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

BA 453 – Global Asset Allocation & Stock Selection Page 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

BA 453 – Global Asset Allocation & Stock Selection Page 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.

BA 453 – Global Asset Allocation & Stock Selection Page 4 Overview of Value and Growth Valuation Measure Value Growth Dividend Yield HigherLower Price/Earnings LowerHigher Price/Book LowerHigher Price/Net Tangible Assets LowerHigher Price/Cash Flow LowerHigher

BA 453 – Global Asset Allocation & Stock Selection Page 5 Historical Trends

BA 453 – Global Asset Allocation & Stock Selection Page 6 Historical Trends Growth and Value Stock have taken turns leading the market.

BA 453 – Global Asset Allocation & Stock Selection Page 7 Goal and The Approach to that Goal 1.Goal:  To recommend a Trading Strategy for this year. 2.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.

BA 453 – Global Asset Allocation & Stock Selection Page 8 The Datasets and Regression Results All Caps Value Variables All Cap Value VariableCoefficientT-Stat IT Govt Tres U Mich Concumer Confidence Index % Change Squared U Mich Concumer Confidence Index % Change Intercept *All variables lagged 1 month

BA 453 – Global Asset Allocation & Stock Selection Page 9 The Datasets and Regression Results All Caps Growth Variables All Cap Growth VariableCoefficientT-Stat IT Govt Tres U Mich Concumer Confidence Index % Change Intercept *All variables lagged 1 month

BA 453 – Global Asset Allocation & Stock Selection Page 10 The Datasets and Regression Results Large Cap Value Variables Large Cap Value VariableCoefficientT-Stat Dividend Yield Dividend Yield Tbill^ YR Tsry yield -3 month (annualized) (10Y-3M)^ Wilshire Growth Intercept *All variables lagged 1 month

BA 453 – Global Asset Allocation & Stock Selection Page 11 The Datasets and Regression Results Large Cap Growth Variables Large Cap Growth VariableCoefficientT-Stat Dividend Yield Dividend Yield Tbill^ YR Tsry yield -3 month (annualized) (10Y-3M)^ Wilshire Growth Intercept *All variables lagged 1 month

BA 453 – Global Asset Allocation & Stock Selection Page 12 The Datasets and Regression Results Mid Cap Value Variables Mid Cap Value VariableCoefficientT-Stat US IT Gvt UM CC -ve Value TR +ve 1 month lag Value TR -ve 1 month lag Intercept

BA 453 – Global Asset Allocation & Stock Selection Page 13 The Datasets and Regression Results Mid Cap Growth Variables Mid Cap Growth VariableCoefficientT-Stat 3 mo TR 1 month lag Aaa Corp Bond Yld Div Yld +ve Aaa-Tbill +ve 1 Month lag New Priv Housing Started +ve New Priv Housing Started -ve Initial Claims Empl. -ve Value TR +ve 1 month lag Value TR -ve 1 month lag Intercept

BA 453 – Global Asset Allocation & Stock Selection Page 14 The Datasets and Regression Results Small Cap Value Variables Small Cap Value VariableCoefficientT-Stat Div Yld+ 1 Month Lag Div Yld- 1 Month Lag Baa-Aaa 1 Month Lag DPI+ 1 Month Lag DPI- 1 Month Lag UM CC+ 1 Month Lag UM CC- 1 Month Lag U.S. IT Gvt 1 Month Lag Value TR 1 Month Lag Intercept

BA 453 – Global Asset Allocation & Stock Selection Page 15 The Datasets and Regression Results Small Cap Growth Variables Small Cap Growth VariableCoefficientT-Stat Div Yld+ 1 Month Lag Div Yld- 1 Month Lag Baa-Aaa 1 Month Lag US CPI 1 Month Lag DPI- 1 Month Lag UM CC+ 1 Month Lag UM CC- 1 Month Lag U.S. IT Gvt 1 Month Lag Growth TR 1 Month Lag Intercept

BA 453 – Global Asset Allocation & Stock Selection Page 16 The Datasets and Regression Results Adjusted R^2 Values Adj R^2 All-Value All-Growth Large Cap Value Large Cap Growth Mid Cap Value Mid Cap Growth Small Cap Value Small Cap Growth0.0134

BA 453 – Global Asset Allocation & Stock Selection Page 17 The Datasets and Regression Results In Sample Direction Predictions In Sample % Of Direction of Value Returns Correctly Predicted % Of Direction of Growth Returns Correctly Predicted % of Max(Value Returns, Growth Returns) Correctly Predicted All69.0%66.8%47.0% Large Cap69.2%63.7%47.8% Mid Cap63.7%64.6%57.1% Small Cap70.4%59.1%56.6%

BA 453 – Global Asset Allocation & Stock Selection Page 18 The Datasets and Regression Results Out of Sample Direction Predictions Out of Sample % Of Direction of Value Returns Correctly Predicted % Of Direction of Growth Returns Correctly Predicted % of Max(Value Returns, Growth Returns) Correctly Predicted All25.0%20.8%41.7% Large Cap66.7%58.3%75.0% Mid Cap70.8% 41.7% Small Cap66.7%54.2%62.5%

BA 453 – Global Asset Allocation & Stock Selection Page 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.

BA 453 – Global Asset Allocation & Stock Selection Page 20 Trading Strategy within a single class (small, mid, large, and all) In Sample Results In Sample Annualized ReturnAnnualized STD All Swap Strategy17.1%13.6% All Value Buy/Hold14.8%14.5% All Growth Buy/Hold-0.2%17.2% Large Swap Strategy16.8%14.7% Large Value Buy/Hold14.8%13.9% Large Growth Buy/Hold16.4%17.4% Mid Swap Strategy18.1%15.5% Mid Value Buy/Hold15.2%14.4% Mid Growth Buy/Hold13.6%19.9% Small Swap Strategy19.2%17.1% Small Value Buy/Hold15.74%13.5% Small Growth Buy/Hold13.8%22.5%

BA 453 – Global Asset Allocation & Stock Selection Page 21 Trading Strategy within a single class (small, mid, large, and all) Out of Sample Results Out Of Sample Annualized ReturnAnnualized STD All Swap Strategy-39.8%15.4% All Value Buy/Hold2.8%16.9% All Growth Buy/Hold-33.8%25.4% Large Swap Strategy2.6%18.0% Large Value Buy/Hold-5.8%16.5% Large Growth Buy/Hold-18.6%22.0% Mid Swap Strategy8.0%20.0% Mid Value Buy/Hold2.6%26.2% Mid Growth Buy/Hold-8.9%26.2% Small Swap Strategy0.5%19.1% Small Value Buy/Hold10.6%19.0% Small Growth Buy/Hold-1.7%23.3%

BA 453 – Global Asset Allocation & Stock Selection Page 22 Trading Strategy within a single class (small, mid, large, and all) Out of Sample Predictions Predicted Dec '02 Monthly Return Predicted Dec '02 Monthly Volatility Suggested Allocation All-Value0.53%20.99%-20.00% All-Growth1.74%5.47%120.00% Large Cap Value-0.27%16.00%120.00% Large Cap Growth-1.38%25.41%-20.00% Mid Cap Value0.92%24.09%120.00% Mid Cap Growth1.82%41.95%-20.00% Small Cap Value0.79%12.82%120.00% Small Cap Growth0.01%40.45%-20.00%

BA 453 – Global Asset Allocation & Stock Selection Page 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.