Growth vs. Value Trading Strategies

1. Growth vs. Value Trading Strategies Global Asset allocation John O’Reilly Sebastian Otero Barba Nikolay Pavlov Franck Violette

2. AGENDA • Overview of Value and Growth • Historical Trends • Goal and The Approach to that Goal • The Datasets and Regression Results • Trading Strategy within a single class (small, mid, large, and all) • Trading Strategy among All • Summary Page 2

3. Overview of Value and Growth Growth and Value are two fundamental approaches: Growth stock represent companies that have demonstrated better than average gains in earnings in recent years and are expected to continue delivering high levels of profit growth. Value Stock represent companies that are currently out of favor in the marketplace and are considered bargain priced. Value stocks are typically priced much lower than stocks of similar companies in the same industry and may include stocks of newer companies with unproven track records. Combining the two styles can help reduce portfolio volatility because each have outperformed the other at different phases of the business cycle. Page 3

4. Overview of Value and Growth Page 4

5. Historical Trends Page 5

6. Historical Trends Growth and Value Stock have taken turns leading the market. Page 6

7. Goal and The Approach to that Goal • Goal: • To recommend a Trading Strategy for this year. • Approach: • Build predictive models for Total Returns of small, mid, large, all cap Value & Growth Indexes. • Variable selection was top down. • Selected variables have low correlation to each other. • Variables were parsed based on a number of measures. • Quadratic relationships were explored. • Mixed style – swap, long/short trading strategies within cap and among cap. • Test in Sample & Out of Sample. Page 7

8. The Datasets and Regression ResultsAll Caps Value Variables Page 8

9. The Datasets and Regression ResultsAll Caps Growth Variables Page 9

10. The Datasets and Regression ResultsLarge Cap Value Variables Page 10

11. The Datasets and Regression ResultsLarge Cap Growth Variables Page 11

12. The Datasets and Regression ResultsMid Cap Value Variables Page 12

13. The Datasets and Regression ResultsMid Cap Growth Variables Page 13

14. The Datasets and Regression ResultsSmall Cap Value Variables Page 14

15. The Datasets and Regression ResultsSmall Cap Growth Variables Page 15

16. The Datasets and Regression ResultsAdjusted R^2 Values Page 16

17. The Datasets and Regression ResultsIn Sample Direction Predictions Page 17

18. The Datasets and Regression ResultsOut of Sample Direction Predictions Page 18

19. Trading Strategy within a single class (small, mid, large, and all) • If the predicted growth and value return is less than the 30 Day T-Bill return, put 100% in T-Bills. • If the predicted growth or value return is greater than the 30 Day T-Bill return put 100% in either growth or value depending on which has the highest predicted return • Compare with buying and holding 100% value. • Compare with buying and holding 100% growth. Page 19

20. Trading Strategy within a single class (small, mid, large, and all) In Sample Results Page 20

21. Trading Strategy within a single class (small, mid, large, and all) Out of Sample Results Page 21

22. Trading Strategy within a single class (small, mid, large, and all)Out of Sample Predictions Page 22

23. Summary • Value versus Growth performance varies across capitalizations. • Implementing a simple trading strategy created larger in sample returns than buying and holding value or growth, but with higher volatility than value. • Better In Sample predictions than Out of Sample due to different market patterns in the late 90’s. Models prediction estimated to be representative for current market conditions. • A more complex trading strategy can be implemented by rebalancing a portfolio each period by using the expected returns and volatility during the next period for each asset class. Page 23