Commodities & Energy Sector
We build a four-stage business cycle framework based on economic growth and capacity utilization, and then analyze historical returns for most major asset allocation decisions for each stage. Given that we are in the early recession stage (negative growth coupled and an overheated economy), our framework recommends a defensive positioning across all asset classes.
In this Strategy Outlook, we present the major investment themes and views we see playing out for the rest of 2023 and beyond.
China’s economic and diplomatic interests in the GCC region will expand, as will its military presence. Whether or not this stabilizes the region is yet to be determined, particularly if tensions in the South China Sea and other international waters traversed by both the US and China escalate. Underlying risk in energy markets will remain elevated. We remain bullish energy generally, and continue to favor equity ETF exposure to energy (XOP and XME), and commodity exposure via the COMT ETF.
The market does not grasp the implied depths of recessions that will be needed to prevent inflation expectations from un-anchoring. Among the major economies, the most vulnerable to a deep recession is the UK. We explain why, and some investment implications. Plus: the yen is a rebound candidate, while Japanese equities are a reversal candidate.
The attempted coup in Russia produced subdued short-covering rallies in oil, gas, and grains markets, as markets over time have observed that coups, rarely result in loss of production and exports. Markets await Putin’s next move. Unless and until a viable threat to the Putin government emerges, markets will continue pricing in fundamentals prevailing prior to Saturday’s attempted coup. We are keeping our base case brent and henry hub natgas price expectations unchanged.
Machine learning has made significant progress in the physical sciences, although it has some ways to go in the social sciences. When asked to make predictions on oil markets, ChatGPT's responses lack in-depth analysis given its inability to understand the language and think critically. While in its current form, AI cannot replace forecasters, its wide breadth of 'knowledge' makes it useful in developing forecasting frameworks in unfamiliar domains.
