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Qi's credit models are in strong macro regimes & valued in line with macro fundamentals. Our Credit Watchlist shows all bar two (EM High Yield & US Municipals) have high model confidence; & all are essentially within 0.5 sigma of macro-warranted model value.

High Yield spreads in both US & Europe are especially notable – macro explanatory power of 90% plus & almost exactly in line with fair value.

No valuation edge in credit itself then, but what about other asset classes?

The Fed’s aggressive policy response in March 2020 resulted in a significant rise in credit’s importance as a factor for risky assets. Given its role as a primary driver, a core Qi theme throughout last year was that, as long as the Fed back-stopped credit markets, any pullback in US equities was a dip buying opportunity. Is the opposite true now?

The chart above shows the S&P500’s independent sensitivity to US High Yield spreads. In Q4’20, a one standard deviation tightening in US HY spreads (in isolation, every other factor held constant), was consistent with a 1% rally in SPX.

The equivalent move today is just a 0.2% gain. On this metric, equities still want tight credit spreads but the sensitivity is a fifth of what it was. Last week’s announcement isn’t the huge game changer it would have been in 2020.

AUDZAR is especially notable. Prior to Friday’s US Payrolls, the FVG was at a 1y low. Even with the recent bounce in spot, the valuation gap stands at -1.1 sigma (-4.2%). Back-testing a buy the dip strategy at a FVG of -1.1. sigma since 2009 produces a 79% hit rate & +1.8% average return.

While the valuation gaps are less extreme, the Rand is expensive to model on USDZAR, CADZAR & EURZAR as well. Of those, CADZAR’s current -0.7 sigma FVG back tests the best with a 63% hit rate & +0.4% average return.

The macro profile is similar across all 4 crosses. Risk off (wider credit spreads, higher VIX) plus weaker domestic growth (Now-Casting tracking GDP growth for SA) dominate the regime & are Rand negative. Put another way, on current FVGs, the Rand has priced a fair amount of good news on risk appetite & growth.

It is also noticeable how important the Rand is for South African equities currently. The sensitivity of the iShares ETF tracking MSCI South Africa to Trade Weighted ZAR has been rising strongly since mid March, & the currency is now the biggest positive driver.EZA is very close to macro fair value so equity investors need to monitor fx shifts.

By George Hatjoullis:

One of the first things that I confronted as a young finance academic (this is pre-history) was the impossibility of running a portfolio of stocks selected for their individual merits. The reason was, once the portfolio had more than a certain number of stocks, the specific risks of individual stocks become largely irrelevant. This is the whole point of diversification. Unless the portfolio holdings are skewed towards one or two stocks the portfolio would be defined by its systemic risk; the risk that cannot be diversified away. If the portfolio consists, say, of bank stocks, then its risk characteristics would accord with those factors that impact all banks. The portfolio risk would be dominated by macro factors such as GDP growth, Inflation, interest rates, credit spreads, and so on. If you check the top ten holdings of any of your funds you will notice it is rare for any individual stock to constitute more than 2-3% and the holdings usually exceed 50 stocks. Every portfolio is effectively a macro portfolio even when it purports to be bottom up. However you pick the stocks, you usually end up with something that is largely driven by macro factors. For those that doubt the veracity of the paragraph take a look at Chapter IX of Portfolio Analysis by J.C. Francis and S. H. Archer, Second Edition, Prentice-Hall, 1979. I am sure there are more up to date discussions of this point but this was the Chapter that made me think back in 1979.

If we accept the premise of the above paragraph then this has profound implications for portfolio management and the wider fund management industry. Portfolio outcomes are determined by a well defined and finite set of macro factors. Macro has always been the only game in town. Portfolio outcome variation has been driven by selecting stock portfolios which were unwittingly weighted towards specific macro factors but attributed to marketing objective of the fund. The understanding of this issue has slowly emerged and we have seen much written about factors in terms of value, momentum etc. However useful these broad categories might have proven they are not clean macro factors. Some banks are clearly value stocks but others momentum or growth stocks. The need for a well defined set of macro factors that could capture portfolio differences remained. One attempt to fill this need is a company called Quant-Insight (https://quant-insight.com), and in which I own a small shareholding.

QI offers a set of independent and finite macro factors against which most diversified portfolios can be characterised. QI tells you what you have in terms of well defined factors such as growth, inflation, credit spreads, interest rates etc. QI tells you if the value of your portfolio (or individual stocks or other portfolios) is out of line with the historical relationship with the set of macro factors. QI tells you how strong is this relationship and when the portfolio relationship to macro factors may be changing. QI cannot tell you how these macro factors will evolve (nothing can) but it can show you to which factors your portfolio is presently exposed. QI can also remind you that whatever you think you have what you actually is some weighting of macro factor exposure. It may be that you can achieve a more efficient portfolio with exactly the same factor weighting. A more efficient portfolio would offer a greater return for the same level of factor risk.

Read the George Hatjoullis blog

In every instance, macro valuation is slightly extended – spot is somewhat rich versus macro model value, suggesting some good news is already in the price. However, the momentum picture shows a new uptrend is being formed. The chart below shows that with the US Energy vs. Retail ratio but the picture is replicated across the examples below.

US single stocks
Halliburton (HAS)
Oil States International (OIS)
Diamondback Energy (FANG)

International single stocks
Repsol (REP)
Aker BP ASA (AKRBP)
China Petroleum (600028 CH)

US Sector RV
Bullish Energy vs. Retail (S5ENRS vs. S5RETL)
Bearish Utilities vs. Energy (S5UTIL vs. S5ENRS)

Critically, crude oil which flirted with a new downtrend in mid May rejected that scenario & RETINA™’s momentum picture shows a healthy uptrend.

Alongside such political factors, bottom up analysis remains critical. Some carriers are promoting free flights for the vaccinated; others are successfully adapting from passengers to cargo in order to boost revenues. But it is notable in the curated Airlines Watchlist below that every single carrier Qi models - in US, Europe & Asia - is in a strong macro regime.

The other standout is how close to model fair value every single carrier is. They are all essentially within 0.5 sigma of model. Macro matters for airlines & currently they are behaving in line with macro fundamentals. Watch the relevant macro factors for the next big move.

While model confidence is uniformly high, there is a wide dispersion of macro regimes. Lufthansa is a high beta inflation play with crude oil & inflation expectations accounting for around a third of model explanatory power.

A desire for credit spreads to remain tight dominates all four US airlines – SouthWest, Delta, United & American.

Asian carriers Quantas & Singapore have the most diverse range of drivers but display a notable bias to domestic economic & financial conditions.

The new regime stresses tech’s defensive qualities. Most notably, the biggest driver for both Hang Seng Tech & KWEB is global economic growth. The relationship is negative & sensitivity is growing.

KWEB - Sensitivity to Global Economic Growth

VIX & measures of risk aversion are the second biggest driver. Higher VIX is consistent with better tech performance; & again sensitivity is increasing.

Hang Seng Tech - Sensitivity to Risk Aversion

In valuation terms both screen as somewhat cheap. However, after a period with diminished explanatory power, macro drivers are only just re-asserting themselves. In both cases macro-warranted fair value is catching down. The ideal scenario for bulls is when model value stabilises & starts to turn higher. This can be tracked in real-time on Qi.

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That retracement was partly a function of macro model value moving higher – itself a function of this week’s bounce in crude oil. But the bigger move, certainly in the US, was the 14bp decline in spot since recent highs.

These are not models forecasting future CPI levels; rather, the empirically observed relationship between market expectations for future inflation versus their macro environment.

Observing where GDP growth is tracking, what financial conditions are doing & how risk appetite is behaving, macro model value has edged higher while the market has re-priced inflation expectations lower. Net-net, spot is now in line with macro fundamentals.

Unsurprisingly, the FVG for 10y USTs has also closed. On this occasion, the signal showing yields as 20bp too high has been closed by spot falling 10bp & model value rising 10bp, again courtesy of the bounce in crude oil prices. Signal from noise™

A more aggressive fiscal response in the US, plus secular trends like green technology remain important arguments for a commodity super cycle. But China’s impact on metal prices is traditionally very strong. Unsurprisingly, the z-scores for copper & iron ore have tracked Chinese GDP growth lower.

Qi’s Optimise Trade Selection enables users to screen their holdings for sensitivity to macro factors such as these.

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Crude oil is the biggest single driver for 10y US Treasury yields currently. Having been indifferent for much of the last year, bond yield’s sensitivity started accelerating higher early in February. That sensitivity continues to trend higher now. On current patterns, lower crude oil would be a big drag on bond yields.

10y UST yields are already high relative to macro model value. A new downtrend in crude oil would imply a more significant re-pricing lower for US bond yields.

The knock-on implications are equally profound. The equity rotation trade could look very different against a backdrop of low bond yields. In fx, higher US yields has been a source of frustration for US Dollar bears.

Which equity value plays are most vulnerable? Which equity growth names likely to benefit? Which USD crosses have interest rate differentials as the key driver?

RETINA™ will monitor the trend / momentum picture for crude oil. Qi’s Optimise Trade Selection function can answer the questions above. For example, US Banks screen as the sector most reliant on higher oil; & they are 1.2 sigma (16.6%) rich to model. Signal from noise™

That has prompted speculation the recovery in tech & growth potentially contains a broader message – that when the more defensive areas of the equity market outperforms, that rotation is signalling an earlier Fed tightening.

On Qi, that would manifest itself in a change in underlying relationships with the macro factors. The biggest driver in the current regime remains expectations around Fed Quantitative Easing. It alone accounts for 37% of model explanatory power.

The current relationship still shows QT is consistent with Value outperforming Growth. Moreover, sensitivity is not only large but rising.

For now, this looks more like a simple correction from an overshoot rather than any signal the Fed’s policy stance is shifting.