A Practical Guide to the WU Stock Health Dashboard

The main purpose of our Stock Health Dashboard is to offer a quick, intuitive snapshot of whether a company is in good shape — and whether its stock is in a potentially attractive position for investing. You’re not going to find every possible financial or technical metric here. There are already countless free resources, like Yahoo Finance, that provide exhaustive detail. Instead, we focused only on the indicators we believe are most essential — or those we specifically designed ourselves — organized across five key dimensions of a company. We also made the dashboard highly visual, so anyone can quickly assess the health of a business and its stock without getting lost in a sea of numbers.

Of course, deep financial and technical analysis becomes important at a certain stage in the investment process. But it’s easy to drown in data, especially when many platforms throw everything at you at once. Our goal was to strip things down to what truly matters.

One of the things we tested the most during development was how clearly the dashboard distinguishes strong companies with solid fundamentals from the weaker, shakier ones. And the difference is instantly visible. Just look at NVDA, which scores highly across the board

and compare it to Virgin Galactic (SPCE).

Or, if you think Nvidia is too much of an outlier, take The Trade Desk: a company that’s remained fundamentally solid despite some volatility in its stock price.

So now, let’s dig into each section of the dashboard — what it contains, and why it matters.

Technical

This section highlights a set of widely used and time-tested technical indicators that help assess whether a stock is currently in a favorable position for investment. While some of them are considered basic, they remain among the most reliable and broadly adopted tools in technical analysis — and for good reason: they’ve proven their worth over decades of market cycles. To complement these classics, we’ve also included one of our own favorite custom-built indicators.

MACD (Moving Average Convergence Divergence): This momentum-based indicator tracks the relationship between two moving averages (usually a short- and long-term EMA). When the MACD line crosses above its signal line, it often signals bullish momentum — and vice versa. It’s a staple for spotting early shifts in trend direction, particularly when paired with volume and context.

RSI (Relative Strength Index): A popular oscillator that ranges from 0 to 100, the RSI helps determine whether a stock is overbought (typically above 70) or oversold (typically below 30). It’s especially useful for identifying potential reversal zones or confirming ongoing trends when used alongside other tools.

BAA (Beta-Adjusted Alpha): This is our proprietary metric designed to measure a stock’s excess return, adjusted for how sensitive it is to the market (its beta). What makes BAA powerful is that it expresses this relative outperformance (or underperformance) in terms of standard deviations, helping to highlight statistically significant moves. In other words, it tells you when a stock is really diverging from what its market relationship would suggest — not just drifting slightly.

52-Week Range (with SMA Overlay): This shows where the stock is currently trading relative to its high and low over the past year. It’s a fast way to contextualize how “hot” or “cold” a stock is on a longer timeframe. We also overlay the SMA50 (50-day simple moving average) and SMA200 (200-day) on this range. The color of this overlay provides a quick signal:

• If the SMA50 is above the SMA200, the trend is considered bullish.

• If the SMA50 is below the SMA200, the trend is generally bearish.

  
  

Together, these indicators give a well-rounded technical snapshot: momentum, trend strength, positioning, and relative outperformance — all at a glance.

Valuation

The Valuation section of our Stock Health Dashboard includes time-tested metrics that help assess how attractive a company’s valuation is, and whether it may currently represent a compelling investment opportunity.

-Market Cap: Stock market capitalization (or market cap) is the total value of a company’s outstanding shares, calculated as share price multiplied by the number of shares. It’s a quick way to gauge a company’s size, risk profile, and how it might fit into an investment strategy—larger caps tend to be more stable, while smaller caps often carry higher growth potential and risk.

-Revenue Multiple: The revenue multiple is a valuation metric calculated by dividing a company’s market cap by its annual revenue. It helps investors understand how highly the market is pricing a company relative to the sales it generates, which is particularly useful when earnings are negative or inconsistent. While this metric isn’t commonly used for well-established companies with strong profits, it is a key benchmark for evaluating growth stocks. In these cases, companies often reinvest heavily to fuel revenue expansion, and earnings may be minimal or negative in the short term. The revenue multiple offers a way to assess whether the market’s pricing aligns with that growth potential. This metric is also widely used in the private venture capital world, where high-growth companies often trade at steep premiums. In that context, rapid revenue growth can quickly make an initially expensive-looking valuation seem more reasonable over time.

-Revenue Multiple Z-Score (coming soon): The Revenue Multiple Z-Score places a stock’s current revenue multiple in the context of its own historical range. Rather than comparing the company to its peers—which can be misleading for long-term premium-growth stocks—this metric shows how expensive or cheap the stock is relative to itself.

This distinction is crucial for companies like Shopify, which have historically traded at high revenue multiples for extended periods. Comparing Shopify’s revenue multiple to lower-multiple peers would have flagged it as severely overvalued throughout 2018–2021—yet this was precisely the period when its stock price experienced massive gains. By anchoring the valuation to a stock’s own history, the Z-Score offers an alternative lens that can reveal opportunities traditional comparisons might miss. It can help investors spot moments when a premium-growth stock is trading at a relative discount—even if its absolute valuation remains high by conventional standards.

This metric is particularly useful for growth investors seeking to understand valuation dynamics in names that don’t fit neatly into peer-based frameworks.

-P/E ratio: The Price-to-Earnings (P/E) ratio is a valuation metric calculated by dividing a company’s share price by its earnings per share. It reflects how much investors are willing to pay for each dollar of profit, and is widely used when evaluating established, profitable companies. While revenue multiples are more relevant for early-stage or high-growth companies with little to no earnings, the P/E ratio becomes more meaningful once a business reaches maturity and generates consistent profits. It helps investors compare valuation levels across peers and sectors, and gauge whether a stock is priced attractively relative to its ability to generate earnings — which, at this stage, is often the market’s primary focus.

-EPS: Earnings Per Share (EPS) is a fundamental metric that represents the portion of a company’s profit allocated to each outstanding share of stock. It’s calculated by dividing net income by the number of shares, and serves as a basic measure of a company’s profitability on a per-share basis. EPS is a cornerstone of financial analysis and is commonly used in valuation ratios like the P/E ratio.

EPS becomes especially relevant as companies reach profitability and begin to deliver returns to shareholders, whether through reinvestment, dividends, or buybacks. It’s also one of the most closely watched numbers during earnings season, since even small surprises — positive or negative — can significantly influence a stock’s price.

-Rule of 40: The Rule of 40 is a benchmark often used to evaluate the financial health of high-growth companies, especially in the software and SaaS sectors. It combines revenue growth and profitability (typically measured by operating or free cash flow margin), and suggests that the sum of the two should exceed 40%.

This rule becomes especially useful when a company is transitioning from rapid, unprofitable growth to a more mature phase where profitability begins to matter. As growth naturally slows, the Rule of 40 offers a framework for rewarding companies that can begin to deliver earnings without completely sacrificing expansion. It’s a practical shorthand to assess whether a company is scaling in a sustainable, investor-aligned way.

Financial

The Financial section is designed to assess how a company generates return on equity and to highlight potential signs of financial distress. While traditional financial metrics such as earnings, revenue, and margins are covered in the Earnings section, this area provides a structural view of financial health by focusing on return decomposition and bankruptcy risk. These indicators are particularly useful for identifying companies that may appear solid on the surface but show early warning signs of imbalance or vulnerability.

DuPont Tree: The DuPont analysis breaks down a company’s Return on Equity (ROE) into three core components: profitability, efficiency, and leverage. This decomposition provides a clearer picture of what’s driving a company’s returns and where strengths or risks might lie:

·       Profit Margin (Net Income / Revenue): This measures how much profit the company generates from its revenue. A higher margin suggests strong cost control or pricing power, while a low margin may indicate operational inefficiencies or margin pressure from competition.

·       Asset Turnover (Revenue / Total Assets): This reflects how efficiently a company uses its assets to generate sales. A higher ratio means the company is making good use of its asset base, while a lower ratio may suggest underutilized assets or a capital-heavy model.

·       Financial Leverage (Assets / Equity): This shows how much the company relies on debt relative to shareholder equity. Higher leverage can amplify returns but also increases financial risk, especially in periods of declining earnings or rising interest rates.

By analyzing these three dimensions together, the DuPont Tree offers insight not just into how much return a company is generating, but how it is being generated — through operational excellence, asset efficiency, or financial engineering.

 It’s also worth noting that the DuPont formula is multiplicative by design, meaning that weakness in any one pillar can significantly drag down the overall Return on Equity, even if the company is strong in the other two. For example, a company with excellent profitability and leverage, but poor asset efficiency, will still show a modest ROE. This makes the DuPont Tree a strict but highly informative framework, especially useful for identifying structural imbalances that might otherwise go unnoticed in headline metrics.

Bankruptcy Scores: This subsection includes three widely used models for evaluating financial distress. These models combine multiple financial ratios into a single score designed to flag companies at risk of insolvency. We include multiple models because no single indicator works universally across all industries or market conditions. Each model has its own strengths and blind spots — some are more conservative, others better suited to certain sectors or accounting assumptions. By using a diversified set of scores, we introduce redundancy into the analysis, which improves reliability and reduces the chance of missing early warning signs. Like this is definitely a scary company

But, I am not necessarily scared for this one:

·       Altman Z-Score: A classic credit-risk metric that blends profitability, leverage, liquidity, and activity ratios to predict the likelihood of bankruptcy. Commonly used for manufacturing and industrial companies. While other models have been proposed to better reflect more modern business contexts, recent studies using NYSE and Nasdaq data have shown that the Altman Z-Score remains highly effective at predicting bankruptcy even today.

·       Zmijewski Score: A statistically driven model that focuses on financial leverage, profitability, and liquidity. Often more conservative, it may identify risk where Altman does not.

·       Grover G-Score: A refinement of the Altman model designed to improve predictive accuracy, especially in more modern or service-oriented business contexts.

Together, these indicators provide a compact yet powerful lens into the financial resilience of a company, helping users spot hidden risks or validate long-term stability.

Earnings

This section uses the most recent earnings reports (updated the day after they’re released) to display key metrics that, based on our analysis, the market tends to reward most when a company performs well in these areas.

Operating Margin: This shows the percentage of revenue left after covering operating expenses, giving a sense of how efficiently the company runs its core business. A higher margin suggests better control over costs relative to revenue.

Cash Flow Margin: This measures how much of a company’s revenue is converted into operating cash flow. It reflects the company’s ability to turn sales into real cash, which is key for funding operations and growth.

Revenue Growth: This indicates how much the company’s top-line sales have increased compared to the previous period. Strong revenue growth suggests healthy demand or market expansion.

EPS Growth: This shows the change in earnings per share over time, reflecting whether the company is becoming more profitable on a per-share basis. It’s often used to track how effectively a company is scaling its earnings.

Analysts

This section compiles the latest expectations and sentiment from professional equity analysts. While analysts don’t always get it right, market participants often react strongly to changes in their forecasts and recommendations. These insights can help investors understand how the broader investment community is pricing in future performance.

EPS Estimate: The consensus forecast for the company’s next reported earnings per share. It reflects what analysts expect in terms of profitability and is often a key driver of short-term stock movement around earnings announcements.

Revenue Estimate: The aggregated projection for upcoming revenue. It gives a sense of expected top-line performance and can influence investor sentiment, especially for growth-oriented companies.

Analysts Price Target (Coming Soon): The aggregated forecast of where analysts believe the stock is headed, based on their research and valuation models. This data includes the mean, maximum, and minimum price targets submitted by covering analysts. It offers insight into market expectations and perceived upside or downside potential.

While not a guarantee of future performance, analyst price targets can influence investor sentiment—especially when they diverge meaningfully from the current share price. In particular, the spread between the highest and lowest targets can reflect varying levels of conviction or uncertainty about the company’s future.

Ratings: This is a distribution of analyst recommendations, ranging from Strong Sell to Strong Buy. We display this as a bar chart, where the length of each bar represents the number of analysts in each rating category. This helps visualize the balance of sentiment and identify whether there is broad agreement or division in the outlook.

Alt Data

There are other types of data we find very useful when analyzing a specific company, even if they don’t directly answer the question, “Is this a good stock to invest in?” We grouped these into the Alt Data section. Just because these metrics don’t contribute directly to the stock health score doesn’t mean they’re not important — in fact, they often provide valuable context for understanding how a company operates or how it’s positioned. Below is a brief description of each data point and why we believe it matters.

ATR (Average True Range): ATR measures the average daily price movement of a stock over a given period, offering insight into its recent volatility. Unlike trend indicators, ATR doesn’t tell you whether a stock is rising or falling — it simply reflects how much it moves. A higher ATR means wider daily swings; a lower ATR suggests more stable behavior.

While not predictive, ATR is widely used by fund managers and active traders for risk management, particularly in two areas: stop-loss placement and position sizing.

For stop-losses, a common method is to set a trailing stop at 2× the ATR below the highest price reached in an uptrend. This allows the position to remain open during normal price fluctuations while protecting against significant reversals — helping to secure profits without being stopped out prematurely.

For example, as of writing, MARA is trading at $16 per share with an ATR of $1.15. Based on the 2× ATR rule, a trailing stop-loss would be placed at $13.70 ($16 – 2 × $1.15). If the stock closes at $17 the next day and the ATR remains the same, the stop would be adjusted upward to $14.70. This process continues as the stock moves higher, allowing profits to be locked in while still giving the trade enough room to fluctuate naturally.

For position sizing, ATR is often used to calculate how many shares to buy based on a fixed dollar risk per trade. For example, if a trader wants to risk $500 on a trade and the stock’s ATR is $2.50, they would buy 200 shares ($500 ÷ $2.50). This ensures that all positions, regardless of a stock’s volatility, expose the portfolio to the same percentage of risk, making volatility-adjusted risk allocation more consistent across different stocks.

Beta: Beta measures how sensitive a stock is to movements in the overall market — typically compared to a benchmark like the S&P 500. A beta of 1 means the stock tends to move in line with the market. A beta above 1 suggests the stock is more volatile than the market (it amplifies moves), while a beta below 1 indicates it tends to move less.

For example, a stock with a beta of 1.3 would, on average, gain 1.3% when the market gains 1%, and lose 1.3% when the market drops 1%. On the other hand, a defensive stock with a beta of 0.7 would typically rise or fall only 0.7% for every 1% move in the market.

Beta is often used by investors to understand how much market risk they’re taking when adding a stock to their portfolio. Higher-beta stocks might offer bigger gains in bull markets, but they can also fall harder in corrections. Lower-beta stocks tend to offer more stability, which can be attractive in volatile or uncertain environments.

DarkPool Activity: Dark pools are private exchanges where institutional investors can buy or sell large blocks of shares without revealing their intentions to the public market. While these trades are hidden from the order book during execution, they must be reported after the fact — typically by around 6:30 p.m. ET each day.

Our DarkPool Activity indicator tracks the reported dark pool volume for each stock and measures how it deviates from its historical average, using a standard deviation model similar to the one we apply in our QQQ signal within the Hedge Strategy. This allows us to detect unusual accumulation or distribution patterns that may not yet be visible in the regular market volume.

Although dark pool data is delayed, we’ve observed that spikes in activity — especially when statistically significant — can sometimes act as a leading signal, hinting at institutional positioning ahead of broader market moves. For that reason, this indicator may provide useful early context for shifts in sentiment or interest around a particular stock.

Market Neutral Price Trend: This indicator was designed to help assess whether a stock’s price trend is truly driven by company-specific strength or weakness, or simply riding the broader market. To do this, we adjust the stock’s performance by accounting for its historical sensitivity to the market — commonly known as its beta.

We start by calculating the return the stock should have delivered based on recent market moves and its beta. We then compare that expected return to the stock’s actual return. The difference between the two shows whether the stock is outperforming or underperforming on a market-neutral basis.

This method strips out broader market noise and gives a cleaner read on a stock’s individual momentum. It can be especially useful for identifying emerging leaders before they’re obvious in raw price action — or spotting early signs of breakdowns hidden within a strong index.

This signal has proven useful in several notable cases. Take Nvidia (NVDA), for example. After moving roughly in line with the beta-adjusted market through most of 2022, it began to meaningfully outperform in November 2022, right after ChatGPT went viral and investors began to realize Nvidia would be one of the main beneficiaries of the AI wave.

Another example is Tesla. After significantly outperforming the market through most of 2022, it began to underperform sharply starting in late September, as the broader EV sector fell out of favor.

Perhaps the most illustrative case is ARKK. Cathie Wood’s flagship fund started gaining traction in late 2019, with its outperformance accelerating during the COVID period, ultimately becoming one of the best performers of 2020. However, its decline didn’t begin with the general market in early 2022 — it started as early as February 2021. That extended underperformance is clearly visible in the Market Neutral Price Trend.

This is exactly why we created the Market Neutral Price Trend indicator. While investing in the overall market carries long-term risks that tend to resolve over time — as most broad downturns eventually recover — individual stocks don’t follow that same pattern. Some stocks rise, peak, and then decline without ever coming close to their previous highs again. Personally, I’m extremely patient with market-level positions, but far less tolerant when it comes to individual stocks as they can cause permanent damage in a portfolio. I wanted a tool that could help me spot real, structural trend changes early — especially when those shifts are masked by broader market strength. The Market Neutral Price Trend was built with that goal in mind: to strip out the market noise and reveal what’s really happening underneath. It has since become for me one of the most useful tools in our entire dashboard. I recently initiated a position in The Trade Desk (TTD) — a stock I’ve always liked, but had previously avoided due to valuation concerns. I took the trade after noticing, while testing our Stock Health Dashboard, that not only were its fundamentals still very strong, but it was also on the verge of flipping from underperforming to outperforming on our Market Neutral Price Trend indicator. So far, that decision has paid off — I’m currently up around 35% on what’s still a very recent trade. Same story with Micron (MU).