In August 2011, I created a Dividend Growth (DG) model portfolio focused on Income Growth. It sought a 4% yield and lower beta by screening the DG universe using criteria including yield, dividend growth rate (DGR), earnings growth, and payout ratio. While income and income growth were the focus, my own goal was to also achieve higher total return than the overall stock market. The DG-IncomeGrowth model started with $300,000 on August 16th, 2011, and has so far met its goals by outperforming the S&P (SPY) and S&P Dividend ETF (SDY) over the last 19 months and having a low beta of 0.67. The portfolio is generally passive, though I replace stocks that cut their dividend or that trigger a -20% stop-loss rule. The portfolio was last rebalanced in September 2012 and I am performing semi-annual rebalances, based on research that found rebalancing beneficial for value-oriented portfolio yields and returns.
Through March 28, 2012, the DG-IncomeGrowth portfolio had the best total return performance on both an absolute and relative basis. It also had the lowest beta over the long-term. Note that the Low-Beta, High DGR model just started three months ago. The DG-IncomeGrowth model benefited from a couple of buyouts, namely Heinz (HNZ) in 2013 and Harleysville Group in 2011, but even factoring out those gains, the model demonstrated excellent reward-to-risk, and also had the lowest maximum drawdown.
The Screening Process
This section outlines my screening process for updating this portfolio. The number in brackets indicates the number of stocks remaining after each filter step. The screening process for these models relies on David Fish's CCC list, so as always, thank you to him for putting it together each month,
- I began with the March 29, 2013 CCC list, combining the champions and contenders, which have 10 or more years of consistent dividend growth. I also included stocks with 9 years of DG from the Challengers list. I wanted a slightly larger universe, as I tightened some of the criteria to ensure more of a value orientation, given that we are at market highs on the indices. [338 stocks in total]
- I sorted the combined list by market cap, and removed those with a market cap less than $500MM. This portfolio seeks mid and larger-cap firms for more stability. [285 remain]
- I sorted the remaining list by current yield, and proceeded to remove stocks with a yield less than 2.25%.  U.K. research found that higher yielding stocks tend to outperform, and also, the purpose of this portfolio is to provide investors with a decent yield as well as growth. Individual readers could choose a higher cut-off, but ultimately, I reviewed survivors starting with higher yielders anyway. This cutoff is lower than previous rebalances because with the market run-up, yields have declined.
- I sorted the remaining list by 5-yr Dividend Growth Rate [DGR] and removed all stocks with a DGR < 4%, since this portfolio seeks equities that are growing their dividend at a decent rate. I repeated this exercise using the 1-yr DGR column as well. 
- From this list, I removed BHP Billiton Ltd (BHP), which is the same as BHP Billiton plc (BBL). BBL is preferable because the UK does not withhold taxes on dividends to US shareholders. 
Screened Group Characteristics
The 102 stocks that survived the screening process had an average yield of 3.39% (a bit lower than in September 2012) and 1-, 3-, and 5-year DGRs of 12.3%, 11.3%, and 11.7%. For comparison, the original 338-stock universe had an average yield of 2.79%, with respective DGRs of 10.5%, 9.8%, and 10.2%. So the screening process raised both the average yield and the average DGRs. I proceeded to add a sector tag for each stock, sort the stocks into sector groups and then by yield. The table below shows the group characteristics.
I calculated the percentages for each sector based on market cap and by representation (count). Since there is a difference between these percentages, I averaged the two values to obtain a weighting for this portfolio. Due to the wider spread in the market caps, I double-weighted the count percentage to maintain better balance. This average weighting determined how many of the 30 stocks were allocated to each sector.
Relative to the March 28, 2013, S&P weightings, the portfolio is heavier on consumer staples, energy and utilities. It is noticeably lighter on technology, consumer discretionary and financials. This allocation should contribute to lower beta and lower standard deviation of weekly returns of this portfolio. It also contributes to the higher yield, as some of the higher yielding DG stocks reside in the utilities and energy sectors.
To decide which stocks to select from the screened list, I added columns for Yield, 3-yr DGR, 1-yr DGR, Payout, next year's EPS Growth Rate, and Beta, assigning point values to help me compare the stocks. Unlike my other models, I did not use a total score to decide which stocks to purchase. Given the generally lower yields at the present market level, I lowered some of the cutoff levels.
NY Earnings Growth Rate
10% to <15%
5% to <10%
0% to <5%
10% <= x < 14%
6% <= x <10%
10% <= x < 14%
6% <= x <10%
The stocks in each sector were ranked based on yield, followed by 3-yr DGR. The 1-yr DGR was used as a tiebreaker if two stocks had the same yield and 3-yr DGR rankings. Likewise, the EPS Growth metric was used as a tiebreaker, but also, all stocks with a negative earnings growth projection were removed. Since earnings drive dividend growth and price appreciation, I want to focus on growing firms. The payout metric verified the firm's ability to cover the dividend. For MLPs, REITs, and stocks with a payout over 65%, I checked operating cash flows and required that the dividend payout be covered by these cash flows for at least three of the last four quarters.
With this information, I selected stocks from each sector, starting with those that had the highest yield and 3-yr DGR combinations. Defense stocks occupied 4 of the top 5 positions for the Industrials sector, so I made an executive decision to limit the model to two defense stocks.
Before final acceptance, I performed my -20% stop-loss test to see if the stock's performance was 20% below the S&P's for four consecutive weeks since its last dividend increase. If the stop-loss was triggered, the stock was removed from consideration. Given that we are at current market highs, I was more aggressive in my interpretation of this rule, removing a few that have been at -18.5% and one that is going on its fourth week at -20%. Impacted stocks included: Intel (INTC), BHP Billiton, NTT DoCoMo (DCM), and Nippon Telegraph & Telephone (NTT). The final list of 30 stocks is presented in the picture below.
The final portfolio has an average yield of 3.94%, and its 1-, 3-, and 5-yr DGRs are 11.7%, 12.0%, and 12.7% respectively, which are comparable to the screened universe's traits, but with a higher yield. The yield is lower than the pre-rebalance portfolio, which had a current yield of 4.21%. This occurred because some very high yielders, such as AstraZeneca (AZN), Meredith Corp (MDP), AT&T (T) and some MLPs were excluded due to negative earnings growth projections or low dividend growth rates. Individual investors may choose to hold these firms for their high yields, which appear to be safe. As this model portfolio is rule-bound, they were excluded in favor of slightly lower yielders with better earnings growth potential, which should result in higher total return.
Of the 30 stocks, 17 are new to the portfolio. In general, stocks with higher yielders and/or higher earnings growth firms replaced the stocks that were sold. The Utilities, Info Tech and Materials sectors experienced the highest turnover. Below is a Yield-Payout matrix that shows most stocks concentrating in the high-yield/high-payout region of the table. Excluding MLPs and REITs, the portfolio yields 3.59% with an average payout of 64%.
High Payout (>60%)
Texas Inst (TXN)
Northeast Util (NU)
Procter & Gamble (PG)
General Mills (GIS)
Kimberly Clark (KMB)
Emerson Electric (EMR)
Air Products (APD)
Harris Corp (HRS)
High Yield (3.5%+)
Enterprise Product Partners (EPD)
Genesis Energy (GEL)
Kinder Morgan (KMP)
Alliance Resource Partners (ARLP)
National Health Investors (NHI)
Digital Realty Trust (DLR)
Omega HC Inv (OHI)
Waste Mgmt (WM)
Shaw Comm (SJR)
Dominion Res (D)
Avista Corp (AVA)
Lockheed Martin (LMT)
Conoco Phillips (COP)
Tax Considerations and Substitutions
While I like the diversity that the foreign ADRs and MLPs add to the portfolio, they add tax considerations. I'm not an accountant, so if others have more accurate information, please post it.
- SJR should be fine for an IRA, as Canada does not withhold taxes on IRA dividends.
- NVS is Swiss, and from what I've read, an investor can submit a claim for withholdings above 15%, plus you can claim a US tax credit for the rest [non-IRA accounts].
- Investors can purchase Kinder Morgan's KMR (KMR) shares instead of KMP to avoid UBTI tax issues in an IRA. The other MLPs could be a concern for an IRA with respect to UBTI.
I updated the virtual DG-IncomeGrowth portfolio with the new holdings as of the closing prices on April 1, 2013. The total account value was $439,266.32, so approximately $14,625 was invested in each of the 30 stocks after commissions of $420.65. I will continue to track this portfolio and report on its performance relative to the S&P, S&P Dividend ETF and the other DG model portfolios. The next full rebalance will occur in October 2013. If any stocks cut their dividend, get bought out, or exhibit the -20% gap rule, they will be removed and replaced with another stock from the same sector based on the screening process.
I welcome feedback on this screening and selection process, as I continue to refine it based on comments, observations and new learning. I hope SA members find the process and the recommended list useful for identifying potential candidates for their portfolios.