Analyst Earnings Surprises with Value and Momentum Filters
Summary
The article defines an earnings surprise factor, ESP, as the difference between actual and expected quarterly net profit divided by the absolute expected amount. It describes deriving quarterly analyst expectations from annual forecasts under an assumption that quarterly and annual forecast growth rates are the same. A factor analysis across valuation, growth, quality, momentum, liquidity, and technical characteristics identifies earnings yield (EP_TTM) and the prior month's return as useful filters for the surprise-stock universe.
The monthly strategy selects stocks in the top 30% on both filters, then holds the 20 names with the largest ESP. The document reports historical results from 2009 through September 2019, including excess returns against Chinese equity benchmarks, and says the portfolio generally outperformed the CSI 500. These figures are historical claims in the supplied summary, not independently verified here. The forecast decomposition assumption, factor coverage, sample construction, rebalancing, and transaction costs are material limits; the text does not provide enough detail to assess robustness or live implementability.
Key ideas
- ESP scales the gap between actual and expected quarterly net profit by the absolute expected amount.
- Quarterly analyst forecasts are estimated using an assumption linking quarterly growth forecasts to annual growth forecasts.
- The strategy filters for stocks ranked highly on both earnings yield and recent monthly return.
- It then selects the 20 stocks with the largest earnings surprise factor values at each month end.
- The reported benchmark outperformance is historical and depends on data construction and implementation assumptions.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.