The conflict in the Middle East has fueled the recent spike
in equity volatility, Goldman says, but the firm’s macro strategy research team
sees an ongoing structural rise in long-term volatility beyond the war’s end.
“We have argued that there are good reasons to expect
that equity volatility could move structurally higher over time, even with a
benign macro backdrop and even if equity prices continue to rise, as some of
the forces that pushed equity volatility higher in the late 1990s as the tech
investment boom matured come increasingly into play.”
Goldman’s strategists reexamined the models they use to
forecast stock volatility, updating their forecasts for longer-term volatility.
The “obvious” route to higher stock market
volatility is cyclical economic deterioration, they say, though they explained
that there are other underlying structural forces contributing to their outlook
for a longer period of volatility.
“Models of the macro and market drivers of equity
volatility suggest that longer-dated implied volatility ‘should’ have been
rising in recent years, driven largely by rising equity market concentration
and a slowly rising unemployment rate,” the bank said.
Instead of the Iran war, the two biggest drivers of a
swingier stock market will be higher market concentration and higher
unemployment, in Goldman’s view.
AI-driven market concentration sets up stock volatility
Stock market volatility is the new norm, Goldman Sachs says,
and it’s not as simple as markets being upset by geopolitical turmoil like
the Iran war.
AI has fueled the stock market’s bull run in the past few
years as investors pile into the emerging tech, a backdrop that sets up
equities for more volatility.
“We think the concentration of value in AI-related
areas of the market adds to the risk of higher volatility over time as focus
increases on whether the benefits from AI justify that value as the AI cycle
matures,” Goldman wrote.
Market concentration has become historically top-heavy as
the AI trade fuels gains for the largest companies. The last time the stock
market was this concentrated at the top was 1932, during the Great Depression.
This phenomenon was on display earlier this year when AI
hype soured, driving major losses in AI stocks and the broader
market.
Goldman says market concentration and high valuations are
the “non-macro” factors they considered in their volatility model.
“Rising concentration and high valuations are symptoms
of this AI-driven market, as they were in the tech boom of the late
1990s,” the note read.
Unemployment data signals an uptrend in equity volatility
Unemployment is the second main driver of equity volatility
that Goldman highlighted.
The bank’s volatility model considers levels and changes in
the US unemployment rate, with higher unemployment being associated with higher
volatility.
“The intuition here is that these measures are
indicators of the stage of the economic cycle,” they wrote.
The unemployment rate has risen slowly from 2023 lows.
“We find a statistically significant relationship
between volatility in labor market data and equity volatilitythe channel here
is likely through uncertainty about future outcomes (where higher data
volatility is associated with increased uncertainty about the macro
outlook),” the bank wrote. – Business Insider