In our earlier article, Can Participation Data Help Identify Tomorrow’s Market Leaders?, we introduced an important research question being explored within our Owl Bundle User Group (OBUG):
Can changing market participation provide clues that a stock may be developing into a future market leader before that leadership becomes obvious?
Since then, we've made considerable progress. What began as an investigation of unusual market participation has evolved into a broader research program involving historical backtesting, comparisons with established technical indicators, and new approaches to identifying potential areas of emerging market leadership.
Along the way, we've learned some important lessons about what our signals may tell us—and, equally important, what they cannot.
From ORPA to OATS: Recognizing Emerging Acceleration
Our original research began with ORPA (OBUG RL30Slope Z Participation Analyzer), building upon Dr. Ken Long's extensive work with regression-line analysis and market states.
One promising direction from this research has evolved into a signal we're now calling OATS — OBUG Accelerating Trend Signal.
The idea behind OATS is relatively straightforward:
Can we recognize when a stock's price behavior begins changing in an unusually positive and persistent way, potentially before it develops into a widely recognized market leader?
Rather than simply identifying stocks already demonstrating strong momentum, we're interested in identifying meaningful changes in behavior.
A stock might spend considerable time displaying relatively ordinary price behavior before something changes. Positive trend acceleration appears, persists, and potentially develops into a much larger advance.
Of course, not every promising beginning becomes a successful investment. Some signals fail, while others produce only modest advances. A relatively small number may develop into exceptional market leaders.
Our objective is not to predict every winner. It's to systematically identify stocks that deserve closer attention.
From Chart Observations to Systematic Validation
Studying charts of a historical winner and identifying what preceded its advance can provide valuable insights. But it raises an important question: Would those same characteristics have helped identify promising opportunities across many other stocks, including those that ultimately disappointed?
To investigate, we've been using EdgeRater to conduct increasingly extensive historical studies across multiple industries, investment themes, and broad stock universes.
We've also compared our developing OATS signal with established technical approaches, including Chaikin Money Flow, Elder Force Index, and Dr. Ken Long's Fireworks entry rules.
These comparisons have helped us investigate whether different signals identify different types of market opportunities and how stocks behave following their activation.
We've examined questions involving signal selectivity, subsequent price behavior, holding periods, and the distinction between identifying emerging strength and recognizing strength already underway. Our current emphasis is on understanding the quality of potential candidates.
These detailed comparative studies and findings are part of our ongoing OBUG member research.
When an Interesting Market Narrative Meets the Backtest
One of the most valuable lessons from our OBUG research is that a compelling market narrative does not necessarily translate into an effective trading approach.
It's relatively easy to develop an explanation for why certain market behavior should precede a significant price advance. The explanation may be logically sound and supported by attractive historical chart examples.
But what happens when we systematically backtest that idea across hundreds or thousands of historical opportunities—including stocks that did not become winners?
Sometimes the evidence supports our original thinking. Other times, it challenges our assumptions, exposes weaknesses, or suggests alternative approaches worth further testing.
Our evolution from ORPA toward OATS illustrates this research process. We began with a hypothesis about changing market participation. As we expanded our testing and compared alternative approaches, our thinking evolved toward identifying unusual and persistent bullish trend acceleration.
The underlying objective remains the same: identifying promising stocks before exceptional leadership becomes obvious. But the research has helped refine how we pursue that objective.
This is why we believe backtesting is so important. The goal isn't to prove our original narrative correct—it's to discover what the evidence actually supports, even when that means changing our approach.
An Important New Direction: From Individual Stocks to Investment Themes
Our next major research focus may be even more interesting.
Consider some of the investment themes that have captured investors' attention in recent years: artificial intelligence, power infrastructure, nuclear energy, robotics, cybersecurity, and other emerging technologies.
These themes rarely involve just one company. As interest develops, related stocks may begin demonstrating changes in market participation at different times and to different degrees.
That observation raises a new question:
Could clusters of accelerating stocks help us recognize investment themes gaining market interest before their leadership becomes widely recognized?
For example, an unusual acceleration signal in one company may simply reflect something happening within that business.
But what if several economically related companies begin demonstrating similar changes around the same time?
Might that indicate something broader is developing?
This is the motivation behind the next phase of our research, which we're calling Theme Intelligence.
We're investigating whether changes in participation across groups of related stocks can help us identify emerging investment themes and, potentially, distinguish more promising opportunities from isolated signals.
We're also exploring how to define meaningful themes, evaluate their breadth, and determine whether theme participation adds useful information to individual stock signals.
These are research questions, not established conclusions. But they represent a natural extension of our original ORPA work.
From Identifying Candidates to Prioritizing Opportunities
Another important lesson is that even an effective screening method can produce more candidates than a trader can reasonably follow or own.
This brings us to a practical question:
Among the stocks displaying promising acceleration, which ones deserve the highest priority?
Our research is evolving toward a systematic process that connects several related decisions.
First, identify stocks displaying unusual and persistent bullish acceleration.
Next, investigate whether those stocks belong to strengthening investment themes.
Then, evaluate additional evidence that may help distinguish more promising candidates from weaker opportunities.
Future studies will examine whether trend characteristics, relative strength, volume behavior, and other technical indicators can improve this prioritization process.
Ultimately, we're interested in applications such as diversified stock baskets, where investors can participate in a group of promising companies without needing to predict precisely which one will become the exceptional winner.
The challenge is to develop a selection process that improves the opportunity set while maintaining appropriate attention to risk.
That remains an important part of our future research.
Why We Continue to Emphasize Research Rather Than Predictions
One of the principles we emphasize within OBUG is that an attractive historical pattern is only the beginning.
Markets are complicated. Techniques that appear effective for a handful of well-known winners may behave differently across other stocks, market environments, and time periods.
This is why we devote considerable attention to testing, comparing alternatives, examining unsuccessful signals, and questioning our own assumptions.
We also recognize that strong historical signal characteristics do not automatically translate into attractive portfolio results.
Our goal is to build understanding progressively, using evidence rather than relying on compelling stories or isolated chart examples.
We believe there is considerable educational value in that process—even when the research challenges our original expectations.
Join Us as the Research Continues
The Owl Bundle User Group (OBUG) is AbleWayTech's ongoing trader research and development community, building upon Dr. Ken Long's trading methodology and the analytical capabilities of EdgeRater.
Members follow the research as it develops, including our detailed backtests, indicator comparisons, research templates, findings, and discussions of practical applications.
Our upcoming studies will increasingly focus on Theme Intelligence—how to identify areas of strengthening market participation and whether that information can improve the selection of promising stocks.
Subsequent phases will examine additional qualification indicators and approaches to portfolio implementation.
We don't claim to have discovered a formula for finding the next NVDA. But we are developing a more systematic way to investigate the market behavior that may precede exceptional leadership.
And that is what makes this research worth pursuing.
If you're interested in understanding not just which stocks are moving today, but where new opportunities may be developing—and how to investigate those opportunities systematically—we invite you to join us.