The Usefulness of Accounting
Fundamentals at the Industry Level:
Which Performance Metric Matters?
Jack Strauss
Philipp Schaberl
University of Denver
Beijing Jiaotong University
Overview
• Can we form industry portfolio using
accounting variables to outperform a
buy-and-hold out-of-sample?
• What variable(s) are most useful in
selecting industry portfolios?
• Why are these variables useful?
• What type of forecasting framework
makes sense?
Background
• Traditional Predictability Model regresses:
• Rt = a + b1Et-1/Pt-1,
Where Rt is the market return
• Predictability measured by OOS R200S < 5%
• Motivated by Timing Varying Risk or Gradual Diffusion of
Information (Hong, Lim and Stein (JF, 1999); Hong, Torous and
Valkanov (JFE, 2007; Rapach, Strauss and Zhou (JF, 2013).
• Pesaran and Timmermann (1995) report `An alternative
approach to evaluating the economic significance of stock
market predictability would be to see if the evidence could
have been exploited successfully in investment strategies. This
can be done' by evaluating portfolio allocation in "real time,"
and see if these portfolios systematically generate excess
returns of forecasting performance, such as the directional
accuracy.
Industry Level
• Very Little Academic Literature on Industry
Predictability or Portfolio Allocation
• Rapach, Strauss and Zhou (JPM, 2013) show size
and book to market can both predict
• Rit = a + bi1SZ/BMi,t-1
• Size/Value Weighted sorts
• Portfolio Allocation: Rotate into long positions for
industries with high returns and short industries with
Value Relevance Approach
• Ball and Brown (1968); Beaver (1979) identify the top
and bottom decile of firm earnings and then plot the
cumulative returns of these firms. A variable is value
relevant if there is a large gap between the two
deciles as the firms with high earnings should have
increasing payoffs and the firms with low earnings
should have declining payoffs.
• Earnings is more value relevant than cash-flow if the
gap is larger as it is more linked to returns.
• Predictable and Relevant for Returns and CF or
Earnings (Ohlson, RAS, 1999)
• So Transitory earnings should not affect returns – they
are not predictable, and should also not be related to
permanent stream of cash-flow/earnings
Our approach
Use forecasted
EAit = a + bi1EAit-1++ bi2EAit-1
•
•
•
•
•
Then Sort
Typically, choose High and Low Rit
To allow for lags in data release, we choose
Highest and Lowest Decile Rit+2M
Use 1980.1 to forecast returns in 1980.06-1980.08
Data
•
•
•
•
•
•
•
We choose Compustat data from 1975.1-2013.4
Net Income/Assets
Cash-Flow/Assets
Operating Profits (Ball et al, 2014)
Gross Profits (Novy-Marx, JFE 2013)
Earnings/Price
Returns are from the Fama-French 38 Industry
Database. We use 31 industries
Predictability of Variables
Industry Portfolio Results – using Actuals
Industry Portfolio Results – using Forecasts
Portfolio Allocation using
4 month Lead
Consistent Over time
Granger Causality
Portfolio not Riskier
Portfolio not Riskier
Portfolio not Driven by Size
Portfolio not determined
by size