Predicting the DJIA: Going up the Income Statement

Predicting the DJIA:Going up the Income Statement BSD: Roberto Alatorre Prakash Arya Brian Chin Philipp Schmahl John Withrow

Agenda • Data Collection • Data Organization • Results • Conclusions

Data Collection • Collected data on the 30 companies that make up the DJIA • Quarterly Data • Q1 1979 through Q4 1999 • DJIA composition changes in: - Q2 1979 - Q4 1985 - Q1 1991 - Q2 1997 - Q4 1998 - Q4 1999

Data Organization • Income Statement data on a per share basis: • EBITDA Yield for DJIA • Dividend Yield for DJIA • Earnings for DJIA • Divisor Calculation • ( Share Prices) / (Actual DJIA) • Base case and adjusting for stock splits, etc. • Modeling the DJIA

BSD-DJIA vs. DJIA:

Hypothesis The further you go up the Income Statement, the better the variables will be to predict the returns for the DJIA Rationale: • Dividends are at managers discretion • EBITDA is hard to manipulate

Regression Results: Dividend Model: DJIAreturns = - 0.054 - 5.016*CrSprdLag + 2.273*TrmSprdLag + 1.255*TyldLag + 5.966*DivLag Earnings Model: DJIAreturns = 0.067 – 4.639*CrSprdLag + 2.479*TrmSprdLag + 0.788*TyldLag + 0.924*EarnLag EBITDA Model: DJIAreturns = 0.008 – 4.018*CrSprdLag + 2.449*TrmSprdLag + 1.014*TyldLag + 1.002*EbitLag

Regression Results:

Regression Results: p-Values Dividend Model 0.0071 Earnings Model 0.1034 EBITDA Model 0.0078

DJIA In-Sample Results:

DJIA Out-Sample Results:

Conclusions: • For DOW 30 Blue Chip Companies, EBITDA Yield is as good a predictor as Dividend Yield • Confidence interval on predictions from Earning Yield is less than 90% • ARCH underestimates DJIA in sample and in validation period

Predicting the DJIA: Going up the Income Statement