Advanced Market Signal Datahub

While our core S&P 500 package is built around efficient downside protection, we’ve always believed that protection alone isn’t enough to navigate today’s complex and fast-moving markets. Timing, positioning, and broader context matter — especially in an environment shaped by sector rotation, volatility cycles, and unpredictable macro shifts.

That’s exactly why we created the Advanced Market Signal Dashboard: a deeper toolkit designed to go beyond binary hedge signals and help our members better understand the evolving structure of the market. WU Advanced package was born from that very goal — to offer more insight and actionable data to those who wanted to go further. Over time, our work naturally expanded to include individual stock analysis, but that original mission of delivering robust, market-level signals remains central.

Even the tools that appear straightforward — like our Downtrend Exhaustion signals (formerly “Buy the Dip” indicators) — are the result of extensive data modeling and months of refinement. It took significant effort to translate complex dynamics into clean, intuitive visuals. We’ve worked hard to make them feel accessible, but they are powered by deep logic and sometime years of development.

The dashboard is organized into three key sections: Sector Strength Indicators, which track where leadership is shifting across the economy; the Downtrend Exhaustion Dashboard, which helps identify when selling pressure may be reaching its limit; and Other Signals, which includes high-value metrics we rely on to interpret volatility regimes, macro stress, and shifting risk environments.

Like the rest of WU Advanced, many of these signals are powered by premium institutional datasets — giving retail investors access to the kind of information typically reserved for large funds and professionals.

What follows is a complete walkthrough of each signal: what it measures, how it works, and how it can help you sharpen your read on the market.

Sector Strength Indicators

Aside from brief moments of broad market euphoria when nearly everything rallies, the stock market is typically a game of rotation. Shifting macroeconomic conditions continuously favor some sectors while weighing on others — creating a dynamic cycle of winners and laggards. Understanding which sectors are gaining strength is critical for smart investing, not only for making direct bets on sector ETFs, but also for evaluating individual stocks within those sectors.

While it’s certainly possible for a company to outperform its sector, it’s usually far easier — and more consistent — to invest in businesses that are riding the tailwinds of their industry. Just think back to 2022: amid the global energy crisis triggered by Russia’s invasion of Ukraine, energy stocks dominated the leaderboard. In fact, two of my best-performing trades that year weren’t flashy growth names, but rather two relatively “boring” energy companies that benefited from that macro shift.

To help capture these rotations, we developed three distinct indicators designed to highlight which sectors are in favor, which are fading, and which may be on the verge of turning. Together, they provide a comprehensive, real-time view of sector leadership — a valuable edge whether you’re managing a portfolio of ETFs or looking to pick the right stock in the right industry at the right time.

Here’s a sector cheat sheet — just in case you’re like me and don’t always remember all the tickers and their associated sectors. We’ve also included ARKK, since the conventional sector breakdown doesn’t directly cover high-growth tech stocks. And let’s be honest: for many retail investors, this category plays a huge role. Knowing when growth names like these are coming back in favor can be just as useful as tracking any of the traditional sectors.

Sector Outperformance Map: This indicator tracks the performance of each sector relative to the S&P 500 over a configurable time window. Behind the scenes, it evaluates percentage return differentials across sectors and applies smoothing techniques to filter out short-term noise. We also factor in recent volatility and normalize sector movements to ensure meaningful comparisons (because some sector are more volatile than others). This helps the map highlight sectors where institutional flows may be shifting — offering a clean and immediate view of which sectors are gaining traction against the broader market trend.

Here is what the map looks like as of May 18th, 2025.

Sector Rotation Quadrant: This indicator blends two key measures — a sector’s relative strength versus the market, and the momentum of that strength over time. Based on these metrics, each sector is plotted into one of four quadrants: Leading, Weakening, Lagging, or Improving.

This layout gives you not only a snapshot of where each sector stands today, but also a sense of its current trajectory. By clicking on a sector name, you can see where it was positioned over the past three months — making directional trends even easier to interpret. For example, a sector moving from Lagging to Improving may signal the early stages of a recovery, while one shifting from Leading to Weakening might be starting to lose momentum. It’s a powerful way to visualize and anticipate sector rotation in real time — especially when timing matters.

As an example, here’s the trajectory of the technology sector over the past three months: it moved from Leading to Lagging, and has now returned to the Leading quadrant as it rebounds out of the correction.

Please note that the recent tariff tantrum caused sectors to rotate faster and more erratically than usual, as the market worked to interpret the implications of the new U.S. presidency and its sweeping policy changes.

Sector matchup (Beta-Adjusted): This is our most analytical sector signal, designed for direct, head-to-head comparisons between any two sectors. Instead of simply looking at raw performance, the tool calculates how each sector has behaved relative to the other — adjusting for differences in volatility and market sensitivity. To do this, we compute a beta between the two sectors, not against the broader market. This allows us to model the expected return of one sector based on the other’s movement, then compare it to the actual return. The result is a market-neutral, pairwise analysis that highlights which sector is truly stronger on its own merits. This approach helps cut through market noise and reveals where real, idiosyncratic strength lies — especially valuable when choosing between overlapping themes or confirming sector leadership.

As an example, just look at the Matchup during COVID between ARKK and QQQ.

The signal clearly captured the explosive strength of disruptive innovation stocks over traditional large-cap tech — well before it became obvious from raw price action, as both were rising sharply at the time. It also highlighted how this outperformance by high-growth tech peaked and began to reverse at the end of February 2021, marking a clear turning point for that segment of the market.

You can also see how Energy (XLE) began a dramatic uptrend against tech in February 2022 — a shift fueled by inflation and the global energy crunch — which was later followed by a steep reversal and has since settled into a largely sideways trend.

Downtrend Exhaustion Dashboard

This section brings together a set of signals we originally referred to as our “Buy the Dip” indicators — a name that reflected how we intended to use them: to identify market bottoms and tactically re-enter during corrections. While these signals have successfully flagged major inflection points (most recently in real-time during the tariff-driven drawdown), we’ve since renamed them the Downtrend Exhaustion Dashboard to better reflect their broader utility. Indeed, these signals aren’t solely about calling a buy. Rather, they help assess when downside pressure is likely exhausted — offering insight that can support a range of actions depending on your positioning and risk profile: reducing hedges, covering shorts, redeploying sidelined cash, or simply staying alert to a potential reversal. They’re designed to work across various correction types — from sharp capitulations to slow, grinding pullbacks — and are meant to complement, not replace, our Hedge model.

Indeed, the Hedge Strategy is designed to signal when market risk is especially high — when stepping aside is often the simplest, safest choice. As a result, it almost never flips back to a bullish state at the very bottom of a correction, since those moments are typically marked by maximum fear and uncertainty — the very definition of risk. But one of the advantages of being hedged during steep declines is that your portfolio may remain relatively intact while opportunities begin to appear. Stocks can become deeply discounted even as overall risk remains elevated. That’s precisely why we developed the Downtrend Exhaustion Dashboard: to help recognize when that moment of asymmetry arrives — when the reward may once again justify the risk.

The amount of time we’ve spent developing these three signals is enormous. In fact, this work started back in 2021 and has evolved significantly since then. A fourth signal is already in the pipeline and should be added to the collection later this summer. After that, I genuinely feel like I will have exhausted (no pun intented) this topic — having explored just about every relevant dataset available. Maybe one day I’ll integrate them into a single composite indicator, much like our Risk Index is built on a blend of three distinct options metrics. But for now, I actually like keeping them separate. I believe redundancy is key here.

Each indicator is intentionally designed to be restrictive, with a strong bias toward avoiding false positives in the middle of a correction. That means it’s entirely possible that not all of them will trigger at a given bottom — and that’s okay. By approaching downtrend exhaustion from multiple angles, we increase the odds of catching real turning points without overreacting to noise. More importantly, redundancy also supports conviction. Buying into a correction may seem easy in hindsight, but in real time — when the red candles are steep and the headlines scream collapse — it’s one of the hardest things to do. That’s why seeing multiple indicators firing simultaneously can make all the difference. It helps validate the moment and gives us the courage to re-enter, reduce a hedge, or simply avoid selling.

For exactly that conviction purpose, some indicators were intentionally designed with tiers of signal strength. Our Market Pattern Exhaustion Index (DE1), for example, includes a rare and highly restrictive red trigger — meant to appear only during the most extreme market conditions. While we were developing the signal, we found that the last occurrence was October 13, 2022, which aligned perfectly with the 2022 bear market bottom. Then, it triggered again on April 7, 2025 — once more, right at the low of the Tariff Tantrum.

The graphical interface allows you to see the current signal strength and color for each of the three indicators, along with their values over the past 10 days. We felt it was essential to give you a way to quickly assess recent signal activity — because “buy the dip” moments don’t happen in a vacuum. In smaller corrections, you might see just one or two minor blue signals, while deeper selloffs — like the one we just experienced — tend to generate multiple, stronger alerts. And since we know how difficult it can be to take action during those emotionally charged moments, we’ve also included a chart window that lets you explore each signal’s historical behavior during previous drawdowns.

Here is a brief description and explanation of each of the three signals.

• Market Pattern Exhaustion Signal (DE1): This signal identifies moments when a correction or multi-leg downtrend shows signs of losing momentum, using a blend of price structure (across multiple timeframes), trading volume, drawdown depth, and realized volatility. It’s designed to flag potential bottoming conditions — where selling pressure may be fading and a rebound could be forming.

The signal is divided into three tiers of strength:

• Blue for moderate signals

• Orange for strong signals

• Red for rare, high-conviction signals

Each level is associated with a value ranging from 0 to 100 — except for red signals, which are not capped and are designed to stand out only in the most extreme market conditions. This tiered approach allows the signal to adapt to different types of corrections. Designing a single threshold to work across all market environments simply wouldn’t be practical: a trigger meant for violent capitulations would likely miss slower, low-volatility pullbacks — and vice versa.

For example, during a soft correction where the largest daily losses are around -2%, don’t expect to see an orange or red signal. In those environments, a blue signal — like the one we saw at the bottom of the April 2024 pullback — is often the only thing that will appear:

In contrast, deeper or faster corrections tend to produce more severe signals. Blue signals often appear mid-way through, right as a dead-cat bounce sets up (still very tradable!). But the eventual bottom usually aligns with an orange or even red signal — as was the case during the Tariff Tantrum:

Another instructive case is the August 2024 correction. Had it not been for the yen carry trade disruption that erupted on Sunday night, the bottom of that moderately volatile summer selloff would likely have been Friday, August 2 — when we recorded a very strong blue signal. But the event in Japan caused a dramatic volatility spike at the open, which elevated the signal to orange, sealing the bottom in real time:

• Protection Premium Distortion: This signal tracks unusual shifts in the cost of market protection, highlighting moments when investors may be overpaying for downside insurance relative to actual price movement. These distortions often appear near market bottoms — signaling heightened fear, and the potential for reversal as sentiment begins to stabilize.

Fun fact: this indicator was largely designed by ChatGPT’s Advanced Reasoning Model (o1). I decided to give it a shot after realizing, while playing with this model, that it could answer some of the hardest technical questions I usually reserve for Ph.D. qualification exams — the kind that regular ChatGPT models typically fail. More impressively, it solved a question that had stumped every Ph.D. candidate I’d posed it to — except for two people: Jennifer Kwiatkowski (WU co-founder) and someone who is now a highly successful university professor in AI. That was the moment I told myself: “If this model can reason at the level of two of the smartest people I know… maybe it can help build an indicator.”

And it did. That might sound anecdotal to someone reading this post two or three years from now, looking to understand how the WU Advanced Signal Datahub work. But as of late 2024, when we were working on it, this was far from typical — ChatGPT-4o wasn’t capable of doing this kind of structured, domain-specific signal design. This made the contribution from the advanced reasoning model genuinely surprising… and honestly, pretty exciting.

While I helped with some of the signal processing techniques, the model surprised me with its conceptual thinking. It proposed what we should be looking for to identify the bottom of a correction, which datasets could reveal those dynamics (including two I’d never considered or even heard of), and even produced a rough first version of the code.

The result is a remarkably robust signal with two tiers:

• A blue signal for weaker corrections

• An orange signal for stronger, high-conviction moments

These signals fired cleanly during several recent drawdowns:

– The April 2024 correction

– The Summer 2024 pullback

– The Christmas 2024 slow-motion correction (we actually used it live to call the bottom of that one.)

It also flagged the initial bottom of the Tariff Tantrum ahead of the mid-correction bounce, but didn’t trigger again at the final low — and that’s precisely why we built this dashboard around multiple indicators. In this case, the relationship between protection pricing and market movement didn’t become statistically distorted at the final leg down, which can happen from time to time. But our two other indicators did catch the bottom — illustrating why looking at different angles of market stress increases reliability and helps maintain conviction when it matters most.

• Option Pricing Conflict Index: This final indicator identifies inconsistencies across different facets of option pricing — such as short-term implied volatility versus longer-term structural hedging behavior. When these elements diverge, it often signals underlying stress or uncertainty in the market — a dynamic that tends to appear near inflection points.

Unlike the other two indicators, which generate punctual, binary signals on specific days, this one can remain elevated for several sessions. Instead of pointing to a precise bottom, it creates a zone where a reversal is statistically more likely to occur. Its output ranges from 0 to 100. Readings near 100 suggest we may be at or very near the bottom of a correction — or, in the case of larger drawdowns, that a bounce is imminent. However, in more moderate pullbacks, like those in Fall 2023 or April 2024, it typically won’t reach those extremes.

Still, its pattern at bottoms is remarkably consistent: it peaks. So when you see this signal start to drop after a short period of elevation, it’s often a sign that the worst is already behind us.

Other Signals

In this final section of the Advanced Signal DataHub, we’ve included several additional tools we frequently rely on — signals that don’t neatly fall into the earlier categories but are nonetheless helpful for navigating the market. Some, like the Sahm Rule, are more contextual and may be rotated out over time as conditions change. For example, once we’re clearly out of a recessionary environment, the Sahm Rule might make way for more timely signals. This section is intended to remain dynamic, evolving as we continue to develop new tools.

Volatility Trend

Market volatility doesn’t move randomly — it comes in clusters. These clusters can play out over the near term but also follow broader multi-month cycles. Understanding which volatility regime we’re in is critical, especially when using leveraged positions. As discussed in our blog post on leveraged ETFs, the biggest threat to leveraged performance is a volatile sideways market — an environment where leverage tends to underperform its amplification factor.

To help identify these regimes, we built a volatility trend indicator specifically designed to reduce whiplash. It categorizes the market into three states:

·      Red for sustained high volatility

·      Green for a stable, low-volatility environment

·     Yellow for transitional phases, where the market is attempting to shift from one state to another

Here’s the historical chart for this signal over the past five years — you’ll notice that volatility environments tend to persist for extended periods, often close to a year.

We knew it was going to be a rougher period in the stock market starting in the summer of 2024, when this (already existing) indicator flipped to red and failed to transition back to green — despite multiple attempts. That persistent red state was a clear sign that we were stuck in a high-volatility environment, and it helped set expectations appropriately. When the market tries several times to revert to green and fails, it tells us that risk remains elevated and that the path forward is likely to be choppy.

Sahm Rule (WU Edition): This indicator is built on the widely followed Sahm Rule, which flags the start of a recession when the national unemployment rate rises by 0.5% or more above its 12-month low. While effective, the original threshold—chosen by economist Claudia Sahm—was somewhat arbitrary. At Wealth Umbrella, we revisited this model with a more data-driven lens and tested a range of thresholds across historical recessions using Wilson score intervals to assess predictive accuracy. The result? We found that a slightly higher threshold of 0.61% offers stronger statistical performance and better real-time reliability. In fact, while the original 0.5% threshold produced a false positive in late 2024, our WU edition did not — and has yet to fail.

The indicator display highlights this logic: it shows in green when the distance from the original threshold remains safe, shifts to orange in a transition zone between the traditional and WU thresholds, and flips to red when our WU recession trigger has been breached. This layered design helps users distinguish between early warning signs and confirmed economic deterioration.

Current Trade in context: The final section of our WU Advanced Signal Datahub introduces a pair of visualization tools designed to help you better assess the current Hedge trade in the context of the strategy’s full history. While the Hedge model is built to operate in a rules-based, binary fashion — either in or out — many investors may want to apply it more flexibly. These tools can support that by providing a clear view of how today’s trade compares with previous ones, helping you make more nuanced, data-informed decisions.

As we’ve noted before, the Hedge Strategy is not intended to capture market bottoms, and it’s also unlikely to exit precisely at the top — though that can occasionally happen. Most of the time, the hedge will be triggered after pulling back of something around -3% from the peak. That may seem like a modest cost to avoid deeper downside, but on QQQ this mean more -4.5% and when using leveraged instruments (which amplifies both gains and losses), that same -3% market drop can equate to losses of -18% on TQQQ, due to compounding effects. For example, this was roughly the scale of retracement we experienced before exiting TQQQ (still at profit) in February 2025 — just ahead of the deeper market meltdown.

Given this, some users might choose to play the Hedge Strategy more proactively, especially when a current trade has already produced outsized returns relative to its historical peers. Taking partial profits, reducing leverage (e.g., shifting from TQQQ to QQQ or SPY), or even stepping aside temporarily are all valid approaches — particularly when backed by statistical context. Personally, I’ve done this on several occasions, which is what inspired us to build these tools for our members.

The first graph shows where the current trade (in red) sits compared to every historical Hedge trade since 2006, using two axes: profit and number of trading days.

If the red dot is already high on the profit axis and relatively early on the time axis, it may indicate that the trade has already outperformed expectations — and that locking in gains, even partially, could be prudent.

The second graph shows a distribution histogram of all trade profits, with the current trade’s position highlighted in red. This gives an even clearer picture of how the present trade ranks in terms of historical outcomes, allowing you to evaluate how probable it is that further gains lie ahead versus the risk of mean reversion.

If you’ve read this far, you’re likely a seasoned investor who prefers having data at your fingertips. Our goal with these visualizations is not to override the Hedge signal, but to empower you with additional context — so that if you choose to fine-tune your exposure around it, you can do so with more confidence and clarity.

Conclusion

The Advanced Market Signal Datahub is the part of our WU Advanced subscription tier where you’ll find many of the same types of signals as in our regular S&P 500 offering — but deeper, broader, and more experimental. It’s built for those who like to drive their decisions with data and simply wanted more. While our core S&P 500 package is built primarily around risk management, this Advanced Datahub is our take on capturing the other side of market dynamics — from momentum to sector rotation to potential bottoms.

Along with TuneMap, this is probably the most dynamic part of WU Advanced. We don’t see this page as something static, but rather as a living, evolving layer that will continuously be shaped by new research, new indicators, and new market regimes. Many signals will first be tested in our internal Sandbox before earning a place here.

We also don’t pretend to have a monopoly on good ideas — and we’d love to hear from you. If there’s a signal you think we should explore or a market dynamic you’d like us to model, don’t hesitate to send your thoughts and suggestions to dev@thewealthumbrella.com.