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Every term, metric and signal the app uses — explained in plain English. Each entry covers what it is, why it matters, and sometimes how it's figured for a long-term investor.
The big annual report every US public company files with the SEC. Contains the audited financials, what the business actually does, and a 'risk factors' section listing what could go wrong.
The single most important document for understanding a business. The 'risk factors' section is especially useful — written by the company itself, in plain English.
The quarterly financial report. Less detailed than the annual 10-K but more current.
Useful for spotting recent operational changes — new products, lawsuits, supply chain issues — between annual reports.
How much interest the US government is currently paying on 10-year bonds, as an annual percentage.
This is the 'reference price' the whole market is measured against. When it rises, almost all other asset prices feel pressure.
Pulled from government yield data when available, otherwise a liquid Treasury market proxy, expressed in percent (4.5 means 4.5% per year).
How much the 10-year Treasury yield has moved over the last 30 days.
Sharp rises tighten financial conditions for stocks and long bonds; sharp falls can ease them.
Latest 10-year yield from government data (or a market proxy) minus the value about 30 days back.
What the dividend yield has averaged over the past 5 years on this stock.
A sanity check. A yield way above this average usually means the price dropped, not that the dividend got more generous.
A plain-English snapshot of what the company does, how it earns money, and where it is headed — so you can follow the story without reading a filing.
Once you know the business, the scores and charts on the rest of the page are easier to read in context.
When a recent annual filing is available, it can be used as background for accuracy, but this section is meant to explain the business, not to walk you through the report page by page.
The score landed within a few points of the next friendlier label bucket — close enough that a small move could change the wording.
Treat it as almost in that zone, not a promise the label will flip. Markets wiggle day to day.
A short write-up that turns the numbers into a story you can actually read. It has three parts. The bull case is the argument FOR the stock — what's working, what could keep working, why an optimist would own it. The bear case is the argument AGAINST — what's weak, what could break, why a skeptic would avoid it (or sell it). Key risks are the specific things that could go wrong: regulation, competition, a soft balance sheet, a customer concentration problem.
Numbers alone don't tell you why anything matters. Reading both the bull case AND the bear case together is how long-term investors build conviction — if you can argue both sides honestly, you understand the stock. If only one side feels true to you, you probably haven't looked hard enough.
The middle (median) of where analysts think the stock could trade about a year out, based on their published price targets.
The median is less swayed by one wild outlier than a simple average. Still a sentiment snapshot — targets get revised after big price moves.
Each analyst's dollar target is collected; the median is the middle value when you sort them. Upside percent compares today's price to that median.
The combined opinion of professional Wall Street analysts who cover this stock. Scaled 1 (Strong Buy) to 5 (Strong Sell).
Useful as one input among many. Analysts as a group tend to follow the price rather than lead it, and rarely issue outright 'Sell' calls.
Third-party data (here via yfinance) averages each firm's letter grade after mapping it to a number. The label is the plain-English version of that average.
A colored bar from the lowest to the highest analyst target, with ticks for today's price and the median.
Lets you see at a glance whether the stock sits below, inside, or above the Street's target cloud.
The bar is drawn between min and max targets on a price scale; a black tick marks last price and a green tick marks the median.
An estimate of the stock's typical daily price swing, expressed as a percentage. Big number = jumpy stock.
Useful for sizing positions and setting realistic expectations. A stock that normally swings 5% a day is a different experience than one that swings 1%.
How much the stock has historically moved when the overall market moves. Beta 1.0 = moves with the market. Beta 1.5 = swings 50% more. Beta 0.5 = half as much.
A rough proxy for how bumpy the ride will be. Higher-beta stocks tend to amplify both wins and losses.
Tells you if the company itself is in good shape: making real money, not buried in debt, and ideally growing.
Over the long run, the stock follows the business. A healthy company tends to keep getting more valuable; a sick one slowly bleeds.
A single score from −100 (weak overall reading) to +100 (strong). It rolls the four lenses into one line for that time horizon.
Easier to scan than four separate numbers. The colored label on the card uses the same score with fixed cutoffs, so everyone sees the same mapping.
Each lens score is multiplied by a horizon-specific weight, the pieces are added, and the result is rounded. The gray bar underneath places your score on a line from left (more negative) to right (more positive), with ticks at the same cutoffs as the labels.
The range the 'true' hit rate is likely to fall within. A statistical hedge against small-sample lucky streaks.
A 60% hit rate based on 10 trades could easily be luck. The same 60% based on 500 trades is much more meaningful. The confidence range captures that.
Uses a Wilson score interval around the observed hit rate so wide ranges mean the sample is still small or noisy.
How much consumer prices have risen over the past year. The standard inflation measure.
Above ~3% historically pressures both stocks (companies feel margin squeeze) and bonds (interest rates rise).
A simple read of credit quality for bond funds — Treasury, investment-grade, high-yield, or municipal — inferred from how the fund is classified in the feed.
Credit class tells you how much default risk the portfolio tends to carry, separate from interest-rate risk.
The fund's distribution yield or similar payout measure as of the latest data pull.
For income-focused funds, this is the cash return you see before price changes.
Can the company pay its bills over the next 12 months using the cash and short-term assets it has now?
Below 1 is a short-term liquidity yellow flag. Most healthy companies sit between 1.5 and 3.
Distribution yield minus trailing inflation — a rough real income read for bond funds.
Nominal yield can look fine while inflation quietly eats it; real yield adjusts for that story.
How much the company has borrowed compared to what the owners have put in. Higher means more borrowed money in the mix.
Lower is generally safer. Heavy debt amplifies the good times and crushes you in the bad ones. A lot of debt = less margin for error.
The cash income the fund distributed over the past year as a percent of today's price — the fund version of a dividend yield.
For bond and income ETFs this is the headline cash return before price changes.
Uses trailing twelve-month distributions from the data feed divided by the current fund price (or NAV), expressed as a percent.
The annual cash the company pays out to shareholders, expressed as a percentage of the stock price. If yield is 3%, you'd collect $3 per year on every $100 of stock.
Part of your total return comes from dividends. But a very high yield often signals the price has crashed — always check whether the dividend is well-covered.
How far the stock has fallen from its recent high. A 20% drawdown means the stock is down 20% from its peak.
Frames the worst case that real investors have actually lived through with this asset. Helps set realistic expectations before things get rough.
How far below its recent all-time high the price sits right now, as a percent.
Deep drawdowns can mean stress or a cheaper entry; shallow drawdowns mean the asset has been riding near its peak.
Compares today's price to the highest close seen in the lookback window: (high minus today) divided by high.
How much the company's profit per share grew compared to a year ago.
Over the long run, stock prices track profits. Growing earnings is the engine.
Tells you if today's economy (interest rates, inflation, growth) is a tailwind or a headwind for this type of asset.
A great company in the wrong moment can underperform for years. Same business, different weather.
Like P/E but adjusts for the company's debt and cash. Tells you what you're really paying for the business itself.
Useful when comparing companies that borrow very different amounts. P/E alone can make a debt-heavy company look misleadingly cheap.
The annual fee the fund charges as a percentage of the money you have invested in it. Comes straight out of returns before they reach you.
Cost is the single most reliable predictor of long-term fund performance. Two funds tracking the same thing usually differ by their expense ratio over decades — and that gap compounds.
A shaded fair-value band through time, with the stock's actual price on top. The band is built from three different fair-price estimates each month.
When price hugs the bottom of the band for a long stretch, the market is pricing the business cheaper than those models suggest. When it rides far above, the market is paying a premium — sometimes deserved, sometimes not.
Each month the app takes three estimates — earnings power, a PEG-based fair value, and a multiple based on five-year median P/E times current EPS — and uses the lowest as the band bottom, the highest as the top, and the average as the dashed midline. Price is the monthly close.
Does the company actually produce enough cash to cover its dividend payments? A simple yes/no check.
If the answer is 'no', the company is paying dividends with borrowed money or reserves. That's often a precursor to a dividend cut.
The actual cash the business produces each year, expressed as a percentage of the stock price. (Free cash flow = the cash left over after running the business and reinvesting.)
Cash is harder to fake than accounting profits. A solid business yielding 5%+ in real cash is a strong sign of real, distributable value.
The fund's broad bucket from the data provider (for example large blend, government bond, or sector tech).
Two tickers can sound similar but behave differently if one is a narrow sector bet and the other is diversified.
What the fund actually owns: its top individual holdings, the sectors they fall into, and how diversified the basket is.
Two funds with the same name can hold very different things. Top-heavy funds (a few names dominating) carry more single-name risk; broadly diversified funds smooth out the bumps but also dampen the peaks.
Whether the fund looks cheap or expensive today compared to its own past — based on the yield it currently pays out vs how much it usually pays.
Funds don't have a P/E to read. But if a fund is currently paying out more income per dollar than it usually does, you're typically getting a better deal than a buyer would have a year ago. The opposite when the yield is unusually low.
A −100 to +100 score for whether the fund looks historically cheap or expensive based mainly on its payout versus its own past.
Funds do not have a classic P/E; comparing today's yield to where it usually sits is one readable substitute.
Built from the gap between today's distribution yield and the fund's historical yield distribution, with caps so tiny yield moves do not swing the score to extremes.
A plain label for the fund's current yield versus its own history — words like cheap, fair, pricey, or expensive from the value model.
Funds do not have a P/E like stocks; comparing today's payout to its past is one readable stand-in for cheap versus rich.
A combined view of how cheap the stock is, how strong the business is, and how fast it's growing.
The most important lens for buy-and-hold investing. Compounding works through the business doing well — not chart patterns.
Valuation, quality, and growth each get a sub-score from −100 to +100 using ratio-based rules; the lens headline blends those buckets (and fund-specific fields for ETFs and bonds).
Out of every dollar the company sells, how much is left after paying the direct cost of producing the product.
Indicates pricing power. Software and luxury brands often keep 70%+. Groceries keep more like 20%. Higher usually means a more durable business.
How fast the company's sales and profits are growing compared to a year ago.
Growth multiplies the value of a good business. But growth alone — without profits or quality — is fragile when conditions get tough.
Year-over-year revenue and earnings growth rates are compared to typical ranges; faster growth pushes the score up, shrinking or negative growth pulls it down.
A one-line summary of how the stock looks today across all four signals.
Describes the picture, not a recommendation. The same picture can be right or wrong for different people, goals, and time horizons.
How much extra interest investors are demanding to hold riskier 'junk' bonds instead of safe Treasury bonds.
When this widens, it's a sign of credit stress — companies are seen as more likely to default. Spreads above ~6% usually accompany recessions or sharp drops.
The highest published price target in the set the app could fetch for this symbol.
Shows the bullish extreme of the Street's range. One optimist can stretch this far from the pack.
Taken as the max of the same target list used for the median.
The median of that same real-yield measure through history for the fund.
Shows whether today's real payout is high or low versus the fund's own past.
The 25th percentile of this fund's past yields — yields were lower than this only about a quarter of the time.
Helps you see if today's payout is unusually high or low versus history.
The 75th percentile of past yields — the fund paid more than this only about a quarter of the time.
If today's yield is above this line, payouts have rarely been richer.
The median of past yields — half the time the fund paid more, half the time less.
A simple middle reference for how generous payouts have been through different markets.
Charts that look back several years: price with averages, valuation versus the sector, a fair-value band, and yearly return-on-capital bars when data exists.
Today's snapshot makes more sense when you see whether price and fundamentals are normal compared with their own past.
Each chart uses the same calendar dates where possible so you can compare patterns. Weekly or monthly frequency depends on the series (see each chart title).
How this metric compares to the same stock's own past — typically the last 5 years.
Strips out noise. A stock trading at its 5-year-low P/E is often more interesting than one trading at the sector median.
How often this signal has been right historically — what percentage of the time the asset moved in the predicted direction over the given period.
Anywhere near 50% is essentially a coin flip. Sustained hit rates above ~55–60% with a lot of data behind them are worth paying attention to.
The app looks at past dates when this signal fired, checks forward price change over the horizon, and counts wins versus total tries. The percentage is wins divided by tries.
The thin bar under the score is a ruler from a more negative overall reading on the left to a more positive one on the right. Center is neutral.
Shows how far you are from the middle, not just the words in the pill.
The score is stretched so −100 sits at the far left, 0 at the center, +100 at the far right. Vertical ticks mark where the label buckets change (same thresholds as the pill).
When a company executive, board member, or large shareholder buys their own company's stock on the open market — reported to the SEC.
Insider buying has historically been a modestly positive signal. Insiders only buy for one reason: they think the stock will go up. Selling can have many reasons (taxes, diversification) so means less.
When multiple insiders buy within a short window — a 'cluster buy'.
Historically a stronger signal than one insider buying alone. When several insiders agree, it tends to mean something.
How complete the data feed was for that lens today, shown as a percent. Higher means more inputs had real numbers instead of gaps.
A half-empty panel is a softer read. Missing macro prints or thin news days pull this down so you do not overweight a thin story.
Macro confidence counts how many of the listed macro inputs were available. Sentiment scales with how many headlines were scored. Other lenses use fixed rules when their core fields exist.
How much extra punch a leveraged ETF aims to deliver. A 2× fund tries to do twice what the underlying index does each day; a 3× fund tries for triple.
The 'each day' part is important. These funds reset every day, and over weeks or months they often drift away from a simple multiple of the index — usually for the worse.
Beyond roughly a year and a half — the mix favors how the business and valuation look versus the macro backdrop. Same figure as the Long column on All assets.
If you plan multi-year holds, this row is the closest match to how compounding actually happens in the real business.
Fundamental and macro weights are highest here; technical and sentiment still matter but count for less of the total.
Across all four signals, this stock currently looks unusually attractive — usually cheap, healthy, and in a friendly environment.
A description of the picture today. Not advice — the same picture can be right or wrong for different people.
Shown when the blended horizon score is at or above the top cutoff on the balanced scale (here +65 on the −100 to +100 line).
The lowest published price target in the same set.
Shows the cautious extreme. A wide high–low band means analysts disagree.
Taken as the min of the target list.
Does the current economy (growth, inflation, interest rates) favor this kind of asset, hurt it, or sit somewhere in between?
Even a great company can struggle for years in a hostile environment. This flags whether the wind is at its back.
Today's macro regime label maps to a preset tilt for your asset class (stock, ETF, bond, crypto). The confidence line reflects how many input gauges had fresh data.
A short label describing today's economic weather — combining growth, inflation, interest rates, and stress in the credit markets.
Different regimes have historically favored different assets. Bonds tend to shine in recessions; growth stocks in calm, low-rate times. The 'weather' affects what works.
The regime is today's big-picture market mood from Clarovest's rules (growth, inflation, rates, stress). The small line under the label shows the top one or two readings that weighed most on that label.
Names like Risk-On are shorthand. The numbers show what the model was actually looking at so the label feels less mysterious.
VIX is a volatility index for US stocks — higher usually means more expected fear or chop. Curve is the gap between long-term and short-term Treasury yields as a percent; when short rates sit above long ones, people call that an inverted curve, often watched as a recession signal. Other drivers can appear the same way (spreads, dollar, inflation).
Short bullets naming which macro inputs mattered most when labeling today's regime (for example VIX level, credit spreads, or the yield curve).
The regime name alone is abstract. Drivers spell out what actually moved the label.
A rules engine reads VIX, 10-year yield, curve shape, high-yield spreads, dollar strength, and CPI growth; the top few hits become the driver lines.
The total value of all shares added together — roughly 'what the whole company would cost to buy at today's price.'
It tells you how big the company is in dollar terms. Bigger usually means more established; smaller can mean more room to grow, but also more bumpiness.
Share price times the number of shares outstanding. For funds, the same field is often used for assets under management (AUM).
About a quarter to a year and a half — a middle ground between mood and business fundamentals. Same figure as the Med column in the screener.
Many company turnarounds show up here first. It catches trends that are too slow for the weekly chart but faster than a five-year story.
Weights on the four lenses sit between the short and long presets; the same cutoff table turns the score into the label.
Mixed signals. Some attractive features, some weaker ones.
A neutral profile. Different long-term strategies will reach different conclusions on this kind of picture.
Shown when the blended score falls between the cautious cutoff (−30) and the positive cutoff (+50).
Most of the signals lean positive. The stock looks like it's worth a closer look for a long-term investor.
A description of the picture today. Not advice — the same picture can be right or wrong for different people.
Shown when the blended score sits between the middle-positive cutoff (+50) and just below the top cutoff (+65).
Roughly how many years of profits it would take the company to pay off all its debt, after using up its cash.
Above 3× starts to look heavy. Above 5× can be dangerous if business slows. Below 1× — or negative, meaning more cash than debt — is very healthy.
Out of every dollar of sales, how much actually ends up as profit after all costs and taxes are paid.
Stable, high margins are usually a sign the company has a real edge. Thin or shrinking margins are a yellow flag.
Price-to-book. Compares the stock price to the company's accounting net worth (what it owns minus what it owes).
Most useful for banks and asset-heavy businesses. Less meaningful for software or brand-driven companies, where the real value isn't on the balance sheet.
Price-to-earnings. If a stock has a P/E of 20, you're paying $20 for every $1 of yearly profit the company makes.
Lower is generally cheaper. But a really low P/E can also mean the market expects profits to fall — always check the business health alongside it.
Price-to-sales. Compares the stock price to how much revenue the company generates each year.
Handy when a company isn't profitable yet. Cheaper is generally better, but $1 of low-margin sales is worth less than $1 of high-margin sales.
What percentage of the company's profits is being paid out as dividends.
Below 60% is usually comfortable. Above 80% leaves the company little room to invest, weather a bad year, or keep the dividend growing.
Takes the P/E and divides it by how fast the company is growing. A PEG of 1 means the price roughly matches the growth.
A P/E of 25 sounds expensive — unless the company is growing 25% per year, in which case PEG is just 1. Lets you fairly compare a fast grower against a slow one.
A weighted average of the technical signal across all your positions. Bigger positions count more.
A quick read on whether your portfolio looks healthy on price-and-trend terms today. Not a forecast — just a snapshot of the current mood.
How your money splits between stocks, ETFs, bonds, and crypto. Percentages are by current dollar value — not by number of shares or number of positions. A small position in a $1,000 stock can be worth more than a big position in a $5 stock.
Different asset types behave very differently in the same market. Stocks and ETFs share most of the same risks (a bad week for stocks is usually a bad week for stock ETFs). Bonds and crypto move much more independently. Knowing the split is the starting point for understanding how your portfolio moves.
For each holding we take shares × current price to get its dollar value, then divide by the total. So 60% ETFs means 60 cents of every dollar you have invested sits in ETFs right now.
The average price you paid per share, including all your buys for this position. Optional.
Required for the up/down calculation on this position. If you bought in pieces, enter the weighted average — or any approximation if you don't have the exact number.
How much of your portfolio sits in your biggest single position, biggest theme, or biggest asset class.
A higher concentration means a single name or theme moves a bigger share of the total. There is no universal 'right' level — context matters and this is just an observation about the current mix.
How closely your holdings have moved together over the last 90 days. 1.0 = lockstep, 0 = unrelated, -1 = opposite.
Helps you see whether your positions are doing different things or basically the same thing. Past correlation doesn't guarantee future correlation.
The total amount of money you put in across all positions, based on the average cost you entered for each one.
Without it we can't show you whether you're up or down. If you skip the average cost when adding a holding, that position won't count toward this number.
What your holdings are worth right now, using the latest prices we have.
The single number that tells you where you stand today. Everything else on this page is a different angle on this total.
How much your portfolio is up or down compared to what you paid. Green = ahead, red = behind.
The bottom line. Only positions where you entered an average cost are included — the rest are left out so the math is honest.
A what-if for your specific mix: how it would tend to behave if the market mood switched to each of these regimes.
Shows hidden sensitivity to regime changes. A mix that scores high in 'risk-on' often scores low in 'risk-off' — same portfolio, different math.
We tag each asset class with a typical tilt under each regime, then weight by how much you own. Directional only — not a forecast or recommendation.
The category each holding belongs to (Cloud, Semis, Energy, etc.). We pick one for you, and you can override it.
Surfaces overlap that's easy to miss — four 'different' funds can all be heavy in the same tech giants. The theme breakdown shows what you're actually exposed to.
An optional category label for this position. We pre-fill one based on the asset; you can change it.
Useful when you bucket things differently than we do — for example, tagging a gold ETF as 'Inflation hedge' instead of 'Commodity'. The theme breakdown card uses your tag.
How big each position is as a share of your total. A 25% weight means a quarter of your money is in that one name.
Weight is the lever that turns a stock's move into a portfolio move: a 25% position swinging 10% moves the whole portfolio 2.5%.
An example of how much a portfolio could put into a single stock, given how jumpy it is, while keeping single-position risk in a sensible range.
Helps frame how much exposure to one company is reasonable. Educational — not a recommendation. Real allocation depends on your situation.
How much money the example position would represent, in dollars, given the chosen portfolio size.
Just an educational reference. What you actually allocate depends entirely on your personal situation.
The stock's weekly closing price over about five years, with two moving averages and a light band for usual volatility.
Moving averages smooth out day-to-day noise so you can see the trend. The band shows when price has stretched far from its recent norm.
The app computes the 50-day and 200-day simple moving averages from daily closing prices, then samples the chart weekly so it stays readable. The light band is based on a 20-day average plus and minus two standard deviations — a classic volatility envelope, not a forecast.
Tells you if the stock looks cheap, fair, or expensive today — compared to how it's been priced in the past, and to other companies in the same industry.
Paying less for the same business is one of the biggest drivers of long-term returns. But cheap isn't always good — sometimes a stock is cheap because the business is in trouble.
A score for how strong the underlying business is — does it make money efficiently, keep debt under control, and run profitable operations?
Strong businesses tend to weather bad years much better and grow steadier over the long run. Quality is the most consistent predictor of long-term success.
Margins, returns on capital, and leverage checks are each converted to a partial score and merged into one −100 to +100 reading.
How much the asset's price has bounced around over the last 30 days, measured as annualized volatility.
Higher numbers mean bigger daily swings — important for calmer sleep and for sizing.
Computed from daily percentage changes over the last month, scaled to a yearly volatility figure.
How wildly the stock has actually moved over the past 30 days, scaled to a yearly figure.
Tells you how jumpy the stock has been recently. Forward-looking proxies can lag — this is the rear-view mirror.
A short log of recent rating or target changes reported by coverage firms.
Shows who moved their opinion lately. Often lags headlines but explains sudden shifts in the consensus numbers.
Rows come from the same third-party feed; upgrades, downgrades, and target edits appear when vendors publish them.
Most signals are negative across price, business, and environment.
A description of the picture today. Not advice — the same picture can be right or wrong for different people.
Shown when the blended score is at or below the weakest cutoff (−60).
A reference price below the current one, where someone using stops might choose to exit. Sized to how volatile the stock typically is.
Illustrative only. Setting a stop is a personal call — many long-term investors don't use stops at all and just ride out drawdowns.
Steady growth combined with falling inflation. The 'best of both worlds' for markets.
Historically the most favorable backdrop for broad stock returns. Things just tend to go up.
The economy is shrinking. Unemployment is rising and corporate profits are falling.
Historically the worst environment for stocks broadly, especially cyclical companies. Government bonds often act as a hedge.
Growth is slowing and investors are getting nervous. Money flows toward safer assets.
Historically friendly to bonds, high-quality stocks, and defensive sectors (utilities, staples). Cyclical and debt-heavy companies often struggle.
The economy is healthy, money is flowing freely, and investors are happy to take chances.
Historically friendly to stocks — especially growth stocks and smaller companies. Bonds and gold often lag in this environment.
Persistent inflation combined with weak growth. Rare and painful — the 1970s, briefly.
Historically tough for both stocks and long-dated bonds. Real assets like commodities and certain real estate have held up better.
Return on assets. For every $100 of stuff the company owns, how much profit does it produce per year?
Higher means the business is squeezing more profit from what it owns. Above ~10% is strong; below ~3% means it either needs lots of capital to operate, or is struggling.
Return on equity. For every $100 the owners have put in, how much profit comes back each year?
A common headline measure of how productive a business is. Watch out — heavy borrowing can puff it up artificially. Always check ROA too.
Return on invested capital. The cleanest version of 'how good is this business at turning money into more money'.
A consistently high ROIC is the fingerprint of a great long-term compounder. The Warren Buffett type.
Simple percent changes in the stock price over 1 week, 30, 90, 180, and 365 days — a quick pulse on momentum without extra indicators.
Lets you see if recent moves are unusually hot or cold compared with longer stretches.
Each cell is (price now minus price at the start of the window) divided by that older price, shown as a decimal in the table until the next full technical refresh adds richer signals.
Year-by-year bars for return on equity (ROE), return on assets (ROA), and return on invested capital (ROIC) — how well the company turns money into profit.
A business that keeps these measures high and steady has historically been a hallmark of durable compounders.
ROE is yearly net income divided by shareholder equity. ROA is net income divided by total assets. ROIC is after-tax operating profit divided by invested capital (debt plus equity, net of excess cash). Each is shown as a percent on the chart. The dashed line marks roughly 10% as a simple benchmark.
How much the company's sales grew compared to a year ago.
Sales are the foundation. Consistent revenue growth is a basic requirement for long-term compounding — without it, the business has to squeeze profits out of a shrinking pie.
How this metric compares to other companies in the same industry. Shown as a percentile from 0 to 100.
A P/E of 30 is expensive for a utility, cheap for a software company. Comparing within the same industry removes that distortion.
How positive or negative the recent news flow has been, plus what company insiders are doing.
Sentiment moves prices fast and changes quickly. Best treated as a tiebreaker, not the main reason to do anything.
Headlines are scored by an AI model from −100 to +100 each, blended with recency, then nudged by a separate insider-activity score before the final lens score.
How many distinct headlines were available to score for this ticker in the latest pull.
Thin coverage means the sentiment score is noisier — one story can swing the average.
Counted from the news feed before scoring; also feeds the confidence percentage on the sentiment lens.
A small nudge up or down based on whether company insiders have been buying or selling in the open market lately.
Insider buys especially cluster buys have historically been a modest positive sign; sells are interpreted more cautiously because people sell for many benign reasons.
Buys add a few points each up to a cap; sells subtract a smaller amount per sale; large dollar clusters move the nudge a bit more before the result is added to the news score.
The headline part of the sentiment lens before insider activity is blended in. Runs from very negative to very positive based on recent news stories.
Captures the tone of the press and wire headlines, which often move the stock before fundamentals fully update.
An AI model scores each headline from −100 to +100, then those scores are averaged with more weight on newer stories. That average is the news score.
A few short phrases summarizing topics that kept showing up across the scored headlines (for example layoffs, AI demand, or a lawsuit).
Helps you see what the news cluster is actually about, not just whether tone was positive or negative.
The same model that scores headlines returns up to four theme tags when it sees repetition.
Roughly the next few weeks to a few months — the lens mix here tilts toward price action and sentiment. Matches the Short column on All assets for this symbol.
Useful for context if you care about near-term bumps. Long-term holders still glance here to see if the mood is extreme.
The composite number weights technical and sentiment more heavily than on the long horizon, then applies the same −100 to +100 scale.
Four side-by-side panels — Technical, Fundamental, Macro, and Sentiment — each with its own score and the main inputs that fed it today.
Shows which force is driving the headline picture: the chart, the business numbers, the economy, or the news and insiders.
Each panel score is computed inside that lens, then the horizon cards above mix the four scores with time-dependent weights.
What recent news, analyst commentary, and company insiders are saying about this stock right now.
Useful as a temperature check. The story can move prices day-to-day, but it shouldn't override the bigger picture.
How the price chart is behaving: is it going up, going down, accelerating, stalling?
Useful for short-term context. Less important for long-term investors — over years, prices follow the business, not the chart.
When full detail is available, trend and momentum statistics are scored against history. From cache you may only see recent return windows until the next full refresh.
A small bucket of assets that do similar things — like 'Semis' for semiconductor companies, 'Cloud' for cloud-software names, or 'Treasury ETFs' for government-bond funds.
Helps you see what kind of business or asset class is having a good or bad moment, instead of staring at one ticker at a time.
The average business-quality score across the theme — profitability, balance-sheet health, and capital efficiency rolled together.
Themes full of high-quality companies tend to behave very differently from speculative buckets, even when both are up.
The average of every member's price-and-trend score. Higher means the typical name in this theme looks healthy on the chart today.
A quick read on whether the whole bucket is moving with the market or against it. One hot name doesn't make a hot theme.
The average 'cheap or expensive' read across the theme. Higher = the typical member looks cheaper than its history and its peers.
Lets you compare whole categories — is 'Semis' cheap or rich on average right now versus 'Energy'?
The three members with the strongest technical reads, and the three with the weakest, inside the theme.
Even in a healthy theme some names are struggling, and vice versa. Spot-checking the extremes is a fast sanity check.
Out of every name in this theme, the share whose technical score is above zero today.
Tells you whether the move is broad or concentrated. 90% positive means almost everything is participating; 30% positive means a few winners are carrying the bucket.
How the average member of this theme has performed over 30, 90, and 365 days.
Helps you see whether a bucket has been quietly compounding, recovering from a slump, or melting up only recently.
Three snapshots of the same ticker using the same scores stored for that day: Short, Medium, and Long. Those three numbers are exactly what the All assets table shows in its Short, Med, and Long columns — one shared pipeline, not a different model on the detail page.
What looks weak short-term can look strong long-term, and vice versa. If you plan to hold for years, the long-term view matters most.
Each horizon blends the four lens scores (technical, fundamental, macro, sentiment) with different weights from the same preset table. Shorter horizons lean more on price and mood; longer ones lean more on business quality and valuation.
The percentage gap between today's price and the median analyst target. Positive means the median target sits above the current price.
Large positive gaps sometimes mean analysts are more optimistic than the market; large negative gaps can mean the stock has run ahead of even bullish analysts.
Computed as (median target minus current price) divided by current price, expressed as a percent.
How strong the US dollar is compared to a basket of other major currencies.
A strong dollar is generally a headwind for US companies that sell abroad, and for emerging-market assets. It quietly shapes a lot of returns.
How this stock's price-to-earnings (P/E) has moved month by month, plotted against the median P/E of its sector at the same dates.
Shows whether today's valuation is high or low versus this company's own history and versus similar companies.
Each month, P/E is price divided by trailing twelve-month earnings per share. The gray dashed line is the median P/E across sector peers that month, from the same data pipeline.
A score from −100 (very expensive) to +100 (very cheap). Combines a few common ratios, compared to the stock's own past and to its peers.
Paying less for the same business has historically been one of the biggest drivers of long-term returns.
Several valuation ratios are each scored versus history and sector, then combined with caps so one broken ratio cannot dominate.
A stock that looks cheap on the numbers — but is cheap for a reason. The business is quietly deteriorating, so the 'bargain' keeps getting cheaper.
Buying cheap-looking stocks that keep falling is one of the most common ways long-term investors lose money. This flag helps separate real bargains from broken businesses.
Often called the 'fear gauge'. Measures how much volatility traders are expecting in the S&P 500 over the next month.
Above 25 signals stress in the market. Above 35 typically marks a panic. Low VIX (below 15) suggests calm — but also complacency.
Derived from options prices on the S&P 500 using a standard industry formula — higher means traders are paying more for protection.
How much the VIX has moved over the last 30 days, in percentage points of the index itself.
A fast jump often means fear spiked recently even if the level is not extreme yet.
Latest VIX minus its level roughly 30 trading days ago, from the same market feed used for spot VIX.
The slow loss that leveraged ETFs suffer when the market is choppy, even if the underlying index ends flat.
A specific reason leveraged ETFs are widely treated as trading tools rather than long-term holdings.
Several signals lean negative — typically expensive, weakening fundamentals, or fighting the current environment.
A description of the picture today. Not advice — the same picture can be right or wrong for different people.
Shown when the blended score is between the weakest cutoff (−60) and the cautious cutoff (−30).
The gap between long-term and short-term interest rates. When it's negative (short rates higher than long), the curve is 'inverted'.
Inverted yield curves have come before most US recessions, usually 6–18 months ahead. Not a perfect predictor — but historically a serious warning sign.
Educational information only. Not investment advice.