Instrument analysis page — full field guide

These gauges compress many internal model checks into two opposing technical alignment scores for the chosen horizon.

• Interpretation: higher = more factors currently line up with that direction; it is not a promise of profit or of “probability of winning one trade”. Regime shifts, gaps, spreads, or news can invalidate the tableau quickly.

• Conflict patterns: both near 45–55 often implies balance or chop; wide separation suggests a directional lean—always reconcile with trend structure and volatility.

• Use: treat as a heads‑up for what the model “sees” now, then decide whether that matches your higher‑timeframe thesis.

The tier and 0–100 score blend where price sits inside recent statistical ranges (e.g. Bollinger context, range placement) with momentum inputs such as RSI and Stochastic.

• Not fundamental value: it does not read balance sheets, earnings quality, or fair value models—only technical positioning vs recent behaviour.

• Sub‑labels (BB, Rng, RSI, Stoch): quick transparency into which ingredients pulled the score; deep value investors should still run their own fundamentals.

• How to use: treat “cheap/expensive” as “stretched vs recent norm”—useful for mean‑reversion vs trend‑following context, not as a standalone trigger.

This is the headline distillate from the indicator stack—a single readable label plus a directional chip.

• Strong vs weak: communicates how tightly the internals agree—not forecast confidence. Weak tags often mean fragmentation: some timeframes disagree, momentum is hesitant, or risk flags are elevated.

• Timestamp: shows when analysis last refreshed—markets move; stale context misleads sizing decisions.

• Reality check: if the tag fights the higher‑timeframe chart, assume the tag is describing a local technical picture until you prove otherwise.

The split bar summarizes a model‑side long/short weighting, not disclosed retail positioning from a broker.

• Purpose: visualize whether the inferred technical narrative is asymmetrically bullish or bearish versus neutral.

• Don’t confuse with sentiment polls elsewhere on the page; those are separate constructs with different methodologies.

• Bid / Ask / Spread: transactional friction—critical on FX crosses and thin instruments; widening spread can invalidate scalp‑style levels.

• TradingView embed: mirrors the symbol mapping logic the app uses elsewhere; equities may fall back to an alternate vendor chart if the prime feed disagrees.

• Stock fundamentals: only appears when the backend has equities data—it is supplementary context, not a sync with the purely technical Monte Carlo machinery.

• Latest news: topic‑matched headlines with AI tagging; correlate spikes with liquidity pools and widen stops mentally when headlines dominate.

• Jump navigation: aligns with each major section Id so you can scan long pages quickly.

This block estimates where resting liquidity or failed‑breakout narratives may cluster using swing structure, pivot maths, and an ATR‑based buffer.

• Buy‑side / sell‑side boxes: highlight reference prices; they are hypotheses that price could revisit to rebalance order flow—not guaranteed magnets.

• Swing high/low & pivot above/below: anchors derived from recent bars; volatile sessions can sweep them intrabar.

• Bull trap / bear trap cards: educational framing for “false breakout then reversal” stories tied to the quoted pool levels—use them to rehearse risk, not to predict exact timing.

• Footer line (ATR buffer, lookback bars): transparency on parameters so you can judge how “tight” or “loose” the geometry is.

Monte Carlo here means: run many independent random forward paths for price, using a volatility/correlation recipe estimated from recent data, then study the distribution of outcomes—not a single prophecy.

• Why do it? Markets are uncertain; a fan of scenarios exposes range risk and central tendency under the model’s assumptions.

• Paths & horizon: the badge shows how many simulations ran and the rough bar/step horizon (e.g. steps × 4H). More paths usually stabilizes the envelope; the horizon tells you how far ahead the diffusion looks.

• Chart bands: the shaded cones are percentile envelopes (often ~68% and ~95% “confidence” language). The median path tracks the 50th percentile trajectory through time.

• Stats tiles: Expected price ≈ average of simulated endpoints; Prob up / down counts how many paths finish above/below spot; Max gain/loss describe extreme moves seen inside that simulation batch—useful stress colour, not a hard cap on reality.

• Critical caveat: if volatility is mis‑estimated, if a regime break occurs, or if liquidity gaps appear, the model can be wrong fast. Treat outputs as risk‑aware colour, then overlay fundamentals, seasonality, and event risk yourself.

The scrollable card is a layered memo: headline, KPI grid, narrative sections, scenario blurbs, and outlook.

• Sentiment pill (bullish/bearish/neutral): classifier on the generated brief—can disagree with raw scores; treat as editorial tone from the model.

• Six KPI tiles: F‑Score (multi‑rule quality), Smart Money Index summary, Risk score, Monte Carlo prob up (mirrors the simulation), Trade confidence, and the text signal—together they triangulate “quality vs heat vs alignment”.

• Executive summary & key observations: condensed reasoning; verify claims on the chart.

• Technical deep dive: either model prose or a structured fallback listing RSI/MACD/EMA/BB/ADX facts.

• Opportunities / risks: bullet planners—good for checklists, not orders.

• Scenario analysis lines: tie bull/base/bear stories to pivots and MC bands when the model doesn’t supply custom text.

• Bull/Bear price targets, regime stripe, 24–96h outlook, macro note: forward‑looking colour—always time‑boxed and assumption‑laden.

The three large cards translate Monte Carlo statistics into story panels.

• Bull: emphasizes upper 68% / 95% objectives and the prob up percentage as a headline weight.

• Base: centres on expected price and the 68% interval width—useful when you want a “middle path” reference.

• Bear: stresses lower interval objectives and pairs with risk score language on the driver line.

• Driver tags: show which theme the UI attached (signal, regime, risk)—read them as annotations, not causal proof.

Remember: they share the same underlying simulation as the chart above; they just narrate different slices of the distribution.

You’ll see two related blocks: a compact sticky card beside the briefing and a wider module lower on the page.

• Direction badge: LONG/SHORT/NEUTRAL template from the model—pedagogical, not an order.

• Entry / TP1 / TP2 / Stop: mechanical scaffolding; compare them to your invalidation rules and session volatility.

• Risk % & R:R lines: show modelled distance to stop vs reward milestones—if ATR or spread swells, effective R:R changes even if numbers on screen stay static until refresh.

• Confidence bar: internal consistency meter for the template—low values should nudge you toward smaller size or waiting for confirmation candles.

• Summary table: surfaces best R:R, daily ATR, and ATR% of price to contextualize how wide the stop is versus typical motion.

This is the classic stack explained in context:

• RSI (14): speed of recent gains vs losses; overbought/oversold tags can persist in trend runs—use failure swings or structure instead of blind fade rules.

• MACD histogram: short‑term momentum acceleration vs its signal line; positive/negative tells direction of impulse, not necessarily entry timing.

• EMA ribbon (20/50/100/200): stack order defines trend architecture; price vs EMA200 and golden cross flags highlight slower participants.

• Bollinger (20,2): middle band is a rolling mean; width shows compression vs expansion; squeeze badge warns of potential volatility release (direction still open).

• Stochastic %K/%D: another bounded oscillator; crossovers near extremes matter more when confirmed by structure.

• ADX + DI pairing: ADX gauges strength of trend, +DI vs −DI the dominant direction—high ADX is not immunity from snaps.

• ATR: average true range—absolute volatility in price units plus % of spot so you normalize across symbols.

The chart column adds a six‑mini‑tile strip mirroring RSI/ADX/etc. while the briefing stays open—use both for redundancy checks.

Structural references only—markets hunt liquidity mechanically.

• Resistance R3→R1 & Support S1→S3: ordered lists with distance from spot percentages to gauge immediacy.

• Daily pivot: mid‑session magnet in classical pivot math; usefulness rises on liquid sessions, fades on headline drift.

• Fibonacci ladder: retracement/extension scaffolding from swing anchors; relevance depends on anchor choice—confirm on chart drawing tools if it matters for your playbook.

Treat every printed level as contested, not sacred.

Two pattern grids serve different inventories:

• Harmonic/classic formations emphasise geometry, timeframe tag, directional bias, reliability bar, optional measured target.

• Dedicated candlestick list enumerates candle grammar (engulfing, stars, etc.) with emoji shorthand and reliability gauges.

• Confidence / reliability sliders: encode pattern strength per backend rules—not win rates on your account.

• Data source chip (H4/D1 real vs SYNTH): tags starting with “real” mean actual provider OHLC powered the run; SYNTH means a fallback engine—be extra skeptical of tight levels and pattern claims.

Always visually confirm patterns; thin markets print misleading wicks.

Each horizon shows a 0–100 score, colour, text signal, and RSI readout, plus a bar chart and quick grid.

• Agreement: when multiple horizons share colour/signal, the story is simpler; when they diverge, expect pullbacks, mean reversion, or fakeouts.

• RSI per TF: spot where heat is isolated (e.g. scalping overbought while daily neutral).

Use this block to answer: “Is my lower‑TF entry fighting the higher‑TF tide?”

The second Monte Carlo card repeats core stats with a large area fan (5th–95th percentile shading) and explicit 68% / 95% interval boxes.

• Volatility profile: annualized vol, z‑score vs own history, percentile rank, and narrative—flags when you are trading hotter or colder than usual conditions.

• Risk score: composite danger meter with colour banding and textual advice—pair with ATR% and spread for real‑world stop placement.

• Expected price mini card: emphasises median/expected move vs spot with colour cue—same family as the MC engine, so don’t double‑count it as “new” information.

These four tiles synthesize quality, emotion, structure, and flow flavour:

• F‑Score: checklist of pass/fail criteria with aggregate score/tier—use as a consistency filter; read each line item to know *why* it passed.

• Sentiment score: composite fear/greed style scale with sub‑components and gradient marker—contrarian or trend‑confirming depending on your style, but never solo.

• Market regime: descriptive state (trend/volatility/squeeze tags) with ADX/Boll width metrics and action advice text—helpful for strategy selection (trend vs range tools).

• Smart money block: SMI score, early/late session bias, retail sentiment label, divergence banner—interpret as modelled flow pressure, not order‑book truth.

When these four conflict, prefer regime + risk score as the tie‑breaker for sizing.

The seven mini cards recap session stats (open/high/low), spread, pip definition, L/S split, and AI view wording—fast desk reference.

• Refresh: pulls a new analysis pass; watch for data‑source changes after refresh on illiquid tickers.

• Watchlist star: local browser storage convenience—does not sync positions or alerts server‑side.

Workflow: start with regime + MTF → check MC distribution for tail risk → map liquidity pools → only then fine‑tune entries with patterns and the trade template.