The recent news of effective COVID-19 vaccines propelled global stock indices to record highs. With that news came a big “sector rotation”, from industries that had so far benefitted from the crisis (Health Care, Information Technology) back into those that had suffered most (Energy, Financials). We used Axioma’s new Factor-based Fixed Income Risk Model (FFIRM) to examine whether a similar effect could be observed in the credit market and found both substantial similarities, as well as some interesting differences.
Many global equity benchmarks recorded their strongest monthly gains on record in November, following reports of three different vaccines that had proven effective against the coronavirus in clinical trials. Yield premia on corporate bonds, meanwhile, tightened further, returning to levels last observed at the end of February, although still wider than before the crisis. The blue and green lines in the graph below show the year-to-date returns of the STOXX® Global 1800 and the Global Market Intercept factor from the Axioma FFIRM, respectively. Please note that the spread returns are plotted against an inverted scale on the right, as a decline in the yield pickup corresponds to an increase in the price of a bond.
Global stock market versus credit spread returns
In the equity market, the surge in prices was predominantly driven by sectors and companies, which had suffered disproportionally in the initial sell-off in March and lagged in the subsequent recovery. As news of the vaccines raised hopes of a possible end to the pandemic, investors shifted their funds back into previously shunned industries, such as Energy and Financials, and out of those that had previously thrived, namely Health Care and Information Technology. The chart below shows the excess returns of the most-affected industries against the global benchmark since November 6—the Friday before the first vaccine was announced.
Global equity sector excess returns over global market
The Energy sector was by far the biggest winner, benefitting from the resurgence in oil prices, which rose more than 20% over the same period. Financial companies also outperformed the broad market by around 10%, after having been among the worst performers for most of the year. Industrials had been badly rattled, too—especially aircraft manufacturers—but were now able to reclaim some of their losses. In contrast, the previous beneficiaries—Information Technology and Health Care—underperformed the overall market.
It is particularly interesting to see that pharmaceutical companies seemed not to have profited from the vaccine news, but it could be a sign that that had already been priced in and investors were now taking profits. The Consumer Discretionary sector, meanwhile, appeared to have neither gained nor lost relative to the broad market. The reason for this could be that it encompasses both online retailers (e.g. Amazon), who would have underperformed, and travel & leisure firms, which would benefit from lockdowns being lifted.
To find out whether this same “sector rotation” was also reflected in the credit market, we looked at the sector-factor returns from the Axioma Factor-based Fixed Income Risk Model. The factors capture the impact of sector-specific particularities on issuer credit-spread movements over and above the Global Market Intercept shown in the first chart. The spread returns are once again plotted against an inverted scale to make them comparable to the equity returns above.
Global credit sector factor returns over global market
The returns of the Energy, Industrials and Information Technology credit-spread factors mirrored their equity counterparts, with the first two outperforming the overall market, while the latter underperformed. The Consumer Discretionary sector once again moved broadly in line with the market average, but Financial bonds did not benefit to the same extent as the corresponding segment of the stock market. Health Care issuers, meanwhile, initially seemed to have profited from the first vaccine announcement, but subsequently gave up their gains over the rest of the month.
Measuring sector performance in fixed income is not as straightforward as it is for equities. Simply calculating the spread average of a segment and comparing it to a broad market benchmark will commingle other significant drivers of bond returns, such as the credit rating of the issuer. Our recent study of the risk of an active, high-yield bond portfolio, using the Axioma Factor-based Fixed Income Risk model, highlighted that sensitivity to movements in the overall market (Beta) and the size of the yield premium (Quality) are at least as important, if not more so, than any sector-specific peculiarities. Having a model that uses statistical techniques to distill those particular factors can help to distinguish the underlying common drivers of fixed income returns.