Univariate and Multivariate Factor Screens on the US Equity Market
May 1987 through January 2003
January 2003 through March 2004
Joe Kippels
April 27, 2004
Executive Summary:
Univariate and Multivariate factor screens were used to evaluate previous U.S. equity performance. The screens reset on a monthly basis and each stock within the universe was placed in one of ten tiers based on its ranking within the screen. The returns were based on fundamental and technical data with returns being measured on both an equal weighted and value weighted basis. The FACTSET data system was used to perform the screens and the returns referred to in this paper are those given through the FACTSET system.
Data:
The FACTSET system used connects through to the COMPUSTAT Database. The same dates that were run in a previous study by Kevin Stoll and Campbell Harvey were used in this study. These dates are from May 1987 through January 2003. Some data sets were not available dating back to May 1987 and when this was the case all available data was used. Time periods are marked on the results. Additional runs of the data were generated for the full year 2003 through March 2004.
The minimum market value used for the companies in the screens was $500 million kept constant throughout the screen. The only exception to this rule was the screen based on the market capitalization of the companies in the screen. In this screen the minimum market capitalization of the company was $15 million in order to take into account micro cap companies.
The number of eligible companies for the screen increases as time goes by. In 1987 slightly over 500 companies were included in the screen per month while there were close to 2000 companies in 2003. This is partly due to the eligible market cap staying constant through time at $500 million.
Univariate Factors Used:
Earnings Yield - Monthly
Stocks were tiered based on the earnings yield as of month-end for the dates requested. This is calculated as Latest Twelve Months EPS divided by Price, multiplied by 100. The data was lagged by 90 days to account for the amount of time it takes individual companies to disclose earnings to the market.
Return on Average Total Equity
This returns the annual return on average total equity as of the fiscal year-end for the dates requested. This is calculated as Net Income Before Extraordinary Items divided by the one-year average of Total Stockholders Equity, multiplied by 100. The data was lagged by 90 days to account for the amount of time it takes individual companies to disclose earnings to the market.
Earnings Momentum - 1 Year Annual Growth
This is calculated as the Current Earnings Per Share divided by Last Year's Earnings Per Share minus one multiplied by one hundred. The data was lagged by 90 days to account for the amount of time it takes individual companies to disclose earnings to the market.
Price Momentum 3-Year Price Change
This measurement calculates the actual percentage change that has taken place over three years.
Price Momentum 1-Year Price Change
This calculates the actual percentage change that has taken place over one year.
Price Momentum – Monthly Percent Change
This returns the month over month change in price as of month-end for the dates requested. This is calculated by taking the month over month percent change.
Price Momentum – One Year Minus One Month Price Momentum
This ranks stocks based on their one year percentage gain, minus their one month percentage gains. Stocks in the first tier of this category are those whose positive difference between their previous year’s percentage gain and their previous month’s percentage gain is the greatest.
Market Value - Monthly
The tiers are based on the market value as of the month-end. This is calculated as Price multiplied by Common Shares Outstanding. For this specific screen the minimum Market Capitalization was lowered from $500 million to $15 million to be able to capture the returns of small and micro cap companies.
Total Debt as a Percent of Total Equity
The tiers are based on the quarterly total debt as a percent of total equity as of the fiscal quarter-end. This is calculated as the sum of Total Long-Term Debt and Total Short-Term Debt, divided by Total Stockholder's Equity.
Price to Book Value
This returns the price to book ratio as of the month-end. This is calculated as Price divided by Book Value per Share. The stocks are tiered in reverse order, to give values based on book to price, where those stocks with higher book values relative their prices are ranking in the first tiers.
Price to Cash Flow
This is based on the latest twelve months of the quarterly price to cash flow ratio for the fiscal quarter for the dates requested. This is calculated as Price divided by latest twelve months of Net Cash Flow from Operations per Share. The lower the price to cash flow ratio, the closer to the first tier the stock will be.
Dividend Yield
This is the dividend yield as of the month-end for the date(s) requested. This is calculated as the Annualized Dividend Rate divided by Price, multiplied by 100.
Reinvestment Rate - LTM
Stocks are tiered based on the latest twelve months of the quarterly reinvestment rate as of the fiscal quarter-end for the date(s) requested. This is calculated as the sum of the latest four quarters of net income minus the sum of the latest four quarters calculation of common and preferred dividends. The result is divided by stockholders equity.
Multi-Factor Model:
A final screen was performed using 4 factors to determine the tiers. The factors used were: Earnings Yield, Return on Equity, 1 Year minus 1 Month Price Momentum, and Cash Flow Yield. Scoring was as follows:
For Earnings Yield, stocks in the first three tiers were given scores of 3, 2, and 1 respectively and stocks in the last decile were given a score of -2.
For ROE, stocks in the first two tiers were given scores of 2 and 1, and stocks in the last tier received a score of -3.
For 1 Year minus 1 Month Price Momentum, stocks in the first two tiers received a score of 4 and 3, and stocks in the last two tiers received scores of -1 and -3.
For Cash Flow Yield stocks in the first three tiers received scores of 4, 4, and 3 respectively, and stocks in the last tier received a score of -4.
Overview of Findings:
The strongest correlations between univariate factor specific variables and equity performance were found in Cash Flow to Price, Reinvestment Rate, Price Momentum, Return on Equity, and the Earnings Yield. In a portfolio consisting of a long position in the top 10% of stocks relative to the specific variable and a short position in the bottom 10% of stocks relative to the specific variables, monthly alphas relative to the S&P 500 of 1.7, 1.46, 1.14, and .92 were found from the initial dates tested from May 1987 through January 2003.
Alphas and Betas are calculated through FACTSET. The alpha value of each fractile’s constituent is the intercept of the regression line drawn for the S&P500 returns versus those of the fractile. The Beta Value for each fractile’s constituents is the slope of the regression line of the S&P500 returns versus those of the model.
EARNINGS YIELD
Results indicate that there is a positive correlation to earnings yield and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the earnings yield and short positions in the 10% of stocks with the lowest earnings yield would have given the returns depicted in the graph below.
Earnings Yield 2003-2004 results
These results have not held constant from January 2003 through March of 2004. Over the 15 months in an equally weighted portfolio stocks in the top 10% of earnings yield have gained a geometric average of 3.95% per month while those in the bottom 10% have gained a geometric average of 5.06%. A similar portfolio during this period would have yielded the following monthly returns:
RETURN ON EQUITY
Results indicate that there is a positive correlation to Return on Equity and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the greatest Return on Equity and short positions in the 10% of stocks with the worst Return on Equity would have given the returns depicted in the graph below.
2003-2004 results
These results have not held constant from January 2003 through March of 2004. Over the 15 months, stocks in the top 10% of year over year earnings momentum have gained a geometric average of 2.93% per month in an equally weighted portfolio while those in the bottom 10% have gained a geometric average of 4.41%. A similar portfolio during this period would have yielded the following returns:
EANINGS MOMENTUM
Results indicate that there is virtually no correlation to earnings momentum and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the greatest year over year percent increases in earnings and short positions in the 10% of stocks with the worst year over year percent increases in earnings would have given the returns depicted in the graph below.
2003-2004 results
Over the 15 months from January 2003 through March of 2004, stocks in the top 10% of year over year earnings momentum have gained a geometric average of 2.95% per month in an equally weighted portfolio while those in the bottom 10% have gained a geometric average of 3.00%. A portfolio during this period would have yielded the following returns:
THREE YEAR PRICE MOMENTUM:
Results indicate that there is a slight negative correlation to 3 year movements in the price of a stock and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the greatest percentage gains over a 3 year history and short positions in the 10% of stocks with the worst 3 year percent gains in price would have given the returns depicted in the graph below.
2003-2004 results
The negative correlations persisted from January 2003 through March of 2004. Over the 15 months stocks in the top 10% of percentage gainers in terms of price have gained a geometric average of 3.17% per month in an equally weighted portfolio while those in the bottom 10% have gained a geometric average of 5.27%. A similar portfolio during this period would have yielded the following monthly returns:
ONE YEAR PRICE MOMENTUM:
Results indicate that there is a slight positive correlation to the one year price movement in a stock and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the greatest percentage gains over the past year and short positions in the 10% of stocks with the worst one year percent increases (or greatest decreases) in price would have given the returns depicted in the graph below.
2003-2004 results
The slight positive correlation reversed itself in 2003 and through March of 2004. Over the 15 months stocks in the top 10% of percentage gainers in terms of price have gained a geometric average of 3.41% per month in an equally weighted portfolio while those in the bottom 10% have gained a geometric average of 4.80%. A similar portfolio during this period would have yielded the following returns:
ONE MONTH PRICE MOMENTUM:
Results indicate that there is very little correlation to 1 month movement in the price of a stock and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the 10% of stocks with the greatest month over month percent increases in price and short positions in the 10% of stocks with the worst month over month percent increases in price would have given the returns depicted in the graph below.
2003-2004 results
The correlations have been slightly negative from January 2003 through March of 2004. Over the 15 months stocks in the top 10% of percentage gainers in terms of price have gained a geometric average of 3.47% in an equally weighted portfolio per month while those in the bottom 10% have gained a geometric average of 4.17%. A similar portfolio during this period would have yielded the following returns:
ONE YEAR MINUS ONE MONTH PRICE MOMENTUM:
Results indicate that there is an extremely high correlation to the difference between a stock’s previous year’s gain and its previous month’s gain and positive stock returns. A portfolio consisting of long positions in the 10% of stocks with the greatest positive differences between the previous year and the previous month and short positions in the 10% of stocks with the lowest year minus month percent differences would have given the returns depicted in the graph below.
2003-2004 results
The positive returns have not held constant from January 2003 through March of 2004. An equally weighted portfolio would have returned a geometric average of 3.38% in the top tier and 4.54% in the bottom tier over the last 15 months.
MARKET CAPITALIZATION
Results indicate that there is a positive correlation to smaller companies and positive stock returns. An equally weighted market neutral portfolio consisting of long positions in the smallest 10% of stocks and short positions in the largest 10% of stocks would have given the returns depicted in the graph below.