U.S. and international equity markets fell sharply to close out 2018. The MSCI USA Index fell 13.7% in the fourth quarter alone. (It fell a total of 4.5% for the year). As we previously examined, investors began rotating from cyclical sectors and factors to defensive ones in June. This pattern continued, in earnest, until October.
One factor in particular, beta, stood out. In fact, this past quarter ranks as the fifth worst quarter for beta since 1975 — itself an historic sell-off. This most recent drawdown went beyond just the FAANG stocks, and it showed the important role beta exposure plays across growth, value and many industry-focused strategies.
In this blog we address three questions. What does this recent drawdown tell us about investor behavior? Secondly, was this behavior limited to the U.S.? Lastly, what types of firms were high beta during the quarter?
In risk modeling, the beta factor explains the common variation in stock returns due to stocks’ sensitivities to the broad market. Its return represents the return to a portfolio of relatively high-risk stocks in excess of the broad market. A drawdown in beta implies that investors are either selling out of high-beta stocks or rotating from higher beta into lower beta ones.
To examine the extent of this current drawdown, we use the MSCI US Deep Equity Risk Model’s long history of factor returns. The top left part of the exhibit below shows the daily returns for the beta factor in the U.S. The factor’s recent volatility is high relative to the current decade, but less so than during periods such as Black Monday, the Technology Bubble or the 2007-2008 Global Financial Crisis.
Looking at cumulative returns since 1975 in the bottom left portion, we can also clearly see that the tide started to turn for the beta factor in the past quarter.
Lastly, the bar chart on the right displays the worst quarterly beta returns in chronological order. The lowest-ever was the third quarter of 2001, which included the lowest daily return for beta on September 17, 2001, the first day markets traded following 9/11. The drawdown in that quarter (15.2%) was considerably higher than the fourth quarter of 2018 (6.3%). However, it was clearly driven by an idiosyncratic event rather than structural market changes.
Source: MSCI US Deep Equity Risk Model. Period: Jan 1, 1975–Dec 31, 2018.
Investors fled the highest-beta stocks…
Given the historical context of last quarter, we want to determine if this was a broader sell-off, or a more discriminating rotation. Below we show the performance of two hypothetical portfolios for each of the the U.S, Europe, Japan and the emerging markets (EM), representing the "Top Beta Quintile" (stocks from the respective regional index with the highest exposure to the beta factor) and "Bottom Beta Quintile" (stocks from the respective regional index with the lowest beta exposure). We used the corresponding regional risk models for the respective portions of the exhibit.
Source: MSCI US Deep, Emerging Markets, European Long Term and Japanese Equity Risk Models. Quintile portfolios formed daily from the MSCI USA IMI Index, MSCI Europe IMI Index, MSCI Emerging Markets IMI Index and MSCI Japan IMI Index based on exposure to each region’s respective beta factor.
…But only in developed markets
As we can see above, the fourth quarter rotation in the U.S. was stark. After outperforming the broad market for the first three quarters of the year, higher risk stocks gave back all their gains by mid-October before falling even further to end the year. At the same time, investors sent the prices of the lowest-risk stocks soaring — they ended the year 5% ahead of the market.
Other developed markets showed a similar rotation with similar magnitudes to the U.S. But this was not the case in emerging markets. While the MSCI EM IMI was down 15% in 2018, including 7% in the fourth quarter alone, higher risk stocks fared no worse than the broader market. The sell-off in EM stocks was more indiscriminate and broad-based.
High beta spanned style factors and sectors
We next return to the U.S. to determine which characteristics, such as style factors and sectors, the highest beta stocks shared. The exhibit below shows the difference in the average style exposure between the top- and bottom-beta quintile portfolios from constituents of the MSCI USA IMI Index as of the end of 2018. Higher beta firms had greater exposure to liqudity, residual volatility and growth and lower exposure to the value, quality and dividend yield factors.
Source: MSCI US Deep Equity Risk Model. As of Dec 31, 2018.
Last, but not least, we looked at individual U.S. stocks with high and low beta exposures to calculate the active return of each stock and its sector, relative to the MSCI USA Index as a function of its beta exposure.
High beta stocks had a strong negative active contribution to the MSCI USA Index during the fourth quarter of 2018. For example, by selecting stocks with an exposure to the beta factor between 1 and 3, we can see that their overall active contribution to the MSCI USA Index was close to -2%. This underperformance is mainly distributed between the information technology, consumer discretionary and communication services sectors and, at the stock level by the FAANG stocks (with the exception of Alphabet Inc.) and Apple Inc. in particular.
The active outperformance of low-beta stocks was more evenly distributed, both for individual securities as well as sectors. Low-beta stocks spanned many sectors beyond the historically defensive ones, such as utilities, health care and consumer staples.
Source: MSCI US Deep Equity Risk Model. Period: Oct 1, 1975–Dec 31, 2018.
The importance of beta
Our models suggest that the performance differentials between high and low-beta stocks during the fourth quarter drawdown were mostly due to a rotation from high-beta to low-beta stocks. While high-beta stocks' underperformance was concentrated in FAANGs, low-beta stocks' outperformance was more indiscriminate. The last quarter drawdown — the sharpest in the last 15 years — reminded us that monitoring beta exposures can be beneficial for both quantitative and fundamental managers.