Commodity and Macro Tail Risk Strategy Commentary
Investment Manager’s Monthly Report
On a net basis, the Commodity and Macro Tail Risk (CAMTR) strategy was up 1.73% in April 2022, to leave it up 13.79% since inception, on the 1st of February.1
Economic background
Within the commodity complex, there was much greater differentiation during April relative to the first quarter of 2022. Industrial metals prices fell, in part because of the lower demand associated with Chinese lockdowns. Precious metals were lower, in line with rising interest rates. Natural gas prices fell too in Europe and the UK, while rising meaningfully in the US. Palm oil prices rose significantly, because Ukraine is the largest exporter of sunflower oil (a substitute), while wheat and corn prices also responded to the fears relating to disruptions to Ukrainian exports. Oil prices were volatile over the month as releases from the Strategic Petroleum Reserve and Chinese lockdowns had an impact, although oil-related products rose significantly. Within the agricultural complex, idiosyncratic factors played an important role, with cotton prices rising strongly (limit up on some days), while coffee and cocoa prices fell.
In general, the growing hawkishness of central banks around the world was a major factor affecting markets in April. In the US, the emphasis on moving “expeditiously” contributed to the possibility of several 50-basis-point hikes, while the Fed minutes suggested that quantitative tightening may proceed more forcefully than had been expected.2 In Australia, the RBA accepted that it could no longer remain patient, while the ECB signaled the possibility of an earlier than expected rate hike in the euro area. The Bank of Canada and the RBNZ both raised rates by 50bp, with the latter surprising markets. The Bank of Japan was a major outlier, in that it stuck to its yield curve control policy, while the Bank of England was perceived as somewhat dovish in that it emphasized the risks associated with a growth slowdown alongside the growing inflation risks.
As a result of this central bank hawkishness, short-term interest rate expectations embodied in futures markets for December 2022 rose meaningfully in many countries: e.g. by more than 80bp in Australia, and by around 60bp in the US. By contrast, expectations moved relatively little in the UK and not at all in Japan. Sovereign 10-year yields also rose in many countries, although April witnessed a reversal of the trend in prior months inasmuch that the 2s-10s yield curve steepened.
In China, the “zero-Covid” policy (and, consequential, spreading lockdowns) contributed to a slowing economy, and led to fears that global inflation may stay high for longer because of associated supply disruptions. Meanwhile, the risks of the Russia-Ukraine conflict being prolonged grew, making investors more nervous about Europe. Consequently, the US stood out as a “safe haven”, with the US Dollar Index (DXY) rising by 4.7% over the month. The euro suffered due to Russia- Ukraine concerns, while the Japanese yen and British pound weakened due to the growing interest rate differential with the US. Commodity currencies also moved lower.
Given the difficult interest rate and geopolitical backdrop, it is perhaps not surprising that equities fell heavily in April. The MSCI World index dropped by 8.3%. The Nasdaq was an underperformer, as higher interest rates undermined growth stock valuations. The “late cycle” sectors (e.g. Healthcare, Utilities, Consumer Staples, Energy and Materials) outperformed.
Performance attribution
Table 1 summarises the CAMTR strategy’s performance by investment style, both for the month of April 2022 and since inception (on the 1st February 2022).
| April | Since Inception | |
|---|---|---|
| Commodities | 1.39% | 14.71% |
| Dynamic Short Equities | 0.35% | 0.43% |
| Currencies (FX Equity Hedge) | 0.22% | -0.13% |
| Yield Curve Slope | 0.10% | 0.75% |
| US Equity Sector | 0.01% | 0.58% |
| Chinese Fixed Income | 0.01% | -0.51% |
| Total | 2.09% | 15.85% |
Notes: Attribution figures are gross internal trading returns calculations excluding fees, expenses and cash interest. Holdings-based analysis is used to illustrate significant performance drivers and is not intended to be a formal accounting of returns. Holdings are subject to change. Totals may not add up due to rounding. The first data column of the table covers the period 1st April 2022 to 29th April 2022, whereas the second (‘Since Inception’) column covers the period 1st February 2022 to 29th April 2022. Source: PGIM Wadhwani.
Past performance is not a guarantee or reliable indicator of future results.
Of the six sleeves within CAMTR, all of them were profitable (albeit two of them were close to flat). The relative contribution of the commodity and non-commodity sleeves was broadly in line with their relative capital allocation.
Of the non-commodity sleeves, gains were registered in the Dynamic Short Equities, FX Equity Hedge and Yield Curve Slope sleeves in April whilst the US Equity Sector and Chinese Fixed Income sleeves were close to flat.
In a month when equities struggled, our Dynamic Short Equities model capitalized by taking our net equity exposure more negative by mid-month, though we did take some profit during the last few days of the month. The FX equity risk mitigation strategy also benefited from the sell-off in equities. Further, our yield curve model had hitherto made money in February to March through positioning for a flattening and so it required some agility for this model to make a positive contribution in April from the steepening that occurred.
Table 2 (overleaf) provides more information regarding the returns of CAMTR’s commodities strategies, both during the month of April and since inception on 1st February.
Within the Commodities sleeve, our Softs model was the star performer during April. We made money with our trading of palm oil, cotton, bean oil, corn, canola and mill wheat which comprised six of our “top ten” winners in the overall portfolio in April. Elsewhere in agricultural markets, within livestock, gains in from feeder cattle futures were more than offset by losses from lean hog futures.
We lost money in metals (industrial and precious alike). Copper and aluminum were the main contributors to our losses in the industrial category. Within precious metals, this was partly driven by long positions in gold and silver, which fell during April.
Within the energy complex, we made gains across a range of instruments (including heating oil and gas oil) but these were more than offset by losses from our trading of coal and crude oil. With regard to natural gas, we made money with our long positions in the US (our single largest winner), but these gains were slightly more than offset by losses on our longs in Europe.
Table 2: CAMTR Commodity Attribution by Commodity Type for the month of April and since inception
| April | Since Inception | |
|---|---|---|
| Energy (ex. Natural Gas) | -0.18% | 4.03% |
| Natural Gas | -0.01% | 3.88% |
| Industrial Metals | -0.46% | 0.50% |
| Precious Metals | -0.32% | -0.37% |
| Softs | 2.39% | 6.94% |
| Livestock | -0.03% | -0.26% |
| Total | 1.39% | 14.71% |
Notes: Attribution figures are gross internal trading returns calculations excluding fees, expenses and cash interest. Holdings-based analysis is used to illustrate significant performance drivers and is not intended to be a formal accounting of returns. Holdings are subject to change. Totals may not add up due to rounding. The first data column of the table covers the period 1st April 2022 to 29th April 2022, whereas the second (‘Since Inception’) column covers the period 1st February 2022 to 29th April 2022. Source: PGIM Wadhwani.
Past performance is not a guarantee or reliable indicator of future results.
End-April positioning
At the end of March, we continued to hold long positions overall in nearly all of the commodities sectors within CAMTR. (Livestock was again the exception, where shorts in the two cattle markets were larger, in aggregate, than the long in lean hogs.) However, the net long position was reduced a little since end-March, as the increase in energy exposure was outweighed by reduced exposure to the other five commodity types. The majority of our commodity-associated risk continues to lie in crops.
By end-April, the Dynamic Short Equities model held a net short position, focused largely in Europe. The US Equity Sector model continued to favour the commodity-related sectors.
At end-April, the Equity Hedge FX model’s biggest long position remained the US dollar, and its biggest short the Swedish krona.
The Yield Curve Slope model had mainly flattener trades on throughout March and a number of these flipped to steepener trades during April. In the US, for example, the model holds a 2s-5s steepener.
The Chinese Fixed Income model considerably reduced its long position in 5-year swaps by end-April.
The Outlook
Last month, we mentioned that the range of possible outcomes was exceptionally wide and, with all the uncertainties associated with the Russia-Ukraine situation, that still remains true. On top of these geopolitical risks, there is considerable uncertainty with respect to monetary policy. For example, the Federal Reserve projects a significant decline of inflation back to close to target despite the fact that it does not forecast the unemployment rate to rise above its equilibrium level, while real rates are expected to remain negative. We suspect that, if it is to achieve its aims, the Fed may well have to raise rates to an above neutral rate and that, by doing that, it will have to take risks that the tightening engenders a decline in confidence, and a “hard landing”. Recall that a tightening of financial conditions is a part of the transmission mechanism of monetary policy. The Fed needs some mixture of a higher US dollar, higher interest rates and lower equity prices to achieve its aims. We are short equities and have long positions in the US dollar and are so aligned.
Of course, geopolitical considerations can considerably complicate the logic of our positioning and, as always, we will need to respond to incoming developments.
1 The Commodity and Macro Tail Risk (CAMTR) strategy was incepted on 1st February 2022. The returns presented are net of actual fees, based on the highest fee structure available. Note that the returns are calculated using the NAV estimate for end-April at 29 April 2022, due to the fact that 30 April 2022 fell on the weekend. Please see pages 5 to 8 for additional performance details. Source: PGIM Wadhwani. Past performance is not a guarantee or reliable indicator of future results.
2 See Fed chair Powell’s NABE speech (March): https://www.federalreserve.gov/newsevents/speech/powell20220321a.htm