As of 05/20/2022
  Indus: 31,262 +8.77 +0.0%  
  Trans: 13,491 +51.76 +0.4%  
  Utils: 991 +1.46 +0.1%  
  Nasdaq: 11,355 -33.88 -0.3%  
  S&P 500: 3,901 +0.57 +0.0%  
YTD
-14.0%  
-18.1%  
 +1.0%  
-27.4%  
-18.1%  
  Targets    Overview: 05/15/2022  
  Up arrow33,500 or 30,500 by 06/01/2022
  Up arrow14,700 or 12,400 by 06/01/2022
  Up arrow1,050 or 940 by 06/01/2022
  Up arrow12,800 or 11,000 by 06/01/2022
  Up arrow4,150 or 3,700 by 06/01/2022
CPI (updated daily): Arrows on 4/21/22
As of 05/20/2022
  Indus: 31,262 +8.77 +0.0%  
  Trans: 13,491 +51.76 +0.4%  
  Utils: 991 +1.46 +0.1%  
  Nasdaq: 11,355 -33.88 -0.3%  
  S&P 500: 3,901 +0.57 +0.0%  
YTD
-14.0%  
-18.1%  
 +1.0%  
-27.4%  
-18.1%  
  Targets    Overview: 05/15/2022  
  Up arrow33,500 or 30,500 by 06/01/2022
  Up arrow14,700 or 12,400 by 06/01/2022
  Up arrow1,050 or 940 by 06/01/2022
  Up arrow12,800 or 11,000 by 06/01/2022
  Up arrow4,150 or 3,700 by 06/01/2022
CPI (updated daily): Arrows on 4/21/22

Bulkowski on the Optimum Trading Hold Time

 

Some statistics have been updated to 4/18-19/2022.

This article discusses how long you need to hold onto a stock to make a profit, based on the performance of a market index.

 

Picture of my dog

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
Daily53%5 Years83%
Weekly56%6 Years86%
Monthly59%7 Years90%
1 Year71%8 Years91%
2 Years79%9 Years92%
3 Years83%10 Years92%
4 Years84%  

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.

2022 Update

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.

Table 2: Performance Over Time
Class Daily  Weekly  Monthly  Yearly 
 Dow industrials53%56%59%68%
 Nasdaq composite 56%57%60%74%
 S&P 500 index54%57%61%73%
 463 stocks51%53%56%64%
 Day trade 463 stocks50%   

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, under-performed 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 year-to-year comparison in Table 2.

Table 3: Overlapping Monthly Periods
Class 1 Year  2 Yrs  3 Yrs  4 Yrs  5 Yrs  10 Yrs 
 Dow industrials: Data starts 10/1/192867.9%73.5%77.3%78.6%80.4%87.9%
 Nasdaq: Data starts 2/5/197176.4%81.9%83.2%82.5%86.5%94.5%
 S&P 500: Data starts 1/3/195074.4%82.2%84.2%83.9%83.0%91.8%
 463 stocks65.0%68.9%71.7%73.7%75.9%83.7%

-- Thomas Bulkowski

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