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1/ The sensitivity to risk appetite macro drivers has accelerated sharply - what can go wrong?

Qi identifies an asset’s sensitivities to a large macro driver information set. Broadly, these macro drivers can be bucketed into financial conditions (e.g. credit spreads, real rates, USD TWI), growth expectations (e.g. GDP Nowcast, metals, energy) and risk appetite (e.g. VIX, gold / silver ratio).

Below, we show the 4wk change in those bucket sensitivities for the S&P 500 – we refer to these 4wk changes as the market’s macro beta impulse to these specific drivers. This highlights the focus on financial conditions but what has caught our eye this week is the increasing attention to risk appetite.

The sensitivity to risk appetite has accelerated as VIX has descended below 13. Reliance on low equity volatility rises as the market accelerates. However, as this reaches close to multi-year highs, the premise presumably is that everyone is close to “all in” on the prevailing narrative.

The charts below plots the sensitivity to risk appetite vs. the S&P 500 and to VIX itself (sensitivity inverted on rhs axis). The simple point is that when sensitivity to risk appetite is becoming extended, it questions whether prevailing market momentum can be sustained. Perhaps no surprise, after the best 3mth risk adjusted return since the tech bubble.

2/ Equities screening rich to bonds & bond vol screening cheap

Below we show Qi’s model value vs. spot for the SPY ETF relative to the GOVT ETF (iShares US Treasury Bond ETF). The second chart shows the current dislocation in terms of the fair value gap vs. the spot price (+1.2 sigma).

Of late, commentators have noted that the correlations between equities and bond prices have started to wane i.e. growth is deemed strong so the level of rates matters less. However, Qi has picked up on that dislocation, arguing in the short term, the move looks over-extended.

In contrast, treasury bond vol as proxied by VXTLT is screening below its Qi macro-warranted value (-0.8 sigma):

3/ Styles synonymous with the current Goldilocks narrative, Momentum & Growth, macro rich also

First, consider the VFMO Vanguard US Momentum Factor ETF. The biggest macro driver for Momentum has been financial conditions – a weaker dollar, lower real rates, tighter credit spreads. Below see Qi’s macro model value vs. spot and secondly against the GS Financial conditions index. The third shows the same dislocation but in FVG terms.

Secondly, consider similar charts for growth (RPG Invesco Pure US Growth ETF) or long duration plays like Biotech (IBB iShares BioTech). Similar drivers, but the over-extension is concerning.

By definition, Momentum performance reflects the returns of the most popular trades. When momentum is extended, it would deem views are crowded.

Chinese equities have been in the red for 3 consecutive years – unprecedented in modern history. Valuation is never enough – decisive and effective policy delivery is needed alongside an exit from deflation. While China deflation may be welcomed by the world, Qi analysis shows a glaring disconnect between China sentiment and DM risky assets.

Qi screened European and US equities most sensitive to China growth expectations. Qi provides macro driver sensitivity exposure, for a large factor information set, across the global single stock universe. We use this data to identify names most exposed to China. This is defined as the sensitivity to China GDP (+ve), Copper (+ve), Iron Ore (+ve), China 5y CDS (-ve), USDCNY (-ve) and VXEEM (-ve).

The performance of the 30 most exposed relative to the 30 least exposed in both regions is shown below. Note this is based on the prevailing sensitivities of stocks today – the names are fixed with no rebalancing. At any one time, risky assets are driven by a host of moving macro drivers, making a static screen somewhat naïve (see more details below).

However, the charts below make a simple point – DM equities exposed to China trade rich relative to the underlying Chinese equity market. This should not surprise, given the domestic growth / inflation focus. However, this is another example showcasing the reliance on a soft landing narrative

Qi has created a China exposure L/S equity basket using the S&P500 universe. This uses Qi’s proprietary optimisation process which looks at all the possible combinations of stocks and their weights that minimize the tracking error to the macro factor in question. This is run out-of-sample for a month, until the next monthly rebalance.

Qi baskets are available to trade via Goldman Sachs. Specifically, the chart below shows the performance of the GSQICFXS / GSQICFXL ratio.

The divergence in performance between the Qi L/S Basket and the CSI 300 (indeed also FXI) has extended since Q4 last year. Is now the time to play for re-convergence i.e. for a US investor to be long FXI and short China exposed US equities?

To provide clues Qi shows that the biggest driver of US equities outperformance over China today is inflation expectations: US wants disinflation to continue / China is looking for a way out of deflation. The sensitivity to inflation expectations for the ratio SPY / FXI is shown below.

In other words, for investors who are more concerned from here about inflation acceleration risk than China risk, this may present a timely mean-reversion opportunity. More details on this basket is available on request.

These conclusions are consistent with our recent screen of stock winners & losers in a soft landing scenario, where we screened sensitivities to growth expectations rather than inflation expectations.

The backbone is Qi’s macro factor sensitivity data across all S&P 500 stocks. From this data, we ran the following screen:

The result is the scatterplot above (click on chart above for a larger image).

The arrow highlights that the direction of travel for beneficiaries of disinflation and easier financial conditions is from the bottom-right to top-left. Specifically, Semiconductors are the most sensitive to inflation expectations and Banks to financial conditions.

Below is an alternative representation ranking the industries by their total exposure to these two drivers.

Leveraging the granularity of Qi’s data, we have the ability to also pinpoint exposures to the stock level in addition to any mispricing given the prevailing macro backdrop.

For an in-depth exploration of our screening process, from sectors to industries to individual stock analyses, feel free to reach out to the Qi team.