Citi on Investment Implications of Cliff Asness' Quality Minus Junk – ValueWalk Premium
Cliff Asness

Citi on Investment Implications of Cliff Asness' Quality Minus Junk

Citi Research discusses a recent white paper from AQR Capital Management analysts Cliff Asness, Andrea Frazzini, and Lasse H. Pedersen on Cliff Asness: Quality Minus Junk Investment Implications.

Citi on Investment Implications of Cliff Asness' Quality Minus Junk

Citi summary of AQR white paper

  • Quality characterises stocks that investors should be willing to pay a higher price for, everything else equal.
  • A portfolio strategy that buys high-quality stocks and sells low-quality stocks earns significant risk-adjusted returns with an information ratio above 1 in the U.S. and globally across 24 countries.
  • The price of quality varies over time, reaching a low during crises; quality stocks are low beta and benefit from ‘flight to quality’.

Cliff Asness: Quality characterizes stocks

This paper is concerned with the study of quality stocks. Asness, Frazzini, and Pedersen define quality by means of variables motivated by the Gordon’s growth model. They conjecture that quality characterizes stocks that investors should be willing to pay a higher price for, everything else equal. The primary objectives of the paper are to investigate the explanatory power of quality on prices and how that varies over time.

Cliff Asness: Quality is measured through proxies

The sample comprises U.S. stocks from 1956 to 2012 as well as stocks from 24 developed markets from 1986 to 2012. The dataset is compiled from CRSP/XpressFeed. The authors use a broad set of proxies to define four composite proxies: Profitability, Growth, Safety and Payout. A single quality score is then computed for each stock on a monthly basis. To evaluate the pricing of quality, the authors run cross-sectional regressions of price-to-book on each stock’s overall and separate quality scores. To gain additional insight they conduct portfolio analysis of the high- vs. low-quality stocks portfolio and construct a quality minus junk factor (QMJ hereafter).

Cliff Asness: The Sharpe ratio of a strategy

The authors document that on average, quality firms today remain high quality firms five and ten years into the future (conditional on survival). Among the characteristics of quality firms, profitability is the most persistent, and growth and payout are the least persistent. Higher quality is significantly associated with higher prices crosssectionally. Interestingly, stocks with high payout appear to command a lower, not a higher, price. The QMJ factor generates a risk-adjusted return of 0.66% per month for the U.S. sample and 0.45% for the Global sample. Moreover, the return of the QMJ portfolio is positive (and in most instances statistically significant) in the 23 out of the 24 countries ranging from 0.20% in Spain to 1.02% in Hong Kong and 1.06% in Greece. The highest Information ratio is observed for the US, i.e. 1.46.

Cliff Asness: Combining Quality with Value

Additional analysis indicates that QMJ benefits from “flight to quality” during crises. The authors stress that QMJ is irrespective of stock prices, i.e. value, and vice versa and hence they suggest that the two concepts can be combined; they term this ‘quality at reasonable price (QARP)’. Overall, the paper documents strong and consistent abnormal returns to quality, and does so in a setting that uses all four components implied by the Gordon Growth Model simultaneously.

Citi comments and investment implications

Quality is obviously not a new concept to equity portfolio managers although it may not always be meant in a unanimous way. This paper uses Gordon’s growth model as a simple framework to define quality in an aggregate measure of profitability, growth, safety, and payout. The variables that comprise the single quality measure in this paper largely overlap with our measures of firm quality7. From an applied point of view the paper enlightens with respect to the construction and the performance of quality-based portfolios through a long and broad backtest. Moreover, we get a better understanding on the relation between the quality determinants and equity returns, as well as on how quality varies over time, and how the current price of quality characteristics predicts the future return on characteristic-based factors. Hence, in a sense the price of quality can be viewed as a market timing factor perhaps also related to market sentiment.


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