As of 12/20/2024
Indus: 42,840 +498.02 +1.2%
Trans: 15,892 +32.54 +0.2%
Utils: 986 +14.76 +1.5%
Nasdaq: 19,573 +199.83 +1.0%
S&P 500: 5,931 +63.77 +1.1%
|
YTD
+13.7%
0.0%
+11.9%
+30.4%
+24.3%
|
 44,200 or 41,750 by 01/01/2025 16,100 or 17,700 by 01/01/20251,050 or 975 by 01/01/202520,500 or 19,300 by 01/01/20256,100 or 5,775 by 01/01/2025 |
As of 12/20/2024
Indus: 42,840 +498.02 +1.2%
Trans: 15,892 +32.54 +0.2%
Utils: 986 +14.76 +1.5%
Nasdaq: 19,573 +199.83 +1.0%
S&P 500: 5,931 +63.77 +1.1%
|
YTD
+13.7%
0.0%
+11.9%
+30.4%
+24.3%
| |
|
44,200 or 41,750 by 01/01/202516,100 or 17,700 by 01/01/20251,050 or 975 by 01/01/202520,500 or 19,300 by 01/01/20256,100 or 5,775 by 01/01/2025 | ||
Initial release: 7/20/2018.
This article discusses discoveries in overhead resistance and stock performance I found while researching round numbers.
I found where price crossed a decade number (10, 20, 30, and so on), moving higher compared to the prior month, and measured how far price moved in the following week to two months.
I included only bull market data starting from January 1990 and lasting to July 2018. Here's what I found.
In an email, Harry Holt asked about round numbers and said he has had success trading options using a setup he describes as:
When a stock has never been above $90 in it's life, and it finally breaks through the resistance level at $90, most of the time, it will make it to $100. (Or $99.90 <grin>) Like it's draw[n] up there by a magnet. So I buy a short dated, in the money call when it crosses $92, and set the broker's software to sell the call when the stock gets to $98. So I might scalp $300 on a $500 investment in less than two weeks.
I decided to test this to see what I could discover about his setup.
I used 509 stocks with data starting from January 1, 1990 and extending to July 18, 2018, logging 18,929 trades. Not all stocks covered the entire range. I also removed the two bear markets from the data (From 3/24/2000 to 10/10/2002 and 10/12/2007 to 3/6/2009), so the results include only bull market data.
I started logging data with daily high prices of $10, in multiples of $10 (that is, if the daily high price crossed 10, 20, 30, ... 200). Also, if price dropped below a $10 multiple by at least 5%, and climbed back above a $10 multiple, then I considered that a new trade.
For example, if the high price moved from 9.79 to 10.11, I'd log it as crossing the $10 threshold. If the stock then dropped to 9.49 and returned above 10, I'd log another trade.
Once the stock crossed a $10 threshold, I measured how far the daily high price moved over time (1-3 weeks, 1 month, 6 weeks, and 2 months), logging the highest high over that interval.
Only stocks rising when they crossed the threshold were counted. I did this by comparing the current high price with one 21 price bars previous (about 1 month prior). If today's high was above a month earlier, then I considered the stock in an uptrend. It might not be, but the comparison seemed to work well.
I also kept track of the all-time high, which is the highest high before price made a decade cross. That told me if there was overhead resistance setup by prior price movement.
For example, if price reached an all-time high of $109 and price now crossed above $110, there would be no overhead resistance (because price is making new highs). However, if the all-time high was $109 and price now crossed from 89 to 90, then there would be overhead resistance because the all-time high (109) was above 90.
In the following tables, the percentage values are not the value at the end of the holding period (1 week, 2 weeks, and so on). Rather, they are the highest high reached during the period.
What does that mean? For example, Say price climbed above the $10 threshold on Monday. On Tuesday, it reached a high of $11 and trended lower from there, closing on Friday at $9. Instead of averaging $9 with the other trades with hold times of one week, I averaged the highest price during the period ($11 in this case).
Why? Because I wanted to capture how well you can do over time. Thus, if you told your broker to sell a call option if the stock reached $11 during the week, you would likely have had your trade executed. Selling the call options one week later (Friday in this case), meant selling the option when the stock was at $9.
I show the results in three tables of numbers. Sorry for that, but it's important. Why? Because if you're going to buy a call at $110 when price just crossed that threshold, it's important to know how far price may rise over the next week to two months. So I show all decade values from $10 to $200.
Definitions: OR means a stock had Overhead Resistance setup by price which was higher than the current price sometime in the past. NOR means No Over Resistance (the stock is making new all-time highs)
| OR | NOR | Minimum | OR | NOR | Minimum | |||
| Decade | Sum | Sum | Samples | Decade | Sum | Sum | Samples | |
| $10 | 66% | 56% | 445 | $110 | 28% | 28% | 95 | |
| $20 | 49% | 45% | 519 | $120 | 33% | 21% | 76 | |
| $30 | 37% | 45% | 461 | $130 | 53% | 22% | 60 | |
| $40 | 35% | 35% | 435 | $140 | 26% | 22% | 41 | |
| $50 | 35% | 35% | 351 | $150 | 28% | 23% | 32 | |
| $60 | 33% | 29% | 278 | $160 | 29% | 25% | 40 | |
| $70 | 32% | 31% | 228 | $170 | 28% | 26% | 28 | |
| $80 | 27% | 27% | 193 | $180 | 23% | 23% | 27 | |
| $90 | 28% | 23% | 153 | $190 | 27% | 20% | 22 | |
| $100 | 37% | 29% | 127 | $200 | 41% | 16% | 12 |
The table on the right shows the sum of the rows of the following two tables. This table emphasizes two findings. First, stocks perform better when overhead resistance is present.
Second: Stocks priced at $20 or below outperform higher priced issues. This second finding is something I've known for years and have proven it in other tests.
For example, look at decade 10. That row represents the performance of stocks whose high price crossed the $10 threshold (rising trend only). The sum of the six time periods (from 1 week to 2 months) was 66%. That was the performance of stocks which had overhead resistance. Compare that with stocks breaking out to new highs. The sum of the six periods was 56% with a minimum of 445 samples (max of 1,474 samples).
The $10 row says that stocks breaking out to new all-time highs underperform those encountering overhead resistance. I've not heard of that before. It suggests that momentum investing (buy high, sell higher) is inferior to bottom fishing (buy low, sell high). That's not necessarily true because you can buy high and sell higher even though overhead resistance exists throughout the trade. Still, the finding is surprising and it's regardless of the stock price (at least between $10 and $200).
Look at the totals. In the left half of the table, where samples remain above 100, the two best performing prices are $10 (66% gain) and $20 (49% gain).
If you compare the results of each row with overhead resistance or not, the performance of stocks encountering overhead resistance beat those with no overhead resistance in all but one contest ($30).
The following table shows the performance of stocks sorted by thresholds of $10 to $200.
For example, say you want to buy a call option on a stock whose high price just crossed above $30, in a bull market. This is not the first time the stock has been that high (meaning, there's overhead resistance because price has been higher than $30 in the past). How much can you expect to make in the coming 2 months?
Scan down the table and find the $30 row. If your stock behaves like the average stock I looked at, you can make from 3% to 10% over the next week to 2 months.
| Gain | Gain | Gain | Gain | Gain | Gain | OR | Minimum | |
| Decade | 1 Week | 2 Weeks | 3 Weeks | 1 Month | 6 Weeks | 2 Months | Sum | Samples |
| $10 | 4% | 7% | 9% | 12% | 15% | 19% | 66% | 445 |
| $20 | 3% | 5% | 7% | 9% | 11% | 14% | 49% | 519 |
| $30 | 3% | 4% | 5% | 7% | 8% | 10% | 37% | 461 |
| $40 | 2% | 4% | 5% | 6% | 8% | 10% | 35% | 435 |
| $50 | 2% | 4% | 5% | 6% | 8% | 10% | 35% | 351 |
| $60 | 2% | 4% | 5% | 6% | 7% | 9% | 33% | 278 |
| $70 | 2% | 3% | 5% | 6% | 7% | 9% | 32% | 228 |
| $80 | 2% | 3% | 4% | 5% | 6% | 7% | 27% | 193 |
| $90 | 2% | 3% | 4% | 5% | 6% | 8% | 28% | 153 |
| $100 | 2% | 4% | 6% | 7% | 8% | 10% | 37% | 127 |
| $110 | 2% | 3% | 4% | 5% | 6% | 8% | 28% | 95 |
| $120 | 3% | 4% | 5% | 6% | 7% | 8% | 33% | 76 |
| $130 | 3% | 6% | 7% | 9% | 12% | 16% | 53% | 60 |
| $140 | 2% | 3% | 4% | 5% | 5% | 7% | 26% | 41 |
| $150 | 2% | 3% | 4% | 5% | 6% | 8% | 28% | 32 |
| $160 | 2% | 3% | 4% | 5% | 6% | 9% | 29% | 40 |
| $170 | 2% | 4% | 4% | 4% | 6% | 8% | 28% | 28 |
| $180 | 2% | 3% | 3% | 4% | 5% | 6% | 23% | 27 |
| $190 | 2% | 3% | 3% | 5% | 6% | 8% | 27% | 22 |
| $200 | 3% | 4% | 6% | 7% | 9% | 12% | 41% | 12 |
Similarly, the following table shows the results over time of stocks I looked at that were making new all-time highs.
For example, stocks which crossed $20 for the first time in their life, showed gains averaging 3% in the first week, and 13% after a hold time of 2 months.
The sample size is robust, too, at 519.
| Gain | Gain | Gain | Gain | Gain | Gain | Minimum | NOR | |
| Decade | 1 Week | 2 Weeks | 3 Weeks | 1 Month | 6 Weeks | 2 Months | Samples | Sum |
| $10 | 4% | 6% | 8% | 10% | 12% | 16% | 445 | 56% |
| $20 | 3% | 5% | 6% | 8% | 10% | 13% | 519 | 45% |
| $30 | 3% | 5% | 6% | 8% | 10% | 13% | 461 | 45% |
| $40 | 2% | 4% | 5% | 6% | 8% | 10% | 435 | 35% |
| $50 | 2% | 4% | 5% | 6% | 8% | 10% | 351 | 35% |
| $60 | 2% | 3% | 4% | 5% | 7% | 8% | 278 | 29% |
| $70 | 2% | 3% | 5% | 6% | 7% | 8% | 228 | 31% |
| $80 | 2% | 3% | 4% | 5% | 6% | 7% | 193 | 27% |
| $90 | 2% | 2% | 3% | 4% | 5% | 7% | 153 | 23% |
| $100 | 2% | 3% | 4% | 5% | 6% | 9% | 127 | 29% |
| $110 | 2% | 3% | 4% | 5% | 6% | 8% | 95 | 28% |
| $120 | 2% | 2% | 3% | 3% | 5% | 6% | 76 | 21% |
| $130 | 1% | 2% | 3% | 4% | 5% | 7% | 60 | 22% |
| $140 | 1% | 2% | 3% | 4% | 5% | 7% | 41 | 22% |
| $150 | 2% | 2% | 3% | 4% | 5% | 7% | 32 | 23% |
| $160 | 2% | 3% | 3% | 5% | 5% | 7% | 40 | 25% |
| $170 | 2% | 3% | 3% | 4% | 6% | 8% | 28 | 26% |
| $180 | 2% | 2% | 3% | 4% | 5% | 7% | 27 | 23% |
| $190 | 2% | 2% | 3% | 4% | 4% | 5% | 22 | 20% |
| $200 | 2% | 2% | 2% | 3% | 3% | 4% | 12 | 16% |
Here's the link to a spreadsheet (.xlsx ~7.7mb) of results collected for this test. The results are at the top of the sheet.
The sheet provides additional information. It tells the average and median times for price to peak for each period. Roughly, the stocks reach the highest high in the period about halfway. For example, price reaches the high during the first week at day 4. In the 2-month period, price peaks on day 34, on average. That helps to know if you're trading options. Of course, your results may vary.
-- Thomas Bulkowski
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