UBS' Paul Winter believes we are witnessing the end of the credit cycle - earnings growth rates are flat, and the stock market impact has been increasing. Importantly, from a risk perspective, Winter warns that Systemic Risk is rising, and Economic Policy Uncertainty has hit all-time highs, warning that the key risk today lies in low-volatility stocks and the broad market's equity risk premia - "either earnings need to pick up dramatically, or alternately, equities would need to correct by around 20% to bring the equation back into equilibrium."
The age of excess liquidity and inexpensive debt is over, according to Winter, and that makes it harder for management to use credit to satiate investors' demands for corporate profits
UBS notes that "77% of stock crashes are driven by earnings announcements," and more companies are likely to disappoint the market in the future.
We are currently witnessing the end of the credit cycle. Credit spreads have been increasing, global earnings growth rates are in aggregate flat and market impact has been increasing.
Market impact is currently running at 80bps across developed markets, a level that tends to be commensurate with negative returns and an elevated risk of correction. The risk today, oddly is in so-called ‘low risk’ assets. We show that low volatility assets are generally more highly geared than higher volatility stocks. As a consequence, they tend to have a high residual beta to credit. As lending standards tighten and credit spreads increase, it is likely that highly geared stocks underperform regardless of their volatility.
Conventional wisdom defines a bubble as any asset driven by ‘irrational exuberance’ that exhibits valuations that have drifted significantly from their long term valuations. This opens the door for bonds, property and equities to all be defined as bubbles right now, and perhaps they are. So how should we frame our thinking in terms of ‘What’s priced in?” and ‘Where’s the mispricing?”.
In theory, bubbles perpetuate themselves due to the business risk of asset managers. This motivates institutional herding and ‘rational bubble-riding’. As a consequence, bubbles, once formed, can last a long time.
What’s priced in?
If we think of asset bubbles in terms of expected growth, valuations and risk premia, then given a world of structurally low growth and low inflation, we expect structurally low bond yields, and hence earnings yields on the market to trade at lower levels. (Please see our paper on Demographics). However, we identify two key areas that may be overvalued.
Where’s the mispricing?
Equity risk premia
Firstly, equities in general are trading at very high multiples given the level of growth that the world is experiencing, which makes sense given the level of bond yields, however, this doesn’t appear to be pricing the level of macro risk that we’re witnessing in the market. Developed world earnings yields are at 4.8% and bond yields at 0.5%, as a consequence, the simple equity risk premium is trading at 4.3% (Earnings Yield – Bond Yield).
However, following Cliff Asness’s (2000) paper ‘Explaining the Equity Risk Premium’ we show the relationship between ten year earnings growth rates and the ten year volatility differential between equities and bonds (Figure 3), and subsequently the ten year volatility differential and the ten year average equity risk premium (Figure 4).
The thesis simply put is that earnings growth risk drives the volatility differential between equities and bonds, and it is this volatility differential that explains the equity risk premium. Why use ten year averages? Quite simply the short term relationships between these variables are not stable. However, Asness theorises that there is a long term generational phenomenon whereby investors frame their risk preferences and return expectations in terms of their prior experiences, as a consequence, using ten year averages (Asness uses 20 year averages) captures this effect.
Given that earnings growth rates are currently running at -1.5% per annum, we should expect a volatility differential of 11% and an equity risk premium of around 6% (assuming historical preferences hold true).
So whilst the simple equity risk premium is currently at 4.3%, the historical relationship between earnings growth, volatility differentials and risk premia, would suggest a more appropriate risk premium of around 6%.
How does this correct itself?
Either earnings need to pick up to around 4%, which would suggest a decline in equity market volatility and justify a 4% risk premium.
Or alternately, equities would need to correct by around 20% to bring the equation back into equilibrium.
Low volatility risk
Secondly, low volatility equities are trading at significantly higher multiples relative to the market. Importantly, whilst low volatility stocks appear to be trading on a premium to their own history, it should also be noted that these stocks make up a significant proportion of the market by weight.
Low volatility deciles 1, 2 and 3 make up approximately 45% of the market by market capitalisation. As a result, the overvaluation of low volatility stocks is significantly contributing to the valuation of the market as a whole.
These stocks tend to have higher levels of gearing and whilst they have a low beta to equity markets (Figure 7), they carry a higher residual beta to credit markets (Figure 8).
If this is indeed the end of the credit cycle, we believe these stocks are likely to underperform.
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While the earnings and credit cycle is rolling over, it is exogenous shocks that are more likely to increase market crash risk...
Exogenous shocks: are by definition difficult (if not impossible) to predict, an example being the 1973 Oil price shock. Importantly, as we have traversed from a world of high growth into a post financial crisis world of lower growth, macro-economic risk has picked up significantly.
We measure these risks using three different approaches:
(a) Macro factor model: the level of market risk explained by macro factors,
(b) Policy uncertainty: the level of policy uncertainty measured using a keyword search in major news publications,
(c) Systemic risk: an estimate of the capital that financial institutions would need to raise in the event of another financial crisis.
Macro risk has been dormant for many years, however, post the Global Financial Crisis, we have traversed into a world of structurally lower growth, and macro risk is dominating as a driver of returns. Below we show the percentage of returns driven by macro factors over time. The key point here is that pre-2007 the twoyear bond yield was a key driver of returns. However, post-2007, the market has been driven by a broader variety of macro risk factors, a key driver of which is the Corporate Credit Spread (shown below in red).
In this environment, understanding the key risk factors (drivers of volatility) is critical. From our perspective, the principal risks that we would like to understand are systemic risk and economic policy risk.
This is measured as the capital shortfall within the financial system in the event of a significant market correction. We use the Robert Engle S-Risk methodology (Brownlees and Engle, 2007). It is a function of market capitalisation, leverage and volatility.
As part of their study Brownlees and Engle found that the SRISK model delivered useful rankings of financial institutions at various stages of the Global Financial Crisis and correctly identified the key contributors as early as 2005. Interestingly, they also found that aggregate SRISK provided early warning signals of weakness in indicators of real activity.
The second principal risk that we seek to understand is economic policy risk. Here, we use data from Economic Policy Uncertainty (www.policyuncertainty.com), a model that has been put together by Scott Baker (Northwestern Universtiy), Nick Bloom (Stanford University), and Steven Davis (University of Chicago).
The indices that they have developed are based on the frequency of economic policy uncertainty coverage.
The methodology is quite intuitive and searches for the trifecta of words pertaining to the economy, uncertainty and policy. They then scale this by the total number of articles in the newspaper and standardise across the newspapers covered and take the monthly average.
Using firm-level data, they find that policy uncertainty increases stock price volatility and reduces employment and investment in policy-sensitive sectors such as healthcare, infrastructure construction and defence. At a macro level, they find that increases in economic policy uncertainty foreshadow declines in economic growth and employment in subsequent months.
In a world of heightened macro factor, systemic and economic policy risk, we should expect higher levels of equity market volatility.