However, if I am trying to project future inflation so I can decide if my retirement funds are growing quickly enough, its handy to know what historical inflation has been.
In a previous post (http://seekingalpha.com/instablog/134376-kiisu-buraun/852671-would-a-dogs-of-the-dow-retirement-portfolio-survived-the-last-12-years) I looked at historical inflation through the eyes of a new retiree in the year 2000. In the post, I looked back 10, 20, 30, 40 and 50 years to get an estimated inflation rate and used that rate to increase withdrawals from a retirement portfolio.
However, it is now mid 2012, not 2000 and I thought it might be interesting to see what has happend to our money.
Years | Date | Cumulative Inflation | Dollars | CAIR |
---|---|---|---|---|
-- | 31.Dec.2011 | -- | $100.00 | -- |
1 | 31.Dec.2010 | 2.96% | $102.96 | 2.96% |
2 | 31.Dec.2009 | 4.50% | $104.50 | 2.23% |
3 | 31.Dec.2008 | 7.35% | $107.35 | 2.39% |
4 | 31.Dec.2007 | 7.44% | $107.44 | 1.81% |
5 | 31.Dec.2006 | 11.83% | $111.83 | 2.26% |
10 | 31.Dec.2001 | 27.71% | $127.71 | 2.48% |
15 | 31.Dec.1996 | 42.29% | $142.29 | 2.38% |
20 | 31.Dec.1991 | 63.65% | $163.65 | 2.49% |
30 | 31.Dec.1981 | 140.08% | $240.08 | 2.96% |
40 | 31.Dec.1971 | 449.08% | $549.08 | 4.35% |
50 | 31.Dec.1961 | 652.24% | $752.24 | 4.12% |
60 | 31.Dec.1951 | 751.59% | $851.59 | 3.63% |
70 | 31.Dec.1941 | 1,355.95% | $1,455.95 | 3.90% |
80 | 31.Dec.1931 | 1,455.70% | $1,545.70 | 3.48% |
90 | 31.Dec.1921 | 1,204.46% | $1,304.46 | 2.89% |
97 | 31.Dec.1914 | 2,134.38% | $2,234.38 | 3.25% |
InflationData (http://inflationdata.com/Inflation/Inflation_Calculators/Cumulative_Inflation_Calculator.aspx) provided the cumulative inflation data, and Investopedia (www.investopedia.com/calculator/CAGR.aspx) provided the CAGR calculator.
CAIR (Compound Annual Inflation Rate) is merely CAGR applied to inflation.
Examples help me understand. And I find the following examples enlightening:
For every $100 of buying power I had at the end of:
Thus, if we ignore taxes and my retirement projections are "golden" with a 3% inflation rate and future inflation mimics the recent sub 3% rate, all is well.
However, if in the future the CAIR creeps up and I don't adjust my projections accordingly, I can easily deceive myself with a rosy projection that does not meet reality.
And that could be "interesting."
]]>However, if I am trying to project future inflation so I can decide if my retirement funds are growing quickly enough, its handy to know what historical inflation has been.
In a previous post (http://seekingalpha.com/instablog/134376-kiisu-buraun/852671-would-a-dogs-of-the-dow-retirement-portfolio-survived-the-last-12-years) I looked at historical inflation through the eyes of a new retiree in the year 2000. In the post, I looked back 10, 20, 30, 40 and 50 years to get an estimated inflation rate and used that rate to increase withdrawals from a retirement portfolio.
However, it is now mid 2012, not 2000 and I thought it might be interesting to see what has happend to our money.
Years | Date | Cumulative Inflation | Dollars | CAIR |
---|---|---|---|---|
-- | 31.Dec.2011 | -- | $100.00 | -- |
1 | 31.Dec.2010 | 2.96% | $102.96 | 2.96% |
2 | 31.Dec.2009 | 4.50% | $104.50 | 2.23% |
3 | 31.Dec.2008 | 7.35% | $107.35 | 2.39% |
4 | 31.Dec.2007 | 7.44% | $107.44 | 1.81% |
5 | 31.Dec.2006 | 11.83% | $111.83 | 2.26% |
10 | 31.Dec.2001 | 27.71% | $127.71 | 2.48% |
15 | 31.Dec.1996 | 42.29% | $142.29 | 2.38% |
20 | 31.Dec.1991 | 63.65% | $163.65 | 2.49% |
30 | 31.Dec.1981 | 140.08% | $240.08 | 2.96% |
40 | 31.Dec.1971 | 449.08% | $549.08 | 4.35% |
50 | 31.Dec.1961 | 652.24% | $752.24 | 4.12% |
60 | 31.Dec.1951 | 751.59% | $851.59 | 3.63% |
70 | 31.Dec.1941 | 1,355.95% | $1,455.95 | 3.90% |
80 | 31.Dec.1931 | 1,455.70% | $1,545.70 | 3.48% |
90 | 31.Dec.1921 | 1,204.46% | $1,304.46 | 2.89% |
97 | 31.Dec.1914 | 2,134.38% | $2,234.38 | 3.25% |
InflationData (http://inflationdata.com/Inflation/Inflation_Calculators/Cumulative_Inflation_Calculator.aspx) provided the cumulative inflation data, and Investopedia (www.investopedia.com/calculator/CAGR.aspx) provided the CAGR calculator.
CAIR (Compound Annual Inflation Rate) is merely CAGR applied to inflation.
Examples help me understand. And I find the following examples enlightening:
For every $100 of buying power I had at the end of:
Thus, if we ignore taxes and my retirement projections are "golden" with a 3% inflation rate and future inflation mimics the recent sub 3% rate, all is well.
However, if in the future the CAIR creeps up and I don't adjust my projections accordingly, I can easily deceive myself with a rosy projection that does not meet reality.
And that could be "interesting."
]]>Back in the late nineties I read a number of financial articles and books as a prelude to picking companies for my IRA. It was then I stumbled across something called the "Dogs of the Dow" or DoD.
I even tried the DoD method for a while before moving on to other things. But in retrospect I've wondered, how good a method was DoD; how well would it have survived, to twist a Southern phrase, "The Recent Unpleasantness;" and if I had retired in 2000 with a portfolio managed according to the DoD method, would the portfolio have survived that aforementioned "Recent Unpleasantness"?
For those unfamiliar with the DoD, I've summarized the method as:
On the last day of the year, sort the thirty stocks that comprise the Dow Jones Industrial Average (the DOW) by dividend yield and buy on the first trading day in the new year, an equally weighted portfolio of the ten stocks with the highest yield. Sell the entire portfolio on the last trading day of the new year. Wash, rinse, repeat. |
I've purloined my DoD historical data from the informative website, http://www.dogsofthedow.com.
A First Look
I split the analysis into two scenarios. Both start with $10,000 cash in an IRA on 1 January 2000. And both end on 31 December 2011.
With Scenario B we withdraw $400 from the portfolio at the end of the first year before investing the balance on the first trading day of the new year. In the following years, we increase the withdrawals each year by 4%.
For simplicity I've made a few simplifying assumptions:
A Results
For scenario A, the computation seems simple and straightforward, multiply the invested amount by the DoD average annual performance. For example, the 2000 DoD performance is:
Symbol | YTD % Change |
---|---|
(MO) | 91.3% |
(JPM) | 30.7% |
(CAT) | 0.5% |
(GM) | -29.9% |
(EK) | -40.6% |
(MMM) | 23.1% |
(XOM) | 7.9% |
(DD) | -26.7% |
(SBC) | -2.1% |
(IP) | -27.7% |
Table 1. Year 2000 DoD performance summarized from http://www.dogsofthedow.com/dogs2000p.htm.
Which gives an average rate of 2.65% for the year. Thus an investment of $10,000 would increase to $10,265.00
However, the DoD website contains the following caution... Note 1: 2000 % change figures do not include for dividends, commissions, or taxes. Similar notes exist for the other historical DoD results.
We've already assumed no commissions or taxes. But will ignoring dividends be a result altering mistake?
Table 2. Year 2000 DoD dividend performance.
(Notes: Historical data from Yahoo! Finance. EK historical data available as EKDKQ. GM historical data was available until the end of June 2012 as LTMQQ. SBC is currently listed as T because SBC later bought the original AT&T and adopted its name and symbol.)
$10,000 invested in the Dogs of the DOW on 3 January 2000 results in dividends of $255.08 or a 2.55% dividend return... nearly the same amount as the increase due to stock price increase.
If we adjust the posted results for dividends, the average annual performance significantly changes... for the better.
Year | Raw DoD | Dividends | DoD + Div |
---|---|---|---|
2000 | 2.65% | 2.55% | 5.20% |
2001 | -7.79% | 2.48% | -5.31% |
2002 | -12.24% | 3.47% | -8.77% |
2003 | 23.57% | 4.09% | 27.66% |
2004 | 0.48% | 5.49% | 5.97% |
2005 | -8.91% | 6.21% | -2.70% |
2006 | 24.82% | 7.44% | 32.26% |
2007 | -1.44% | 6.53% | 5.09% |
2008 | -41.62% | 9.03% | -32.59% |
2009 | 12.91% | 4.01% | 16.92% |
2010 | 15.49% | 3.40% | 18.89% |
2011 | 12.22% | 2.78% | 15.00% |
Table 3. Annual average DoD performance raw and corrected with dividend returns.
Chart 1. Annual average DoD performance raw and corrected with dividend returns.
At the end of twelve years we have the following results assuming we make a one time initial investment of $10,000.
Year | Raw DoD | Direction | DoD+Div | Direction |
---|---|---|---|---|
2000 | $10,265.00 | ↑ | $10,520.08 | ↑ |
2001 | $9,465.36 | ↓ | $9,955.32 | ↓ |
2002 | $8,306.80 | ↓ | $9,073.84 | ↓ |
2003 | $10,264.71 | ↑ | $11,569.64 | ↑ |
2004 | $10,313.98 | ↑ | $12,240.71 | ↑ |
2005 | $9,395.00 | ↓ | $11,871.47 | ↓ |
2006 | $11,726.84 | ↑ | $15,647.37 | ↑ |
2007 | $11,557.98 | ↓ | $16,389.48 | ↑ |
2008 | $6,747.55 | ↓ | $10,960.86 | ↓ |
2009 | $7,618.66 | ↑ | $12,760.00 | ↑ |
2010 | $8,798.79 | ↑ | $15,156.80 | ↑ |
2011 | $9,874.00 | ↑ | $17,418.85 | ↑ |
Table 4. Result of $10,000 invested at the beginning of 2000.
In twelve years from January 2000 to December 2011 the "raw" DoD portfolio experienced 7 up years and 5 down years with a net loss of $126 and a CAGR of -0.11%. If we account for dividends, the portfolio experienced 8 up years and 4 down years with a gain of $7,418.85 for a CAGR of 4.73%.
To quote Paul Harvey, "we now know the rest of the story"... dividends significantly improve the results published on the Dogs of the DOW website.
B Results
For scenario B, we need to compute the annual withdrawals. We start with 4% of the initial investment and increase the withdrawal by 4% each year. Why?
While 4% is arbitrary, it is a commonly used withdrawal rate. Why increase the withdrawal rate by 4%? Inflation.
For example I used the cumulative inflation calculator at inflationdata.com (inflationdata.com/Inflation/Inflation_Ca...) and the CAGR calculator at investopedia (http://www.investopedia.com/calculator/CAGR.aspx) to discover the following:
Start | End | years | Cum Infla | $100.00 | CAGR |
---|---|---|---|---|---|
Jan.1991 | Dec.2000 | 10 | 29.27% | $129.27 | 2.60% |
Jan.1981 | Dec.2000 | 20 | 100.00% | $200.00 | 3.53% |
Jan.1971 | Dec.2000 | 30 | 337.19% | $437.19 | 5.04% |
Jan.1961 | Dec.2000 | 40 | 483.89% | $583.89 | 6.06% |
Jan.1951 | Dec.2000 | 50 | 585.04% | $685.04 | 4.93% |
Table 5. Historical inflation table. $100 in 1991 would have to grow to $129.27 by 2000 to have the same purchasing power.
Based on recent history, increasing the withdrawal rate by 4% per year to account for inflation seems reasonable.
Year | Withdrawals |
---|---|
2000 | $400.00 |
2001 | $416.00 |
2002 | $432.64 |
2003 | $449.95 |
2004 | $467.94 |
2005 | $486.65 |
2006 | $506.13 |
2007 | $526.37 |
2008 | $547.43 |
2009 | $569.32 |
2010 | $592.10 |
2011 | $615.78 |
TOTAL | $6,010.32 |
Table 6. Withdrawing 4% of initial investment at the end of the first year, increased by 4% each year.
When we make the annual withdraws the computations become a bit more complex, but the results are decidedly different.
Year | Raw DoD | Direction | DoD+Div | Direction |
---|---|---|---|---|
2000 | $9,865.00 | ↓ | $10,120.08 | ↑ |
2001 | $8,680.52 | ↓ | $9,170.48 | ↓ |
2002 | $7,185.38 | ↓ | $7,952.43 | ↓ |
2003 | $8,429.03 | ↑ | $9,733.97 | ↑ |
2004 | $8,001.55 | ↓ | $9,928.28 | ↑ |
2005 | $6,801.95 | ↓ | $9,278.41 | ↓ |
2006 | $7,984.06 | ↑ | $11,904.59 | ↑ |
2007 | $7,342.72 | ↓ | $12,174.22 | ↑ |
2008 | $3,739.25 | ↓ | $7,952.57 | ↓ |
2009 | $3,652.66 | ↓ | $8,794.01 | ↑ |
2010 | $3,626.46 | ↓ | $9,984.38 | ↑ |
2011 | $3,453.72 | ↓ | $10,998.58 | ↑ |
Table 7. DoD with annual withdrawals.
Chart 2. DoD performance raw and corrected. Withdrawing 4% of initial investment at the end of the first year, increased by 4% each year
In the twelve years from January 2000 to December 2011 the "raw" DoD portfolio with annual withdrawals experienced two up years and ten down years with a net loss of $6,546.28... if we don't include the twelve withdrawals which total $6,010.32. If we do include the withdrawals we are still down $535.96.
If we include dividends in the DoD portfolio and make the annual withdrawals, the portfolio experienced 8 up years and 4 down years and gained $998.58... if we don't include the twelve withdrawals of $6,010.32. If we do include the withdrawals we are up $7,008.90.
I know of no one in the U.S. who would have retired in 2000 on $10,000, but the numbers are easily scaled. For example, multiply the numbers by 100 and an initial portfolio of $1,000,000 grows over twelve years to a value of $1,099,858. The initial cash 4% withdrawal at the end of 2000 grows from $40,000 to $61,578 at the end of 2011. The total amount withdrawn sums to $601,032.
The Answer
The results published on the Dogs of the DOW website don't include dividends. However, as shown above, Doggy dividends are absolutely critical.
If dividends are (unrealistically) ignored, this historical DoD portfolio fails with a CAGR of -0.11%. Annual 4% cash withdrawals (increased by 4% each year) crash the portfolio and generate a CAGR of -8.48%.
But actual DoD performance which includes dividends, paints a better and more realistic picture. For the period from 2000 to 2011 dividends exceeded required annual withdrawals for five years and contributed a significant fraction of the withdrawals in the remaining years.
A DoD portfolio created at the beginning of 2000 would have survived and grown nearly 75% for a CAGR of 4.73%.
Furthermore, even with the "Recent Unpleasantness" this DoD portfolio with annual withdrawals grew nearly $1000... even though we extracted 4% of the initial investment at the end of 2000 and thereafter grew the annual withdrawals by 4% each year. Over the 12 years we withdrew more than $,6000 even so, the portfolio grew with a CAGR of 0.80%.
So, yes a DoD portfolio established at the beginning of 2000 would have survived and grown... even if I had extracted 4% of the initial investment at the end of 2000 and thereafter grew my annual withdrawals by 4% each year.
But that raises another question, is there a better method? I'll examine that question in a future article.
]]>Back in the late nineties I read a number of financial articles and books as a prelude to picking companies for my IRA. It was then I stumbled across something called the "Dogs of the Dow" or DoD.
I even tried the DoD method for a while before moving on to other things. But in retrospect I've wondered, how good a method was DoD; how well would it have survived, to twist a Southern phrase, "The Recent Unpleasantness;" and if I had retired in 2000 with a portfolio managed according to the DoD method, would the portfolio have survived that aforementioned "Recent Unpleasantness"?
For those unfamiliar with the DoD, I've summarized the method as:
On the last day of the year, sort the thirty stocks that comprise the Dow Jones Industrial Average (the DOW) by dividend yield and buy on the first trading day in the new year, an equally weighted portfolio of the ten stocks with the highest yield. Sell the entire portfolio on the last trading day of the new year. Wash, rinse, repeat. |
I've purloined my DoD historical data from the informative website, http://www.dogsofthedow.com.
A First Look
I split the analysis into two scenarios. Both start with $10,000 cash in an IRA on 1 January 2000. And both end on 31 December 2011.
With Scenario B we withdraw $400 from the portfolio at the end of the first year before investing the balance on the first trading day of the new year. In the following years, we increase the withdrawals each year by 4%.
For simplicity I've made a few simplifying assumptions:
A Results
For scenario A, the computation seems simple and straightforward, multiply the invested amount by the DoD average annual performance. For example, the 2000 DoD performance is:
Symbol | YTD % Change |
---|---|
(MO) | 91.3% |
(JPM) | 30.7% |
(CAT) | 0.5% |
(GM) | -29.9% |
(EK) | -40.6% |
(MMM) | 23.1% |
(XOM) | 7.9% |
(DD) | -26.7% |
(SBC) | -2.1% |
(IP) | -27.7% |
Table 1. Year 2000 DoD performance summarized from http://www.dogsofthedow.com/dogs2000p.htm.
Which gives an average rate of 2.65% for the year. Thus an investment of $10,000 would increase to $10,265.00
However, the DoD website contains the following caution... Note 1: 2000 % change figures do not include for dividends, commissions, or taxes. Similar notes exist for the other historical DoD results.
We've already assumed no commissions or taxes. But will ignoring dividends be a result altering mistake?
Table 2. Year 2000 DoD dividend performance.
(Notes: Historical data from Yahoo! Finance. EK historical data available as EKDKQ. GM historical data was available until the end of June 2012 as LTMQQ. SBC is currently listed as T because SBC later bought the original AT&T and adopted its name and symbol.)
$10,000 invested in the Dogs of the DOW on 3 January 2000 results in dividends of $255.08 or a 2.55% dividend return... nearly the same amount as the increase due to stock price increase.
If we adjust the posted results for dividends, the average annual performance significantly changes... for the better.
Year | Raw DoD | Dividends | DoD + Div |
---|---|---|---|
2000 | 2.65% | 2.55% | 5.20% |
2001 | -7.79% | 2.48% | -5.31% |
2002 | -12.24% | 3.47% | -8.77% |
2003 | 23.57% | 4.09% | 27.66% |
2004 | 0.48% | 5.49% | 5.97% |
2005 | -8.91% | 6.21% | -2.70% |
2006 | 24.82% | 7.44% | 32.26% |
2007 | -1.44% | 6.53% | 5.09% |
2008 | -41.62% | 9.03% | -32.59% |
2009 | 12.91% | 4.01% | 16.92% |
2010 | 15.49% | 3.40% | 18.89% |
2011 | 12.22% | 2.78% | 15.00% |
Table 3. Annual average DoD performance raw and corrected with dividend returns.
Chart 1. Annual average DoD performance raw and corrected with dividend returns.
At the end of twelve years we have the following results assuming we make a one time initial investment of $10,000.
Year | Raw DoD | Direction | DoD+Div | Direction |
---|---|---|---|---|
2000 | $10,265.00 | ↑ | $10,520.08 | ↑ |
2001 | $9,465.36 | ↓ | $9,955.32 | ↓ |
2002 | $8,306.80 | ↓ | $9,073.84 | ↓ |
2003 | $10,264.71 | ↑ | $11,569.64 | ↑ |
2004 | $10,313.98 | ↑ | $12,240.71 | ↑ |
2005 | $9,395.00 | ↓ | $11,871.47 | ↓ |
2006 | $11,726.84 | ↑ | $15,647.37 | ↑ |
2007 | $11,557.98 | ↓ | $16,389.48 | ↑ |
2008 | $6,747.55 | ↓ | $10,960.86 | ↓ |
2009 | $7,618.66 | ↑ | $12,760.00 | ↑ |
2010 | $8,798.79 | ↑ | $15,156.80 | ↑ |
2011 | $9,874.00 | ↑ | $17,418.85 | ↑ |
Table 4. Result of $10,000 invested at the beginning of 2000.
In twelve years from January 2000 to December 2011 the "raw" DoD portfolio experienced 7 up years and 5 down years with a net loss of $126 and a CAGR of -0.11%. If we account for dividends, the portfolio experienced 8 up years and 4 down years with a gain of $7,418.85 for a CAGR of 4.73%.
To quote Paul Harvey, "we now know the rest of the story"... dividends significantly improve the results published on the Dogs of the DOW website.
B Results
For scenario B, we need to compute the annual withdrawals. We start with 4% of the initial investment and increase the withdrawal by 4% each year. Why?
While 4% is arbitrary, it is a commonly used withdrawal rate. Why increase the withdrawal rate by 4%? Inflation.
For example I used the cumulative inflation calculator at inflationdata.com (inflationdata.com/Inflation/Inflation_Ca...) and the CAGR calculator at investopedia (http://www.investopedia.com/calculator/CAGR.aspx) to discover the following:
Start | End | years | Cum Infla | $100.00 | CAGR |
---|---|---|---|---|---|
Jan.1991 | Dec.2000 | 10 | 29.27% | $129.27 | 2.60% |
Jan.1981 | Dec.2000 | 20 | 100.00% | $200.00 | 3.53% |
Jan.1971 | Dec.2000 | 30 | 337.19% | $437.19 | 5.04% |
Jan.1961 | Dec.2000 | 40 | 483.89% | $583.89 | 6.06% |
Jan.1951 | Dec.2000 | 50 | 585.04% | $685.04 | 4.93% |
Table 5. Historical inflation table. $100 in 1991 would have to grow to $129.27 by 2000 to have the same purchasing power.
Based on recent history, increasing the withdrawal rate by 4% per year to account for inflation seems reasonable.
Year | Withdrawals |
---|---|
2000 | $400.00 |
2001 | $416.00 |
2002 | $432.64 |
2003 | $449.95 |
2004 | $467.94 |
2005 | $486.65 |
2006 | $506.13 |
2007 | $526.37 |
2008 | $547.43 |
2009 | $569.32 |
2010 | $592.10 |
2011 | $615.78 |
TOTAL | $6,010.32 |
Table 6. Withdrawing 4% of initial investment at the end of the first year, increased by 4% each year.
When we make the annual withdraws the computations become a bit more complex, but the results are decidedly different.
Year | Raw DoD | Direction | DoD+Div | Direction |
---|---|---|---|---|
2000 | $9,865.00 | ↓ | $10,120.08 | ↑ |
2001 | $8,680.52 | ↓ | $9,170.48 | ↓ |
2002 | $7,185.38 | ↓ | $7,952.43 | ↓ |
2003 | $8,429.03 | ↑ | $9,733.97 | ↑ |
2004 | $8,001.55 | ↓ | $9,928.28 | ↑ |
2005 | $6,801.95 | ↓ | $9,278.41 | ↓ |
2006 | $7,984.06 | ↑ | $11,904.59 | ↑ |
2007 | $7,342.72 | ↓ | $12,174.22 | ↑ |
2008 | $3,739.25 | ↓ | $7,952.57 | ↓ |
2009 | $3,652.66 | ↓ | $8,794.01 | ↑ |
2010 | $3,626.46 | ↓ | $9,984.38 | ↑ |
2011 | $3,453.72 | ↓ | $10,998.58 | ↑ |
Table 7. DoD with annual withdrawals.
Chart 2. DoD performance raw and corrected. Withdrawing 4% of initial investment at the end of the first year, increased by 4% each year
In the twelve years from January 2000 to December 2011 the "raw" DoD portfolio with annual withdrawals experienced two up years and ten down years with a net loss of $6,546.28... if we don't include the twelve withdrawals which total $6,010.32. If we do include the withdrawals we are still down $535.96.
If we include dividends in the DoD portfolio and make the annual withdrawals, the portfolio experienced 8 up years and 4 down years and gained $998.58... if we don't include the twelve withdrawals of $6,010.32. If we do include the withdrawals we are up $7,008.90.
I know of no one in the U.S. who would have retired in 2000 on $10,000, but the numbers are easily scaled. For example, multiply the numbers by 100 and an initial portfolio of $1,000,000 grows over twelve years to a value of $1,099,858. The initial cash 4% withdrawal at the end of 2000 grows from $40,000 to $61,578 at the end of 2011. The total amount withdrawn sums to $601,032.
The Answer
The results published on the Dogs of the DOW website don't include dividends. However, as shown above, Doggy dividends are absolutely critical.
If dividends are (unrealistically) ignored, this historical DoD portfolio fails with a CAGR of -0.11%. Annual 4% cash withdrawals (increased by 4% each year) crash the portfolio and generate a CAGR of -8.48%.
But actual DoD performance which includes dividends, paints a better and more realistic picture. For the period from 2000 to 2011 dividends exceeded required annual withdrawals for five years and contributed a significant fraction of the withdrawals in the remaining years.
A DoD portfolio created at the beginning of 2000 would have survived and grown nearly 75% for a CAGR of 4.73%.
Furthermore, even with the "Recent Unpleasantness" this DoD portfolio with annual withdrawals grew nearly $1000... even though we extracted 4% of the initial investment at the end of 2000 and thereafter grew the annual withdrawals by 4% each year. Over the 12 years we withdrew more than $,6000 even so, the portfolio grew with a CAGR of 0.80%.
So, yes a DoD portfolio established at the beginning of 2000 would have survived and grown... even if I had extracted 4% of the initial investment at the end of 2000 and thereafter grew my annual withdrawals by 4% each year.
But that raises another question, is there a better method? I'll examine that question in a future article.
]]>
AVERAGE(divt_{n}/divt_{n-1}-1;
divt_{n-1}/divt_{n-2}-1;
…;
divt_{0+1}/divt_{0}-1) =
(divt_{n}/divt_{0})^(1/(t_{n}-t_{0}))-1
Where divt_{m} is the dividend payment for time period m.
Answer:
AVERAGE(a; b; c; d; …; z)
is a shorthand notation for:
(a + b + c + d + … + z)
/ (number_of_terms)
But if the individual terms, a, b, c, …, z are all equal, then:
(a + b + c + d + … + z)
/ (number_of_terms) =
(a + a + a + a + … + a)
/ (number_of_terms)
And
(a + a + a + a + … + a)
/ (number_of_terms) = a
Thus,
divt_{n}/divt_{n-1}-1 =
divt_{n-1}/divt_{n-2}-1 =
… =
divt_{0+1}/divt_{0}-1 =
(divt_{n}/divt_{0})^(1/(t_{n}-t_{0}))-1
Or for any sequential dividend payments, divt_{m} and divt_{m-1}
divt_{m}/divt_{m-1}-1 =
(divt_{n}/divt_{0}) ^(1/(t_{n}-t_{0})) -1
Summary: If the AADGR is composed of a series of exactly equal annual DGRs, then the AADGR for the time period is the same as any individual annual DGR which is also the same as the DGR for the entire time period.
]]>
AVERAGE(divt_{n}/divt_{n-1}-1;
divt_{n-1}/divt_{n-2}-1;
…;
divt_{0+1}/divt_{0}-1) =
(divt_{n}/divt_{0})^(1/(t_{n}-t_{0}))-1
Where divt_{m} is the dividend payment for time period m.
Answer:
AVERAGE(a; b; c; d; …; z)
is a shorthand notation for:
(a + b + c + d + … + z)
/ (number_of_terms)
But if the individual terms, a, b, c, …, z are all equal, then:
(a + b + c + d + … + z)
/ (number_of_terms) =
(a + a + a + a + … + a)
/ (number_of_terms)
And
(a + a + a + a + … + a)
/ (number_of_terms) = a
Thus,
divt_{n}/divt_{n-1}-1 =
divt_{n-1}/divt_{n-2}-1 =
… =
divt_{0+1}/divt_{0}-1 =
(divt_{n}/divt_{0})^(1/(t_{n}-t_{0}))-1
Or for any sequential dividend payments, divt_{m} and divt_{m-1}
divt_{m}/divt_{m-1}-1 =
(divt_{n}/divt_{0}) ^(1/(t_{n}-t_{0})) -1
Summary: If the AADGR is composed of a series of exactly equal annual DGRs, then the AADGR for the time period is the same as any individual annual DGR which is also the same as the DGR for the entire time period.
]]>=AVERAGE(
div2010/div2009-1;
div2009/div2008-1;
div2008/div2007-1;
div2007/div2006-1;
div2006/div2005-1;
div2005/div2004-1;
div2004/div2003-1;
div2003/div2002-1;
div2002/div2001-1;
div2001/div2000-1;
div2000/div1999-1)
Computing the BC requires fourteen divisions, twelve exponents, a multiplication and a square root.
Computing the AADGR requires twelve divisions.
When examining the computation cost of a procedure:
Additions and subtractions are ignored because they are "computationally cheap".
Multiplications and divisions are a bit more expensive but are ignored.
Exponents and roots tend to be very expensive and they drive the "computational cost".
The number of exponents for computing the BC is equal to one plus the number of years of dividend increases.
The number of divisions for computing the AADGR is equal to one plus the number of years of dividend increases.
As the number of years of dividend payments increase the computational cost of the BC compared to the AADGR increases.
One further point, AADGR can be viewed as "a rule of thumb", an easily learned and easily computed procedure for approximating a score to predict the bumpiness of a company's non-decreasing dividend history.
=AVERAGE(
div2010/div2009-1;
div2009/div2008-1;
div2008/div2007-1;
div2007/div2006-1;
div2006/div2005-1;
div2005/div2004-1;
div2004/div2003-1;
div2003/div2002-1;
div2002/div2001-1;
div2001/div2000-1;
div2000/div1999-1)
Computing the BC requires fourteen divisions, twelve exponents, a multiplication and a square root.
Computing the AADGR requires twelve divisions.
When examining the computation cost of a procedure:
Additions and subtractions are ignored because they are "computationally cheap".
Multiplications and divisions are a bit more expensive but are ignored.
Exponents and roots tend to be very expensive and they drive the "computational cost".
The number of exponents for computing the BC is equal to one plus the number of years of dividend increases.
The number of divisions for computing the AADGR is equal to one plus the number of years of dividend increases.
As the number of years of dividend payments increase the computational cost of the BC compared to the AADGR increases.
One further point, AADGR can be viewed as "a rule of thumb", an easily learned and easily computed procedure for approximating a score to predict the bumpiness of a company's non-decreasing dividend history.
We are looking for factors that “correlate” well with dividend bumpiness. If the correlation is linear then R^{2 }or the “coefficient of determination” will be near one and R or the “Pearson product-moment correlation coefficient” will be either near one (for a positive correlation, i.e. as the factor increases the bumpiness increases) or near minus one (for a negative correlation i.e. as the factor increase the bumpiness decreases).
Fortunately, these kind of calculations no longer have to be worked out by hand, nor do we have to buy a sophisticated software statistics-package. Free tools are now available on-line. For this problem I used the “Linear Correlation and Regression” tool provided by Richard Lowry of Vassar College, which can be found here: faculty.vassar.edu/lowry/corr_big.html. The tool has a companion e-text in basic statistics “Concepts & Applications of Inferential Statistics”. I found Chapter 3 “Introduction to Linear Correlation and Regression” to be lucid and well-written. The complete e-text is here: faculty.vassar.edu/lowry/webtext.html.
Mr. Schwartz defines dividend bumpiness as the (scaled) standard deviation about the “Dividend Computed Annual Growth Rate” (also known as the Dividend Growth Rate or DGR). As you might recall, standard deviation shows the degree of variation from an expected value. Thus, a low standard deviation means the data tends to cluster very close to the expected value, while a large standard deviation means the data tends to be scattered over a much larger range of values.
The 31 May 2011 version of the Champions spreadsheet provides a dividend history table that ranges from 2010 back to 1999 (columns AP through BA, 12 years of dividend history or 11 years of dividend increases). I also reanalyzed the data after I augmented the dividend table with the projected 2011 dividends (13 years of dividends or 12 years of dividend increases). As augmenting the data with the projected 2011 dividends made no appreciable difference to the results, the discussion below is for the unaugmented data.
I also added the following new columns:
• Average Annual Dividend
(average of all dividend payments).
• Average Annual Dividend Growth Rate
or AADGR (average of all the
annual dividend growth rates).
• Data Points (the number of years
of dividend increases).
• Dividend Growth Rate or DGR
(also known as the Dividend
Compounded Annual Growth Rate).
• Bumpiness Coefficient
(100 x Standard Deviation
computed about the DGR).
In the above list of new columns, the term “all dividends” means all monotonically increasing dividends, which means dividends with “no decreases” and “no-zeros” (mathematically, dividing by zero is a “bad-thing”). For the Champions that is not an issue. For the Contenders and Challengers it means some of the dividend history is discarded.
Why discard some of the dividend history?
For example, the Raytheon Company (RTN) has 12 years of dividend payment history listed in the spreadsheet. In 1999, 2000, and2001 the company paid an annual $0.0008 dividend. It also paid a $0.80 annual dividend in 2003 and 2004. Those series of “flat” dividend payments are why it is a Challenger instead of a Contender. However, as there was “no-decrease” in the dividend payment those dividends are used for computing values for the new columns listed above.
In the other hand, Alliant Energy Corporation (LNT) paid a $2.00 annual dividend for the years 1999 through 2002. However, in 2003, the dividend was cut to $1.00. Thereafter the company consistently raised its dividend. In order to maintain a monotonically increasing data set, the dividend payments for 2002 and prior years were discarded. Discarded data were not used in any calculation.
Fortunately, modern spreadsheets include functions that make computing such otherwise cumbersome and tedious calculations rather easy.
The details for each new column can be found in the Appendix A at the end of this blog.
What are the results of the analysis?
For each proposed predictive factor, I examined the range of values then computed the R and R^{2} values with the Linear Correlation and Regression tool. The tool also computes the Y-intercept and Slope of the resulting data trend line.
Years of available data.
The Champions' BC ranges from a high of 64.42 for CenturyLink Inc. (CTL) to a low of 0.00 for Tootsie Roll Industries (TR).
The Contenders' BC ranges from a high of 92.87 for Flowers Foods (FLO) to a low of 0.1344 for Atmos Energy (ATO).
The Challengers' BC ranges from a high of 2,261 for the Raytheon Company (RTN) to a low of 0.2471 for ROC Resources (ROCO).
All the Champions have 12 years of available data, yet the BC ranges across two orders of magnitude (from 0.00 to 64.42). Thus, years of available data does not predict dividend bumpiness. The Linear Correlation and Regression tool confirms this.
Conclusion: Years of available data
does not predict dividend bumpiness.
Average Annual Dividend.
The Champions' average annual dividend ranges from a high of $2.27 for Consolidated Edison (ED) to a low of $0.16 for Lowe's Companies (LOW).
The Contenders' average annual dividend ranges from a high of $3.29 for NuStar Energy LP (NS) to a low of $0.10 for SEI Investments Company (SEIC).
The Challengers' average annual dividend ranges from a high of $3.45 for ONEOK Partners LP (OKS) to a low of $0.03 for Aaron's Inc (AAN).
The Linear Correlation and Regression tool computes an R of -0.097 and an R^{2} of 0.0094 for the Champions' Average Annual Dividend and BC. In other words, Average Annual Dividend predicts about one percent of the variation in dividend bumpiness.
Conclusion: Average Annual
Dividend does not predict
dividend bumpiness.
DGR.
The Champions' DGR ranges from a high of 0.2875 (~29%) for CenturyLink Inc (CTL) to a low of 0.0084 (~1%) for California Water Service (CWT).
The Contenders' DGR ranges from a high of 0.6969 (~70%) for Fastenal Company (FAST) to a low of 0.0176 (~2%) for Atmos Energy (ATO).
The Challengers' DGR ranges from a high of 1.1285 (~113%) for Crestwood Midstream Partners LP (CMPL) to a low of 0.0079 (~1%) for OGE Energy Corp (OGE).
The Linear Correlation and Regression tool computes an R of 0.5622 and an R^{2} of 0.3161 for the Champions' DGR and BC. In other words, changes in DGR predicts about 32% of the variation in dividend bumpiness.
Conclusion: DGR predicts only a third
of dividend bumpiness.
AADGR.
The Champions' AADGR ranges from a high of 0.7310 (~73%) for CenturyLink Inc (CTL) to low of 0.0084 (~1%) for California Water Service (CWT).
The Contenders' AADGR ranges from a high of 1.2568 (~126%) for Flowers Foods (FLO) to low of 0.0176 (~2%) for Atmos Energy (ATO).
The Challengers' AADGR ranges from a high of 23.0323 (~2,303%) for the Raytheon Company (RTN) to low of 0.0079 (~1%) for OGE Energy Corp (OGE).
The Linear Correlation and Regression tool computes an R of 0.8742 and an R^{2} of 0.7642 for the Champions' AADGR and BC. In other words, changes in AADGR predicts about three quarters of the variation in dividend bumpiness. These results seem promising.
Repeating the analysis with the full set of 449 data points gives an R of 0.9964 and an R^{2} of 0.9928. This is very significant.
The corresponding linear regression data trend line has a slope of 97.179754 and a Y-intercept of -10.969416.
The maximum AADGR that results in zero predicted bumpiness is ~11%. The computational details are in Appendix B.
However, when we graph the complete data set for the 449 companies, we notice something interesting.
There are two extreme outliers that warp the trend line:
• the Raytheon Company (RTN)
(23.0323, 2261.7913) has an
AADGR of 2,303% and a BC of 2,262
• Waste Management (WM)
(6.7766, 667.8622) with an AADGR
of 678% and a BC of 668.
If we drop the two outliers and re-run the analysis for the remaining 447 data points, the R and R^{2} are still very good at 0.9608 and 0.923 respectively.
The resulting maximum AADGR that results in zero predicted bumpiness is 8%.
Conclusion: AADGR is an excellent
predictor of dividend bumpiness.
Appendix A
The new columns for the analysis are shown below along with a brief description and (where possible) an Excel Spreadsheet formula.
A note about the formulas...
A symbolic reference such as “div2010” means the spreadsheet cell which contains a specific company's dividend for 2010 instead of the actual cell reference which might be something like “AP7”. A symbolic reference retains its meaning while an actual cell reference might become invalid if columns are added to or deleted from the spreadsheet.
DGR as used in the formulas means the company specific DGR that is computed as one of the new columns.
Bold upper case terms (such as AVERAGE) are spreadsheet functions.
Average Dividend.
The average of all dividend payments.
Formula:
=AVERAGE(div2010; div2009; div2008; ...)
AADGR.
The average of all annual dividend growth rates.
Formula:
=AVERAGE(div2010/div2009-1; div2009/div2008-1; ...)
Data Points.
Determined by inspection.
For the Champions page, the resulting Data Points column was all 11s. For the Contenders page the Data Points column ranged from a high of 11 to a low of 8. For the Challengers page, the Data Points column ranged from a high of 11 to a low of 3.
Why?
The Champions page lists companies that have consistently raised dividends for 25 or more years. Thus, with only the most recent 12 years of data, you would expect (and inspection shows) that the dividend data “monotonically” increases. Why a 11 when there are 12 years of data? Because a growth rate requires two years of data. For example, the year 2000 annual dividend growth rate is div2000/div1999 – 1. The 1999 annual dividend growth rate can't be computed from this data set as no data is listed for 1998.
The Contenders page lists companies that have consistently raised dividends for 10 to 24 years. With 12 years of data a company may have recently made it onto the list due to a zero dividend or a dividend cut prior to 2002. And it takes nine years of data to give 8 data points.
The Challengers page lists companies that have consistently raised dividends for 5 to 9 years. With 12 years of data a company may have recently made it onto the list due to a zero dividend or a dividend cut prior to 2007. And it takes four years of data to give 3 data points.
DGR.
The DGR is computed from the first and most recent year of monotonically increasing dividend payments.
Data
Points Formula
11 =(div2010/div2000)^(1/11)
10 =(div2010/div2001)^(1/10)
9 =(div2010/div2002)^(1/9)
8 =(div2010/div2003)^(1/8)
7 =(div2010/div2004)^(1/7)
6 =(div2010/div2005)^(1/6)
5 =(div2010/div2006)^(1/5)
4 =(div2010/div2007)^(1/4)
3 =(div2010/div2008)^(1/3)
Bumpiness Coefficient.
The Bumpiness Coefficient (or BC) is 100 times the Standard Deviation about the dividend CAGR.
Data
Points Formula
11 =100/11*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2001/div2000-1-DGR)^2))
10 =100/10*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2002/div2001-1-DGR)^2))
9 =100/9*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2003/div2002-1-DGR)^2))
8 =100/8*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2003/div2002-1-DGR)^2))
7 =100/7*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2004/div2003-1-DGR)^2))
6 =100/6*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2005/div2004-1-DGR)^2))
5 =100/5*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2006/div2005-1-DGR)^2))
4 =100/4*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2007/div2006-1-DGR)^2))
3 =100/3*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
(div2008/div2007-1-DGR)^2))
Appendix B
If you took basic algebra, you might remember the equation for a straight line as:
Y := a + b•X
Where X is the independent variable, Y is the dependent variable, a is the Y-intercept and b is the slope.
For the linear regression trend line, the AADGR is our X and the bumpiness coefficient or BC is our Y.
With the Linear Correlation and Regression tool computed (449 company) Y-intercept of -10.969416 and slope of 97.179754, the trend line equation for predicting BC is:
[BC] := a + b•[AADGR]
With the restriction that the bumpiness coefficient can never be negative.
Solving for the maximum AADGR that yields zero BC gives:
0 := a + b•[AADGR]
-a := b•[AADGR]
[AADGR] := -a / b
[AADGR] :=
-(-10.969416) / 97.179754
[AADGR] := 0.112877 => ~11%
Repeating the process for the reduced (447 company) data, the Linear Correlation and Regression tool computed Y-intercept of -5.965385 and slope of 74.523808, the trend line for predicting BC is:
[BC] := -5.965385
+ 74.523808•[AADGR]
Solving for the maximum AADGR that yields a zero BC gives:
[AADGR] := 0.0800467 => 8%
We are looking for factors that “correlate” well with dividend bumpiness. If the correlation is linear then R^{2 }or the “coefficient of determination” will be near one and R or the “Pearson product-moment correlation coefficient” will be either near one (for a positive correlation, i.e. as the factor increases the bumpiness increases) or near minus one (for a negative correlation i.e. as the factor increase the bumpiness decreases).
Fortunately, these kind of calculations no longer have to be worked out by hand, nor do we have to buy a sophisticated software statistics-package. Free tools are now available on-line. For this problem I used the “Linear Correlation and Regression” tool provided by Richard Lowry of Vassar College, which can be found here: faculty.vassar.edu/lowry/corr_big.html. The tool has a companion e-text in basic statistics “Concepts & Applications of Inferential Statistics”. I found Chapter 3 “Introduction to Linear Correlation and Regression” to be lucid and well-written. The complete e-text is here: faculty.vassar.edu/lowry/webtext.html.
Mr. Schwartz defines dividend bumpiness as the (scaled) standard deviation about the “Dividend Computed Annual Growth Rate” (also known as the Dividend Growth Rate or DGR). As you might recall, standard deviation shows the degree of variation from an expected value. Thus, a low standard deviation means the data tends to cluster very close to the expected value, while a large standard deviation means the data tends to be scattered over a much larger range of values.
The 31 May 2011 version of the Champions spreadsheet provides a dividend history table that ranges from 2010 back to 1999 (columns AP through BA, 12 years of dividend history or 11 years of dividend increases). I also reanalyzed the data after I augmented the dividend table with the projected 2011 dividends (13 years of dividends or 12 years of dividend increases). As augmenting the data with the projected 2011 dividends made no appreciable difference to the results, the discussion below is for the unaugmented data.
I also added the following new columns:
• Average Annual Dividend
(average of all dividend payments).
• Average Annual Dividend Growth Rate
or AADGR (average of all the
annual dividend growth rates).
• Data Points (the number of years
of dividend increases).
• Dividend Growth Rate or DGR
(also known as the Dividend
Compounded Annual Growth Rate).
• Bumpiness Coefficient
(100 x Standard Deviation
computed about the DGR).
In the above list of new columns, the term “all dividends” means all monotonically increasing dividends, which means dividends with “no decreases” and “no-zeros” (mathematically, dividing by zero is a “bad-thing”). For the Champions that is not an issue. For the Contenders and Challengers it means some of the dividend history is discarded.
Why discard some of the dividend history?
For example, the Raytheon Company (RTN) has 12 years of dividend payment history listed in the spreadsheet. In 1999, 2000, and2001 the company paid an annual $0.0008 dividend. It also paid a $0.80 annual dividend in 2003 and 2004. Those series of “flat” dividend payments are why it is a Challenger instead of a Contender. However, as there was “no-decrease” in the dividend payment those dividends are used for computing values for the new columns listed above.
In the other hand, Alliant Energy Corporation (LNT) paid a $2.00 annual dividend for the years 1999 through 2002. However, in 2003, the dividend was cut to $1.00. Thereafter the company consistently raised its dividend. In order to maintain a monotonically increasing data set, the dividend payments for 2002 and prior years were discarded. Discarded data were not used in any calculation.
Fortunately, modern spreadsheets include functions that make computing such otherwise cumbersome and tedious calculations rather easy.
The details for each new column can be found in the Appendix A at the end of this blog.
What are the results of the analysis?
For each proposed predictive factor, I examined the range of values then computed the R and R^{2} values with the Linear Correlation and Regression tool. The tool also computes the Y-intercept and Slope of the resulting data trend line.
Years of available data.
The Champions' BC ranges from a high of 64.42 for CenturyLink Inc. (CTL) to a low of 0.00 for Tootsie Roll Industries (TR).
The Contenders' BC ranges from a high of 92.87 for Flowers Foods (FLO) to a low of 0.1344 for Atmos Energy (ATO).
The Challengers' BC ranges from a high of 2,261 for the Raytheon Company (RTN) to a low of 0.2471 for ROC Resources (ROCO).
All the Champions have 12 years of available data, yet the BC ranges across two orders of magnitude (from 0.00 to 64.42). Thus, years of available data does not predict dividend bumpiness. The Linear Correlation and Regression tool confirms this.
Conclusion: Years of available data
does not predict dividend bumpiness.
Average Annual Dividend.
The Champions' average annual dividend ranges from a high of $2.27 for Consolidated Edison (ED) to a low of $0.16 for Lowe's Companies (LOW).
The Contenders' average annual dividend ranges from a high of $3.29 for NuStar Energy LP (NS) to a low of $0.10 for SEI Investments Company (SEIC).
The Challengers' average annual dividend ranges from a high of $3.45 for ONEOK Partners LP (OKS) to a low of $0.03 for Aaron's Inc (AAN).
The Linear Correlation and Regression tool computes an R of -0.097 and an R^{2} of 0.0094 for the Champions' Average Annual Dividend and BC. In other words, Average Annual Dividend predicts about one percent of the variation in dividend bumpiness.
Conclusion: Average Annual
Dividend does not predict
dividend bumpiness.
DGR.
The Champions' DGR ranges from a high of 0.2875 (~29%) for CenturyLink Inc (CTL) to a low of 0.0084 (~1%) for California Water Service (CWT).
The Contenders' DGR ranges from a high of 0.6969 (~70%) for Fastenal Company (FAST) to a low of 0.0176 (~2%) for Atmos Energy (ATO).
The Challengers' DGR ranges from a high of 1.1285 (~113%) for Crestwood Midstream Partners LP (CMPL) to a low of 0.0079 (~1%) for OGE Energy Corp (OGE).
The Linear Correlation and Regression tool computes an R of 0.5622 and an R^{2} of 0.3161 for the Champions' DGR and BC. In other words, changes in DGR predicts about 32% of the variation in dividend bumpiness.
Conclusion: DGR predicts only a third
of dividend bumpiness.
AADGR.
The Champions' AADGR ranges from a high of 0.7310 (~73%) for CenturyLink Inc (CTL) to low of 0.0084 (~1%) for California Water Service (CWT).
The Contenders' AADGR ranges from a high of 1.2568 (~126%) for Flowers Foods (FLO) to low of 0.0176 (~2%) for Atmos Energy (ATO).
The Challengers' AADGR ranges from a high of 23.0323 (~2,303%) for the Raytheon Company (RTN) to low of 0.0079 (~1%) for OGE Energy Corp (OGE).
The Linear Correlation and Regression tool computes an R of 0.8742 and an R^{2} of 0.7642 for the Champions' AADGR and BC. In other words, changes in AADGR predicts about three quarters of the variation in dividend bumpiness. These results seem promising.
Repeating the analysis with the full set of 449 data points gives an R of 0.9964 and an R^{2} of 0.9928. This is very significant.
The corresponding linear regression data trend line has a slope of 97.179754 and a Y-intercept of -10.969416.
The maximum AADGR that results in zero predicted bumpiness is ~11%. The computational details are in Appendix B.
However, when we graph the complete data set for the 449 companies, we notice something interesting.
There are two extreme outliers that warp the trend line:
• the Raytheon Company (RTN)
(23.0323, 2261.7913) has an
AADGR of 2,303% and a BC of 2,262
• Waste Management (WM)
(6.7766, 667.8622) with an AADGR
of 678% and a BC of 668.
If we drop the two outliers and re-run the analysis for the remaining 447 data points, the R and R^{2} are still very good at 0.9608 and 0.923 respectively.
The resulting maximum AADGR that results in zero predicted bumpiness is 8%.
Conclusion: AADGR is an excellent
predictor of dividend bumpiness.
Appendix A
The new columns for the analysis are shown below along with a brief description and (where possible) an Excel Spreadsheet formula.
A note about the formulas...
A symbolic reference such as “div2010” means the spreadsheet cell which contains a specific company's dividend for 2010 instead of the actual cell reference which might be something like “AP7”. A symbolic reference retains its meaning while an actual cell reference might become invalid if columns are added to or deleted from the spreadsheet.
DGR as used in the formulas means the company specific DGR that is computed as one of the new columns.
Bold upper case terms (such as AVERAGE) are spreadsheet functions.
Average Dividend.
The average of all dividend payments.
Formula:
=AVERAGE(div2010; div2009; div2008; ...)
AADGR.
The average of all annual dividend growth rates.
Formula:
=AVERAGE(div2010/div2009-1; div2009/div2008-1; ...)
Data Points.
Determined by inspection.
For the Champions page, the resulting Data Points column was all 11s. For the Contenders page the Data Points column ranged from a high of 11 to a low of 8. For the Challengers page, the Data Points column ranged from a high of 11 to a low of 3.
Why?
The Champions page lists companies that have consistently raised dividends for 25 or more years. Thus, with only the most recent 12 years of data, you would expect (and inspection shows) that the dividend data “monotonically” increases. Why a 11 when there are 12 years of data? Because a growth rate requires two years of data. For example, the year 2000 annual dividend growth rate is div2000/div1999 – 1. The 1999 annual dividend growth rate can't be computed from this data set as no data is listed for 1998.
The Contenders page lists companies that have consistently raised dividends for 10 to 24 years. With 12 years of data a company may have recently made it onto the list due to a zero dividend or a dividend cut prior to 2002. And it takes nine years of data to give 8 data points.
The Challengers page lists companies that have consistently raised dividends for 5 to 9 years. With 12 years of data a company may have recently made it onto the list due to a zero dividend or a dividend cut prior to 2007. And it takes four years of data to give 3 data points.
DGR.
The DGR is computed from the first and most recent year of monotonically increasing dividend payments.
Data
Points Formula
11 =(div2010/div2000)^(1/11)
10 =(div2010/div2001)^(1/10)
9 =(div2010/div2002)^(1/9)
8 =(div2010/div2003)^(1/8)
7 =(div2010/div2004)^(1/7)
6 =(div2010/div2005)^(1/6)
5 =(div2010/div2006)^(1/5)
4 =(div2010/div2007)^(1/4)
3 =(div2010/div2008)^(1/3)
Bumpiness Coefficient.
The Bumpiness Coefficient (or BC) is 100 times the Standard Deviation about the dividend CAGR.
Data
Points Formula
11 =100/11*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2001/div2000-1-DGR)^2))
10 =100/10*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2002/div2001-1-DGR)^2))
9 =100/9*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2003/div2002-1-DGR)^2))
8 =100/8*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2003/div2002-1-DGR)^2))
7 =100/7*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2004/div2003-1-DGR)^2))
6 =100/6*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2005/div2004-1-DGR)^2))
5 =100/5*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2006/div2005-1-DGR)^2))
4 =100/4*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
…
(div2007/div2006-1-DGR)^2))
3 =100/3*SQRT(SUM(
(div2010/div2009-1-DGR)^2;
(div2009/div2008-1-DGR)^2;
(div2008/div2007-1-DGR)^2))
Appendix B
If you took basic algebra, you might remember the equation for a straight line as:
Y := a + b•X
Where X is the independent variable, Y is the dependent variable, a is the Y-intercept and b is the slope.
For the linear regression trend line, the AADGR is our X and the bumpiness coefficient or BC is our Y.
With the Linear Correlation and Regression tool computed (449 company) Y-intercept of -10.969416 and slope of 97.179754, the trend line equation for predicting BC is:
[BC] := a + b•[AADGR]
With the restriction that the bumpiness coefficient can never be negative.
Solving for the maximum AADGR that yields zero BC gives:
0 := a + b•[AADGR]
-a := b•[AADGR]
[AADGR] := -a / b
[AADGR] :=
-(-10.969416) / 97.179754
[AADGR] := 0.112877 => ~11%
Repeating the process for the reduced (447 company) data, the Linear Correlation and Regression tool computed Y-intercept of -5.965385 and slope of 74.523808, the trend line for predicting BC is:
[BC] := -5.965385
+ 74.523808•[AADGR]
Solving for the maximum AADGR that yields a zero BC gives:
[AADGR] := 0.0800467 => 8%