Market participants have used common risk factors such as value, momentum, dividends, low volatility, quality, and size (small cap) to construct portfolios historically. Our recently published research paper, “Do Earnings Revisions Matter in Asia?,” explored the performance of earnings revision strategies as an alternative source of return drivers across seven markets in Pan Asia, including Australia, China, Hong Kong, India, Japan, South Korea, and Taiwan. In this article, we will take a closer look at the performance and characteristics of this strategy in India.
The study examined the EPS revision strategies based on two different measures: the first is based on the three-month change in the consensus EPS estimate (EPS change), and the second is the three-month diffusion of the EPS estimates (EPS diffusion.) The study concluded that stock prices tended to move in the same direction as their earnings revisions in the majority of Pan Asian markets. In India, an equal-weighted top quintile portfolio of EPS diffusion and EPS change strategy generated an excess return (against the base universe) of over 8% and 4.5% (CAGR) over the 11 years ending December 2016 (see Exhibit 1).
|Exhibit 1: Performance Characteristics of Equal-Weighted Earning Revision Portfolios Versus Base Universe in India
||S&P INDIA BMI
||EPS DIFFUSION STRATEGY
||EPS CHANGE STRATEGY
|Excess Return (%)
|Tracking Error (%)
Source: S&P Dow Jones Indices LLC. All portfolios shown are hypothetical. Performance based on local currency total return from Dec. 31, 2005, to Dec. 31, 2016. Table is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of “Do Earnings Revisions Matter in Asia?” for more information regarding the inherent limitations associated with back-tested performance.
Some factor strategies such as value and low volatility witness pronounced sector biases, which could be the dominant driver for factor performance. For most markets in Pan Asia, sector compositions for EPS revision factor portfolios were correlated with the base universe, and therefore one may be able to conclude that sector revision strategies were free from sector allocation bias. Within these markets, however, India had a relatively higher sector bias, with the correlation between sector representation in the factor portfolio and base universe dropping below 70% in the majority of the periods covered in the study. In India, industrials was the most under-represented sector in the EPS revision portfolios compared to the base universe. Although some sector bias was observed in India, it was also observed that sector allocation bias wasn’t a dominant driver of alpha, as can be seen in the performance of sector-neutral stock selection quintiles. For example, the top quintile equal-weighted portfolios of EPS change and EPS diffusion delivered a monthly excess return of 0.31% and 0.52%, respectively, over the base universe. Sector-neutral, stock-selection-based EPS change and EPS diffusion strategies delivered monthly excess returns of 0.30% and 0.47%, respectively, over the base universe.
The study also notes that size bias was not an important driver of excess returns for the earnings revision strategies in India. Over the back-tested period, the average weight of the small-cap factor in the equal-weighted base universe was 58.6%, whereas the factor’s weight in equal-weighted top quintiles of the EPS change strategy and the EPS diffusion strategy was 60.4% and 55.8%, respectively.
In India, market participants tended to penalize stocks with poor earnings revisions more during downward and neutral market periods. In contrast, the portfolio of stocks with poor EPS change outperformed the base universe with significant excess return during upward market trends, indicating that market participants in India tended to disregard earnings downgrades when the market was bullish (see Exhibit 2).
|Exhibit 2: Average Monthly Excess Returns of the Earnings Revision Portfolios Versus Their Respective Universes in Different Market Trends (%)
||EPS DIFFUSION STRATEGY
||EPS CHANGE STRATEGY
Source: S&P Dow Jones Indices LLC. All portfolios shown are hypothetical. *Denotes statistical significance at 5% using one-tailed t-test. **Denotes statistical significance at 1% using one-tailed t-test. Figures based on monthly local currency total return from Dec. 31, 2005, to Dec. 31, 2016. Table is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of “Do Earnings Revisions Matter in Asia?” for more information regarding the inherent limitations associated with back-tested performance.
A potential challenge to implement this strategy is the relatively high average annualized turnover of 257% for the EPS diffusion top quintile portfolio and 263% for the EPS change top quintile portfolio over the entire back-tested period in India. The turnover for India was at the lower end of the spectrum when compared with other markets studied. A combination of an EPS revision strategy with other fundamental factors may help lower turnover and provide a practical approach to passively implement this strategy.
 The three-month EPS change was calculated as the current median EPS estimate minus the prior three-month median EPS estimate, divided by the absolute value of the prior three-month median EPS estimate. EPS estimates are in INR.
 EPS diffusion was computed as the number of upward revisions minus the number of downward revisions of EPS estimates divided by the total number of EPS estimates.
 Constituents from the S&P India BMI with at least three analyst estimates at the time of rebalancing formed the base universe.
 Excess returns and tracking error for the base universe was calculated against the S&P India BMI. Excess returns and tracking error for EPS diffusion and EPS change strategies were calculated against the base universe.
 For a full comparison versus a sector-neutral portfolio, please refer to Exhibit 4 and 9 in the report.
 Market trend was calculated based on S&P India BMI performance, with periods of monthly return greater than 1% representing up markets, periods of monthly return less than -1% representing down markets, and the rest of the periods representing neutral markets.
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