1. Stock Selection in Korea
Beyond Efficient Frontier Capital Management
Onthida Boonpiamsak
Pab Jotikasthira
Jeongsik Lee
Neal Triplett
Jaekeun Yoon

2. Agenda Sorting method and attributes for screening Diagnostics
Factor/portfolio selection
Optimization
Conclusion

3. Sorting Method Attributes for Screening
We used sorting method in stock selection:
Univariate Attributes
Dividend yield
Earning growth
Projected Earnings Growth
Projected P/E
ROE
Reinvestment Rate
Momentum (1mo., 1yr.)
Cash Flow to Price
Earnings to Price
Book to Price
Revenue Growth
Bivariate Attributes
BV/P and MCAP
Dividend yield and Earning growth
Dividend yield and Projected EY

4. Diagnostics Performance Measurement Consistency Measurement
Average return and excess returns over market and risk-free
% Periods > Market
% Periods with positive return
Average ranking score
Consistency Measurement
Standard deviations of returns and excess returns
Year by year ranking score

5. Factor /Portfolio Selection
Significant Attributes
CF/P
E/P
PPE
ROE
RIR
BV/P and MCAP
DY and PPE

6. Korean Stock Market (6/93-5/98)

7. Factor/Portfolio Selection
Cash Flow/Price

8. Factor/Portfolio Selection
Earning/Price

9. Factor/Portfolio Selection
Prospective Price/Earning

10. Factor/Portfolio Selection
Return On Equity

11. Factor/Portfolio Selection
RIR

12. Factor/Portfolio Selection
Low Book Value/price Sorted by MCAP

13. Factor/Portfolio Selection
Low Dividend Yield Sorted by Projected P/E

14. Optimization Match market volatility and maximize return:
Weight Weight
(Top) (Bottom)
BV/P and DY
CF/P
E/P
PPE
ROE
RIR

15. Optimization In-sample performance:
Beat market by 0.96% per month on average.
Beat market 68.75% of the time.
Out-of-sample test on 11-month data:
Beat market by 2.83% per month on average.
Beat market 72.73% of the time.

16. Conclusion
Significant attributes in selecting stocks include CF/P, E/P, PPE, ROE, RIR, and BV/P and dividend yield together.
In Korea, stock selection (by sorting method) can help improve performance.
One important finding is that top fractiles tend to have high correlations with one another; hence, we may need to use bottom fractiles to reduce volatility.