether recent past demand for industrial commodities has been excessive or repressed. Unlike other derivatives markets, for commodity futures, there is a direct relation between economic activity and demand for the underlying assets. ![]()
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