Monthly Archives: May 2016

Who loses now when oil spikes, Fed hikes and China slides?

As we have been experiencing low oil price – indeed we even feared about oil collapse earlier this year – for almost one year and a half, one may have underestimated the impact of the recent oil rally on macro and markets.

One important transmission channel is via inflation. Higher oil price may translate into higher inflation and higher inflation expectation. It in turns slows down the pace of monetary easing in major DMs/EMs, and/or increasing the odds of Fed rate hike being pushed forward. In such scenario, a country may face double hit if it is a net oil importer – meaning higher trade deficit when oil price rises – and vulnerable to Fed normalization/stronger USD – e.g. with higher refinancing cost for its USD-denominated debt.

What could be a triple hit is that it couples with renewed Chinese slowdown. Note that oil can remain strong when China slows, as the former is affected by Chinese consumption demand while the latter is more of a function of Chinese investment demand. Countries that export a lot of investment goods are vulnerable in this scenario.

Considering all the three shocks, I think the following three countries could be the one that get hit particularly significantly: Mongolia, South Africa and Indonesia. All have relatively high current deficit to finance, exposed to China and are net importers of oil.

Their currencies could face renewed pressure under the triple hit scenario.

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Interesting takeaway from “Quality Minus Junk” 2014, AQR

  • Quality factor seems to generate positive raw return. It also generates positive alpha even if other popular factors (value, momentum, size and market beta) are controlled for. In other word, quality stocks outperform junk stocks.
  • There are quite a few plausible explanations why quality factor generates positive alpha. One (behavioral) explanation is that the cross-stock valuation difference can only be marginally explained by cross-stock quality difference. In other word, quality stocks tend to claim higher valuation vs junk stocks. But there are a lot more in valuation that is unexplained by quality. This provides an opportunity for quality factor to generate alpha. Another (efficient market) explanation is that, given quality companies today are more likely to be quality (than junk) in the future, quality stocks should indeed outperform junks as price depends on future quality which relates to today’s quality. However, a puzzle rises when “flight to quality”occurs, i.e. quality factor generates positive raw return and positive alpha in extreme bear market. It means that the positive alpha from quality factor is not compensation for tail risk.
  • Understandably, quality risk premium varies through time. More specifically, the (generally small) explanatory power of quality against valuation difference varies through time. In retrospect, quality-based strategy performs well after the time when the market under-appreciates the importance of quality (e.g. tech bubble in year 2000).
  • If one tries to explain quality factor with traditional factors (value, momentum, size and market beta), one tends to find that quality has negative exposure to market beta (by construction), size and value, This is because quality stocks are geared towards large, expensive and low-beta stocks.
  • Of course, one can also do the opposite by using quality factor to explain other factors or strategies. Indeed, one lesson is that it’d be truly rewarding to identify small and cheap stocks with strong quality, though it is rare. Another (well-known) lesson is that it’d be rewarding to combine quality with other factors (e.g. value), such as buying good things as low price, or avoid buying rotten fruit (value trap). The third lesson is that, large stocks are usually expensive even controlling for quality (size effect).
  • Quality factor can be built with four components: profitability (e.g. ROE, ROA, CFOA, Gross profit over asset, profit margin), growth (5-year change in those profitability measures), safety (low beta, low price volatility and low volatility in ROE and low debt/bankruptcy risk) and payout (high dividend yield).
  • The combined factor has stronger predictive power than any of the four individual components. Among the four components, the profitability component seems to have more consistent, persistent and robust result than other components. It implies that the level of profitability is probably more important than its change, though the latter somewhat complements the former. payout ratio indeed has quite obscure effect. For safety component – which is probably as contentious as payout – better research should be found in the paper “Betting against Beta”.

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What businesses don’t care that markets assume they do: a required return disconnect

This post was partly inspired by a few charts in GMO’s 2015 whitepaper “The Idolatry of Interest Rates”.

It’s well accepted that monetary easing boosts real economic activity as lower interest rate reduces required return of investment, and boosts financial asset prices which encourages consumption via wealth effect. And it is usually true that lower interest rate reduces nominal bond yield which in turn should reduce the refinancing cost of corporates that are large and profitable enough to tap into the bond market.

However, the majority of investments made by corporates and businesses are financed not by equity or bond issuance – whose issuing cost is influenced by central bank interest rate 0 but rather by retained earnings, or internal financing. Therefore, a CFO of a business would normally spend its CAPEX on a new project if its prospective return is higher than the required return of the business retained earnings.

And here is the DISCONNECT between central bank interest rate – which has large influence on financial markets and financial assets – and real business activities. Over the past few decades,  the required returns of CFOs have been on average between 12% and 15%. In other word, despite consistent decline in interest rate from three decades ago that have inflated financial asset prices and reduced bond returns, the required return on business investment has never been lower by the same extent as central bank interest rate.

Such disconnect has large economic and policy consequences:

  • It reduces the economic impact of monetary easing as it boosts asset prices more than business investment that policies desire to affect.
  • It discriminates against businesses that cannot tap the bond market (usually the mid and small-sized enterprises) versus those that can, usually the large corporates or SOEs with sovereign (explicit or implicit) guarantee.
  • It results in global savings glut (from higher asset prices) and investment slump (from lack of projects that meet the CFO’s 12-15% required return target), and such phenomenon may persist for a long time.
  • It encourages capital and talent to flow into non-productive sectors that directly benefit from lower interest rate and higher asset prices – such as the financial industry and housing (housing construction and property agency) – but do not contribute to long-term economic productivity growth.

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