HDBR50 Returns versus Earnings Yield
Moderator: hocus2004
HDBR50 Returns versus Earnings Yield
These are the final balances of the HDBR50 portfolio at years 10, 14, 18, 22, 26 and 30 when there are no withdrawals and when the initial balances are all $100000.
The HDBR50 portfolio consists of 50% stocks and 50% commercial paper. It is rebalanced annually. Expenses are 0.20%. In this case, all dividends were reinvested. There were no withdrawals. The initial balances were all $100000.
Curve fit equations
These are the equations for fitting a straight line to the final balances as a function of Professor Robert Shiller's P/E10.
P/E10 is the current value of the S&P500 index (in real dollars) divided by the average of the most recent ten years of (real) earnings.
Excel calculated the curve fit equations as a function of the percentage earnings yield 100E10/P.
The calculator has dummy data with heavy stock market losses after 2002. I excluded all sequences that ended after 2002.
Curves from sequences beginning in 1923-1984
At year 10: Final balance = 1100700/[P/E10] + 70098 and R-squared equals 0.3845.
At year 14: Final balance = 2064500/[P/E10] + 32820 and R-squared equals 0.6136.
At year 18: Final balance = 2558900/[P/E10] + 21155 and R-squared equals 0.6437.
Curves from sequences beginning in 1923-1972
At year 22: Final balance = 2120100/[P/E10] + 77317 and R-squared equals 0.5745.
At year 26: Final balance = 1372700/[P/E10] + 170189 and R-squared equals 0.3949.
At year 30: Final balance = 1049600/[P/E10] + 252306 and R-squared equals 0.2108.
Predictability
Look at R-squared. We see that P/E10 (actually, 100E10/P) predicts a portfolio's return best in the medium-term.
There is considerable randomness in the short-term.
We cannot rely upon significant portfolio gains prior to year 22. [Put today's P/E10 of 28 or so into the equations. While you are at it, put in a P/E10 of 44 to see what happened at the top of the bubble (in December 1999).]
Valuations always matter. We can take best advantage of them in the medium term.
Relationship with previous findings
In the New Tool we found that knowing a portfolio's total return at year 14 allowed us to estimate its 30-year Historical Surviving Withdrawal Rate with the greatest accuracy. R-squared was around 90%. When we waited much later to make estimates, R-squared was much lower. There was almost no variation of Historical Surviving Withdrawal Rates at year 30 based upon a portfolio's 30-year total return.
These results help to explain why. We have only a limited ability to estimate total returns as a function of earnings yield before year 10 and after year 26. Year 18 is the best, but year 14 is also good.
Considering only the predictability of returns, we would expect the best estimates at year 18. But Historical Surviving Withdrawal Rates are most sensitive to the returns during the earliest years. This pulls the best number of years for predicting Historical Surviving Withdrawal Rates forward slightly, favoring 14 years over 18.
Have fun.
John R.
The HDBR50 portfolio consists of 50% stocks and 50% commercial paper. It is rebalanced annually. Expenses are 0.20%. In this case, all dividends were reinvested. There were no withdrawals. The initial balances were all $100000.
Curve fit equations
These are the equations for fitting a straight line to the final balances as a function of Professor Robert Shiller's P/E10.
P/E10 is the current value of the S&P500 index (in real dollars) divided by the average of the most recent ten years of (real) earnings.
Excel calculated the curve fit equations as a function of the percentage earnings yield 100E10/P.
The calculator has dummy data with heavy stock market losses after 2002. I excluded all sequences that ended after 2002.
Curves from sequences beginning in 1923-1984
At year 10: Final balance = 1100700/[P/E10] + 70098 and R-squared equals 0.3845.
At year 14: Final balance = 2064500/[P/E10] + 32820 and R-squared equals 0.6136.
At year 18: Final balance = 2558900/[P/E10] + 21155 and R-squared equals 0.6437.
Curves from sequences beginning in 1923-1972
At year 22: Final balance = 2120100/[P/E10] + 77317 and R-squared equals 0.5745.
At year 26: Final balance = 1372700/[P/E10] + 170189 and R-squared equals 0.3949.
At year 30: Final balance = 1049600/[P/E10] + 252306 and R-squared equals 0.2108.
Predictability
Look at R-squared. We see that P/E10 (actually, 100E10/P) predicts a portfolio's return best in the medium-term.
There is considerable randomness in the short-term.
We cannot rely upon significant portfolio gains prior to year 22. [Put today's P/E10 of 28 or so into the equations. While you are at it, put in a P/E10 of 44 to see what happened at the top of the bubble (in December 1999).]
Valuations always matter. We can take best advantage of them in the medium term.
Relationship with previous findings
In the New Tool we found that knowing a portfolio's total return at year 14 allowed us to estimate its 30-year Historical Surviving Withdrawal Rate with the greatest accuracy. R-squared was around 90%. When we waited much later to make estimates, R-squared was much lower. There was almost no variation of Historical Surviving Withdrawal Rates at year 30 based upon a portfolio's 30-year total return.
These results help to explain why. We have only a limited ability to estimate total returns as a function of earnings yield before year 10 and after year 26. Year 18 is the best, but year 14 is also good.
Considering only the predictability of returns, we would expect the best estimates at year 18. But Historical Surviving Withdrawal Rates are most sensitive to the returns during the earliest years. This pulls the best number of years for predicting Historical Surviving Withdrawal Rates forward slightly, favoring 14 years over 18.
Have fun.
John R.
Year, P/E10, 100E10/P, balance at year 10, balance at year 14, balance at year 18
Warning: there are dummy data from 2003-2010 with heavy losses in stocks.
More follows.
Have fun.
John R.
Code: Select all
1871 13.3 7.52 277710 392896 451662
1872 14.5 6.90 241678 389434 458749
1873 15.3 6.54 239898 354898 418159
1874 13.9 7.19 243399 359901 460238
1875 13.6 7.35 232884 356052 406945
1876 13.3 7.52 250144 311995 390992
1877 10.6 9.43 284516 385542 440500
1878 9.7 10.31 232003 320116 381436
1879 10.7 9.35 206331 280548 331405
1880 15.3 6.54 220278 289514 343904
1881 18.5 5.41 176458 246225 321137
1882 15.7 6.37 218354 274256 300117
1883 15.3 6.54 204123 278828 324096
1884 14.4 6.94 201051 291967 324692
1885 13.1 7.63 200943 241728 293603
1886 16.7 5.99 174039 231907 241440
1887 17.5 5.71 170200 232687 254102
1888 15.4 6.49 188477 231835 293617
1889 15.8 6.33 197455 210026 267662
1890 17.2 5.81 158107 215708 225127
1891 15.4 6.49 185934 249197 267836
1892 19.0 5.26 171715 209309 226410
1893 17.7 5.65 168021 196973 245094
1894 15.7 6.37 154466 213721 240065
1895 16.5 6.06 164123 198162 221093
1896 16.6 6.02 178588 205693 209015
1897 17.0 5.88 166645 203225 193351
1898 19.2 5.21 144199 186126 202127
1899 22.9 4.37 147170 160258 167684
1900 18.7 5.35 164728 176690 149850
1901 21.0 4.76 154366 173895 122527
1902 22.3 4.48 148650 150783 108415
1903 20.3 4.93 151316 123374 110266
1904 15.9 6.29 150666 117689 134314
1905 18.5 5.41 129508 99278 137370
1906 20.1 4.98 129749 87064 123730
1907 17.2 5.81 123701 105392 142774
1908 11.9 8.40 105240 131623 168381
1909 14.8 6.76 85059 115119 159421
1910 14.5 6.90 82225 131990 193753
1911 14.0 7.14 75592 135321 228521
1912 13.8 7.25 86422 141926 213174
1913 13.1 7.63 101973 173658 210491
1914 11.6 8.62 105718 224889 196546
1915 10.4 9.62 123054 224060 214761
1916 12.5 8.00 120124 193827 235357
1917 11.0 9.09 139918 187842 233654
1918 6.6 15.15 212989 253227 365212
1919 6.1 16.39 287904 334029 442573
1920 6.0 16.67 292286 324964 392051
Code: Select all
1921 5.1 19.61 288854 408627 431834
1922 6.3 15.87 220474 387792 369511
1923 8.2 12.20 202470 283338 299939
1924 8.1 12.35 246806 303866 255650
1925 9.7 10.31 202440 272764 227746
1926 11.3 8.85 228262 234461 223559
1927 13.2 7.58 236135 184607 217590
1928 18.8 5.32 166379 155147 208752
1929 27.1 3.69 142844 132383 132144
1930 22.3 4.48 149802 144867 125131
1931 16.7 5.99 145307 172223 133340
1932 9.3 10.75 137509 151199 161974
1933 8.7 11.49 130494 130549 163720
1934 13.0 7.69 114102 109811 140604
1935 11.5 8.70 130299 130217 161274
1936 17.1 5.85 121743 113519 131059
1937 21.6 4.63 85962 106120 142511
1938 13.5 7.41 93289 133677 191827
1939 15.6 6.41 89191 124016 179712
1940 16.4 6.10 96644 149561 166587
1941 13.9 7.19 110517 181210 209446
1942 10.1 9.90 135740 213606 253147
1943 10.2 9.80 143354 199517 255176
1944 11.1 9.01 133816 219659 259387
1945 12.0 8.33 154656 214775 239917
1946 15.6 6.41 152889 189650 227714
1947 11.5 8.70 194264 259856 308353
1948 10.4 9.62 199433 277757 353381
1949 10.2 9.80 228243 294117 326474
1950 10.7 9.35 214910 287840 313748
1951 11.9 8.40 203389 281783 302153
1952 12.5 8.00 210496 254975 268668
1953 13.0 7.69 193837 253328 251790
1954 12.0 8.33 211527 261714 262607
1955 16.0 6.25 185999 200063 230245
1956 18.3 5.46 171855 175464 179016
1957 16.7 5.99 162029 181220 147003
1958 13.8 7.25 182018 206712 175717
1959 18.0 5.56 159436 154882 151322
1960 18.3 5.46 144062 124041 135076
1961 18.5 5.41 141452 137390 136182
1962 21.2 4.72 135477 128146 123474
1963 19.3 5.18 148422 120921 134849
1964 21.6 4.63 120192 113418 117376
1965 23.3 4.29 92613 104054 123169
1966 24.1 4.15 99167 105991 128251
1967 20.4 4.90 105791 105743 138719
1968 21.5 4.65 92524 112998 145052
1969 21.2 4.72 91669 119605 161580
1970 17.1 5.85 96740 131649 168762
1971 16.5 6.06 103812 145937 181056
1972 17.3 5.78 94545 161030 188108
1973 18.7 5.35 99500 146639 169111
1974 13.5 7.41 123122 177463 216172
1975 8.9 11.24 152898 231893 262940
1976 11.2 8.93 150253 198941 242948
1977 11.4 8.77 170243 221258 238598
1978 9.2 10.87 179989 241460 297853
1979 9.3 10.75 188063 245102 324173
1980 8.9 11.24 206395 247625 371693
1981 9.3 10.71 186132 267088 398438
1982 7.4 13.48 221360 313242 446993
1983 8.7 11.51 197709 314010 376884
1984 9.8 10.25 187853 329283 315246
1985 9.9 10.07 181962 340734 268810
1986 11.7 8.57 189992 293601 213608
1987 14.7 6.78 183912 233353 162988
1988 13.7 7.28 213066 209696 146465
1989 15.2 6.60 228452 172176 120258
1990 17.0 5.88 224663 139527 97454
1991 15.6 6.42 221746 127002 88706
1992 19.6 5.11 179549 98724 68955
1993 20.4 4.90 156312 85947
1994 21.5 4.65 132107 72638
1995 20.5 4.89 116295 63944
1996 25.4 3.93 88507
1997 29.2 3.43 69766
1998 33.8 2.96 54115
1999 40.9 2.44 41440
2000 44.7 2.24 34148
2001 37.0 2.70
2002 30.3 3.30
2003 22.9 4.37
Warning: there are dummy data from 2003-2010 with heavy losses in stocks.
More follows.
Have fun.
John R.
Year, P/E10, 100E10/P, balance at year 22, balance at year 26, balance at year 30
Warning: there are dummy data from 2003-2010 with heavy losses in stocks.
Have fun.
John R.
Code: Select all
1871 13.3 7.52 573867 725450 911156
1872 14.5 6.90 561101 716211 906163
1873 15.3 6.54 563112 761009 822779
1874 13.9 7.19 544871 632573 755885
1875 13.6 7.35 514436 646125 768034
1876 13.3 7.52 499078 631442 777482
1877 10.6 9.43 595307 643627 806973
1878 9.7 10.31 442831 529156 630542
1879 10.7 9.35 416240 494775 599590
1880 15.3 6.54 435113 535746 573707
1881 18.5 5.41 347203 435320 506468
1882 15.7 6.37 358621 427333 557357
1883 15.3 6.54 385245 466857 518971
1884 14.4 6.94 399786 428114 467900
1885 13.1 7.63 368117 428281 427109
1886 16.7 5.99 287700 375238 403276
1887 17.5 5.71 307931 342305 350853
1888 15.4 6.49 314421 343642 286024
1889 15.8 6.33 311408 310557 247178
1890 17.2 5.81 293626 315566 214152
1891 15.4 6.49 297734 305168 216962
1892 19.0 5.26 247451 205961 220595
1893 17.7 5.65 244423 194541 259261
1894 15.7 6.37 258003 175088 246035
1895 16.5 6.06 226614 161113 261554
1896 16.6 6.02 173970 186331 278346
1897 17.0 5.88 153892 205088 288430
1898 19.2 5.21 137169 192751 323222
1899 22.9 4.37 119216 193538 360403
1900 18.7 5.35 160497 239755 395892
1901 21.0 4.76 163288 229644 337056
1902 22.3 4.48 152346 255467 283234
1903 20.3 4.93 179009 333346 312416
1904 15.9 6.29 200643 331308 393116
1905 18.5 5.41 193193 283556 322620
1906 20.1 4.98 207481 230033 355768
1907 17.2 5.81 265870 249177 408702
1908 11.9 8.40 278036 329906 372938
1909 14.8 6.76 233987 266222 349809
1910 14.5 6.90 214812 332227 360022
1911 14.0 7.14 214173 351288 317276
1912 13.8 7.25 252943 285936 262007
1913 13.1 7.63 239489 314682 269425
1914 11.6 8.62 303977 329408 297714
1915 10.4 9.62 352252 318146 324588
1916 12.5 8.00 266056 243791 333816
1917 11.0 9.09 307015 262861 284016
1918 6.6 15.15 395766 357687 330585
1919 6.1 16.39 399722 407816 366803
1920 6.0 16.67 359241 491899 423157
Code: Select all
1921 5.1 19.61 369728 399484 463868
1922 6.3 15.87 333959 308655 411525
1923 8.2 12.20 306013 275237 378759
1924 8.1 12.35 350054 301135 376841
1925 9.7 10.31 246075 285734 407949
1926 11.3 8.85 206620 275483 424866
1927 13.2 7.58 195707 269316 394332
1928 18.8 5.32 179580 224726 309544
1929 27.1 3.69 153441 219071 290791
1930 22.3 4.48 166835 257302 311137
1931 16.7 5.99 183491 268667 326621
1932 9.3 10.75 202695 279198 392901
1933 8.7 11.49 233747 310272 362609
1934 13.0 7.69 216848 262218 322975
1935 11.5 8.70 236137 287073 374816
1936 17.1 5.85 180524 254042 319876
1937 21.6 4.63 189166 221075 270580
1938 13.5 7.41 231962 285708 338641
1939 15.6 6.41 218477 285254 324567
1940 16.4 6.10 234430 295181 299215
1941 13.9 7.19 244775 299587 317957
1942 10.1 9.90 311802 369570 387097
1943 10.2 9.80 333169 379086 412425
1944 11.1 9.01 326605 331069 340213
1945 12.0 8.33 293641 311646 266409
1946 15.6 6.41 269902 282703 260559
1947 11.5 8.70 350849 381705 332994
1948 10.4 9.62 358210 368104 335866
1949 10.2 9.80 346492 296198 333582
1950 10.7 9.35 328628 302887 299510
1951 11.9 8.40 328726 286776 298665
1952 12.5 8.00 276088 251909 269618
1953 13.0 7.69 215241 242408 286256
1954 12.0 8.33 242038 239340 313024
1955 16.0 6.25 200862 209190 263381
1956 18.3 5.46 163338 174820 256067
1957 16.7 5.99 165557 195504 291819
1958 13.8 7.25 173759 227252 303121
1959 18.0 5.56 157595 198421 274859
1960 18.3 5.46 144572 211761 287643
1961 18.5 5.41 160815 240041 273325
1962 21.2 4.72 161487 215400 283532
1963 19.3 5.18 169782 235187 291975
1964 21.6 4.63 171925 233533 277990
1965 23.3 4.29 183848 209340 257665
1966 24.1 4.15 171068 225179 283090
1967 20.4 4.90 192158 238556 331231
1968 21.5 4.65 197029 234538 354826
1969 21.2 4.72 183984 226455 393839
1970 17.1 5.85 222143 279273 448574
1971 16.5 6.06 224773 312094 428474
1972 17.3 5.78 223918 338760 375768
1973 18.7 5.35 208149 362002 307496
1974 13.5 7.41 271767 436518 305548
1975 8.9 11.24 365089 501230 323552
1976 11.2 8.93 367550 407703 252660
1977 11.4 8.77 414956 352477 218436
1978 9.2 10.87 478417 334876 207528
1979 9.3 10.75 445057 287291 178039
1980 8.9 11.24 412298 255507 158342
1981 9.3 10.71 338446 209740
1982 7.4 13.48 312880 193897
1983 8.7 11.51 243285 150767
1984 9.8 10.25 195363 121069
1985 9.9 10.07 166586
1986 11.7 8.57 132376
1987 14.7 6.78 101006
1988 13.7 7.28 90767
1989 15.2 6.60
1990 17.0 5.88
1991 15.6 6.42
1992 19.6 5.11
1993 20.4 4.90
1994 21.5 4.65
1995 20.5 4.89
1996 25.4 3.93
1997 29.2 3.43
1998 33.8 2.96
1999 40.9 2.44
2000 44.7 2.24
2001 37.0 2.70
2002 30.3 3.30
2003 22.9 4.37
Have fun.
John R.
"We have only a limited ability to estimate total returns as a function of earnings yield before year 10 and after year 26."
Say that I currently own no stocks but plan sometime in the not-too-distant future to put $10,000 into an S&P index fund. Say that my intent would be to hold this investment for a minimum of 26 years. Is the data saying that I do not gain much if any advantage by waiting for S&P valuation levels to come down before making the purchase?
Say that I currently own no stocks but plan sometime in the not-too-distant future to put $10,000 into an S&P index fund. Say that my intent would be to hold this investment for a minimum of 26 years. Is the data saying that I do not gain much if any advantage by waiting for S&P valuation levels to come down before making the purchase?
I have checked the graphs. The answer is no. There is a definite advantage to waiting.hocus2004 wrote:"We have only a limited ability to estimate total returns as a function of earnings yield before year 10 and after year 26."
Say that I currently own no stocks but plan sometime in the not-too-distant future to put $10,000 into an S&P index fund. Say that my intent would be to hold this investment for a minimum of 26 years. Is the data saying that I do not gain much if any advantage by waiting for S&P valuation levels to come down before making the purchase?
At years 26 and 30, there is a lot of scatter in the data. Waiting four years, from year 22 to year 26, pays off if the earnings yield falls from valuation around 4% (with P/E10 = 25) to 6% to 8% (P/E10 = 12 to 17). It does not pay to wait eight years, from year 22 to year 30.
My own interpretation is that one should start buying when P/E10 falls below 20 and start buying heavily when P/E10 falls to 15. Others may decide differently even though using the same set of data.
P/E10 can vary enough to be exploited if one patiently waits for a good buying opportunity. For example, even though P/E10 is now around 28, it dipped to 21 last February and March. The S&P500 index for those two months stood at 837 and 846 (nominal, that is, without special adjustments for inflation).
In terms of what we can see in the equations, the slopes are biggest around 14, 18 and 22 years. (The slopes are the numbers just before the "/[P/E10]" terms.} They are big enough for you to pay attention at other times, even at year 30.
Have fun.
John R.
"Waiting four years, from year 22 to year 26, pays off IF [my emphasis] the earnings yield falls from valuation around 4% (with P/E10 = 25) to 6% to 8% (P/E10 = 12 to 17). It does not pay to wait eight years, from year 22 to year 30. "
I'm not trying to be difficult. I'm fascinated by these findings and I am trying to gain a better grasp of the implications.
I guess I can see how one would be better off waiting if one assumes that the earnings yield is going to fall. But do we really know that that is going to happen within four years? My gut tells me that it will. But the data says that short-term changes in price levels are unpredictable. So I am not sure that we can assume a significant drop in the earnings yield within four years.
One of the criticisms that you often hear of long-term timing strategies is that those who hold off on purchases of stocks when prices are high may "miss out" on gains that take place despite their expectations. This would not be a concern if you could use historical data to successfully predict long-term returns. But it seems to me that what the thread-starter is saying is that you can only predict intermediate-term returns, not long-term returns.
It seems to me that what you are finding is that the long-term benefits of owning stocks are great enough to overcome valuation concerns so long as you are sure that you can avoid selling any shares for at least 26 years. Perhaps I am overstating things a bit with that interpretation. That's the message that I am getting when I read the thread-starter, but my understanding of the data presented on this thread is definitely fuzzy.
I am going to continue trying to get it straight. I think this is potentially an important finding. I understand that you have been suggesting conclusions along these lines for some time. I've just been struggling to come to terms with the distinction between intermediate-term and long-term predictability and my hope is that this thread-starter is beginning to make it a little more clear (but obviously not entirely so) for me.
I'm not trying to be difficult. I'm fascinated by these findings and I am trying to gain a better grasp of the implications.
I guess I can see how one would be better off waiting if one assumes that the earnings yield is going to fall. But do we really know that that is going to happen within four years? My gut tells me that it will. But the data says that short-term changes in price levels are unpredictable. So I am not sure that we can assume a significant drop in the earnings yield within four years.
One of the criticisms that you often hear of long-term timing strategies is that those who hold off on purchases of stocks when prices are high may "miss out" on gains that take place despite their expectations. This would not be a concern if you could use historical data to successfully predict long-term returns. But it seems to me that what the thread-starter is saying is that you can only predict intermediate-term returns, not long-term returns.
It seems to me that what you are finding is that the long-term benefits of owning stocks are great enough to overcome valuation concerns so long as you are sure that you can avoid selling any shares for at least 26 years. Perhaps I am overstating things a bit with that interpretation. That's the message that I am getting when I read the thread-starter, but my understanding of the data presented on this thread is definitely fuzzy.
I am going to continue trying to get it straight. I think this is potentially an important finding. I understand that you have been suggesting conclusions along these lines for some time. I've just been struggling to come to terms with the distinction between intermediate-term and long-term predictability and my hope is that this thread-starter is beginning to make it a little more clear (but obviously not entirely so) for me.
At a 4% earnings yield (P/E10 = 25), the equations predict balances of $162K, $225K and $294K at 22, 26 and 30 years respectively. This works out to an increase of $63K to $69K for waiting an additional 4 years.
There is scatter around each line of about $70K on the downside. [There is more variation on the upside.]
The question is whether waiting for a higher earnings yield (i.e., a lower value of P/E10) gains enough in four years to overcome this hurdle.
Waiting for better valuations is sufficient to overcome both the scatter and the different starting point among the lines only when the earnings yield falls into the 6% to 8% range (and P/E10 = 12 to 17) or better.
There is excellent predictability about price fluctuations in the short-term. Prices fluctuate a lot. It is only when you estimate returns (which involves the ratio of the final price to the initial price) that there is little predictability.
Stated differently, predictable returns require small price fluctuations. Unpredictable returns go along with large price fluctuations.
When we hope to get a good price in the short-term, we are hoping that short-term prices fluctuate a lot. When we hope to get good, reliable returns in the long term, we hope that long-term prices fluctuate little.
You can count on short-term price fluctuations of the order of 25%. [This corresponds to P/E10 = 21 and 28 inside of a year.] It is dangerous to depend upon larger fluctuations although they occur often.
With P/E10, the earnings are smoothed. Almost all of the fluctuations come from prices, not earnings.
Have fun.
John R.
There is scatter around each line of about $70K on the downside. [There is more variation on the upside.]
The question is whether waiting for a higher earnings yield (i.e., a lower value of P/E10) gains enough in four years to overcome this hurdle.
Waiting for better valuations is sufficient to overcome both the scatter and the different starting point among the lines only when the earnings yield falls into the 6% to 8% range (and P/E10 = 12 to 17) or better.
There is excellent predictability about price fluctuations in the short-term. Prices fluctuate a lot. It is only when you estimate returns (which involves the ratio of the final price to the initial price) that there is little predictability.
Stated differently, predictable returns require small price fluctuations. Unpredictable returns go along with large price fluctuations.
When we hope to get a good price in the short-term, we are hoping that short-term prices fluctuate a lot. When we hope to get good, reliable returns in the long term, we hope that long-term prices fluctuate little.
You can count on short-term price fluctuations of the order of 25%. [This corresponds to P/E10 = 21 and 28 inside of a year.] It is dangerous to depend upon larger fluctuations although they occur often.
With P/E10, the earnings are smoothed. Almost all of the fluctuations come from prices, not earnings.
Have fun.
John R.
For unclemick: HELP! Benjamin Graham has a famous quote about prices always becoming attractive again within a reasonable amount of time. That is, you do not have to worry about having missed out on an opportunity.hocus2004 wrote:One of the criticisms that you often hear of long-term timing strategies is that those who hold off on purchases of stocks when prices are high may "miss out" on gains that take place despite their expectations. This would not be a concern if you could use historical data to successfully predict long-term returns. But it seems to me that what the thread-starter is saying is that you can only predict intermediate-term returns, not long-term returns.
The historical data do allow us to predict long-term returns. The historical data tell us that we can exploit the effects of valuations best during the intermediate-term.
This is consistent with capital preservation approaches such as varying stock strategies depending upon valuations.
Have fun.
John R.
????? You got me????
page 109 the 4th ed.
"Basically, price fluctuations have only one significant meaning for the true investor. They provide him with an opportunity to buy wisely when prices fall sharply and to sell wisely when they advance a great deal. At other times he will do better if he forgets about the stock market and pays attention to his dividend returns and to the operating results of his companies."
Chapter 8: The Investor and Market Fluctuations.
page 109 the 4th ed.
"Basically, price fluctuations have only one significant meaning for the true investor. They provide him with an opportunity to buy wisely when prices fall sharply and to sell wisely when they advance a great deal. At other times he will do better if he forgets about the stock market and pays attention to his dividend returns and to the operating results of his companies."
Chapter 8: The Investor and Market Fluctuations.
Thanks, unclemick.
In this case we are trying to decide whether it is worthwhile to wait for a good opportunity to buy. We anticipate holding onto the index fund for a long time.
This is a great time "to sell wisely."
Back when Ben Graham wrote his comments, there was no such thing as an index fund.
How long will hocus2004 have to wait before he can buy wisely? He is not greedy. He just does not want to act rashly.
Have fun.
John R.
In this case we are trying to decide whether it is worthwhile to wait for a good opportunity to buy. We anticipate holding onto the index fund for a long time.
This is a great time "to sell wisely."
Back when Ben Graham wrote his comments, there was no such thing as an index fund.
How long will hocus2004 have to wait before he can buy wisely? He is not greedy. He just does not want to act rashly.
Have fun.
John R.
I have posted tables that show the volatility of the S&P500 index in terms index levels (nominal prices) and valuations (P/E10).
There is less volatility than I had thought.
There is a real possibility that the market would continue to climb while you are waiting for a buying opportunity.
Have fun.
John R.
There is less volatility than I had thought.
There is a real possibility that the market would continue to climb while you are waiting for a buying opportunity.
Have fun.
John R.
In view of what Mike has said, I have looked at what has happened with P/E10 around 21 to 22 in the past.Mike wrote:The data on your new tables shows P/E 10 going over 20 in the early 90s, and never coming back. This is historically unprecedented. Data is not yet in on how this long period out of the S&P will affect long term switching performance.
The relevant comparisons are in 1937 and in the decade of the 1960s, especially 1965. [Other Depression years turned out not to be too bad for retirees.]
The worst case annualized, real returns have been 2.7% to 3.3% at 26 to 30 years (almost always 3.3%, not 2.7%). This is better than long-term TIPS have been this year (around 2.5%). OTOH, these are data points that correspond to calculated rates, not to safe rates which are at a lower confidence limit.
Our research of switching stock allocations suggested that we make limited stock purchases with P/E10 up to 24.
Along those same lines and in view of recent history, it makes sense to purchase some (S&P500) index funds when P/E10 falls to 21 to 22. There is a significant chance of loss if sold at year 14 or earlier.
I doubt that it is worthwhile to wait for TIPS yields to push into the 2.7% to 3.3% range. I doubt that it is worth holding short-term TIPS or ibonds at 1% real interest to fill the gap while waiting for P/E10 to fall into its normal range (12 to 17). I do think that it is reasonable to buy individual stocks (or one of the very few index alternatives) to implement a dividend-based strategy. The objective would be for a dividend yield around 3.3% (or at least 2.7%) that grows with inflation.
Have fun.
John R.
The time tested live off the dividends, don't touch the principal strategy, only using high dividend stocks instead of the S&P. I am wondering if the high dividend indexes can grow dividends as fast as the S&P, when stripped of their higher growth company components. The S&P itself grows dividends faster than inflation, but there are long periods where it lags before catching up. I am wondering if the this lag might be magnified in high dividend stocks under certain economic scenarios.
Mike has brought up an excellent question.
I went to CBS.Marketwatch.com. I looked up the Dow Jones Utility Average Index, which they identify with a number instead of a symbol 260998 or 26099800. What I learned was not encouraging.
The index has become highly volatile. Within the last five years, the average peaked around 420, fell to 160 and recovered to 330. It used to be stable.
Looking at a graph, the (rolling) dividend amount peaked around 1987 at $4.00 per share and it has fallen almost steadily to $2.50 per share. In 1984 the dividend yield was close to 9%. Now it is 3%. [There was a spike to 6%+ in 2002 when the price of the utility average took a nosedive.]
More precisely, the current index level (or price) is $329.09. The dividend amount is $2.56 over the last year. The dividend yield is 3.11%.
I had expected to see some changes as a result of deregulation. I had not expected this kind of behavior. Dividend amounts have been falling since 1987.
Between these results and what has happened to the DVY's yield, it looks as if 3% is the highest dividend yield that an index fund buyer can purchase today. To do better requires buying individual securities.
I expect stock prices to fall enough in the next year or two to make it worthwhile to wait for better yields, at least when buying an index fund. I may be wrong. Dividends are becoming more and more popular these days. This growing popularity may cancel out any improvement in yields.
Have fun.
John R.
I went to CBS.Marketwatch.com. I looked up the Dow Jones Utility Average Index, which they identify with a number instead of a symbol 260998 or 26099800. What I learned was not encouraging.
The index has become highly volatile. Within the last five years, the average peaked around 420, fell to 160 and recovered to 330. It used to be stable.
Looking at a graph, the (rolling) dividend amount peaked around 1987 at $4.00 per share and it has fallen almost steadily to $2.50 per share. In 1984 the dividend yield was close to 9%. Now it is 3%. [There was a spike to 6%+ in 2002 when the price of the utility average took a nosedive.]
More precisely, the current index level (or price) is $329.09. The dividend amount is $2.56 over the last year. The dividend yield is 3.11%.
I had expected to see some changes as a result of deregulation. I had not expected this kind of behavior. Dividend amounts have been falling since 1987.
Between these results and what has happened to the DVY's yield, it looks as if 3% is the highest dividend yield that an index fund buyer can purchase today. To do better requires buying individual securities.
I expect stock prices to fall enough in the next year or two to make it worthwhile to wait for better yields, at least when buying an index fund. I may be wrong. Dividends are becoming more and more popular these days. This growing popularity may cancel out any improvement in yields.
Have fun.
John R.
I have collected information on the dividend amounts of the S&P500 index.
I used Professor Robert Shiller's data. I thinned the data by excluding everything except the January levels for each year. I have attached tables with nominal and real dividend amounts from 1871-2003. Each amount is the average for the month.
I exclude the curve fit of the nominal data for 1871-2003 since it diverges around 1980. A straight line makes a good fit for the real dividend amount. The dividend amount y is estimated by y = 0.0879*x -161.45, where x is the calendar year. For example, in the year 1950, the value of x was 1950. R-squared is 0.8153.
A plot of the real dividend amount versus calendar year shows fluctuations similar to a sine wave above and below the trend line. The worst cases are plus $3.00 and minus $2.00.
Using 1921-2003 data, the curve fit for the nominal dividend amount is y = 6*[10^(-41)]* exp(0.0476*x). R-squared is 0.9518. Putting values x = 1921 and x = 2003 into this equation and taking the ratios, we find that the dividend amount (as estimated by the curve) has grown by a factor of exp(0.0476*82) or 49.56079 in 82 years. To find the annualized growth rate r, (1+r)^82 = 49.56079 or r = 4.875% (nominal).
The equation for the real dividend amount based on 1921-2003 data is y = 0.1298*x - 244.05. R-squared is 0.8101. Once again, there are oscillations around the trend line. They are heavily damped in recent years. Letting x = 1950 and x = 2000, the calculated real dividend amount increases from $9.06 to $15.55, which is $1.298 per decade.
[Dividend amounts got far ahead of the trend in the 1960s. They peaked in 1966. It took until 1991 before the real dividend amount returned to the 1966 level. The trend line did not catch up until 1993.]
Real dividend amounts were about $1.00 below trend in January 2003.
Have fun.
John R.
I used Professor Robert Shiller's data. I thinned the data by excluding everything except the January levels for each year. I have attached tables with nominal and real dividend amounts from 1871-2003. Each amount is the average for the month.
I exclude the curve fit of the nominal data for 1871-2003 since it diverges around 1980. A straight line makes a good fit for the real dividend amount. The dividend amount y is estimated by y = 0.0879*x -161.45, where x is the calendar year. For example, in the year 1950, the value of x was 1950. R-squared is 0.8153.
A plot of the real dividend amount versus calendar year shows fluctuations similar to a sine wave above and below the trend line. The worst cases are plus $3.00 and minus $2.00.
Using 1921-2003 data, the curve fit for the nominal dividend amount is y = 6*[10^(-41)]* exp(0.0476*x). R-squared is 0.9518. Putting values x = 1921 and x = 2003 into this equation and taking the ratios, we find that the dividend amount (as estimated by the curve) has grown by a factor of exp(0.0476*82) or 49.56079 in 82 years. To find the annualized growth rate r, (1+r)^82 = 49.56079 or r = 4.875% (nominal).
The equation for the real dividend amount based on 1921-2003 data is y = 0.1298*x - 244.05. R-squared is 0.8101. Once again, there are oscillations around the trend line. They are heavily damped in recent years. Letting x = 1950 and x = 2000, the calculated real dividend amount increases from $9.06 to $15.55, which is $1.298 per decade.
[Dividend amounts got far ahead of the trend in the 1960s. They peaked in 1966. It took until 1991 before the real dividend amount returned to the 1966 level. The trend line did not catch up until 1993.]
Real dividend amounts were about $1.00 below trend in January 2003.
Have fun.
John R.
Year, S&P500 Nominal Dividend Amount, S&P500 Real Dividend Amount
Have fun.
John R.
Code: Select all
1871 0.260 3.52
1872 0.263 3.51
1873 0.303 3.95
1874 0.330 4.50
1875 0.328 4.80
1876 0.300 4.67
1877 0.291 4.49
1878 0.189 3.46
1879 0.182 3.71
1880 0.205 3.46
1881 0.265 4.75
1882 0.320 5.31
1883 0.321 5.42
1884 0.328 6.00
1885 0.304 6.20
1886 0.238 5.03
1887 0.223 4.70
1888 0.248 5.01
1889 0.229 4.84
1890 0.220 4.88
1891 0.220 4.76
1892 0.222 5.11
1893 0.241 5.15
1894 0.247 6.08
1895 0.208 5.36
1896 0.189 4.80
1897 0.180 4.70
1898 0.182 4.61
1899 0.201 5.02
1900 0.218 4.65
1901 0.302 6.61
1902 0.321 6.86
1903 0.332 6.47
1904 0.347 7.07
1905 0.312 6.21
1906 0.336 6.69
1907 0.403 7.69
1908 0.437 8.51
1909 0.403 7.61
1910 0.443 7.55
1911 0.470 8.60
1912 0.471 8.70
1913 0.480 8.27
1914 0.475 8.02
1915 0.421 7.03
1916 0.441 7.15
1917 0.571 8.24
1918 0.680 8.20
1919 0.567 5.80
1920 0.528 4.62
Code: Select all
1921 0.506 4.49
1922 0.464 4.64
1923 0.512 5.14
1924 0.532 5.19
1925 0.554 5.41
1926 0.608 5.73
1927 0.697 6.72
1928 0.777 7.58
1929 0.860 8.49
1930 0.971 9.58
1931 0.967 10.26
1932 0.793 9.36
1933 0.495 6.48
1934 0.441 5.64
1935 0.450 5.59
1936 0.480 5.87
1937 0.730 8.74
1938 0.793 9.43
1939 0.513 6.19
1940 0.623 7.57
1941 0.673 8.06
1942 0.703 7.56
1943 0.590 5.89
1944 0.613 5.95
1945 0.643 6.10
1946 0.667 6.18
1947 0.713 5.60
1948 0.843 6.01
1949 0.947 6.66
1950 1.150 8.26
1951 1.487 9.88
1952 1.413 9.00
1953 1.410 8.95
1954 1.457 9.14
1955 1.547 9.78
1956 1.670 10.52
1957 1.737 10.62
1958 1.783 10.53
1959 1.757 10.23
1960 1.867 10.75
1961 1.947 11.03
1962 2.027 11.40
1963 2.137 11.86
1964 2.297 12.55
1965 2.517 13.62
1966 2.740 14.54
1967 2.880 14.78
1968 2.930 14.50
1969 3.080 14.60
1970 3.163 14.13
1971 3.130 13.27
1972 3.070 12.61
1973 3.157 12.51
1974 3.400 12.32
1975 3.623 11.74
1976 3.683 11.18
1977 4.097 11.82
1978 4.713 12.73
1979 5.113 12.64
1980 5.700 12.37
1981 6.200 12.03
1982 6.660 11.92
1983 6.883 11.88
1984 7.120 11.79
1985 7.573 12.12
1986 7.940 12.23
1987 8.300 12.60
1988 8.857 12.92
1989 9.813 13.68
1990 11.140 14.76
1991 12.107 15.18
1992 12.240 14.96
1993 12.413 14.69
1994 12.623 14.57
1995 13.180 14.80
1996 13.893 15.19
1997 14.953 15.86
1998 15.550 16.24
1999 16.283 16.73
2000 16.573 16.57
2001 16.170 15.59
2002 15.737 15.00
2003 16.120 14.98
John R.