As of 01/27/2023
Indus: 33,978 +28.67 +0.1%
Trans: 14,483 +191.14 +1.3%
Utils: 968 +1.08 +0.1%
Nasdaq: 11,622 +109.30 +0.9%
S&P 500: 4,071 +10.13 +0.2%

YTD
+2.5%
+8.1%
+0.0%
+11.0%
+6.0%

34,900 or 33,150 by 02/01/2023
15,100 or 13,500 by 02/01/2023
1,040 or 950 by 02/01/2023
12,400 or 11,000 by 02/15/2023
4,100 or 3,800 by 02/01/2023

As of 01/27/2023
Indus: 33,978 +28.67 +0.1%
Trans: 14,483 +191.14 +1.3%
Utils: 968 +1.08 +0.1%
Nasdaq: 11,622 +109.30 +0.9%
S&P 500: 4,071 +10.13 +0.2%

YTD
+2.5%
+8.1%
+0.0%
+11.0%
+6.0%
 
34,900 or 33,150 by 02/01/2023
15,100 or 13,500 by 02/01/2023
1,040 or 950 by 02/01/2023
12,400 or 11,000 by 02/15/2023
4,100 or 3,800 by 02/01/2023
 
Some statistics have been updated to 4/1819/2022.
This article discusses how long you need to hold onto a stock to make a profit, based on the performance of a market index.
The following results use data ending April 2010.
To make money, how long should you hold onto a stock? I'll give you the probabilities in a moment, but here's how I did it. I downloaded the daily, weekly, and monthly price data from yahoo finance using the S&P 500 index and then went to work. The data ranges from January 3, 1950 to April 13, 2010. For the computation, I used overlapping periods. For one year, as an example, I determined whether price closed higher from April 1, 2010 to May 1, 2009. Then I used the next month, March 1, 2010 to April 1, 2009, and so on. I summed the number of up closes compared to the number of samples and found the percentage.
In other words, I counted the number of times price closed higher for each period. The table below shows what I found.
Period  Percentage Up Closes  Period  Percentage Up Closes 
Daily  53%  5 Years  83% 
Weekly  56%  6 Years  86% 
Monthly  59%  7 Years  90% 
1 Year  71%  8 Years  91% 
2 Years  79%  9 Years  92% 
3 Years  83%  10 Years  92% 
4 Years  84% 
For example, if you bought the S&P 500 index and sold it a day later, you would have a 53% chance of making money  all else being equal. If you hold onto the index for a week, the probability of a gain rises to 56%. Hold for 5 years, and the probability rises to 83%.
If you are having problems making money in this market, then consider holding longer. Or just buy low and sell high.
For Table 2, I counted the number of up closes (ties not allowed) for the Dow industrials, Nasdaq composite, S&P 500 index and 463 stocks (the stocks I follow daily) over various time periods, ranging from a day to a year. For example, if the Dow industrials closed higher the next day compare to the prior day, I counted that. The numbers show how often the Dow closed higher over the period studied, from October 1928 to April 2022.
If you want to buy and hold a position, select the Nasdaq. That index closed higher most often (winning or tying in 3 of 4 columns).
The table shows that the longer you hold a position, the more likely it is to be profitable. If you compare the S&P in this table (ending April 2022) with the prior one (ending April 2010), it made more sense (and cents!) to hold longer (meaning the numbers in the below table are higher than the prior table).
At the bottom of the table, I counted how often a stock closed higher than it opened and found it to be 50%. This would be a day trade.
Class  Daily  Weekly  Monthly  Yearly 
Dow industrials  53%  56%  59%  68% 
Nasdaq composite  56%  57%  60%  74% 
S&P 500 index  54%  57%  61%  73% 
463 stocks  51%  53%  56%  64% 
Day trade 463 stocks  50% 
Table 3 measures performance slightly differently. I chose a series of overlapping periods of x years long to measure performance over time. For example, I compared the opening price of February and compared that to the closing price of January a year later (that is, February 28, 2000 to January 31, 2001). If price climbed over that time, I logged it. Then I advanced one month and did the same computation, March to February, and so on until end of data. I did the same computation for the other time periods.
What I found was that the success rate of holding an index or individual stock increased over time (mostly). The Nasdaq stumbled in years 3 and 4 (dropping from 83.2% to 82.5%) and the S&P dropped in years 3 through 5.
Notice that the 463 stocks, as a group, underperformed the indices. I expected the numbers to be closer to the S&P's results.
The difference between Table 2s Yearly column and Table 3s 1 Year column is the overlapping monthly periods (used in Table 3) versus a yeartoyear comparison in Table 2.
Class  1 Year  2 Yrs  3 Yrs  4 Yrs  5 Yrs  10 Yrs 
Dow industrials: Data starts 10/1/1928  67.9%  73.5%  77.3%  78.6%  80.4%  87.9% 
Nasdaq: Data starts 2/5/1971  76.4%  81.9%  83.2%  82.5%  86.5%  94.5% 
S&P 500: Data starts 1/3/1950  74.4%  82.2%  84.2%  83.9%  83.0%  91.8% 
463 stocks  65.0%  68.9%  71.7%  73.7%  75.9%  83.7% 
 Thomas Bulkowski
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