Has the love affair with FAANG stocks ended? Just as Bank of America Merrill Lynch was pointing out that technology stocks started to become a crowded trade, along comes Morgan Stanley analysis that breaks down the beta factor performance models. In short, they see volatility ahead — which can disrupt existing momentum trades. When looking at the recent FAANG price breakdown, they consider the relative value analysis with the larger technology universe and are not as alarmed by the relative price move lower.
Morgan Stanley quants see volatility ahead -- which typically isn't positive for an existing price trend
Within the FAANG stocks – Facebook, Apple, Amazon, Netflix and Google – there has been idiosyncratic price divergences. From an algorithmic standpoint, the price modeling of Facebook appears in a longer-term mean reversion pattern, for instance. Both Facebook and Apple have been in market uptrends. But unlike Facebook, where upward price momentum is fading, Apple continues to exhibit signs of strength. This strength in price persistence from the May 13, 2016 low $90.52 has passed a statistically mature point on a mid-term basis, just observing the stock's price history.
This is idiosyncratic price movement on display.
When Morgan Stanley's Brian Hayes and his “QuantWise” team of equity analysts look at the FAANG stocks, they see various factors contributing to the performance – and point to a mean reversion.
In particular, when considering the beta factors of volatility and momentum, Hayes and his team see an inverse relationship that is pointing to an expectation.
They run a dynamically weighting momentum exposure model that considers a 21-day time horizon. Using this as a measure, they forecast volatility to come, which points to the inverse relationship with momentum. “Momentum stocks are at risk of underperforming, based on this recent volatility of the factor,” the December 20 report predicted.
Momentum and volatility have a history of modeling differently. When looking at the most significant price trends in history – 2008, for instance – volatility has led to momentum. When this pattern occurs – volatility first – momentum follows. But when a momentum signal has been given prior to volatility, many trading algorithms view this as a negative. This is because volatility often signals a reversal of the price trend. This isn’t the case to the same degree with individual stocks as it is to an index – idiosyncratic variables play a bigger role in individual stocks – but nonetheless when price volatility occurs there is often a fundamental force driving the change. Volatility and a change in the skew of a price are highly correlated, and the reversal of a price trend is most often the case when volatility spikes significantly higher than average.
FAANG stock sell-off wasn't that bad -- on a relative basis
With the December sell-off in FAANG stocks appearing similar to the previous sell-offs in terms of their sharp nature -- the sell-offs most often occurred quickly, over a short period. Looking beyond this, Morgan Stanley points out that the sell-offs were not extreme, on a relative basis.
“In the context of 2017 idiosyncratic moves, the end of November sell-off for FAANG was not an extreme reversal,” the report stated. During this period, the stocks moved from near 0.10 to 0.08, or nearly 20% lower in a few short weeks. While on a historical basis, a 20% move might be meaningful, on a relative basis it has a different value. The top 1500 tech stocks moved from near 0.07 to 0.04, by Morgan Stanley’s calculation.
“By comparison, the decline in the overall tech sector was relatively more severe, as its alpha declined by about 3% in the sell-off,” the report noted. Earlier in the month, Morgan Stanley had predicted an end to the run in FAANG stocks.
Beyond the FAANG stocks, Morgan Stanley’s quants continue to see an “idiosyncratic” bent that has not been eclipsed since 2000 – just before the last technology-led market price readjustment. The report notes that the typical stock price moment can only be explained by traditional risk factors such as market, size and style.
“In the same way that some people are paranoid about leaving friends and relatives off of their shopping list, we were concerned that the low systematic risk we were finding for the typical stock meant that we were missing some emergent risk factor,” the report noted. “In other words, maybe stocks aren't all that idiosyncratic after all, and it's just that our risk model isn't looking at the 'right' risk or risks for the moment.”