1. Informing the Choice of Fractile Usage in Factor-Based Stock Screening
Maria Fernandez
David Marcus
Matthew Meares
Hiren Patel
Hong Wan

2. Introduction
Purpose: To study the trade-offs (risk-return) in factor-based screening by varying portfolio size
Fractiles are used as the standard method for choosing portfolio size
Potential to overlook the impact of fractile choice in portfolio formation
FactSet offers limited defaults of 4, 5, 10 fractiles

3. Factor Rank Order Expectation
Good factors will produce a rank order with a large negative slope
Downward slope may exhibit linear relationship (R2)

4. Factor Rank Order Reality
Factor is not sole driver of stock returns
Unsystematic risk also exists

5. Fractile Portfolios for Diversification
Placing securities into fractiles provides diversification of risk, but potentially at a cost…

6. Consequences of Diversification
As portfolio size increases (# of fractiles decreases), portfolio is adding in securities that, based on factor rank, are expected to generate a lower return

7. Finding Risk/Return Balance
The advantage of diversification diminishes rapidly in randomly selected stock portfolios
Factor-ranking portfolios may not reduce risk as well, given non-random portfolio formation
Source: `

8. Methodology Two universes: Period: Factors for screening:
750 Biggest US Companies by Market Cap
750 Small Cap US Companies
Equally weighted portfolio composition
Period:
Monthly Dec 30, 1994 till Nov 1, 2004; rebalanced every month
Factors for screening:
ROA
Dividend Yield
Price / IBES Standardized Unexpected Earnings (SUE)
Price / IBES Mean EPS
LTM EPS / Price
Prior month trading volume
LTM total return
Cash / Price

9. Fractile Analysis - SUE
SUE exhibited the one of the best factoring ranking characteristics

10. Fractile Analysis - SUE
Long portfolio exhibits expected loss of diversification benefit
Dynamics of long-short portfolio not completely understood

11. Fractile Analysis - SUE

12. Conclusion
Similar dynamic exists across many factor ranked models and across market caps (see paper for details)
Trade-off between return and risk directly applies to fractile selection and should probably be managed more effectively
Areas for further study
Application to value weighted portfolios
Estimation of trading costs in small versus large factor ranked portfolios
Stability across time intervals – perhaps measured with slope and R2 – and return periods