If you invested $100 in the S&P 500 at the beginning of 2015, you would have about $321.15 at the end of 2024, assuming you reinvested all dividends. This is a return on investment of 221.15%, or 13.19% per year.
This lump-sum investment beats inflation during this period for an inflation-adjusted return of about 141.27% cumulatively, or 9.80% per year.
If you used dollar-cost averaging (monthly) instead of a lump-sum investment, you'd have $307.52.
The graph below shows the performance of $100 over time if invested in an S&P 500 index fund. The returns assume that all dividends are automatically reinvested.
The nominal return on investment of $100 is $221.15, or 221.15%. This means by 2024 you would have $321.15 in your pocket.
However, it's important to take into account the effect of inflation when considering an investment and especially a long-term investment. You can convert S&P returns to their real (inflation-adjusted) value using an inflation calculation based on the U.S. Bureau of Labor Statistics Consumer Price Index (CPI).
In the case of the returns described above, the CPI in 2015 was 237.017 and the CPI in 2024 was 315.493.
The ratio between these CPIs describes how relative buying power of a dollar has changed over 9 years.
Adjusted for inflation, the $321.15 nominal end value of the original $100 investment would have a real return of roughly $141.27 in 2015 dollars. This means the inflation-adjusted return is 141.27% as opposed to the original 221.15%.
The table below shows the full dataset pertaining to a $100 investment, including gains and losses over the 113-month period between 2015 and 2024.
Note that data shown is the monthly average closing price. Returns include dividends.
Year
Month
Return (%)
Amount ($)
CPI
2015
1
2.83%
102.83
233.71
2015
2
0.06%
102.88
234.72
2015
3
0.88%
103.79
236.12
2015
4
0.98%
104.80
236.60
2015
5
-0.44%
104.35
237.81
2015
6
-0.08%
104.26
238.64
2015
7
-2.42%
101.74
238.65
2015
8
-4.51%
97.15
238.32
2015
9
4.32%
101.35
237.95
2015
10
2.93%
104.32
237.84
2015
11
-1.10%
103.17
237.34
2015
12
-6.42%
96.54
236.53
2016
1
-0.55%
96.01
236.92
2016
2
6.36%
102.12
237.11
2016
3
2.83%
105.01
238.13
2016
4
-0.30%
104.69
239.26
2016
5
1.07%
105.81
240.23
2016
6
3.30%
109.30
241.02
2016
7
1.20%
110.61
240.63
2016
8
-0.44%
110.12
240.85
2016
9
-0.51%
109.57
241.43
2016
10
1.20%
110.88
241.73
2016
11
3.95%
115.26
241.35
2016
12
1.44%
116.92
241.43
2017
1
2.58%
119.93
242.84
2017
2
1.75%
122.03
243.60
2017
3
-0.15%
121.84
243.80
2017
4
1.69%
123.90
244.52
2017
5
1.78%
126.10
244.73
2017
6
0.99%
127.35
244.96
2017
7
0.25%
127.66
244.79
2017
8
1.65%
129.77
245.52
2017
9
2.73%
133.32
246.82
2017
10
1.59%
135.44
246.66
2017
11
2.88%
139.35
246.67
2017
12
4.86%
146.12
246.52
2018
1
-2.89%
141.90
247.87
2018
2
0.06%
142.00
248.99
2018
3
-1.66%
139.63
249.55
2018
4
1.96%
142.37
250.55
2018
5
2.11%
145.38
251.59
2018
6
1.58%
147.68
251.99
2018
7
2.45%
151.30
252.01
2018
8
1.68%
153.84
252.15
2018
9
-3.85%
147.92
252.44
2018
10
-2.08%
144.85
252.89
2018
11
-5.56%
136.79
252.04
2018
12
1.74%
139.16
251.23
2019
1
5.83%
147.28
251.71
2019
2
1.95%
150.14
252.78
2019
3
3.72%
155.73
254.20
2019
4
-1.53%
153.35
255.55
2019
5
1.40%
155.50
256.09
2019
6
3.83%
161.46
256.14
2019
7
-3.13%
156.39
256.57
2019
8
3.09%
161.22
256.56
2019
9
0.01%
161.24
256.76
2019
10
4.43%
168.38
257.35
2019
11
2.47%
172.54
257.21
2019
12
3.35%
178.32
256.97
2020
1
0.12%
178.53
257.97
2020
2
-18.92%
144.76
258.68
2020
3
4.32%
151.01
258.12
2020
4
5.89%
159.90
256.39
2020
5
6.51%
170.31
256.39
2020
6
3.48%
176.23
257.80
2020
7
5.89%
186.61
259.10
2020
8
-0.63%
185.44
259.92
2020
9
1.73%
188.65
260.28
2020
10
3.95%
196.10
260.39
2020
11
4.26%
204.46
260.23
2020
12
2.80%
210.17
260.47
2021
1
2.49%
215.41
261.58
2021
2
0.82%
217.18
263.01
2021
3
6.02%
230.26
264.88
2021
4
0.76%
232.01
267.05
2021
5
1.81%
236.21
269.20
2021
6
3.07%
243.46
271.70
2021
7
2.19%
248.78
273.00
2021
8
-0.08%
248.57
273.57
2021
9
0.45%
249.69
274.31
2021
10
4.74%
261.54
276.59
2021
11
0.27%
262.23
277.95
2021
12
-2.05%
256.85
278.80
2022
1
-2.90%
249.39
281.15
2022
2
-0.89%
247.17
283.72
2022
3
0.12%
247.46
287.50
2022
4
-7.87%
227.98
289.11
2022
5
-3.37%
220.30
292.30
2022
6
0.46%
221.32
296.31
2022
7
6.45%
235.59
296.28
2022
8
-7.28%
218.45
296.17
2022
9
-3.09%
211.69
296.81
2022
10
5.29%
222.88
298.01
2022
11
0.01%
222.91
297.71
2022
12
1.38%
225.97
296.80
2023
1
3.15%
233.08
299.17
2023
2
-2.59%
227.06
300.84
2023
3
4.00%
236.13
301.84
2023
4
0.74%
237.87
303.36
2023
5
4.94%
249.63
304.13
2023
6
3.88%
259.31
305.11
2023
7
-1.00%
256.72
305.69
2023
8
-0.95%
254.27
307.03
2023
9
-3.04%
246.55
307.79
2023
10
4.60%
257.89
307.67
2023
11
5.18%
271.24
307.05
2023
12
2.91%
279.14
306.75
2024
1
4.20%
290.86
308.42
2024
2
3.28%
300.41
310.33
2024
3
-1.01%
297.38
312.33
2024
4
2.52%
304.86
313.55
2024
5
5.34%
321.15
314.07
Click to show 102 more rows
Remember, returns are based on the average closing price across the entire month. Some losses are offset by dividend returns.
Dollar-cost averaging
Dollar-cost averaging is an alternative to investing the full lump-sum of $100.00 up-front. Instead, the capital is invested over a period of time.
Consider a strategy in which $100.00 was invested in the S&P 500 over a period of no more than 24 months beginning in 2015. This would result in a final amount of $307.52, including dividend reinvestments. In this particular case, dollar-cost average returns are less than the returns of a lump-sum investment (which ends with $321.15).
Year
Month
Contribution ($)
Amount ($)
2015
1
4.16
4.27
2015
2
4.16
8.43
2015
3
4.16
12.69
2015
4
4.16
17.01
2015
5
4.16
21.07
2015
6
4.16
25.20
2015
7
4.16
28.65
2015
8
4.16
31.32
2015
9
4.16
37.00
2015
10
4.16
42.36
2015
11
4.16
46.00
2015
12
4.16
46.94
2016
1
4.16
50.81
2016
2
4.16
58.46
2016
3
4.16
64.38
2016
4
4.16
68.33
2016
5
4.16
73.25
2016
6
4.16
79.96
2016
7
4.16
85.12
2016
8
4.16
88.88
2016
9
4.16
92.56
2016
10
4.16
97.88
2016
11
4.16
106.06
2016
12
4.32
111.95
2017
1
-
114.84
2017
2
-
116.85
2017
3
-
116.67
2017
4
-
118.64
2017
5
-
120.75
2017
6
-
121.94
2017
7
-
122.24
2017
8
-
124.27
2017
9
-
127.66
2017
10
-
129.69
2017
11
-
133.43
2017
12
-
139.92
2018
1
-
135.88
2018
2
-
135.97
2018
3
-
133.71
2018
4
-
136.33
2018
5
-
139.21
2018
6
-
141.41
2018
7
-
144.88
2018
8
-
147.31
2018
9
-
141.64
2018
10
-
138.70
2018
11
-
130.98
2018
12
-
133.26
2019
1
-
141.03
2019
2
-
143.77
2019
3
-
149.13
2019
4
-
146.84
2019
5
-
148.90
2019
6
-
154.60
2019
7
-
149.76
2019
8
-
154.38
2019
9
-
154.39
2019
10
-
161.24
2019
11
-
165.22
2019
12
-
170.75
2020
1
-
170.96
2020
2
-
138.62
2020
3
-
144.60
2020
4
-
153.12
2020
5
-
163.08
2020
6
-
168.75
2020
7
-
178.70
2020
8
-
177.57
2020
9
-
180.64
2020
10
-
187.78
2020
11
-
195.78
2020
12
-
201.25
2021
1
-
206.27
2021
2
-
207.96
2021
3
-
220.49
2021
4
-
222.16
2021
5
-
226.18
2021
6
-
233.12
2021
7
-
238.22
2021
8
-
238.02
2021
9
-
239.09
2021
10
-
250.44
2021
11
-
251.10
2021
12
-
245.95
2022
1
-
238.81
2022
2
-
236.68
2022
3
-
236.96
2022
4
-
218.30
2022
5
-
210.95
2022
6
-
211.93
2022
7
-
225.59
2022
8
-
209.18
2022
9
-
202.71
2022
10
-
213.42
2022
11
-
213.45
2022
12
-
216.38
2023
1
-
223.19
2023
2
-
217.42
2023
3
-
226.11
2023
4
-
227.78
2023
5
-
239.04
2023
6
-
248.30
2023
7
-
245.82
2023
8
-
243.48
2023
9
-
236.09
2023
10
-
246.95
2023
11
-
259.73
2023
12
-
267.29
2024
1
-
278.52
2024
2
-
287.66
2024
3
-
284.76
2024
4
-
291.92
2024
5
-
307.52
Click to show 102 more rows
Data Sources
The information on this page is derived from Robert Shiller's book, Irrational Exuberance and the accompanying dataset, as well as the U.S. Bureau of Labor Statistics' monthly CPI logs.
Note that S&P index value for the current quarter is based on a moving average of closing prices, per Robert Shiller's methodology. The inflation data used is based on annual CPI averages.
Ian Webster is an engineer and data expert based in San Mateo, California. He has worked for Google, NASA, and consulted for governments around the world on data pipelines and data analysis. Disappointed by the lack of clear resources on the impacts of inflation on economic indicators, Ian believes this website serves as a valuable public tool. Ian earned his degree in Computer Science from Dartmouth College.
