As a dividend growth investor, when considering purchasing a stock, I think most would agree that it's important to consider the initial yield. It makes sense that by waiting until a stock's price drops (and the yield rises) one can have a greater portfolio value over time than if a lower yield is settled for. As someone with ~35 years until retirement, I'd like to get a sense of just how much the initial yield can make a difference in final investment value when dividends are reinvested. To do this, I wrote a python program to back test how much an investment in three separate dividend champions (Target (TGT), Colgate-Palmolive (CL) and Medtronic (MDT)) would be worth today using every day between January 1, 2001 and December 31, 2002 as a possible purchase date. By also looking at the dividend yield on each possible purchase date, the close relationship between future investment value and initial yield becomes apparent.
Stock price and dividend data were obtained from Yahoo Finance. The program uses this data to project what a $1,000.00 investment would be worth on March, 28, 2013 using every day between January 1, 2001 and December 31, 2002 as a purchase date. By doing this, it becomes apparent what a $1,000.00 investment would currently be worth had the position been initiated on any day in the two year time period between 2001 and 2002. For this analysis, all dividends are reinvested on the ex-dividend date and no further contributions are made after the purchase. To display the results, the investment value (number of shares owned * stock price) on March 28, 2013 and dividend yield at the time of purchase are plotted on the same graph as functions of the date of purchase.
The following graphs demonstrate the close relationship between long-term dividend investment value and initial dividend yield when dividends are reinvested for 10+ years. Along the x-axis are all the days between January 1, 2001 and December 31, 2002. For each of those days, the program simulated an investment of $1,000 in the specified stock and used Yahoo Finance data to calculate what the investment would have been worth on March 28, 2013; this value is on the left hand y-axis. On the right hand y-axis is what was the annual dividend yield at the time of purchase, i.e. the initial yield. The color of the line indicates whether it is value on March 28, 2013 data (blue) or initial annual dividend yield data (red).
For each of these three dividend champion back tests, one can easily see that over time, an investment is worth much more when the dividend yield at the time of purchase is high. For example, in the case of TGT, the difference in investment value on March 28, 2013 between initiating a position on August 1, 2001 and initiating a position on October 1, 2001 is a difference of about 20% ($2,095.56 versus $2,511.49, respectively). This disparity comes about from a seemingly small 12 basis point difference in annual dividend yield (0.58% and 0.70%, respectively). In other words, in this case, a 12 basis point difference in initial dividend yield means that a $1,000.00 investment in TGT made on August 1, 2001 is worth 20% less than a $1,000.00 investment made on October 1, 2001.
Another example is CL. Here, the difference in investment value on March 28, 2013 between initiating a position on April 16, 2002 and July 21, 2002 is about 28.5% ($2,565.25 versus $3,292.76, respectively). The initial annual dividend yield difference between these two dates was only 36 basis points (1.23% and 1.59%, respectively).
I think there are two important lessons from this analysis. The first is that a seemingly small basis point difference in yield can have a profound effect on the long-term value of a DG investment. Secondly, notice that for these stocks, for most of the two-year time period between 2001 and 2002, the value on March 28, 2013 is not very different (especially for CL and MDT), but when the stock price suddenly drops, the yield rises and an investor has the chance to significantly increase the long-term value of their investment. Together, these results lend even more credence to the notion of "buying on the dips," and being patient until good buying opportunities present themselves.
1) The program was written in python using Spyder 2.1.10
2) matplotlib.finance modules were used to fetch and parse stock price data from Yahoo Finance
3) The graphs were generated using LibreOffice