How to read your analysis

The headline. We blend several valuation models into one estimate of fair value, then compare today's price to it: price below our estimate = Undervalued, roughly on it = Fair value, above it = Overvalued. The percentage is how far the price sits from our fair-value estimate.

What to look for: "Undervalued" is not "buy" and "overvalued" is not "sell". It's one estimate, and a cheap stock can be cheap for a good reason. Treat it as a starting question, not an answer. If the analysis is marked unverified, don't lean on the number at all (see Data integrity).

One line that brings the two halves of investing together: our fundamental verdict (is it cheaper or pricier than we estimate it's worth?) and a quick technical read of the price, its trend over roughly the last 12 months and where it sits in its 52-week range. It says whether the two agree or are in tension.

What to look for: green "agree" means the value case and the price point the same way; amber "tension" is the interesting one, cheap but still falling ("value trap or falling knife?"), or expensive but rising ("momentum vs. value"). It's rough context to frame your own research, not a buy/sell signal, the technical side is a simple price-trend read, not a full chart analysis.

How we work it out (no black box): the technical read uses the price history only. Trend, we average the most recent ~3 months of weekly closing prices against the earliest ~3 months of the past year: more than +5% higher reads as "trending up", more than −5% lower as "trending down", anything in between as "sideways". Position, where today's price sits in its 52-week range: the top 20% is "near highs", the bottom 20% "near lows", the middle "mid-range". We then pair that read with the valuation verdict to call agree or tension. Deliberately simple — no RSI/MACD, no moving averages, no chart image.

Different models give different answers, so we blend the ones that apply into a single weighted fair value, and wrap a ±10% range around it. Valuation is never a precise point — the range is us being honest that it's a zone, not a single "correct" price.

What to look for: a narrow spread between the models means they agree (more confidence); a wide spread means the answer is sensitive to assumptions, read the individual methods to see why.

The average price target from professional analysts, shown next to our estimate, not because they're always right, but so you can see when we disagree with them.

What to look for: agreement is reassuring; a big gap is interesting, it means either the market/analysts know something our model doesn't, or the reverse.

The raw ingredients the models use, price, cash flow, debt, cash, shares, earnings, book value, growth rates, and so on, each with its source and the date it was retrieved.

What to look for: this is the "show your work" layer. If a verdict surprises you, the inputs usually explain it (e.g. a huge growth rate driving a high fair value). A ⚠ flag means that figure failed a consistency check, see Data integrity.

Context around the verdict, in two groups. Valuation multiples (below) are quick price ratios every investor uses. Returns & quality answer a different question, not "is it cheap?" but "is it a good business?"

What to look for: a stock can be cheap and a poor business, or expensive and excellent. The multiples and the quality numbers help you tell which.

Small bar charts of the recent quarters (toggle to years for the long view): free cash flow, revenue, EBITDA, net income, EPS, the three margins, shares outstanding, and debt vs cash. Green bars are positive, red bars are negative, the dashed line is zero, and the left axis shows the scale.

What to look for: the shape, not any single bar. A single number can mislead: a company can show strong annual free cash flow while its latest quarter turned negative (heavy spending, one-off costs). That is exactly what the chart catches, and when annual and the latest quarter disagree in sign, we flag it above the charts. Two often-overlooked ones: shares outstanding falling means buybacks (your slice of the company grows); rising means dilution. Debt vs cash shows whether the balance sheet is strengthening or leaning harder on borrowing. One weird bar is a question to investigate, not a verdict, and quirks in reported figures (one-off gains, accounting noise) show up here honestly. The valuation itself still uses the annual figure, so one unusual quarter never swings the fair value. Depth is the last four-to-five years and the recent quarters — what our free data sources provide.

Price ÷ earnings per share, how many dollars you pay for $1 of the company's yearly profit. Trailing uses the last 12 months; forward uses next year's expected profit.

Rough guide: under ~15 is often "cheap" (or a company the market expects to shrink); ~15–25 is around the market average; 30+ means big growth is being priced in. But context rules: a fast grower deserves a high P/E, that's what PEG adjusts for. Compare trailing vs forward: a much lower forward P/E means profits are expected to jump.

The P/E divided by the earnings growth rate. It answers "is this P/E reasonable given how fast the company is growing?"

Rough guide: around 1 or below is often read as "fairly priced for its growth"; well above ~2 can mean you're paying a lot even after accounting for growth. It's one of the better single sanity-checks on a scary-looking P/E.

Price ÷ revenue per share. Useful when a company has little or no profit yet (many young or fast-growing firms), because it doesn't depend on earnings.

What to look for: low single digits is common for mature businesses; high P/S (10+) means the market is paying up for future growth. Only compare it within the same industry — software and grocery stores live in completely different ranges.

Price ÷ the company's accounting "book value" (assets minus liabilities). The classic value-investor ratio; most meaningful for asset-heavy businesses like banks.

What to look for: under ~1 means the market values the company below its accounting net worth (a classic value signal, or a warning). For tech/brand companies P/B is often huge and not very meaningful, because their value isn't on the balance sheet.

Enterprise Value is the whole-company price (market value + debt − cash). Dividing it by EBITDA (operating profit before depreciation) or by revenue gives a valuation that's neutral to how a company is financed, which is why professionals use it to compare companies.

What to look for: lower is cheaper. EV/EBITDA around 8–12 is common for mature firms; 20+ signals high growth expectations. Best used to compare peers in the same industry.

Yield = annual dividend ÷ price (the income you collect just for holding). Payout ratio = the share of earnings paid out as dividends.

What to look for: a very high yield (say 8%+) can be a red flag that the market expects a cut. A payout ratio under ~60% usually means the dividend has room; over ~100% means they're paying out more than they earn, often unsustainable.

Of every dollar put into the business (from lenders and shareholders), how many cents of profit it earns per year. We pair it with the company's cost of capital (what its money costs to raise): if ROIC is higher, the business creates value; if lower, it destroys value even while looking "profitable."

Rough guide: consistently above ~10–15% (and above its cost of capital) is a sign of a genuinely good business. This is often the single best "is this a quality company?" number. We show "n/a" when the accounting figures would distort it rather than print a misleading value.

ROE = profit ÷ shareholders' equity. ROA = profit ÷ total assets. Both measure how efficiently the company turns its resources into profit.

What to look for: higher is better, but ROE can be inflated by heavy debt or share buybacks, which is exactly why we show ROIC alongside it. Read them together, not in isolation.

The share of revenue the company keeps at each stage: after direct costs (gross), after running the business (operating), and as final profit (net).

What to look for: higher and stable or rising margins signal pricing power and a durable business. Compare only within an industry, software margins dwarf retail margins by nature.

Before we sound confident, the data has to pass a gauntlet: a second independent price source must agree within 5%, revenue must reconcile with sales × shares, the price must sit in its 52-week range, and so on. Anything that fails is shown, not hidden.

What to look for: all-pass = trust the number. If it's marked unverified, the headline % is suppressed and the ticker can't be watchlisted. Treat the verdict as provisional. "A confident number built on bad data is worse than no number" is our founding rule.

Think our data is off, or want to test a scenario? Edit any of the core inputs (growth, margin, debt, shares…) and the models recompute instantly with your numbers, labeled "user-adjusted."

What to look for: a great way to learn, nudge the growth rate up and watch the fair value move to see how sensitive the verdict is to that one assumption.

We run up to five methods, two Discounted Cash Flow horizons, Discounted EPS, Mean Price-to-Book, and PSG (a sales-and-growth model), then blend the applicable ones into the weighted fair value. Each has strengths, so together they show valuation as a range of reasonable answers. Full math on the methodology page.

What to look for: when the methods cluster tightly, the verdict is robust. When they scatter, the "right" answer depends heavily on assumptions, a signal to dig into the inputs.

The cash a company has left after paying to run and maintain the business, the money genuinely available to pay down debt, buy back shares, or pay dividends. It's the fuel for our DCF models.

What to look for: positive and growing FCF signals a healthy, self-funding business; consistently negative FCF means the company depends on outside money to keep going.

What the company owes (debt) and what it holds (cash). We use both to get from whole-company value to per-share value, adding cash, subtracting debt.

What to look for: debt is only worrying relative to cash flow and cash — a profitable company with plenty of cash can carry large debt comfortably. The raw dollar figure alone isn't good or bad, which is exactly why we don't color it.

EPS = profit per share. Book value per share = accounting net worth per share. Sales per share = revenue per share. Each feeds a different valuation model.

What to look for: these are building blocks, not verdicts. They become meaningful as ratios, e.g. P/E = price ÷ EPS, which you'll find colored over in Financials.

How much a stock tends to swing relative to the overall market. Beta of 1 = moves with the market; above 1 = more volatile; below 1 = steadier. We use it to set the discount rate.

What to look for: it's a risk input, not good/bad, a high beta just means bigger swings in both directions.

The annual rate we use to translate future cash back into today's dollars, essentially the return an investor should demand for taking the risk. Higher risk → higher discount rate → lower fair value.

What to look for: it's a modeling assumption (around 9% is typical). A higher rate is more conservative, not "bad", it just means we're demanding more before calling something cheap.

The heart of any valuation, how fast we assume cash flow, earnings, and revenue will grow. We derive these from the company's own history and cap them for realism (AI proposes a number within guardrails; tested code does the math).

What to look for, this one's counterintuitive: these are assumptions, and a higher growth number pushes the fair value up, so a rosy growth rate makes a stock look cheaper-than-it-is, not "good news." That's why we cap them and show our work. Use Adjust Inputs to nudge growth and watch how much the verdict moves.

ReadR's read on the overall direction the chart is leaning, based on trend, structure, and momentum visible in the image.

What to look for: it's a description of the picture, not a prediction. "Bullish" means the chart is trending/structured upward right now, which can change.

Support = a price level where buying has repeatedly stepped in (a "floor"). Resistance = a level where selling has repeatedly appeared (a "ceiling").

What to look for: these are zones, not exact lines. They matter because lots of traders watch them, price often pauses or reverses there, until it decisively breaks through.

The pattern of highs and lows. A series of higher highs and higher lows is an uptrend; lower highs and lower lows is a downtrend; sideways is a range.

What to look for: a "break of structure" (e.g. a first lower-low after an uptrend) is how traders spot that a trend may be changing.

Each candle shows the open, close, high, and low for a period. Named patterns (doji, engulfing, hammer…) are common shapes traders read as hints about momentum shifts.

What to look for: single candles are weak signals on their own; they matter most at a support/resistance level or with volume behind them.

Volume is how many shares traded, the "effort" behind a price move. VSA reads volume with price: a big move on high volume is convincing; a big move on low volume is suspect.

What to look for: rising price on rising volume confirms strength; a price move on weak volume, or a huge volume spike that goes nowhere, often signals exhaustion. ReadR flags these "effort vs result" mismatches.

The popular modern vocabulary, often called ICT concepts after the Inner Circle Trader methodology that popularized it: liquidity sweeps, order blocks, breaker blocks, fair value gaps, displacement, inducement, and market-structure shifts. Much of it is a rebrand of classical ideas (a liquidity sweep ≈ a Wyckoff spring; an order block ≈ a supply/demand zone), so ReadR speaks both dialects and explains them side by side.

What to look for: treat these as descriptions of chart areas, not certainty about what institutions are doing, nobody can prove that from a screenshot. The teaching is the value. Deliberately absent: time-of-day setups (kill zones) and "optimal trade entry" zones. Those are trade signals, not chart observations, and ReadR never signals entries.

Paste up to three charts (e.g. daily + 4-hour + 1-hour) and ReadR describes whether they agree or conflict. Chart 1 is treated as the primary.

What to look for: alignment across timeframes is a stronger picture; conflict (up on one, down on another) is a signal to be cautious rather than confident.

ReadR tells you when the screenshot itself limits the read, no volume shown, timeframe not labeled, low resolution, etc.

What to look for: this is the honesty layer for charts. A better screenshot (clear timeframe, volume visible, readable candles) gets you a better analysis.