Selecting candidates for Swing Trading positions is difficult. I have found that finding moat-type businesses make the best initial candidates. Good financial underpinnings are essential. Joseph Belmonte of Buffett and Beyond has developed a screening tool based on Clean Surplus ROE(Return on Equity). His conclusion is that “portfolios made of stocks with high Clean Surplus ROE’s outperform all other portfolios”. An example is portrayed below. Salesforce (CRM) first qualified with a higher than average Clean Surplus ROE during 2016 when the shares were trading between $70 and $80. 
Closing prices are as of the close on Friday, November 5, 2021. First, find the candidates and then use weekly technicals to find the overall trend. Use the daily as a trend decision trigger. The weekly signaled a buy decision at the end of June 2021. That is, only trade LONG from that date. The daily concurred with a long position on October 13, 2021.
Swing Trading
Another PerfectStorm example COST
The following is another example of waiting for the long-term signal, in this case weekly. When that signal is LONG, then if and when the shorter-term time frame is also LONG, jump aboard.
The signal in COST from April 9, 2021, has been LONG only. A corresponding LONG signal was signaled on June 23 and the next day COST opened at 393. A close signal was signaled on September 20, and the opening the next day was 456. Approximately a 16% return in about 3 months.
Please refer to my previous post on REGN for more detail.
Relative Strength
In the many past posts, I have recommended that to be successful in swing trading, one has to be aware of the individual securities relative strength as it compares to some index of its peers.
The following chart is an example of OIH which is the oil VanEck oil services ETF. I have compared this ETF to SPY, which represents the Standard & Poors 500 index.
The prices are as of the close yesterday, January 12, 2021.
The rules are very simple, and the action indicated by the up and down arrows reflects the result of following the rules.
- Buy when the target security is stronger, on a relative strength basis than the index.
- Buy ONLY when the target is stronger, has positive momentum, and the index is also going up.
- Close the position when any condition is violated. Shown by blue vertical lines.
- The rules apply to shorting when the actions are the opposite of the buy rules.
High Volatility versus Low Volatility
There is a fascinating article in today’s Wall Street Journal in its quarterly “Investing In Funds & ETFs on page R3.: The Time to High-Beta?
Once a Quarter.
The thesis is that new research conducted says that: “high -beta stocks tend to outperform in just one week per quarter. Only in that week, therefore, does it make sense that traders bet on high-beta stocks. That week occurs in the quarterly earnings season.
The article goes on to that to test the theory, one would invest, during the first week of earnings season in a high-beta stock ETF while shorting an equal dollar amount of a low ETF.
Their example in the article regarding a high-beta fund is the Invesco High Beta ETF. (SPHV) That ETF contains the 100 highest beta stocks of the S&P 500 index. The 100 selected have the “highest sensitivity to market movements, or beta, over the past 12 months. The fund and the index are rebalanced and reconstituted quarterly in February, May, August, and November.”
The example of low beta is the Invesco S&P Low Volatility ETF(SPLV) which contains 100 S&P 500 stocks with the lowest realized volatility over the past 12 months. It then weighs each stock based on its volatility(well, lack thereof).
I assume it is rebalanced every month, but was unable to speak to anyone at Invesco to give me that information.
The article begs the question of whether a strategy of ALWAYS having a position in being long/short SPHV versus the reverse in SPLV would be successful?
The following illustration says YES!
The green vertical lines indicate long SPHB and short SPLV. The red vertical lines indicate long SPLV and short SPHB.
Swingtrader Suite for Day Trading
Many times I have been asked if the PerfectStorm strategy that works so well for swing trading has any use for the thousands of traders who day trade. Perhaps the following illustrations will be helpful. All graphs are as of the close of business of Friday, June 5, 2020.
The above picture is the daily results of BA versus SPY.
The top is BA, and the next security is SPY. The next line represents the relative strength of BA versus SPY. When the line is going up and GREEN, BA is stronger than SPY. When the line is going down and RED, SPY is stronger than BA.
The Vertical lines represent, when GREEN, that BA should be bought. When the vertical line is BLUE, the trade should be closed. When the vertical line is RED, BA should be short. Many hedge funds, when the trade indicates, will be short the opposite security, that is, when indicated long BA, they will be short SPY and vice versa.
The next picture is of BA versus SPY on a twenty-minute basis. I have left off the vertical signal lines, but a careful analysis will dictate the long/short position.
The next picture is of BA versus SPY on a two-minute chart.
There are thousands of “pairs” that can be traded in the same manner. Just ask Medallion Fund, or Citadel, or World Quant or the many other Quant funds.
I can be reached for further information at rfeit@msn.com or (516) 902-7402
Apple
Apple shares declined on news that sales of the iPhone were declining because of the downturn of consumer spending in China. Whether you believe that spin or realize that the costs of the new models do not offer a serious reason to upgrade the older phones is of little concern. Whatever the real reason, Apple stock went down.
Apple is one of the most widely held and more importantly one of the more actively traded stocks in the world. Share and options are traded with very small bid-asked spreads.
From a swing trading perspective, the following attached charts should be of some interest.
Daily prices are at 8:00 on Thursday, July 11 , 2019:
Relative Strength with Momentum
Readers of the swingtrader.com blog will have noticed that the overall theme that I have proposed is that to be a successful swing trader one has to understand the principle of relative strength with positive momentum.
I originally proposed the concept in an e-book that I had offered in 2000. Because of my lack of web marketing, it was only downloaded a few times, although it was free.
Over the past few months, I have received multiple offerings of momentum services that offer similar strategies that I have been discussing on my swingtrader.com, relativevalue.com and perfectstormtradingstrategy.com websites for the past ten years or more.
One of the offers was a service, using only four ETF’s, that the provider stated would constantly beat the market.
Over the next few weeks and months, I am going to have on the swingtrader.com website an example, updated weekly or daily if necessary, of my 4 ETF strategy. If followed, the strategy should emulate the best of the services being offered. It is certainly not a recommendation of what to buy or sell, but an example of what can be accomplished by using a relative strength with momentum strategy. It is for illustrative purposes ONLY!
The four ETF’s chosen are the result of my own research. They should portray a representation of the changes in market sector rotation. The four ETF’s have a positive and negative correlation with each other. The ETF’s are displayed here on daily charts.
I will update the daily charts when appropriate.
Remember, Green=XLE, Energy. Red=XLY, Consumer Discretionary. Light Blue=XLU, Utilities. Yellow=XTN, Transportation.
Latest update July 11, 2019, 8:00 AM
Dividend Aristocrat strategy
Many traders only look for high probability trades without making sure that there is also a high expectancy outcome.
A great example is so-called Russian roulette. Load a six capacity revolver with five bullets leaving one chamber empty. Spin the revolver mechanism and put the gun to your head. Pull the trigger. The player has an 83% chance of not killing him or herself. High probability, 83% versus 13%, but the 13% is a total loss. Not a few ticks or pennies, but a total loss with no possibility of recovery, ever!
Expectancy knows that regardless of the probability, there is a high level of payout that outweighs the losses.
The successful trader realizes that a system of small probability can be very successful if the average trade has a very high payout for wins versus little loss if the trade doesn’t work out. The best strategy would have a high probability AND a high expectancy.
For example, if one flips a coin a few hundred times and receives $300 each time the coin shows ‘heads’ and loses $100 each time the coin shows ‘tails’, the normal distribution of approximately 50% would earn the coin flipper a high expected return. The coin flipper would have high expected return with anything better than a 25% heads versus tails distribution.
An example of a high probability, high expectancy swing trader strategy is derived from an article in Seeking Alpha, December 23, 2016, “The 10 Best Dividend Aristocrats for 2017 And Beyond”. The piece refers to 10 stocks from a wide range of industries which have increased their dividends for at least 25 consecutive years. “Market Watch” reported on September 9, 2016, that Dividend Aristocrats stocks almost doubled the returns of the S&P stocks in 2016. Many other studies of dividend aristocrats show similar results over much longer time periods.
Below are the 10 Dividend Aristocrats mentioned in the Seeking Alpha article. Once again, the relative momentum is color coded to represent the issues that are also color coded.
It is expected that performance will be better if one were to chose only the issues that are exhibiting only positive(above the zero line, purple) momentum.
Higher probability with a higher expected outcome.
VFC=VFC Corp, ABT=Abbott Labs, JNJ=Johnson & Johnson, CAH=Cardinal Health, ABBV=AbbVie.
GWW=Grainger , MDT=Metronic, WMT=Walmart, BDX=Becton Dickinson, HRL=Hormel Foods.
Color coding on bottom chart refers to the color coding of the securities. Yellow=Yellow, etc.
Prices as of the close May 29, 2019