TAG, You’re It! Rotation Away From Semiconductors Benefiting These Stocks

One hallmark of secular bull markets is rotation. When leading stocks, sectors, and industry groups falter, there needs to be others that grab the baton and help to keep the bull market intact. Semiconductors ($DJUSSC) have been the clear leader in the stock market for years, but especially since the end of October 2023, when the group embarked on its most powerful rally of the 21st century. Below is a 25-year chart of the DJUSSC. Pay particular note to the bottom panel, which reflects a 170-day rate of change (ROC), or roughly 8 months. Compare this most recent 8-month rally to other 8-month periods throughout this century:

The 8-month ROC recently hit 115%, which is the biggest rally EVER on this index. And if you look at the price chart, we should at least CONSIDER the possibility that this is a parabolic top. This is how these form – with tremendous amounts of positivity and what could end up being unsustainable revenue and EPS growth. The entire group is being priced off of record revenue and earnings growth and for perfection. Should traders even get a HINT that future growth might be lower than what we’ve been experiencing the past couple quarters, the semiconductor trade could be weak for months, possibly quarters.

In a secular bull market, however, it’s rotation that keeps our major indices in uptrends. Where might the new leadership emerge from if semiconductors do in fact weaken? Well, I think it’s already showing here:


A breakout has already been made here. Yes, we’re a bit overbought, but nothing like how overbought technology (XLK) has been. One industry that typically revs up when the XLC is hot is internet ($DJUSNS). This group remains in the midst a major rally:


The red-shaded area highlights the fact that, on relative basis, internet hasn’t been leading the past couple months. The breakout this week, though, might indicate renewed relative strength. It’s also noteworthy that since the financial-crisis low in 2009, internet stocks have been leaders during July, rising in 14 of the past 15 years:

The average July return has been 6.8%, more than double any other calendar month since 2009.

There’s one other key sector, consumer discretionary (XLY), that could play a big leadership role over the second half of 2024. This group has been a drag on U.S. equities, but it really hasn’t been felt that much, because the XLK has been so strong. NOW is the time, however, when U.S. equities could be looking for rotation to and leadership from this sector:


Relative strength has begun to turn higher over the past two weeks and this relative strength could be fueled much further by an absolute breakout in the price of the XLY near the 184-185 level.

It’s been amazing what a stock like NVIDIA Corp (NVDA) has done for semiconductors, technology, and our major indices. But if NVDA struggles on a relative basis, which it certainly deserves, I see 3 critical stocks not named Apple (AAPL) and Microsoft (MSFT) that could swoop in and “save the day” for our major indices, especially the NASDAQ 100.

TAG, You’re It!

Ok, so if we’re going to need a replacement, temporary or otherwise, for a leadership stock like NVDA, which stock(s) might we look to for future leadership?


Relative to its peers, GOOGL hit rock bottom in early March. Since then, GOOGL has been significantly outperforming its internet peers and is currently awaiting another one. From mid-May to mid-June, GOOGL didn’t go anywhere. Semiconductors were flying, but GOOGL took a back seat. Now that it’s latest breakout to all-time highs have occurred, it certainly appears as though GOOGL is well-prepared to take the baton for the next leg of this secular bull market.


I don’t know if there’s a better stock anywhere right now. AMZN is absolutely one of my favorites. Discretionary stocks have been lagging most of the year and AMZN is the top holding in the XLY. AMZN just broke out, after consolidating, on excellent volume and I expect the stock to be a leader during the 2nd half of 2024. AMZN’s best calendar month during this secular bull market (since 2013) has been July – check it out:

AMZN has climbed more often in November, but its actual average monthly performance in July (+7.3%) easily surpasses all other months. So we have technical conditions turning bullish just as we move into, arguably, AMZN’s best month.


Ok, I get it. TSLA’s been disappointing for sure. But there are improvements on the chart that suggest TSLA could be on the verge of a much bigger run. We do need to see one more key price level cleared to give me more confidence of a big rally:

I see rather significant improvement in momentum (PPO), volume trends, and relative strength. TSLA, relative to its auto peers, just hit nearly a 4-month high. This, combined with other technical improvements, tells me that we could just be getting started here. I do want to see gap resistance near 208 cleared, because after that, I don’t see any major resistance until 265 or so.

There’s one more thing to like. Over the past 6 years, June, July, and August have posted AMAZING average returns. This time of the year is when TSLA has really shown extreme absolute and relative strength. Check out this seasonality chart:

The average return during June, July, and August has been a STAGGERING and BLISTERING 43%!!! That’s the AVERAGE since 2019. So if TSLA is going to get the job done, history tells us that NOW is the time.

Remember, the sustainability of secular bull markets is not much different than the game we all played as kids. Hey AMZN, GOOGL, and TSLA! You’re IT!!!!

I published my first StockCharts YouTube video in quite awhile and it’s great to be back! I spent a lot of time discussing the beauty of secular bull markets and how rotation keeps them alive, providing areas to keep a close eye on for future leadership. Please be sure to check out the video HERE and also be sure to hit that “Like” button and “Subscribe” to the StockCharts YouTube channel! I’d really appreciate the support!

Happy trading!


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Investing with the Trend: Conclusions

Note to the reader: This is the twenty-fifth and final in a series of articles I’m publishing here, taken from my book, “Investing with the Trend.” Hopefully, you will find this content useful. Market myths are generally perpetuated by repetition, misleading symbolic connections, and the complete ignorance of facts. The world of finance is full of such tendencies, and here, you’ll see some examples. Please keep in mind that not all of these examples are totally misleading — they are sometimes valid — but have too many holes in them to be worthwhile as investment concepts. And not all are directly related to investing and finance. Enjoy! – Greg

Technical analysis used to be greeted with as much enthusiasm as Jeffrey Skilling addressing the Better Business Bureau, and was often referred to as a black art. It still is often called charting, which is not unlike referring to space flight as flying. Fortunately, those times have passed. The following quote from the Reverend Dr. Martin Luther King could easily be applied to a rules-based trend-following investment model, substituting model for man (and it for he).

The ultimate measure of a man is not where he stands in moments of comfort and convenience, but where he stands at times of challenge and controversy. — Dr. Martin Luther King

Near the beginning of this book, I stated that this was not a storybook, but a compilation of ideas, concepts, and research from almost 40 years in the markets, primarily as a technical analyst. We started out by uncovering numerous facts that are routinely used in modern finance that simply do not meet the test of rigorous mathematics or logical scrutiny. Many things in finance are truly fiction or terribly flawed. Next, we moved into a section that dealt with market facts, which were basically about how markets work and after covering the fiction and flaws, appeared relatively simple but were based on sound principles of logic and reason. A large section of the book introduced research on risk, and hopefully redefined what risk is. Research that used a simple process of filtered waves and time to determine if markets trended was presented across a wide range of data sets.

The final part of the book, after hopefully convincing you that markets are unpredictable and that there are risk reduction techniques such as trend following that will make you a successful investor over the long term, introduced a rules-based trend-following model affectionately called “Dance with the Trend.” Many examples of how to measure what the market was doing, with variable risk categories based on that weight of the evidence, were presented. Security ranking and selection methods were introduced along with a sample set of rules and guidelines to follow. In the end, hopefully, you realized that a rules-based model, along with the discipline to follow it, will help remove the human subjectivity and those horrible human emotions that we all have.

The story about Abraham Wald’s work as a member of the Statistical Research Group during World War II can shed some light into money management (widely disseminated as Abraham Wald’s Memo). Wald was tasked with damage assessments to aircraft that returned from service over Germany, and determined which areas of the aircraft structure should be better protected. He found that the fuselage and fuel systems of returned planes were more likely to be damaged than the engines. He made a totally unconventional assessment: Do not focus on the areas that sustained the most damage on these planes that returned, but focus on the essential sections that came back relatively undamaged, such as the engines. By virtue of the fact the planes returned, the heavily damaged areas did not contribute to the loss of the aircraft, but losing the engine would, and therefore would not return. Hence, focus on more armor around the engines. For an airplane in battle, protect the essential parts and it will fly again.

Investing is not unlike an airplane in battle: Protect the assets from destruction, such as large losses (drawdown), and the investor will live to invest again. Most of modern finance is focused on the nonessential parts.

Existing theories about the behavior of stock prices are remarkably inadequate. They are of so little value to the practitioner that I am not even fully familiar with them. The fact that I could get by without them speaks for itself. — George Soros, Alchemy of Finance, 1994

As stated previously and often, my critique of much about modern finance is without offering any solutions. When someone complains to me about something, my usual response is that they need to offer a solution to validate their complaint. I am guilty of violating that principle in this book. Gaussian statistics are used extensively in finance because anyone who has taken mathematics, engineering, finance, or economics has learned them. Plus, they are relatively simple to understand and, while they have shortcomings, they do provide some understanding about distributions of market data, but never about the extremes.

There are statistical techniques that deal with this shortcoming simply referred to as power laws. A number of papers present sufficient evidence to this concept. An Internet search for “power laws in finance” will provide you with a host of works. You will quickly see that Benoit Mandelbrot started something.

For those who still believe that markets do not trend, here is a simple attempt to move you away from that belief. Trends exist because of the herding characteristics of humans. For example, limit orders and stop loss levels are usually set based on an incremental measure from a recent price. Robert Prechter provides an exceptional paper on this subject.

Financial Advice

It is far from the purpose of this book to get into financial advice, other than to blatantly state, “If you cannot control your emotions when making investment decisions, then seek help.” Remember, experts cannot predict the market any better than anyone else, but they can offer a systematic approach to investing. They will assist in your switching/abandoning of strategies for whatever reason and truly help with your behavior when it comes to the markets. Usually, they will also help your accountability, so that you continue to make periodic contributions to your portfolio. Outside objectivity is also a benefit, as the advisor can slow you down on your dash to follow the herd, and cause you to stick to your plan.

The sad part is that most investors will wait too late in life to realize they need help. Wanting to act rational because you know you should, and doing so, are often far apart. Here are some simple questions to ask a potential advisor: how do you manage risk, and how do you make investment decisions? Look for answers that involve a process.

Remember: It is not important to be right every time, but it is important to be right over time.

A return of your money; or a return on your money.

Performance tells you nothing about the risks assumed to attain that performance, risks that tend to show up later. It is better to manage risk than to just measure it.

According to William Bernstein, successful investors need:

  1. An interest in the process.
  2. An understanding of the laws of probability and a working knowledge of statistics.
  3. A firm grasp of financial history.
  4. The emotional discipline to execute their planned strategy faithfully, come hell, high water, or the apparent end of capitalism as we know it.

A Compilation of Rules and Guidelines for Investors

Over the years, I have collected lists of rules, guidelines, steps, and so on written by various individuals for various reasons. Most of them were created by folks after they had spent decades in the business and were sharing some things they not only learned over that time, but also believed.

Robert Farrell ‘s 10 Rules for Investing

Robert Farrell was Merrill Lynch’s technical analyst for many years. Here are his 10 rules for investing:

  1. Markets tend to return to the mean over time. When stocks go too far in one direction, they come back. Euphoria and pessimism can cloud people’s heads. It’s easy to get caught up in the heat of the moment and lose perspective.
  2. Excesses in one direction will lead to an opposite excess in the other direction. Think of the market baseline as attached to a rubber string. Any action too far in one direction not only brings you back to the baseline, but leads to an overshoot in the opposite direction.
  3. There are no new eras—excesses are never permanent. Whatever the latest hot sector is, it eventually overheats, mean reverts, and then overshoots. Look at how far the emerging markets and BRIC nations ran over the past six years (as of 2013), only to get cut in half. As the fever builds, a chorus of “this time it’s different” will be heard, even if those exact words are never used. And of course, it—Human Nature—never is different.
  4. Exponential rapidly rising or falling markets usually go further than you think, but they do not correct by going sideways. Regardless of how hot a sector is, don’t expect a plateau to work off the excesses. Profits are locked in by selling, and that invariably will lead to a significant correction, which eventually comes.
  5. The public buys the most at the top and the least at the bottom. That’s why contrarian-minded investors can make good money if they follow the sentiment indicators and have good timing. Watch Investors Intelligence (measuring the mood of more than 100 investment newsletter writers) and the American Association of Individual Investors survey.
  6. Fear and greed are stronger than long-term resolve. Investors can be their own worst enemy, particularly when emotions take hold. Gains “make us exuberant; they enhance well-being and promote optimism,” says Santa Clara University finance professor Meir Statman. His studies of investor behavior show that “Losses bring sadness, disgust, fear, regret. Fear increases the sense of risk, and some react by shunning stocks.”
  7. Markets are strongest when they are broad and weakest when they narrow to a handful of blue-chip names. Hence, why breadth and volume are so important. Think of it as strength in numbers. Broad momentum is hard to stop, Farrell observes. Watch for when momentum channels into a small number of stocks (“Nifty 50” stocks).
  8. Bear markets have three stages—sharp down, reflexive rebound, and a drawn-out fundamental downtrend. I would suggest that as of August 2008, we are on our third reflexive rebound—the January rate cuts, the Bear Stearns low in March, and now the Fannie/Freddie rescue lows of July. Even with these sporadic rallies end, we have yet to see the long drawn out fundamental portion of the Bear Market.
  9. When all the experts and forecasts agree—something else is going to happen. As Stovall, the S&P investment strategist, puts it: “If everybody’s optimistic, who is left to buy? If everybody’s pessimistic, who’s left to sell?” Going against the herd, as Farrell repeatedly suggests, can be very profitable, especially for patient buyers who raise cash from frothy markets and reinvest it when sentiment is darkest.
  10. Bull markets are more fun than bear markets, especially if you are long only or mandated to be fully invested. Those with more flexible charters might squeak out a smile or two here and there.

James Montier (GMO)

Risk isn’t a number and it isn’t volatility, it’s the permanent impairment of capital.

Volatility creates the opportunity.

Leverage cannot turn a bad investment into a good one, but it can turn a good one bad.

Leverage limits staying power.

Often financial innovation is often just leverage in thinly veiled disguise.

James Montier ‘s Seven Immutable Laws of Investing

  1. Always insist on a margin of safety.
  2. This time is never different.
  3. Be patient and wait for the fat pitch.
  4. Be contrarian.
  5. Risk is the permanent loss of capital, never a number.
  6. Be leery of leverage.
  7. Never invest in something you don’t understand.

My Rules

  1. Turn off the TV and stop surfing the Internet for advice (stop the noise).
  2. Develop a simple process, one that you can explain to anyone (mine is trend following).
  3. Create a security selection process based on momentum.
  4. Devise a simple set of prudent and reasonable rules and guidelines.
  5. Follow your process with discipline; without it, you will fail.
  6. If you do not have the discipline to do this, seek professional help from someone who does.
  7. Do not be upset with yourself if you do not have the discipline at times; be proud of yourself for recognizing it.
  8. Do not confuse luck with skill.
  9. Listen and learn from the market—it is always right.
  10. Read this list often.

It is never the indicator or the model; it is the user of those tools who is probably at fault.

“If I’ve learned a little

My Grandad told me so

It ain’t so much the fiddle,

It’s the man who holds the bow.”

Co-written by my favorite Texas musicians, John Arthur Martinez and Mike Blakely

Secular Markets and the Efficiency Ratio

I want to show you that a number of the indicators/measures discussed in this book have other uses. For example, the Efficiency Ratio mentioned in Rules-Based Money Management – Part 4 used to select the most efficient buy candidates can also be used to confirm market action, such as in Secular markets. Figure 17.1 shows the weekly Dow Industrials with the secular markets identified (only secular bears identified with no identification for the secular bulls) and the four-year Efficiency Ratio. In other words, how efficiently did the market move over a four-year period? You can see that secular bull markets are much more efficient (higher ER) than secular bear markets. This result is not surprising, but at least is now somewhat quantified.

The Rules-Based Trend-Following Model in October 1987

Okay, I always get asked this — how did the Dance with the Trend model perform on Black Monday, October 1987?

First of all, this model was not in existence until the early 1990s, but I have data back to the late 1970s to show how it would have performed. As you can see, the S&P 500 is the top plot in Figure 17.2, and the Weight of the Evidence is in the lower plot. The Weight of the Evidence began to decline the first week in September and was below 50% by September 10, 1987. While stops in the zone below 50% are extremely tight, it is highly probable that any money management at this time would be fully defensive in cash or cash equivalents. And this is over a month prior to the crash. Notice how just prior to the crash the Weight of the Evidence popped up slightly, then dropped quickly prior to the crash.

The Flash Crash of May 6, 2010

Big market declines rarely occur while the market is making new highs. When one is a trend follower, it means they never get out at the top and never get in at the bottom. A fact of life and one that is only apparent in the remarkably beautiful world of hindsight. Often, I get a question along the lines of how do you handle panic selloffs, such as 1987 and the May 2010 Flash Crash. The year 1987 was explained previously. The Flash Crash on May 6, 2010, was a really scary day. The good news is that the market had peaked on April 23, 2010, and had been in a downtrend for two weeks prior to the Flash Crash, which I believe most have forgotten.

In Figure 17.3, the April 23 peak is denoted by point A and the Flash Crash of May 6 by point B, nine trading days later. The Weight of the Evidence dropped from 100 into the second zone two days prior to May 6. Recall that when a zone changes, so do the stops on all holdings. This tightening of the stops took the holdings down to only one that remained on the morning of May 6. Recall also that all selling is done only when the individual holding hits its stop. The last holding was sold the morning of May 6 because it hit its stop.

Luck? Of course there was some luck involved. If the crash had occurred a few days earlier, most of the holdings would have gotten clobbered. However, the trend peaked nine days before the Flash Crash and the system worked.

This event prompted some research into market action prior to crash days. The results were strong evidence that rarely do markets crash while making new highs. February 27, 2007, was about the only time it happened, as of 2013.

In today’s complex markets, money management must remain focused on process, which helps control their investment philosophy and the nature of their client base. Controlling the process of investing is absolutely critical for long-term success in the markets. And my final quote from James Montier: “when athletes were asked what went through their minds just before the Beijing Olympics, the consistent response was a focus on process, and not outcome.” Don’t forget that.

Final Observations

I want to avoid, even though it is tempting, repeating much of what I have elaborated on in this book, but some of the pontifications are so important in my opinion that I’m going to repeat a few. The goals of this book are numerous.

  • Understand how markets work and how they have worked in the past.
  • Understand the plethora of information that exists in modern finance that is just wrong.
  • Understand how the tools of modern finance work and their shortcomings.
  • Understand that you, as a human being, have terrible natural investment tendencies.
  • Understand what risk is.
  • Understand that most markets trend and those trends can be identified.
  • Understand that there are ways to use technical analysis to invest successfully over the long term.
  • And finally, understand that there are many techniques for investing, but until you grasp full control over your emotions and have exemplary discipline, you will probably fail. Failure is how one can learn—hopefully.

Although this has been alluded to throughout this book, I’m going to put it as simply as I can. A rules-based trend follower never asks the questions: Which way is the market going to go? Are we near a top, a bottom, and so on? A trend follower doesn’t need to know and shouldn’t actually care other than inherent curiosity. We know that increasing capital by participation in up markets is favorable, there is still some joy associated with being totally defensive during down markets while most others are being clobbered. Although that may sound cruel to some, it alleviates some of the frustration of usually underperforming in volatile bull moves. It also falls nicely into a number of the behavioral traits outlined in The Hoax of Modern Finance – Part 8.

I have injected many personal opinions in this book, most of which are opinions formed by learning about the markets over the past 40 years, and not all those periods were good — in fact, many were not good. I paid high tuition to learn some things. Once I learned to get my gut feelings out of the process, things got steadily better. I have challenged many things in modern finance and a few things in technical analysis. Again, just opinions, as I cannot offer formal proof either way. There are two recommended reading lists in the appendix if you are just starting out, or if you are an old timer, maybe you will enjoy those recommendations also. And now:

Dance with the Trend!

Thanks for reading to the end! Want to own a physical copy? The book is for sale here.

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Investing with the Trend: Appendix

Note to the reader: This is a set of appendices for a series of articles I’m publishing here, taken from my book, “Investing with the Trend.” Hopefully, you will find this content useful. Market myths are generally perpetuated by repetition, misleading symbolic connections, and the complete ignorance of facts. The world of finance is full of such tendencies, and here, you’ll see some examples. Please keep in mind that not all of these examples are totally misleading — they are sometimes valid — but have too many holes in them to be worthwhile as investment concepts. And not all are directly related to investing and finance. Enjoy! – Greg

Appendix A: Passive vs. Active Management

Passive management means that the investor or manager does not change the portfolio components, except for occasional (usually based on the calendar) rebalancing to some preconceived ratio of stocks and bonds. Passive is prosaic, and often is designed just to replicate the market. An active investor or manager is one who attempts to invest in top-performing stocks or assets using some methodology to assist in that process. Often, it is difficult to tell the difference between some active managers and their benchmark. They have become benchmark huggers, often because of career risk. This is not a complete list, but does address the most popular strategies and while there is some overlap in some strategies, that is not unexpected.

Examples of Passive

Buy and hold. The concept of long-only investments is usually based on fundamental research. For decades, this was the much touted method to long-term success in the stock market, and, in fact, for most people, that is probably correct, especially if much of their holding period was during a secular bull market. Value investing is generally attributed to this type of investing. Sadly, buy and hold can be devastating during secular bear markets. Five of the strong arguments for buy and hold are:

  1. The market goes up over the long run.
  2. Equity returns will keep you ahead of inflation.
  3. The market always recovers from bear markets.
  4. Commissions, fees, and taxes are kept low.
  5. No one can time the market’s up and down moves.

This book is about why those arguments are false. Hopefully when you read them, you were aware that they are not strong arguments at all, but merely selling points for those who benefit from your decision to buy and hold.

Strategic asset allocation. A very popular process, which basically infers that the investor or manager sets up a portfolio of assets based on their individual risk to return measures. This concept has been the tenant of modern portfolio theory and, like buy and hold, works quite well in secular bull markets. The really sad part is that buy-and-hold probably will outperform strategic asset allocation in those secular bull markets. Strategic asset allocation almost always involves periodic rebalancing to the predetermined ratio. Personally, I find it hard to adapt to a strategy that sells its best performing assets and buys more of the worst. Peter Mauthe says strategic asset allocation does not have a tactic. Mauthe goes on to say that nothing gets better with neglect. My tire pressure is low, so I can be passive or active in attending to them. Health, relationships, customer relations, nothing I know of gets better with neglect. So why would my investments be any different?

Portfolio rebalancing seems flawed from its basic premise: selling the best performing assets and buying more of the worst performing assets. Or, selling the best and buying the worst hoping that mean reversion kicks in before you kick off.

Dollar cost averaging. The act of investing a fixed dollar amount on a periodic basis. This was addressed in more detail in The Hoax of Modern Finance – Part 3: Fictions Told to Investors.

Examples of Active

Momentum. A concept that selects the top-performing assets based on their price performance. While this sounds good, the process does involve determining the period of time to use to measure that performance and usually involves some sort of ranking capability.

Sector rotation. Somewhat similar to a momentum strategy, but restricted to market sectors and sometimes includes the industry groups. This technique is probably easier to put into practice, as it involves fewer issues to monitor and measure. One of the problems with this strategy is that it cannot protect you from bear markets, only reduce the pain. If this strategy is long only and the goal is to remain fully invested, then it was described in The Hoax of Modern Finance – Part 11: Valuations, Returns, and Distributions.

Alternatives. These strategies usually come to fruition during the mid-to-later years of secular bear markets, when investors realize that passive investing is no longer working. Futures, hedging, options, and a whole host of derivative products are used across the board in the alternatives category.

Absolute return. This falls under the Alternatives header and generally relates to strategies that are totally unconstrained in long, short, hedges, leveraged, and so on. They are not tied to any benchmark, hence, absolute return vs. relative return.

Tactical asset management. This was listed last as this is essentially what this book is all about. Tactical asset management infers that the investor or manager is unconstrained not only in which assets, but when to invest in them.

Table A.1 gives brief comments on the various strategies. With the benefit of hindsight, the market can seem predictable; however, many of these strategies are more useful in describing the market’s past than in anticipating its future.

Note: Active management is quite broad. At one end, it can be a manager who rebalances a portfolio once a year. This approach rarely uses stop loss protection and is always 100% invested, which means it does not ever hold cash or cash equivalents. At the other end of the spectrum is the tactical unconstrained manager, similar to my “Dancing with the Trend” strategy. This is an approach that utilizes stop loss protection, treats cash and cash equivalents as an asset class, and is determined to protect the downside.

Appendix B: Trend Analysis Tables

See the tables in Market Research and Analysis – Part 3: Market Trend Analysis.

Appendix C: Market Breadth

In 2006, McGraw-Hill published my book, The Complete Guide to Market Breadth Indicators. Breadth was an area I had spent a great deal of time on over the past 30-plus years. Breadth was almost totally ignored by the technical analysis community as most of the popular books on technical analysis usually only devoted a chapter to the subject of breadth. The book was in actuality a giant research project for me, one that took well over a year to complete even though I had been collecting breadth data and information since the 1980s. I tried to include every known breadth indicator or relationship in existence. I think I almost did that. The information following is from that book, and what I feel is the absolute most important part of the book. Enjoy!

Why Breadth?

  • It takes advantage of inefficient markets. If investors are irrational and prone to excessive optimism with the latest hot stocks and excessive pessimism with those issues that have suffered recently, then market capitalization weighting reflects those inefficiencies from its very definition of shares times price. Breadth, which is equal weighted, does not have that problem.
  • Avoid heavy concentration into a few stocks. Market capitalization weighting often causes a large portion of a portfolio to be concentrated in only a few issues—concentration risk. Breadth totally avoids this.
  • Get more exposure to small capitalization stocks. Merely by the concept of capitalization weighting, small stocks will have a smaller effect on the portfolio. True, they are generally considered riskier, but they have also had historically stronger performance. Breadth deals with large and small capitalization stocks equally.

Breadth analysis is like quantum mechanics, it does not predict a single definite result, instead it predicts a number of different possible outcomes, and tells us how likely each one will be. Breadth directly represents the market, no matter what the indices are doing. It is the footprint of the market and the best measure of the market’s liquidity.

Most breadth indicators are at best, coincident indicators, and usually somewhat lagging. Any of the indicators that are smoothed with moving averages are certainly lagging. Lagging means that the indicator is only telling you what is happening after it has happened. Lagging is not a problem, once you realize that picking exact tops and bottoms in the market is better left to gamblers. Th e confirmation of lagging indicators, however, is very important. Some breadth indicators, especially some of the ratios, can offer leading indications based upon the identification and use of previous levels or thresholds that are consistent with similar market action. An oscillator that reached a threshold level, either positive or negative, with consistency relative to market tops and bottoms is such an indicator. Many breadth indicators work in this manner.

A Familiar Breadth Indicator

Most investors are familiar with the long-running Friday night show, Wall Street Week, on Public Broadcasting hosted by Louis Rukeyser, who, every week would comment on his elves (his term for technical analysts) and the Wall Street Week Index. What you may not have known is that this index was a composite of 10 indicators, three of which were breadth-based. Robert Nurock, long-time panelist and Chief Elf, created it. Robert Nurock was the editor of the Astute Investor, a technical newsletter for many years.

The Arms Index was one of the indicators in the Wall Street Week Index. A 10-day moving average was used with bullish signals given when it was about 1.2 and bearish when it was below 0.8. The advances minus the declines were used over a 10-day period and bullish signals were from the point where the index exceeds 1,000 to a peak and down to a point 1,000 below the peak. Bearish signals were just the opposite. The third breadth indicator used was the new highs compared to the new lows. For bullish signals an expansion of the 10-day average of new highs from less than 10 up to 10-day average of new lows. Similarly, bearish signals were an expansion of 10-day average of new lows from less than 10 until it exceeds the 10-day average of new highs.

Breadth Components

Breadth components are readily available from newspapers, online sources, and so on and consist of daily and weekly statistics. They are: Advances, Declines, Unchanged, Total Issues, Up Volume, Down Volume, Total Volume (V), New Highs, and New Lows.

From one day to the next, any issue can advance in price, decline in price, or remain unchanged. Also any issue can make a new high or a new low. Here are more specific definitions:

  • Advancing Issues or Advances (A)—Stocks that have increased in price from one day to the next, even if only by one cent, are considered as advancing issues or advances.
  • Declining Issues or Declines (D)—Stocks that have decreased in price from one day to the next are considered declining issues or declines.
  • Unchanged Issues or Unchanged (U)—Stocks that do not change in price from one day to the next are considered unchanged issues or unchanged.

Note: Prior to July 1997, stock prices were measured in eighths of a point, or about 12.5 cents as the minimum trading unit. In July 1997 the NYSE went from using eighths to sixteenths. This made the minimum trading unit about 6.25 cents. On January 2, 2002, they went to a decimalization pricing that made the minimum trading price equal to one cent (a penny).

  • Total Issues (TI)—This is the total of all issues available for trading on a particular exchange. If you added the advances, declines, and unchanged issues together it would equal the total issues.
  • Advancing Volume or Up Volume (UV)—This is the volume traded on a day for each of the stocks that are advancing issues. It is the total volume of all the advances.
  • Declining Volume or Down Volume (DV)—This is the total volume for all the declines for a particular day.
  • Total Volume (V)—This is the total volume of all trading for a particular day. Total volume is the sum of Up Volume, Down Volume, and Unchanged Volume. To find Unchanged Volume subtract the sum of Up Volume and Down Volume from the Total Volume. Total volume is not generally considered a breadth component, but is many times used in a ratio with the up or down volume to alleviate the increase in trading activity over long periods of time.
  • New High (H)—Whenever a stock’s price reaches a new high price for the last 52 weeks it is termed a new high. New Low (L)—Whenever a stock’s price reaches a new low price for the last 52 weeks it is termed a new low.

Note: The NYSE new highs and new lows are now computed on a fixed 52-week moving time window starting on January 1, 1978. Before that, the new highs and new lows were computed on a variable time window of anywhere from two and a half months to 14 and a half months. This rendered the new high new low data prior to 1978 almost useless, and certainly confusing to use.

Breadth vs. Price

Breadth does not consider the amount or magnitude of price change. It also does not consider the number of shares traded (volume). And it does not consider the shares outstanding for individual stocks. Most stock market indices, such as the New York Stock Exchange Composite Index, the Nasdaq Composite Index, S&P 500 Index, the Nasdaq 100, and so on, weigh each stock based on its price and number of outstanding shares. This makes their contribution to the index based on their value and are some.times called market-value weighted indices or capitalization weighted indices. Because of this (at this writing), Microsoft, Qualcomm, Intel, Cisco, eBay, Nextel, Dell, Amgen, Comcast, and Oracle account for more than 40 percent of the Nasdaq 100 Index and its ETF, QQQQ. Ten percent of the components account for 40 percent of the price movement of the index. This can lead to an incorrect analysis of the markets, especially if some of these large cap stocks experience price moving events. Many times the reference to the large caps issues is that of the generals, while the small caps are referred to as the soldiers. As you will find out, the generals are not always the leaders.

Breadth treats each stock the same. An advance of $10 in Microsoft is equally represented in breadth analysis as the advance of two cents of the smallest, least capitalized stock. Breadth is truly the best way to accurately measure the liquidity of the market.

The Difference Between Daily and Weekly Breadth Data

You just cannot add up daily breadth data for the week to get the weekly data. Here is a scenario that will explain why.

Here’s the narrative: An advance or decline for the week should be based on its price change from the previous Friday close to the close of the current week. It has absolutely nothing to do with the daily data. Take a single stock; its previous Friday close price was $12. On Monday, it was up $1 to $13. It went up a dollar each day for the first four days of the week and closed on Thursday at $16. However, on Friday, it dropped $5 to $11. For the week it was down $1, which would be one decline for the week. However, on a daily basis, it accounted for four advances and one decline, or a net three advances.

John McGinley, past editor of Technical Trends and sidekick of the late Arthur Merrill, sent this note: “I strongly believe that in creating weekly figures for the advance declines, one does not use the published weekly data for they disguise and hide what really went on during the week. For instance, imagine a week with 1,500 net advances one day and the other four days even. The weekly data would hide the devastation which occurred that dramatic day.”

Advantages and Disadvantages of Using Breadth

Consider a period of distribution (market topping process) such as 1987, 1999, 2007, 2011, and so on. As an uptrend slowly ends and investors seek safety, they do so by moving their riskier holdings, such as small-cap stocks, into what is perceived to be safer large-cap and blue chip stocks. This is certainly a normal process and one that can’t be challenged. However, the mere act of moving from small- to large-cap stocks causes the capitalization-weighted (Nasdaq Composite, New York Stock Exchange Index, S&P 500) and price-weighted (Dow Industrials) to move higher simply because of the demand for large-cap issues. Breadth, on the other hand, begins to deteriorate from this action. It is said that breadth arrives at the party on time, but always leaves early. Another analogy is that the troops are no longer following the generals. There is a nice chart showing this concept in Figure 13.9.

Breadth data seems to not be consistent among the data providers. If you think about it, if a stock is up, it is an advance for the day, so why is there a disparity? Some data services will not include all stocks on the exchange. They will eliminate preferred issues, warrants, rights, and so on. This is fine as long as they tell you that is what they are doing. In the past few years, the number of interest-sensitive issues on the New York Stock Exchange has increased so that they account for more than half of all the issues. These issues are preferred stocks, closed-end bond funds, and electric utility stocks, to mention a few.

Many analysts such as Sherman and Tom McClellan, Carl Swenlin, and Larry McMillan use common-stocks-only breadth indicators. Richard Russell refers to it as an operating company-only index. Using stocks that have listed options available is another good way to avoid the interest-sensitive issues, since most stocks that have listed options are common stocks.

Each breadth indicator seems to have its benefits and its shortcomings. The fact that breadth measures the markets in a manner not possible with price is the key element in these conclusions. Breadth measures the movement of the market, its acceleration and deceleration. It is not controlled by General Electric, Microsoft, Intel, Cisco, General Motors, and so on, any more than it is controlled by the smallest capitalized stock on the exchange.

Table C.2 shows the breadth components needed for calculation of the indicator, whether the indicator is better for picking market bottoms, market tops, trend analysis, and whether it is better for short- or long-term analysis. Keep in mind that short-term is generally some period of time less than five-to-six months. Identification of a market bottom can be an event that can last only a few days or launch a giant secular bull market. In Table C.2, the terms short- and long-term refer to the frequency of signals as much as anything. A number of the long-term indicators are good for trend following; in Table C.2, if neither Bottoms nor Tops were checked, it was because the indicator is better at trend analysis.

Some indicators are better at Tops, Bottoms, and both, and, at different times, but are only identified by Bottoms and/or Tops below. Great effort was made to determine if one appeared to be better at one or the other. If no difference could be ascertained, they were reported as being good for both Bottoms and Tops. Please keep in mind the nature of market bottoms versus market tops. Bottoms are generally sharp and quick and usually much easier to identify, whereas market tops are usually long periods of distribution where most market indices rotate through their peaks at different times. You will notice that considerably more indicators are noted as being good at Bottoms than at Tops. Add to that the subjective interpretation of the various indicators, and the table that follows should be viewed as a beginning guide only.

Favorite Breadth Indicators

Here is a list of breadth indicators that I believe are good ones to follow. Some are for daily analysis and some are used merely to be kept aware of their indications. There are some really good breadth indicators that have made some very good market calls over the years—they are marked as awareness-only below. I try to avoid noisy indicators that require too much interpretation and very short term in nature.

New High New Low Validation Measure

During my research on breadth, I became acutely aware that most analysts treated new highs and new lows in the same manner as they did with advances, declines, up volume, and down volume. A terrible mistake, as I will attempt to explain. This will help validate and show how to interpret new high and new low data. If you consider the facts relating to new highs and new lows, you will see the necessity for this. A new high means that the closing price reached a high that it had not seen in the past year (52 weeks). Similarly, a new low is at a low not seen for at least a year. This indicator tries to identify when the new high or new low is determined to be good or bad using the following line of thinking.

Consider that prices have been in a narrow range for more than a year. Something then triggers an event that causes the market to move out of that trading range to the upside. This will immediately cause almost every stock that moves with the market to also become a new high. New highs are generally the force that keeps good up moves going. The new lows in this scenario will dry up, as expected. Now consider that the market has had a steady advance for quite some time. The number of new highs will generally continue to remain high as most stocks will rise with the market. Of course, there will be drops as the market makes corrections on its path to higher prices. When the number of new highs starts to dry up, you will probably notice that the number of unchanged issues starts to increase slightly, because a lot of stocks will just cease to participate in the continuing rise. New lows will not happen for some time because the market is just starting to form a top. The number of new lows will increase as the market forms its broad top, while the number of new highs gets smaller and smaller. It will be the time frame of this topping action that determines when the new lows will start to kick in. Remember, you cannot have a new low until an issue is at a new low price over the last year.

When the market declines and you start to see fewer new lows, it means the market is losing its downside momentum. Why is this so? It is because some issues have already bottomed and are not continuing to make new lows. This is tied to the rotational effect, sometimes caused by various market sectors hitting bottoms at different times. Figure C.1 is an attempt to show this visually. Up spikes (solid line) equal to +2 represent good new highs. Up spikes (dashed line) equal to +1 represent bad new highs. Similarly, down spikes (solid line) at –2 equates to good new lows and –1 (dotted line) equates to bad new lows. You might read that again, since it is not obvious. I wanted to keep the new highs as the up spikes and the new lows as the down spikes. Short up spikes are bad new highs, and short down spikes are bad new lows. Bad, in this case, means they did not conform to the theory talked about above.

In Figure C.1, the top plot is the NYSE Composite index, with a 252-day exponential average overlaid. The bottom plot is the new lows, the next to the bottom is the new highs, and the second from the top plot is the New High New Low Validation Measure. It is the plot that has the tooth-like moves both up and down. The top of the up moves is at a value of 2 and represents valid new highs. The bottom of the down moves is at –2 and represents valid new lows. The smaller up and down moves are at +1 and –1 and represent new highs and new lows, respectively, which are good, but not as good as the ones at +2 and –2. Although this is a great deal of information to put into a single chart in a black-and-white book, you can look at the validated periods and compare them to the top plot of the NYSE Composite and see that they do a really good job of pointing out new highs and new lows that are meaningful.

This method of trying to determine when the new highs and new lows are truly good ones involves the rate of change of the market, a smoothed value of each component relative to the total issues traded, and their relationships with each other. For example, if the market is in a rally (rate of change high) and the new highs are increasing, any new lows that appear are not good ones. Similarly, if the market is in a downtrend, with high negative rate of change, then any new highs that appear are not good ones. The use of the term good ones refers to whether they are valid to use in any new high-new low analysis.

Appendix D: Recommended Reading

There are many great books available in the field of technical analysis and finance. However, I’m going to keep the list short and focused. The bibliography contains many other wonderful books on technical analysis, finance, and behavioral analysis, but if I had to pick a library of only four books, this is it.

Getting Started List

  • Kirkpatrick, Charles D., and Dahlquist, Julie R., 2011, Technical Analysis, Pearson Education, Upper Saddle River, NJ.
  • Easterling, Ed., 2011, Probable Outcomes, Cypress House, Fort Bragg, CA.
  • Bernstein, Peter L., 1998, Against the Gods, John Wiley & Sons, New York.
  • Montier, James, 2010, The Little Book of Behavioural Investing, John Wiley & Sons, West Sussex, England.

Additional Recommended Reading

I’m not sure why I started this list, because there are so many great books on investing out there now that it is difficult to decide which to read. I guess I just answered my own dilemma, as I have read many, if not most, of them, and these are the ones I personally would recommend because they complement this book.

  • Pring, Martin J., 1985, Technical Analysis Explained, McGraw-Hill, New York.
  • Bernstein, Peter L., 1992, Capital Ideas, John Wiley & Sons, Hoboken, NJ.
  • Makridakis, Spyros and Hogarth, Robin, 2010, Dance with Chance, Oneworld Publications, Oxford, England.
  • Mandelbrot, Benoit, 2004, The (Mis)Behavior of Markets, Basic Books, New York.
  • Shefrin, Hersh, 2002, Beyond Fear and Greed, Oxford University Press, New York.
  • Solow, Kenneth R., 2009, Buy and Hold Is Dead Again, Morgan James Publishing, Garden City, NY. 
  • Tetlock, Phlip E, 2005, Expert Political Judgement: How Good Is It? How Can We Know?, Princeton University Press, Princeton, NJ.
  • Fox, Justin, 2009, Myth of the Rational Market, HarperCollins, New York.
  • Coleman, Thomas S., 2012, Quantitative Risk Management, John Wiley & Sons, Hoboken, NJ.
  • Weatherall, James O., 2013, The Physics of Wall Street, Houghton Mifflin Harcourt Publishing, New York.

Thanks for reading this far. The conclusion to this series will publish in one week. Can’t wait? The book is for sale here.

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Here Are 4 Steps To Improve Your Trading Process and Results

Let’s jump right in. For me, everything starts at the TOP. I take a top-down approach to trading. And when I say “the TOP”, I mean market direction.

Step 1: Is it a Bull or Bear Market?

Listen, this is a very easy step to me. Look at a LONG-TERM chart of the S&P 500. Are prices moving UP from left to right? Or are they moving DOWN from left to right? It’s that simple. Stop trying to figure out why it’s going up or down. Don’t interject your own personal biases into it. Just look at the chart and answer the question:

I have stripped out nearly all technical indicators. There’s no volume. There are no momentum indicators like the PPO, MACD, RSI, or Stochastic. There are no moving averages. This is nothing more than a 10-year weekly price chart of the S&P 500, NASDAQ 100, and the broader NYSE. What do you see as you look across this chart from left to right? Is there a debate here? The stock market has been moving higher for YEARS (with occasional weakness)!!!! If you find yourself constantly being in cash or, worse yet, trying to short sell stocks, because YOU think stocks are overvalued, you have missed out on creating enormous personal wealth. STOP doing that!

We are heavily influenced by listening to news, whether you believe so or not. I remember my parents talking about the enormous debt of the U.S. back in the 1970s and that discussion has never ended. Meanwhile, $1 invested in the S&P 500 on January 1, 1980, is now worth $50 (prior to adjusting for inflation). So the absolute FIRST STEP in becoming a better investor/trader is to understand that your odds of making money are MUCH, MUCH BETTER on the long side than on the short side. Shorting stocks should be considered very infrequently and only when the chart is moving DOWN from left to right. Calling for repeated tops in a bull market is financial suicide. The trend is your friend, right?

Step 2: Sectors, Industries, and Stocks Are Not Created Equal

The Semiconductors Index ($DJUSSC) is an industry group loaded with high-octane, growth companies. As our economy and GDP grow, many of these companies find very exciting growth opportunities and take full advantage of them. This allows the LEADERS within this rising group to post gains that make accumulating massive wealth in the stock market possible. But not every group is high-growth like the semiconductor group. Companies in those slower-growth areas will never post that type of sustainable earnings growth. Yet we put way too much faith that the short-term growth rate in other industries will evolve into long-term growth like the semiconductors. It simply doesn’t happen that way and we lose money waiting for it.

Let’s compare semiconductors to several other industry groups within the aggressive sectors (XLK, XLY, XLC, XLI, and XLF) over a 20-year period. The 9 “other” industries are software ($DJUSSW), specialty retailers ($DJUSRS), gambling ($DJUSCA), internet ($DJUSNS), broadcasting & entertainment ($DJUSBC), fixed line communications ($DJUSFC), airlines ($DJUSAR), insurance brokers ($DJUSIB), and banks ($DJUSBK). The chart below is a 20-year weekly chart and each industry is shown as a ratio chart, relative to the benchmark S&P 500. See if you notice differences:

Look at these 10 different industry group RELATIVE charts. If you were to trade a stock in one of these industry groups, would it matter to you which of the industry groups above that it belonged to?

If I looked at the above charts and I was contemplating a trade in one or more of them, the very first question I’d consider is “what’s my time frame?”. If I’m thinking about a long-term swing trade, I would very much prefer for the stock to be in one of those industry groups in BLUE above – those showing much better long-term track records. If I were to look at a trade in say gambling, it would very likely be a quick, short-term trade. And if I did let the stock run, because it was performing well, I’d absolutely want to keep a trailing stop in play. The falling relative strength lines tells me that money is rotating AWAY from this RED group and into groups like those above in BLUE.

So, short-term I could trade stocks in any of the 10 groups, but from a longer-term perspective, I’d clearly be much more interested in the BLUE groups that are uptrending vs. the benchmark S&P 500.

I think that makes common sense, but I would bet that most traders don’t consider this.

Step 3: Trade Leading Stocks

There are a number of ways to evaluate relative strength, but one simple way that’s already a part of the StockCharts.com trading platform is to view top SCTRs (acronym for StockCharts Technical Rank). Personally, I would only tend to use the SCTR if I was looking at very recent performance. If you study the formula for the SCTR calculation, you’ll quickly realize that none of the formula is based on performance beyond 5-6 months. It’s a very near-term relative strength indicator, but a powerful one nonetheless, especially for those that are trading momentum in the very near-term.

You can pull up ChartLists using the Summary view and add the SCTR column. For instance, on our Raised Guidance ChartList (RGCL) that we research for our EarningsBeats.com members, here is how I can look for internet stocks that have raised their guidance in the past quarter, while also listing their SCTR score in order from strong to weak:

Personally, I’d concentrate much more on trading the above stocks with SCTRs at or above 75 and ignoring the rest. Remember, leading stocks in leading industry groups. That’s how you’ll improve your trading success.

Step 4: Exercise Patience and Use Great Timing Techniques

An impatient trader that simply wants to have money invested at all times is generally a bad trader. Buy stocks at YOUR price, not the price market makers want you to buy. In my experience, “chasing” trending stocks has resulted in my biggest and quickest losses. Many times, a stock becomes a leading stock after an excellent quarterly earnings report that’s accompanied by a gap higher in price. Chasing such a stock can be a big problem, especially if that stock “fills its gap”, or returns to the prior closing price before the gap. We try to coach our members to “stalk” stocks. Find stocks you like and then wait, wait, and wait a little bit longer. Buy them at key price/moving average support with tighter stops. That won’t eliminate poor trades, but it’ll certainly reduce your risk at the time of purchase.

Conclusion: Examples

Every weekend (or nearly every weekend), I provide my Fab 5 on YouTube, which is essentially 5 trade setups. Keep in mind that the risk of any trades you make is yours and yours alone, but I believe if you time your trades similar to these setups, you’ll experience better trading results over time. Check out this video:

Fab 5: 5 Stocks You Should Be Stalking Right Now

If you like these setups and would like additional setups more often, please SUBSCRIBE to our FREE EB Digest newsletter with only your name and email address. We provide “Charts of the Day” 3 times per week and the newsletter is absolutely 100% free! You may unsubscribe at any time.

Have a great holiday-shortened week ahead and happy trading!


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Stock Market Ends Week on Optimistic Note, With a Few Surprises



  • The stock market started out slow, sold off, and then recovered some of those losses to end the week on an optimistic note.
  • Market internals continue to be strong indicating that the stock market has a bullish bias.
  • Several stocks made new highs including NVDA, FSLR, and DELL.

It was a roller-coaster week in the stock market, a reminder that, when markets are trading at their all-time highs, it pays to be cautious. Any negative news can trigger emotions, resulting in a domino effect reaction.

In the early part of the week, the stock market was pretty lethargic, with investors waiting for Nvidia’s earnings. When NVDA earnings were announced after the close on Wednesday, the stock price soared in after-hours trading. The upside move continued when the market opened on Thursday, with the stock price closing at a record high on Friday.

However, despite NVDAs’ rally, the rest of the market threw some surprises. On Thursday, there was a significant selloff, which threw many investors off. The broader equity indexes fell, as did precious metals.

The May Purchasers Manufacturing Index (PMI) came in higher than expected, which may have reminded investors that the strong economy could mean higher rates for longer. The FOMC minutes this week suggested that Fed members aren’t confident that inflation has come down enough to warrant rate cuts any time soon.

On Friday, the S&P 500 ($SPX) and Nasdaq Composite ($COMPQ) recovered some of Thursday’s losses. This was a surprise; you’d think the selloff would continue ahead of the Memorial Day weekend.

Follow the live chart!

Another interesting area is the price action in US Treasury yields, which seem to. be going through a consolidation pattern. Until they break out of this pattern, there’s no telling which way yields will go. The Fed is committed to bring inflation to 2%, but we don’t know how long it’ll take to get there.

CHART 1. 10-YEAR US TREASURY YIELDS IN CONSOLIDATION. Yields could break out in either direction. A lot depends on future economic data points. Chart source: StockCharts.com. For educational purposes.

A comforting thought is that the CBOE Volatility Index ($VIX) is low, indicating that investors aren’t fearful. This supports a bull market thesis. It’s challenging to forecast which direction the stock market will move, and we could see continued sideways movement for a while, especially after the FOMC minutes.

You can sense the presence of investor enthusiasm as stocks continue to reach all-time highs. Over 100 stocks hit an all-time high (check out the New All-Time Highs Predefined StockCharts scan). The New Highs-New Lows index ($NYHL) also shows more new highs than lows, although the number of new highs is not as high as it was in recent weeks (see chart below).

CHART 2. NEW HIGHS – NEW LOWS. The number of new highs is greater than the number of new lows. Chart source: StockCharts.com. For educational purposes.

A Few Stocks to Note

Follow the live chart!

Look at how First Solar (FSLR) performed this week. The stock surged, surpassing its last high of around $230 about a year ago. Despite FSLR’s rise, its relative strength compared to the S&P 500 index is at -32.81%. It’s got a lot of catching up to do.

CHART 3. FSLR JUMPS ON THE AI RIDE. The AI infrastructure needs to depend on energy companies and

What makes the stock appealing? FSLR has attracted the attention of analysts as a company that will benefit from the AI revolution. There’s a lot of talk about how the increased capacity of data centers will require energy, and FSLR could be one company that would benefit from the increased demand.

FSLR made it to three StockCharts Predefined Scans—New 52-Week Highs, Moved Above Upper Price Channel, P&F Double Top Breakout.

Another stock that hit a new high is Dell Technologies (DELL), again because of its contribution to the AI space. From the daily chart of DELL (see below), the stock is in an upward trend, and its relative strength index (RSI) has just crossed above the 70 level.

Follow the live chart!

The stock also reached the top 5 SCTR stocks (see end-of-week wrap-up below). Will the strength continue? We’ll find out when the company announces earnings next week.

CHART 4. DELL HITS NEW HIGHS. The stock has been gaining strength and is trading well above its 50-day simple moving average. Will earnings push this stock higher? Chart source: StockCharts.com. For educational purposes.

Closing Thoughts

With NVDA earnings in the rearview mirror, could FSLR or DELL be the next stock investors will get excited about? You can’t rule it out. This market hits you with surprises, so be prepared for anything. Even though the market went through its ups and downs this week, the overall sentiment appears to be bullish, a good way to start the holiday weekend.

End-of-Week Wrap-Up

  • S&P 500 closes up at 5,304.72, Dow Jones Industrial Average up 0.01% at 39,069.59; Nasdaq Composite up 1.1% at 16,920.79
  • $VIX down 6.66% at 11.92
  • Best performing sector for the week: Technology
  • Worst performing sector for the week: Energy
  • Top 5 Large Cap SCTR stocks: MicroStrategy Inc. (MSTR); Vistra Energy Corp. (VST); Super Micro Computer, Inc. (SMCI); Vertiv Holdings (VRT); Dell Technologies (DELL)

On the Radar Next Week

  • Earnings from Salesforce (CRM), Abercrombie and Fitch (ANF), Dell Technologies (DELL).
  • March Home Prices
  • Consumer Confidence
  • April PCE
  • Fed speeches

Disclaimer: This blog is for educational purposes only and should not be construed as financial advice. The ideas and strategies should never be used without first assessing your own personal and financial situation, or without consulting a financial professional.

Jayanthi Gopalakrishnan

About the author:
Jayanthi Gopalakrishnan is Director of Site Content at StockCharts.com. She spends her time coming up with content strategies, delivering content to educate traders and investors, and finding ways to make technical analysis fun. Jayanthi was Managing Editor at T3 Custom, a content marketing agency for financial brands. Prior to that, she was Managing Editor of Technical Analysis of Stocks & Commodities magazine for 15+ years.
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Rules-Based Money Management – Part 5: Security Selection, Rules, and Guidelines

Note to the reader: This is the twenty-first in a series of articles I’m publishing here taken from my book, “Investing with the Trend.” Hopefully, you will find this content useful. Market myths are generally perpetuated by repetition, misleading symbolic connections, and the complete ignorance of facts. The world of finance is full of such tendencies, and here, you’ll see some examples. Please keep in mind that not all of these examples are totally misleading — they are sometimes valid — but have too many holes in them to be worthwhile as investment concepts. And not all are directly related to investing and finance. Enjoy! – Greg

Pullback Rally Analysis

The Pullback Rally Analysis is not a ranking measure, but a technique for determining the relative strength of issues by looking at the most recent rally from a previous pullback. To summarize, in pullback rally analysis, you measure the amount of the pullback in percent, then measure the current rally up to the current date in percent. The concept is fairly simple; those issues that dropped the least in the pullback, will probably outperform in the following rally.

This concept measures the percentage move during the pullback, the percentage to date of the current rally, and the percentage to date from the beginning of the pullback. This is a great method to see strength outside of the snapshot of the ranking measures. Figure 14.23 shows an example on how to determine the dates for the beginning and end of the pullback. From the chart, you can see a peak at point A with a pullback down to point B. The rally is then measured from point B to the current date.

A ratio of the percentage move of the current rally to the percentage move of the previous pullback is calculated. Another calculation is percentage the current price is from the beginning of the pullback (previous high). This data, when ranked, will help you determine strength in the rally as compared to the previous pullback. Often the stronger issues in a pullback are the leaders during the rally.

Table 14.1 shows the data for the Pullback Rally Analysis. You can see from even a quick glance at Table 14.1 that the international ETFs are outperforming, not only in the rally phase (% Rally), but also how almost all are now above where the previous high (beginning of pullback) began (% Prev. High). The iShares FTSE China 25 Index Fund also performed well during the pullback phase, with the only international ETF displaying a gain for that period of 2.95%, while the others were losses. The Ratio column shows the ratio of the percent of rally compared to the percent of pullback. The pullback is completed, so only the extent of the rally is unknown.

This ratio will show ETFs that performed in a couple of ways. One is that, if the ETF did not decline much during the pullback and rises quickly in the rally, it will have a large ratio. For example, in the Broad category, the SPDR S&P MidCap 400 ETF Trust (MDY) has a ratio of 1.40, highest in that category. This is because it was the best performer (least decline) in the pullback phase and ranked third in performance in the rally phase. This would indicate that MDY is a strong performer and a candidate to consider for buying. The last column, % Previous High, will also show you which ETFs are making new highs from the beginning of the pullback. This method of selection shows which issues are strong on a relative basis. In fact, it will also tell you which sectors and styles are strongest if you use ETFs that are tied to those strategies.

Pair Analysis

I remember following Martin Zweig years ago, and in fact used one of the techniques he described in his book, Winning on Wall Street, in the mid-1980s. In it, he described a really simple technique using his unweighted index (ZUPI) and on a weekly basis trading it whenever it moved 4% or more. If it moved up 4% in a week, he bought; if it moved down 4% in one week, he sold. Positions were held until the next opposing signal—just that simple. The problem I had back then was not only not following it, but trying to tweak it into something better. Eventually experience told me that he had already been down that road and I was the beneficiary of the results.

Anyway, I took this concept and used it on Index/ETF pairs, actually calculating the ratio of Index/ETF pairs and using the weekly movement of 4% to swap between the numerator and the denominator. It really works well with asset classes that are not correlated, such as equity vs. fixed income or equity vs. gold, and so on. Figure 14.24 shows an example of this pair strategy the S&P 600 small cap index (IJR) vs. the BarCap 7-10 Year Treasury index (IEF). The ratio line is the typical price line, with the binary signal line overlaid while the lower plot is the percent up and down moves for each weekly data point. Remember, this is a weekly chart. Whenever the ratio line moves by 4% in a week, as shown by the lower plot moving above or below the horizontal lines shown as +4% and -4%, the binary line overlaid on the price ratio changes direction. Repeated moves in the same direction are ignored.

The ratio significantly outperformed each of the individual components (IJR and IEF) and the S&P 500. Figure 14.25 shows the performance of the ratio (with the numerator and denominator swapped whenever there was a move of 4% or greater), the performance of the individual components that make up the ratio, and the S&P 500.

Table 14.2 shows the annualized performance statistics from 01/02/1998 until 12/28/2012 (weekly data). The Sharpe Ratio is slightly modified, in that the return is used as the numerator without a reduction for risk-free return. The Ratio rotation strategy outperformed in annualized return, and, when compared to the equity component, it reduced the Drawdown (DD) considerably, improved the Sharpe Ratio, and lowered the Ulcer Index.

I also found that smoothing the ratio with just a two-period moving average greatly enhanced the performance because it reduced the number of trades. Trying different percentages other than Zweig’s 4% worked well occasionally, but, overall, the 4% on weekly data yielded the most robust results time and time again.

The real advantage for a pair rotation strategy is when it is used as a core holding situation. In other words, if a strategy required a core holding percentage but that core could be actively managed, this would give an actively managed core holding that would have much lower drawdowns than a buy-and-hold core, and with considerably better returns. Table 14.3 shows the pairs used with an equal allocation of 25% each given to the four pairs. This adds up to an allocation of 100%, but, in this example, it means 100% of the core and the core percentage of total allocation is determined by the strategy, often 50%.

Figure 14.26 shows the results using the four different pairs in a core rotation strategy compared to buy-and-hold of the S&P 500. The drawdown in 2008 was limited to only 14%, and other than that was a nice ride. The average drawdown (see Table 14.4) is only 20% of the maximum drawdown. I was curious about the lack of performance in 2012 and found it was the fact that in the Gold/20-Year Treasury pair gold was the holding the entire period.

Table 14.4 shows the performance statistics for the Core Rotation Strategy (CRS) compared to the S&P 500. In this rotation strategy example, each of the pairs were smoothed by their two-period average prior to measuring the 4% rate of change. This process removes many of the signals and, while not affecting the results that much, reduces the number of trades significantly.

Figure 14.27 is the drawdown of the core rotation strategy compared to the S&P 500. You can see that the cumulative drawdown for the rotation strategy is considerably less than the drawdown of the index. The average drawdown for the rotation strategy was -3.39%, while the average drawdown for the S&P 500 was -15.88%. This would make for a very comfortable core, considering the exceptional returns and reduced risk statistics from just holding the index in a buy-and-hold situation. This core rotation strategy still meets the requirement of an always invested core while actively switching between four pairs of equity, gold, and fixed income ratios.

Ranking and Selection

Ranking and Selection is another critical component to a rules-based model. Once you have measured the market, you need to determine what to buy. This is the technical process of determining securities that meet the rules when the time to buy arrives.

Mandatory Measures

Once you have your collection of ranking measures, you need to determine which are to be used, along with the rules and guidelines as mandatory ranking measures. This means that you predefine the value range that they must be in before you can purchase that ETF. This is necessary to keep the subjectivity out of the process.

Tiebreaker Measures

Once you have determined your mandatory ranking measures, the remaining ranking measures are considered tie-breaker ranking measures. These are used to help in the selection process, especially when there are hundreds of issues that qualify based on the mandatory measures. You can further reduce these into categories if desired, such as frontline tie-breakers, those you use more often than the others.

Ranking Measures Worksheet

Table 14.5 is a partial view of the ranking measures worksheet. It only shows the top 50 to 60 issues as an example, since there are more than 1,400 ETFs in the full listing. One really important concept to grasp when looking at technical values in a spreadsheet is that you are only seeing a snapshot in time. Here is an example: let’s say that the Trend value is of primary importance and you have two ETFs, one with a Trend of 60 and one with a trend of 70. Which would you choose? Well, the quick answer is probably 70 as that is a stronger trend measure than 60. However, don’t you also need to know which direction the trend indicator is heading? If the trend that was at 60 was in an uptrend, while the one with the trend measure at 70 was in a downtrend, a completely different picture is presented. This is why all of the mandatory ranking measures also show their individual five-day rate of change, so that you can glean from the spreadsheet not only the absolute value of the ranking measure, but also the direction it is headed. It should be noted that any short-term period for rate of change will work.

Ranking Measures Are All About Momentum

Throughout this chapter it should be obvious that the ranking and selection process is centered on the concept known as momentum. Simply said, I want to buy an ETF that exhibits an upward trend that is determined by a number of different technical measures.

A final thought on momentum is that every day, in almost every newspaper’s business section, there is an excellent list of stocks to buy. It is called the 52-week new high list, or often stocks making new highs. If you were to only use this readily available tool, along with a simple stop-loss strategy, you would probably do much better at investing in the market. Sadly, many investors think about buying stocks like they think about buying something at Walmart, they look for bargains. Although this is a valid method also known as value investing, it is very difficult to put into action and seems better in theory. When you buy a stock, you buy it simply because you think you can sell it later at a higher price, I think momentum will work much better in that regard.

Rules and Guidelines

Rules and guidelines are a critical element to a good trend-following model. Once you have the weight-of-the-evidence measure telling you what the market is currently doing, the rules and guidelines provide the necessary process on how to invest based on that measure. If there was a simple answer as to why they are necessary, it is to invoke an objective approach, one that does as much as possible to remove the frail human element in the model. Rules are mandatory, while guidelines are not. That being said, if a guideline is to be ignored, one needs to ensure there is ample supporting evidence to allow it. Basically, the strategy I use is one of a conservative buyer and an aggressive seller.

After many decades in aviation and the always-increasing use of checklists, the rules and guidelines are no different for maintaining a nondiscretionary strategy than a checklist is for a pilot. In aviation, checklists grew in length over time because as accidents or incidents happened a checklist item was created to help prevent it in the future. There is an old axiom about checklists that said behind every item on a checklist, there is a story. Same philosophy goes for rules and guidelines in an investment strategy. A checklist (rules) ensures portfolio managers follow all procedures precisely and unfailingly. This overcomes the problem with experienced managers thinking they can accomplish the task and do not need any assistance. That attitude is costly.

Buy Rules

B1—If asset commitment calls for an amount greater than 50%, then only 50% will be committed, with the remainder the next day, ensuring objectives remain aligned. Forty percent can be the maximum per day if necessary for Guideline G6. This rule keeps the asset purchases to a maximum for any single day. It would not be prudent to go into the market at 100% on one day.

B2—No Buy Days are (1) FOMC announcement day, (2) First/Last day of calendar quarter, (3) days in which the market has reduced hours. FOMC announcement days are typically high-volatility days and the end/beginning of a quarter involves a lot of window dressing. Leave the noise alone.

B3—No buying unless 50 (this can also be a percentage) tradable ETFs (not counting non-correlated) have:

Weight of the Evidence = Weak: Trend>60, Intermediate: Trend>55, Strong: Trend>50

I call this the “soup on the shelf” rule. If you have been to a large grocery store lately and strolled down the aisle that has soup, you probably noticed there are thousands of cans of soup with hundreds of blends, styles, and so on to choose from. Now imagine your spouse has sent you to the store to buy soup. When you turn down the soup aisle, you notice they are essentially empty except for two cans of rhubarb turnip barley in cream sauce. You probably aren’t going to buy any soup that day. The market is similar, especially during the early stages of an uptrend, there just isn’t much to choose from. In addition, the early stages have stricter buying requirements, so the number of issues to pick from could be very small, if any. Because you never violate the rules, a rule to protect you during this period was created, hence rule B3.

B4—No buying on days when stops on current holdings are hit and assets sold. This is usually the first hint that the ensuing uptrend is faltering. It just doesn’t make sense as a trend follower to be buying on the same day as you are selling something that has hit its stop. The argument that one holding might not be correlated is weak in this example, as, with proper trading up, weak holdings should have been previously traded.

B5—No buying on days when the Nasdaq or S&P 500 is down greater than 1.0% (the indices used need to be tied you what you are using in the trend measures). Simply put, this means that if the market as determined by the S&P 500 and/or Nasdaq Composite is down more than 1% during the day, something is wrong with the uptrend and it is better to not buy that day. An argument from bargain hunters or value investors would be that one would get a better price on that day if the uptrend resumed. I can’t argue with that, but I ‘m not a value investor or a bargain hunter. It seems many investors want to buy stocks at bargain prices and I can understand that. However, we are not buying soap at a discount store; we are buying a tradable investment vehicle whose price is determined by buyers and sellers. Moreover, you only want to buy what is going up.

Sell Rules

S1—If stops are hit with End of Day data and still in place at 30 minutes (this time period is based solely on your comfort level) after the open the next day, a sell is initiated; if not in place at the 30-minute point, the issue falls under intraday monitoring (see S2).

S2—Intraday monitoring of Price and Trend (between the hours of 30 minutes after the open until 60 minutes before the close) will invoke a Sell order sent to brokers for execution. Once an issue hits its stop, then a 30-minute period is allowed before it is sold. With the constant barrage of Internet and financial media trying to be first with breaking news, often the story is presented incorrectly, and it can have an effect on a large stock, an industry, or even a sector and cause a big sell-off. Usually, if the story was reported in error or incorrectly, and then reported correctly, the issue quickly recovers. Most of this happens in a very short period of time. The 30-minute rule will help avoid most of these short-term sell-off with quick recoveries.

S3—In a broad-based sell-off and stops are hit, holdings hitting stops can begin liquidating before the 30-minute limit.

S4—If a holding has experienced a sharp run-up in price, once it reaches a 20% gain, sell 50% of the holding and invest in another holding or a new holding. This is just a prudent way of locking in exceptional gains.

S5—Any holding that is still being held after experiencing S4, once a gap open (above previous day’s high) occurs, can warrant a further reduction in the holding. Additionally, this can also anticipate a blow-off move or island reversal, while protecting most gains but still allowing for more upside, although with limited exposure. This is not a good process when trading only one issue, but is prudent when trading many issues with the ability to always find something else to trade.

Trade Up Rules

T1—With Weight of the Evidence strong: If stops are hit, but limited to single sector/industry/style, replace next day as long as the Initial Trend Measures are all indicating an uptrend.

T2—With Weight of the Evidence strong: If stops are hit on more than one sector/industry/style, reenter when Initial Trend Measures are all indicating an uptrend or Initial Trend Measures are improving, as long as there is no deterioration in the weight of the evidence.

T3—With Weight of the Evidence at an intermediate level: If stops are hit, but limited to single sector/industry group, replace next day as long as Initial Trend Measures are all indicating an uptrend.

T4—With Weight of the Evidence at an intermediate level: If stops are hit on more than a single sector/industry/style, the normal Buy rules apply.

 T5—There is no trading up when weight of the evidence or initial trend measures are deteriorating. Clearly, in this situation, there is something not good about the uptrend and it is not a time to trade up.


Note: Guidelines are used as reminders and offer the opportunity to be ignored, but only after considerable deliberation and examining all other possibilities. The absolute most important guideline is the first one, G1.

G1—In the event a situation arises in which there is not a rule or guideline, a conservative solution will be decided on and implemented based on immediate needs. A new guideline or rule will be developed only after the event/conflict has totally passed. This is a critically important guideline to ensure the “heat of the moment” is not used to create or change a rule. The absolute worst time to create or change a rule is when you are emotionally concerned about something that just seems to not be working correctly. In the 1970s, the Navy F-4J Phantom jet had analog instruments and, compared to today’s electronic technology, was antiquated. We had to memorize what we called initial action items for emergency procedures; these were designed to handle the quick and necessary steps to shut down an engine because of fire, no oil pressure, and so on. During simulator (talk about antiquated compared to now), many would pull the wrong lever or shut off the wrong switch during the emotional surge that comes with bright red flashing lights and loud horns. I was not excluded from that group, but found that, when something happened that required immediate action, winding the clock (they weren’t electric back then) for a few seconds to rid yourself of the adrenaline rush would allow you to perform better during the procedure. Beside the reasons given for S1 previously, this falls in line with that thinking.

G2—Try to adhere to this if possible: Weak Weight of the Evidence: SPY, MDY, DIA (ensure liquidity); Intermediate Weight of the Evidence: Styles and Sectors; Strong Weight of the Evidence: Wide Open (a pilot term meaning full throttle). The mandatory ranking measures will dominate this guideline.

G3—European ETFs need to be monitored closely after 1pm Eastern Time to ensure adequate execution time. This is because when the Europe markets close, liquidity in those issues becomes a problem.

G4—Every day when invested, trading up needs to be evaluated. Often, this involves selling the poor-performing holding and buying additional amounts of current holdings.

G5—All buy candidates should be determined by A) rising mandatory ranking components using a chart of the Ranking Measures, and B) an awareness of the issue’s price support and resistance levels.

G6—Always be aware of the Prudent Man concept. This is sort of a catchall to make one think about an action that has not been adequately covered with rules or guidelines. If deciding to do something as far as asset commitment or ETF selection, one needs to be prepared to stand in front of the boss and explain it.

There are a host of additional rules and guidelines that can be created. I would caution you on trying to develop a rule for every inconsistency or disappointment that surfaces while trading with a model. There is probably a good equilibrium about the depth and number of rules is best. I strongly suggest adding rules rationally and unemotionally.

Asset Commitment Tables

In addition to measuring what the market is doing (weight of the evidence) and a set of rules and guidelines to tell you how to invest based on what the market is doing, you then need a set of tables for each strategy to show you the asset commitment (equity exposure goal) levels to be invested to for each Weight of the Evidence scenario.

Table 14.6 is an example table showing the Initial Trend Measure Level (ITM), Weight of the Evidence (WoEv), the Points assigned to each level, and the Asset Commitment Level Percentage (Asset Commitment percent). This is merely a sample and should be based on your risk preferences and objectives. As you can see, even with the WoEv at its lowest level, as long as the much shorter-term trend measures (ITM) are all saying there is an uptrend, one can commit equity to the market.

An alternative and more conservative asset commitment table is shown in Table 14.7. It is easier and a more simple process to divide the WoEv into only three levels, with the middle or intermediate level being the transition zone.

The rules and guidelines offer a few exceptions to the above table of asset commitment, but only based on fairly rare events. Following the rules and commitment levels will lead to an objective process, which is the ultimate goal.

This article contains many measures one can use to determine which holdings should be bought. Many are only valuable in assisting in the selection process. If you consider the fact that you might only need to purchase a few holdings and there are more than 1,400 available, you need a strong set of technical measures to help you reduce the number of issues into a more manageable number. There are some that were identified as mandatory measures, which means these are the ones that have the best track record at identifying early when a holding is in an uptrend. I am positive there are many momentum indicators that are not in this chapter, but these are the ones that I have used for many years. Just keep in mind what the goal of this is: to remove human input into the selection process.

Thanks for reading this far. I intend to publish one article in this series every week. Can’t wait? The book is for sale here.

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These Three Strong Financial Stocks Look Ready To Surge Higher



  • XLF on strong RRG-Heading, rotating back into leading quadrant
  • XLF price approaching overhead resistance after short setback
  • Three major financial stocks ready for upward breaks to lead the sector higher

The Relative Rotation Graph for US sectors shows long tails for XLE and XLU. Both are on a strong RRG-Heading toward or into the leading quadrant. Also inside the leading quadrant are XLB and XLI, though they have rolled over and are starting to lose a bit of relative momentum.

Sectors on negative RRG-Heading and inside the lagging quadrant are XLRE, XLY, XLV, and XLK, with the S&P 500 moving higher in the last three weeks.

For this article, I want to focus on the Financials sector (XLF). The tail for XLF just completed a short rotation through the weakening quadrant and is now returning into the leading quadrant.

The Weekly Chart

The chart above, in combination with the RS-Line and the RRG-Lines, shows what is happening presently. At the dashed vertical line, both RRG-Lines had crossed above the 100-level, pushing the XLF tail into the leading quadrant on the RRG. At the start of 2024, the green JdK RS-Momentum line started to roll over and lose some strength, causing the XLF tail to roll over while still inside the leading quadrant. At the start of the red-shaded box, the RS-Momentum line dips below 100. This has pushed the XLF tail into the weakening quadrant. Note that the red JdK RS-Ratio line remains above 100. At the end of the shaded box, the RS-Momentum line crosses back above the 100-level, which pushes the tail back into the leading quadrant.

When you study the raw RS-Line, you see that it is moving inside a narrow uptrend channel. The period covered by the shaded area reflects a flat period of relative strength inside that channel, after which the rhythm of higher highs and higher lows continues. This rotation on the RRG reflects the continuation of an existing relative uptrend, making it much less risky than the turnaround from a downtrend to an uptrend, which happened at the dashed vertical line.

The Daily Chart

The recent dip to 39.50 and the subsequent rally show up in more detail on the daily chart. This week, XLF takes out its most recent high, starting a new series of higher highs and higher lows. The next resistance level is at the all-time high of 42.20 at the end of March. The setback off of that all-time high has caused relative strength to correct slightly, causing the (daily) RRG-Lines to dip below 100 and push the XLF tail into lagging on the daily RRG.

With the price chart already back on the way up, relative strength is expected to follow shortly. As soon as the daily tail starts to turn back into a 0-90 degree RRG-Heading, relative strength for XLF is expected to improve further, making it one of the leading sectors in the S&P 500.

Individual Stocks

The RRG for individual stocks inside the financials sector shows an evenly-distributed universe around the (XLF) benchmark. Going over the tails for the individual stocks, I found a few names that are definitely worth a closer look.

This RRG shows the tails at a strong heading, narrowing the search for good stocks. While checking out the individual charts, I found several promising names. The three that I want to mention here are not only at strong rotational trajectories, but also (close to) breaking out, AND they are some major names in the sector.

Morgan Stanley

MS is breaking a double resistance level this week, as the horizontal barrier over the most recent peaks and the falling resistance line coming off the 2021 peaks coincided. This unlocks fresh upward potential for MS, with intermediate resistance waiting around 100 before nearing the area around the all-time high at 105.

Subsequently breaking these barriers will push this stock further into the leading quadrant, making it one of the leaders in the sector.


Citigroup is still trading below its previous high. However, given the recently-formed higher low and the strong rally out of it, an upward break is likely. Such a break is supported by the recent relative rotation back into leading from weakening.

Just like MS, C is also one of the bigger names in the financials sector. Strength in big names is usually what drives a sector up.

Bank of America

BAC is also close to breaking overhead resistance, after which there is plenty of upside. Relative strength is coming out of a long downtrend that started early in 2022, making this a major reversal. Taking out the barrier at 38 opens the way for a further move toward 50, which is substantial. But unlike you may think, that area is NOT the all-time high for BAC… that was set around 55 in October 2006.

Like MS and C, BAC is also one of the more important stocks in the Financials sector. Another important name in the sector is GS, which I did not include as it is already well underway after breaking higher.

When such important names in a sector are all starting to break higher, it is good news for that sector.

#StayAlert, –Julius

Julius de Kempenaer
Senior Technical Analyst, StockCharts.com
CreatorRelative Rotation Graphs
FounderRRG Research
Host ofSector Spotlight

Please find my handles for social media channels under the Bio below.

Feedback, comments or questions are welcome at [email protected]. I cannot promise to respond to each and every message, but I will certainly read them and, where reasonably possible, use the feedback and comments or answer questions.

To discuss RRG with me on S.C.A.N., tag me using the handle Julius_RRG.

RRG, Relative Rotation Graphs, JdK RS-Ratio, and JdK RS-Momentum are registered trademarks of RRG Research.

Julius de Kempenaer

About the author:
Julius de Kempenaer is the creator of Relative Rotation Graphs™. This unique method to visualize relative strength within a universe of securities was first launched on Bloomberg professional services terminals in January of 2011 and was released on StockCharts.com in July of 2014.

After graduating from the Dutch Royal Military Academy, Julius served in the Dutch Air Force in multiple officer ranks. He retired from the military as a captain in 1990 to enter the financial industry as a portfolio manager for Equity & Law (now part of AXA Investment Managers).
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Rules-Based Money Management – Part 4: Security Ranking Measures

Note to the reader: This is the twentieth in a series of articles I’m publishing here taken from my book, “Investing with the Trend.” Hopefully, you will find this content useful. Market myths are generally perpetuated by repetition, misleading symbolic connections, and the complete ignorance of facts. The world of finance is full of such tendencies, and here, you’ll see some examples. Please keep in mind that not all of these examples are totally misleading — they are sometimes valid — but have too many holes in them to be worthwhile as investment concepts. And not all are directly related to investing and finance. Enjoy! – Greg

It is not uncommon for investors to believe that the more information they have, the better their chance at choosing good investments. Financial websites offer alerts on stocks, the economy, and just about anything you think you might need. The sad part is that the investor thinks every iota of information is important and tries to draw a conclusion from it. The conclusion may turn out to be correct, but it is usually not.

The issue is that investor is trying to tie each item of news to the movement of a stock, which generally never seems to work; just a few minutes watching the financial media should tell you that it doesn’t work. Human emotions make the investor feel good about having news that supports their beliefs, but rarely do those emotions contribute to investment success. I find it amazing how many times I go into an office and find the financial television playing, sometimes muted, but probably only when they see me coming. Too much information can lead to a total disarray of investment ideas and decisions. Keep it simple, turn off the outside noise, and use a technical approach to determine which issues to buy and sell. You’ll be healthier.

Ranking Measures

Ranking measures are the technical indicators used to determine which issues to buy based on their trendiness. They can be assigned as mandatory or tie-breaker ranking measures. The mandatory ones are the ranking measures that have to meet certain requirements before an issue can be bought. The tie-breaker ranking measures are there to assist in issue selection, but are not mandatory.

Ranking measures can be used with individual stocks, Exchange Traded Funds (ETFs), mutual funds, and bonds; however, there must be a process for selecting them, if for no other reason than to reduce the number down to a usable amount. For example, in an exchange-traded fund (ETF)-only strategy, consider that there are nearly 1,400 ETFs, and a fully invested portfolio might only have positions in 20 ETFs. Ranking measures are indicators, mainly of price or price relationships that assist in the determination of whether an issue is in an uptrend.

Throughout this section, the charts show the exchange-traded fund SPY in the top plot whenever possible, the ranking measure in the bottom plot, and the ranking measure’s binary overlaid on the SPY in the top plot. Some exceptions to using SPY are when volume is needed for the ranking measure, in which case another broad-based ETF will be used. A discussion of the parameters that can be used for each ranking measure is also included. I do not go into excruciating analysis on each chart, as the concept is really simple. The binary is the signal line, and it only represents the ranking measure’s signals exactly. Not all ranking measures have a binary signal, as they are used for confirmation of a trend direction.

The discussion for each ranking measure is varied as some are fairly simple to understand and won’t involve a detailed discussion. I certainly am not the type that discusses the wiggles and waggles of each indicator.


Trend is the name given to a derivative of an indicator originally created by Jim Ritter of Stratagem Software. He wrote about it in the December 1992 (V. 12:12, 534–534) issue of Stocks & Commodities magazine, in the article “Create a Hybrid Indicator.” Trend is a simple concept, yet is a powerful combination of two overbought oversold indicators: Stochastics (%K) and Relative Strength Index (RSI). The indicator uses 50% of each one in combination, and while both are range-bound between zero and 100, the combination is also range-bound between zero and 100. Stochastics, normally much quicker to react to price changes, is dampened by the usually slower-to-react RSI. In combination, you have an indicator that shows strong trend measurements whenever it is above a predetermined threshold.


The Stochastic needs to be much longer than when used by itself, while RSI can be used close to its original value. The Stochastic range of 20 to 30 should work well, with the final value determined by the length trend you want to follow. The RSI range can vary, but you don’t want to make it too long, as it is already a slower-reacting measure. Finally, the threshold used for Trend should be in the 50 to 60 range, again dependent on how soon you want the signal, remembering that early signals will also give more whipsaws.

 The examples of Trend in Figure 14.1 have the threshold drawn at 50, which is a good all-around value. The concept is simply that whenever Trend is above 50, the ETF is in an uptrend, and whenever Trend is below 50, it is not in an uptrend. The binary is overlaid on the price plot (top) so that you can see the signals better. Notice that when prices are in an uptrend, the binary is usually at the top, and when prices are not, it is at the bottom. Also note that, in the middle of the plot, there were a number of quick signals in succession; this is why one should not rely on a single indicator for analysis.

Trend Rate of Change (ROC)

This is merely the five-day rate of change of Trend. Why would you use that? When viewing a lot of data on a spreadsheet that does not contain any charts, and you see the value for Trend is 65, you also need to know if it is rising through 65 or declining through it. A snapshot of the data can be dangerous if you don’t also look at the direction the indicator is moving.

Figure 14.2 is a chart of the five-day rate of change of Trend. You can see that while Trend is still slightly positive (above the 50 line), it is declining (see Figure 14.1). Then, when you compare it with the Trend ROC in Figure 14.2, it is showing significant weakness. Of course, showing the five-day rate of change of an indicator without showing the indicator itself is foolish; it was done here so that you could see the measure being discussed.


This can be almost any value you desire based on what you are using it for. I used it here to see the short-term trend of an indicator, so five days is just about right. If you were using rate of change as an indicator for measuring the strength of an ETF or an index, then a longer period would probably be more appropriate. I use 21 days when I use ROC by itself.

Figure 14.3 shows the Trend with the five-day rate of change of Trend overlaid (lighter). This is the way that all the mandatory ranking measures and some of the tiebreaker measures are shown. You can see from this that the Trend is above 50, but the five-day rate of change is deteriorating and is well below zero (negative).

Trend Diffusion

This is also known as Detrend, which is a technique where you subtract the value of an indicator’s moving average from the value of the indicator. It is a simple concept, actually, and not unlike the difference between two moving averages with one average being equal to 1, or MACD for that matter. Technical analysis is ripe with simple diversions from concepts and often with someone’s name attached to the front if it— don’t get me started on that one.

Figure 14.4 is the same Trend as previously discussed, except that it is the 15-day Detrend of Trend, or Trend Diffusion. The middle plot is the Trend, with the lighter line being a 15-day simple moving average of the Trend. The bottom plot is the Trend Diffusion, which is simply the difference between the Trend and its own 15-day moving average. You can see this when the Trend moves above its moving average, the Trend Diffusion moves above the zero line. Similarly, whenever the Trend moves below its 15-day moving average in the middle plot, the Trend Diffusion moves below the zero line in the bottom plot. The information from the 15-day Trend Diffusion is absolutely no different that the information in the middle plot showing the Trend and its 15-day moving average, just easier to visualize.


The example in Figure 14.4 uses 15 days, which is three weeks. Parameters need to be chosen based on the timeframe for your analysis. A range from 10 to 30 is probably adequate for Trend Diffusion.

Price Momentum

This indicator looks back at the price today compared to X days ago. It is created by calculating the difference between the sum of all recent gains and the sum of all recent losses and then dividing the results by the sum of all price movement over the period being analyzed. This oscillator is similar to other momentum indicators, such as RSI and Stochastics, because it is rangebound, in this case from -100 to +100.


Price Momentum is very close to being the same as rate of change; generally the only difference between the two is the scaling of the data. Momentum oscillates above and below zero and yields absolute values, while the Rate of Change moves between zero and 100 and yields relative values. The shape of the line, however, is similar. With momentum, the threshold is shown at 50, but could be higher if requiring more stringent ranking requirements.

Figure 14.5 shows the Price Momentum ranking measure (dark line) and its five-day rate of change (lighter line). You can see that the Price Momentum is weak and the ROC is negative and declining.

Price Performance

This indicator shows the recent performance based on its actual rate of change for multiple periods, added together, and then divided by the number of rates of change used. In this example, I used three rates of change of 5, 10, and 21 days, which equates to 1 week, 2 weeks, and 1 month. Simply calculate each rate of change, add them together, and then divide by three. This gives an equal weighting to rates of change over various days.


Like many indicators, the parameters used are totally dependent on what you are trying to accomplish. Here, I am trying only to identify ETFs that are in an uptrend.

Figure 14.6 shows the Price Performance measure using the three rates of change mentioned above. There is no need to show the typical five-day rate of change of this indicator, since it is in itself a rate of change indicator.

Relationship to Stop

This is the percentage that price is below its previous 21-day highest close. This is an extremely important ranking measure, and here’s why.

If you are using a system that always uses stop loss placement (hopefully you are), then you certainly would not want to buy an ETF that was already close to its stop. This is the case when using trailing stops; if using portfolio stops, or stops based on the purchase price, this measure does not come into play. I like to use stops during periods of low risk of 5% below where the closing price had reached its highest value over the past 21 days. If you think about this, this means that, as prices decline from a new high, then the stop baseline is set at that point and the percentage decline is measured from there.


In most cases, this is a variable parameter determined by the risk that you have assessed in the market or in the holding. I prefer very tight stops in the early stages of an uptrend, because I know there are going to be times when it does not work, and when those times happen, I want out. The setting of stop loss levels is entirely too subjective, but I would say that as risk lessens, the stops should become looser, allowing for more daily volatility in the price action.

Figure 14.7 shows the 5% trailing stop using the highest closing price over the past 21 days. The two lines are drawn at zero and -5%. When this measure is at zero, it means that the price is at its highest level in the past 21 days. The line then continuously shows where the price is relative to the moving 21-day highest closing price. When it drops below the -5% line, then the stop has been hit and the holding should be sold.

Please notice that I did not beat around the bush on that last sentence. When a stop is hit, sell the holding. Like Forrest Gump, that is all I ‘m going to say about that.

Relative Performance

This indicator shows the recent performance of an ETF relative to that of the S&P 500. Often, there is a tendency to show the performance relative to the total return version of the S&P 500. This is only advisable if you are actually measuring and using the total return version of an ETF. In addition, most measurements are of a timeframe where the total return does not come into play. However, purists may want one over the other, and the results will be satisfactory if used consistently.

Usually the data analyzed is price-based; therefore, the relative performance should be using the price only S&P 500 Index. Also, when comparing an ETF to an index, one must be careful when comparing, say the SPY with the S&P 500 Index, two issues that should track relatively close to each other. The mathematics can blow up on you, so just be cognizant of this situation. Hence, the example in the chart below has switched from using SPY to using the EFA exchange-traded fund.

Finally, you cannot simply divide the ETF by the index and plot it, or you will have a lot of noise with no clear indication as to the relative performance. I like to normalize the ratio of the two over a time period that is appropriate for my work; in this case, over 65 days. This can further be expanded, similar to the Price Performance measure covered previously, and also use another normalization period, say 21 days, then average them. Additionally, you can then smooth the results to help remove some noise. Remember, you are only trying to assess relative performance here.


This, like many ranking measures, is based totally on personal preference, and also on the time frame you are using for analysis. In this example, I normalized the ratio with 65 and 21 days, then smoothed the result with the difference between their 15- and 50-day exponential average.

Figure 14.8 shows EFA relative to the S&P 500 Index. Whenever it is above the horizontal zero line, then EFA is outperforming the S&P 500. This would be considered an alpha-generating ranking measure if your benchmark is the S&P 500.

Power Score

This is a combination indicator that takes four indicators into account to get a composite score. Those indicators are Trend, Price Momentum, Price Performance, and Relationship to Stop. Additionally, the PowerScore also factors in the five-day rates of change of the Price Momentum and Trend measures.


There are not really any parameters to discuss with PowerScore, as it is created by using four of the mandatory ranking measures. The concept here can be as broad or as narrow as needed. Using only the mandatory ranking measures seems reasonable; however, the PowerScore is unlimited in what components can be used.

Figure 14.9 shows the PowerScore with a horizontal line at the value of 100. Based on the calculations of the components for this indicator, whenever PowerScore is above 100, then it is saying that the components are collectively saying the ETF is in an uptrend. This could be considered a composite measure, but, unlike the ones referred to in the weight of the evidence components, this one uses all components.

Efficiency Ratio

This ratio shows how much price movement in the past 21 days was essentially noise. It is a measure of the smoothness of the 21-day rate of change, created years ago by Perry Kaufman. It is an excellent ranking measure, but you need to know that it is an absolute measure of how an ETF gets from point A to point B; in this case, from 21 days ago until today.

Figure 14.10 is an example of how to think about this. If you were interested in two funds, fund 1 (solid line) and fund B (thicker dashed line), measuring their price movements of the same period of time, then which of the two would you prefer? The one that smoothly rose from point A to point B, or the one that had erratic movements up and down but ended up at the same place? I think everyone agrees that the smoother ride, or the solid line, is preferable.


I use 15 or 21 days, but as always, this is more dependent on your trading style and time frame of reference. The value should closely mirror what the minimum length trend you are trying to identify, independent of direction.

Figure 14.11 shows the 21-day efficiency ratio for SPY. You can see that whenever the ETF is trending, the Efficiency Ratio rises, and when the ETF is range-bound and moving sideways, the Efficiency Ratio remains low. In other words, a high efficiency ratio means the ride is more comfortable. It is moving efficiently.

Average Drawdown

If you read the section in this book on Drawdown Analysis (Chapter 11), then you know exactly what this ranking measure accomplishes. The concept of average Drawdown for analysis and using it for a ranking measure are considerably different. To utilize average drawdown as a ranking measure, you need to use a moving average drawdown, such as over the past year. This is because an issue that has been in a state of drawdown for a number of years will not give you the ranking data that is needed for a frame of reference over the past few months. A moving average of drawdown will help reset the drawdown as time moves forward.


I like to see the average drawdown over the past year, which is, on average 252 market days. This is enough time for a measurement, but short enough to get a feel for how long it remains in a state of drawdown.

Figure 14.12 shows the average drawdown over the past 252 days. The horizontal line is drawn at -5% as a reference. The lower plot is the cumulative drawdown, with the horizontal line being the long-term average.

Relative Average Drawdown

Figure 14.13 shows the difference between the average drawdown of the issue compared to that of the S&P 500 Index. This is shown here only as an example of another type of ranking measure, and certainly would never qualify as a mandatory ranking measure.

Price x Volume

Figure 14.14 shows the 21-day simple average of the volume times the close price. The purpose here is to show if the issue has enough liquidity to be traded. The ranking measures should always give a quick view on a variety of indicators, and this one might show you immediately if there is enough trading volume to give you the liquidity you would need to trade it. Of course, the ideal solution is to have a good relationship with the trading desk that you will be using, as they can give you up-to-date information on what volume you can trade.

Adaptive Trend

Adaptive Trend is an intermediate trend measure that changes based on the volatility of the price movements. The Adaptive Trend measure incorporates the most recent 21 days of market data to compute volatility based on a true range methodology. This process always considers the previous day’s close price in the current day’s high–low range to ensure we are using days that gap either up or down to their fullest benefit. When the price is trading above the Adaptive Trend, a positive signal is generated, and when below, a negative signal is in place.

The chart in Figure 14.15 shows the Adaptive Trend as an oscillator above and below zero, so that when it is above zero, it means the price is above the Adaptive Trend, and when below zero, price is below the Adaptive Trend. The top plot shows the Adaptive Trend binary. If you prefer, the horizontal line at zero is the adaptive trend, similar to the Trend Diffusion discussed earlier.

Weighted Performance

Figure 14.16 is a weighted average of the 1-, 3-, 5-, 10-, and 21-day rates of change. One can argue that it is difficult to decide which exact period to measure for performance, and I would not disagree. The method takes a number of periods into consideration and averages them for a single result. One could carry this concept further and weight each of the measurements and have a double-weighted performance measure.

You should, however, try to keep things simple, as complexity has a greater tendency to fail.

Slow Trend

This measure, shown in Figure 14.17 , is similar to Trend, but uses a longer period for its calculation. This concept can be used on many of the ranking measures as a second line of defense or confirmation. The faster version is good for initial selection, and the slower version is good for adding to positions (trading up).

Ulcer Index

The Ulcer Index (Figure 14.18) takes into account only the downward volatility for an issue, plus uses price crossover technique with a 21-period average. This concept was first written about by Peter Martin in The Investor’s Guide to Fidelity Funds, in 1989.

Sortino Ratio

Figure 14.19 shows the downside risk after the return of the issue falls below that of the 13-week T-bill yield. It is a risk-adjusted return like the Sharpe Ratio, but only penalizes downward volatility, whereas the Sharpe Ratio uses sigma (standard deviation). This is also similar to the Treynor ratio, which uses beta as the denominator and expected return for the numerator.


Figure 14.20 is the issue’s beta based on the past 126 days (6 months). The same issue exists here as with the Relative Performance earlier. You cannot measure beta unless it is measured against something, in this case the S&P 500. Therefore, be careful when comparing a large-cap ETF to a large-cap benchmark, small-cap ETF to a small-cap benchmark, and so on.

Relationship to Moving Average

Figure 14.21 shows the percent above or below the simple 65-day exponential moving average. This is similar to detrend or diffusion. I think here the value is that one should always pick a moving average period to use and stick with it, so that you get a feel for its action during certain market movements. In other words, you become accustomed to how this moving average works over time. I equate this to using only one wedge in golf instead of multiple ones. Most of us cannot devote the time to practice with multiple wedges, so learn one and stick with it.


Correlation is an attempt to find a close relationship with an index such as the S&P 500. This is another one of those ranking measures you need to be careful not to compare a like ETF to a similar index. For example, the mathematics of correlation would blow up if you tried to compare the ETF SPY with the S&P 500 Index.

In Figure 14.22, whenever the line is near the top of the plot, then it is saying the correlation of the top plot is correlated to the benchmark being used. When the market is advancing, you want highly correlated holdings. When the market is declining, or you see it begin to roll over in a topping manner, you want to move into less correlated holdings. You must keep in mind that you are still a momentum player and, even though you want less correlation to the market, they still must be advancing on an individual basis.

Correlation is not always causation, but don’t try explaining that to your dog when he hears the can opener. — Tom McClellan

Thanks for reading this far. I intend to publish one article in this series every week. Can’t wait? The book is for sale here.

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Diverging Tails on This Relative Rotation Graph Unveil Trading Opportunities



  • Comparing equal-weighted and cap-weighted sectors on a Relative Rotation Graph can offer interesting insights
  • When the trajectory of the tails and their position on the chart differ significantly, further investigation is warranted
  • At the moment, two sectors are showing such divergences

All on the Same Track… or?

The difference between equal-weighted sectors and cap-weighted sectors is obvious. Namely, the cap-weighted variant is much heavier and is impacted by the changes in some heavy-weight, often mega-cap, stocks. Nevertheless, when you plot these sectors on Relative Rotation Graphs, you will often find that their tails generally move in the same direction and/or follow the same path.

When that does not happen, when the tails of the two versions of the same sector are on different paths or in completely different positions on the RRG, it’s time to investigate.

The RRG above shows the two universes, cap-weighted and equal-weighted, plotted on the same RRG and against SPY as the benchmark. Looking closely, you will find most sector pairs on the same trajectory. If you have a SC account, you can click on the graph, open the RRG in your own account, and do a closer inspection.

*You can save RRGs as bookmarks in your browser. By doing that, you can create your own custom RRGs and save them for later retrieval. Scroll to the bottom of the page, click “permalink,” and then copy and save this link as a bookmark in your browser.

Zooming In

To get a better handle and a clearer picture, I have removed the sectors where both tails are on similar trajectories and positions and only left the tails on the graph where they differ. As a result, two sectors remain: Consumer Discretionary and Communication Services.

Consumer Discretionary

Both tails are inside the lagging quadrant. However, that is as far as the comparison goes. XLY is moving higher on the RS-Momentum scale, indicating an improvement in relative momentum, while RSPD is moving lower and is on a negative RRG-Heading. Also, the tail on XLY is substantially longer than on RSPD, indicating the power behind the move.

Looking at the composition of the sector, it’s obvious which stocks inside Consumer Discretionary are causing the difference.

AMZN, TSLA, HD, and MCD comprise 50% of the index, while AMZN and TSLA are already 38%.

Looking at the performance over the last five weeks (tail length on the RRG), we can see how the sector’s performance has shifted to the large names. The table above shows the top 50 stocks in the discretionary sector. AMZN and TSLA are in the upper end of the range, and MCD is just above XLY, which is at position 17 out of 50. This implies that most stocks are performing worse than that sector index.’

Roughly the bottom half is at double-digit declines. While AMZN and TSLA are “only” up 2.4%, they drag the sector index up to around 1/3 of the entire universe, even with HD showing a 12.5% decline over that period.

Now, look at the same table. Instead of using XLY as the benchmark, we are now using RSPD as the benchmark.

RSPD is showing up at position 27 / 50, right where you’d expect an equal weight benchmark — in the middle of the universe, balancing out all the performances.

The bottom line is that XLY has been picking up recently only because of TSLA, AMZN, and MCD. But, under the hood, most discretionary stocks are going through a horrible correction.

From a trading perspective, such observations can offer great pair trading ideas.

Communication Services

The tails for XLC and RSPC are also far apart on the RRG. XLC is still inside the weakening quadrant and has just started to show the first signs of curling back up. RSPC is deep inside the lagging quadrant at a really low reading on the RS-Ratio scale overall, and is picking up relative momentum, but no relative trend (RS-Ratio) yet.

Over the five-week period, XLC lost 2.8%, while RSPC lost 4.3%. The composition for this sector is even more top-heavy than Consumer Discretionary.

META is listed as the top holding in XLC at 21%. But when we add up the weights for Alphabet A and B, it comes out to 26%. So together, the top two stocks in XLC are a whopping 47% of the sector.

Looking at the same table for XLC, we find Alphabet at the top of the list over the last five weeks. Meta is in the lower part at -9%. The sector (XLC) comes in at -2.8%, which means that META is UNDERperforming (-9% + 2.8% =) -6.2%. But Alphabet Class A is OUTperforming (10.4% + 2.8% = ) 13.2% and Alphabet Class C is OUTperforming (10.6% + 2.8% = ) 13.4%. This is a way stronger upward pull for the index than the drag caused by META.

Changing the benchmark to the EW version of Communication Services shows this table.

Again, we see the equal-weight benchmark (RSPC) dropping to near the middle of the list, balancing out the return more evenly.

All in all, this provides a similar pair trading opportunity.

This relative trend is much more mature than the XLY:RSPD pair, but, as long as the rhythm of higher highs and higher lows continues, buying the dips in this relative line offers opportunities.

Most of the time, the cap-weighted and equal-weighted versions of a sector will move more or less in tandem. But when they don’t, they’re worth investigating, as they may offer interesting trading opportunities.

#StayAlert and have a great weekend, –Julius

Julius de Kempenaer
Senior Technical Analyst, StockCharts.com
CreatorRelative Rotation Graphs
FounderRRG Research
Host ofSector Spotlight

Please find my handles for social media channels under the Bio below.

Feedback, comments or questions are welcome at [email protected]. I cannot promise to respond to each and every message, but I will certainly read them and, where reasonably possible, use the feedback and comments or answer questions.

To discuss RRG with me on S.C.A.N., tag me using the handle Julius_RRG.

RRG, Relative Rotation Graphs, JdK RS-Ratio, and JdK RS-Momentum are registered trademarks of RRG Research.

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S&P 500 Makes a New All-Time High By End of June?

We’ve been covering the signs of weakness for stocks, from the bearish divergences in March, to the mega-cap growth stocks breaking through their 50-day moving averages, to even the dramatic increase in volatility often associated with major market tops. While Q1 was marked by broad market strength and plenty of new 52-week highs, Q2 has so far provided a much different playbook for investors. Both bulls and bears have felt validated by the recent choppiness for the major market averages.

Over the last week, the S&P 500 managed to gain about 2.7%, despite some hotter-than-expected inflation data and a mixed bag of earnings for the Magnificent 7 stocks. Does this set us up for much further gains, and a potential break to new all-time highs, as we continue through the second quarter? Or are we currently experiencing the “dead cat bounce” phase with a countertrend move to the upside before the great bear market continues?

Psst! Check out the January 2024 edition of this exercise, and guess which scenario actually played out!

Today, we’ll lay out four potential outcomes for the S&P 500 index. As I share each of these four future paths, I’ll describe the market conditions that would likely be involved, and I’ll also share my estimated probability for each scenario. And remember, the point of this exercise is threefold:

  1. Consider all four potential future paths for the index, think about what would cause each scenario to unfold in terms of the macro drivers, and review what signals/patterns/indicators would confirm the scenario.
  2. Decide which scenario you feel is most likely, and why you think that’s the case. Don’t forget to drop me a comment and let me know your vote!
  3. Think about how each of the four scenarios would impact your current portfolio. How would you manage risk in each case? How and when would you take action to adapt to this new reality?

Let’s start with the most optimistic scenario, involving a move to new all-time highs over the next six to eight weeks.

Option 1: The Very Bullish Scenario

If you think the April pullback was just another buyable dip within a primary bullish trend, then the Very Bullish Scenario is for you. This scenario would be made possible only if the Magnificent 7 stocks returned to their former magnificent ways, with stocks like AMZN and NVDA following GOOGL in making new all-time highs.

We’d need to see economic indicators, especially inflation readings, come in much weaker, which would give the Fed confidence to begin cutting rates at the June Fed meeting. By the end of June, we’d be talking about the S&P 500 breaking above 5500, and even 6000 could be on the table.

Dave’s Vote: 10%

Option 2: The Mildly Bullish Scenario

What if the S&P manages to hold the April low around 4950, but is unable to push to new all-time highs? Scenario 2 could mean that value-oriented sectors like industrials and materials experience a resurgence, outpacing the growth leadership stocks from Q1. But since these sectors are much lower weight in the S&P 500, it’s just not enough market cap to move the needle on the major benchmarks.

Perhaps the rest of earnings season yields mixed results, and by the end of Q2 we are left with more questions than answers as the Fed is unable to commit to aggressive rate cuts. Interest rates remain elevated, which creates a major headwind for growth stocks.

Dave’s vote: 30%

Option 3: The Mildly Bearish Scenario

Now we get to two scenarios that would mean a more bearish picture emerges in the coming weeks. Scenario 3 would mean the S&P 500 is unable to hold the April low around 4950, but we remain above a 38.2% retracement level around 4820. The Fed either delays its first rate cut or uses language that exudes little confidence in multiple additional rate cuts in 2024.

The Magnificent 7 stocks would be choppy at best, and as they stall out attempting to return to new all-time highs, investors see that as a signal of limited upside. Gold and gold stocks become the trade of the day, as investors are looking for anything other than stocks to try and generate positive returns.

Dave’s vote: 45%

Option 4: The Super Bearish Scenario

You always have to include a doomsday scenario, and our final option would mean the April selloff was indeed just the beginning. May and June are marked with lower lows and lower highs, and Q2 feels very similar to September and October of 2023. The S&P 500 breaks through Fibonacci support around 4820, and even pushes below the 200-day moving average for the first time since the October 2023 low.

What could cause this last scenario? Economic data could come in way higher than expected, and the Fed could then become unwilling to cut rates while the economy shows signs of renewed strength. The market braces for “higher for longer” interest rates, growth-oriented sectors like technology and communication services begin the lead the way lower, and defensive sectors bump higher as investors ignite the “flight for safety” trade.

Dave’s vote: 15%

What probabilities would you assign to each of these four scenarios? Check out the video below, and then drop a comment with which scenario you select and why!



P.S. Ready to upgrade your investment process? Check out my free behavioral investing course!

David Keller, CMT

Chief Market Strategist


Disclaimer: This blog is for educational purposes only and should not be construed as financial advice. The ideas and strategies should never be used without first assessing your own personal and financial situation, or without consulting a financial professional.

The author does not have a position in mentioned securities at the time of publication. Any opinions expressed herein are solely those of the author and do not in any way represent the views or opinions of any other person or entity.

David Keller

About the author:
David Keller, CMT is Chief Market Strategist at StockCharts.com, where he helps investors minimize behavioral biases through technical analysis. He is a frequent host on StockCharts TV, and he relates mindfulness techniques to investor decision making in his blog, The Mindful Investor.

David is also President and Chief Strategist at Sierra Alpha Research LLC, a boutique investment research firm focused on managing risk through market awareness. He combines the strengths of technical analysis, behavioral finance, and data visualization to identify investment opportunities and enrich relationships between advisors and clients.
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