As of 07/10/2020
Indus: 26,075 +369.21 +1.4%
Trans: 9,312 +172.05 +1.9%
Utils: 791 +17.12 +2.2%
Nasdaq: 10,617 +69.69 +0.7%
S&P 500: 3,185 +32.99 +1.0%

YTD
8.6%
14.6%
10.0%
+18.3%
1.4%

24,000 or 27,800 by 07/15/2020
8,400 or 10,000 by 07/15/2020
825 or 700 by 07/15/2020
10,800 or 10,000 by 08/01/2020
2,900 or 3,300 by 07/15/2020

As of 07/10/2020
Indus: 26,075 +369.21 +1.4%
Trans: 9,312 +172.05 +1.9%
Utils: 791 +17.12 +2.2%
Nasdaq: 10,617 +69.69 +0.7%
S&P 500: 3,185 +32.99 +1.0%

YTD
8.6%
14.6%
10.0%
+18.3%
1.4%
 
24,000 or 27,800 by 07/15/2020
8,400 or 10,000 by 07/15/2020
825 or 700 by 07/15/2020
10,800 or 10,000 by 08/01/2020
2,900 or 3,300 by 07/15/2020
 
I looked at 10 years of my trades and found that 2x volatility for stocks in the range of $0.90 to $1.90 (a volatility reading, not a stock price) gives the best results. A stock too volatile or one showing too little volatility hurts trading performance.
Volatility is the average of the highlow price range of each day over the prior month (21 entries) multiplied by 2. I multiplied volatility by 2 to keep it consistent with how I use it for stops, but it is otherwise unnecessary.
I measured the 2x volatility of each stock on the buy date and logged how the trade performed. I used data from 1/1/1997 to 6/22/2007. This range included both bull and bear markets. I created three results: the entire 10.5year period, 5, and 5.5year periods with nearly equal number of trades (over 100 for both 5 and 5.5year periods). The first period from 1/1/1997 to 1/1/2002 incorporated most of the bear market of 3/24/2000 to 10/10/2002, as posted by the S and P 500 index.
Using the median 2x volatility of $1.13 showed that high volatility trades made 5.25 times as much money as low volatility ones.
The median 2x volatility was $1.29 and high volatility trades beat low volatility trades by 2.69 to 1.
The median 2x volatility was $1.04 and high volatility trades beat low volatility ones by 2.58 to 1.
The in sample and out of sample results were similar. Trades using high volatility stocks resulted in performance that was about 2.5 times more profitable than low volatility ones, despite the in sample results incorporating most of a bear market.
Next, I did a frequency distribution of volatility versus performance and found that volatility too high also hurt performance. The chart shows the sum of profits or losses from trades with low and high volatility readings over the 10year period. The thinking is that there is a range of 2x volatility that improves the performance of both low and high volatility trades. The area between the red lines is where 2x volatility results in good profit per trade. Performance deteriorates outside of the red lines.
The results described here are for stocks only. Check the results of your trades and see what range works best for you.
 Thomas Bulkowski
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