import { useMemo } from "react"; import { useSQLQuery, useDiveState } from "@motherduck/react-sql-query"; import { ResponsiveContainer, ScatterChart, Scatter, XAxis, YAxis, ZAxis, CartesianGrid, Tooltip, LineChart, Line, BarChart, Bar } from "recharts"; import { BookOpen, Coins, Gem, Landmark, Search, ShieldAlert, Store, TrendingUp, ScrollText } from "lucide-react"; export const REQUIRED_DATABASES = [ { type: 'database', path: 'md:osrs_data', alias: 'osrs_data' } ]; const N = (v) => (v != null ? Number(v) : 0); const fmt = (v) => N(v).toLocaleString(); const gpShort = (v) => { const n = N(v); if (Math.abs(n) >= 1_000_000_000) return `${(n / 1_000_000_000).toFixed(2)}B`; if (Math.abs(n) >= 1_000_000) return `${(n / 1_000_000).toFixed(2)}M`; if (Math.abs(n) >= 1_000) return `${(n / 1_000).toFixed(1)}K`; return `${Math.round(n)}`; }; const pct = (v, d = 2) => `${N(v).toFixed(d)}%`; const usd = (v) => `$${N(v).toFixed(2)}`; const WOOD = "#3b2414"; const DARK_WOOD = "#1d120b"; const PARCHMENT = "#ead7aa"; const PARCHMENT_2 = "#d9bd7f"; const INK = "#2a1b10"; const MUTED_INK = "#715838"; const GOLD = "#c88a1a"; const RED = "#8e2f23"; const GREEN = "#2f6b3f"; const RUNE = "#2d6f84"; const LINE = "#8f7346"; function LoadingBlock({ height = 120 }) { return

; } function Shell({ children }) { return (

{children}

); } function Header({ refreshedAt }) { return (

Grand Exchange Alpha

An interactive explanation of the economy inside Old School RuneScape: Jagex's 2013 revival of the 2007-era version of RuneScape, a game lineage now roughly 25 years old.

Live market snapshot: {refreshedAt || "loading"}
Uses live Grand Exchange prices to explain spreads, tax, liquidity, Bonds, and purchasing power for non-players.

); } function NavButton({ children, active, onClick }) { return ( ); } function ScrollPanel({ children, style }) { return

{children}

; } function SignTitle({ icon: Icon, label, title, children }) { return (

{Icon ? : null}{label}

{title}

{children ?

{children}

: null}

); } function ChartFrame({ title, subtitle, x, y, footnote, children }) { return (

{title}

{subtitle ?

{subtitle}

: null}

{x ?

X: {x}

: null} {y ?

Y: {y}

: null}

{children} {footnote ?

{footnote}

: null}

); } function RuneKpi({ label, value, sub, accent = GOLD }) { return (

{value}

{label}

{sub ?

{sub}

: null}

); } function ItemButton({ children, onClick }) { return ( ); } function SelectBox({ value, onChange, children }) { return ( ); } const labelFor = { avg_active_items: "Active traded items", avg_priced_items: "Priced items observed", active_item_share_pct: "Active item share", capital_required: "Capital required", expected_roic_pct: "Expected ROIC (quoted)", real_margin: "Margin after tax", ge_tax: "GE tax", naive_margin: "Paper spread", limit_constrained_units: "Practical units", limit_constrained_profit: "Practical profit", vol_1h: "1h volume", buy_limit: "Buy limit", bond_mid_gp: "Bond midpoint", membership_days_per_1m_gp: "Days per 1M GP", usd_per_1m_gp: "USD per 1M GP", mid_price: "Midpoint price", daily_volatility: "Daily movement", avg_daily_volume_signal: "Volume signal", portfolio_roic_pct: "Portfolio ROIC (quoted)", blended_roic_pct: "Blended ROIC (quoted)", tax_take_pct: "Tax take", items: "Items", candidates: "Candidates", value: "Observed items" }; function prettyValue(key, value) { if (value == null || value === "") return "n/a"; if (typeof value !== "number") return String(value); if (key.includes("pct") || key.includes("roic") || key.includes("volatility")) return `${value.toFixed(1)}%`; if (key.includes("usd")) return `$${value.toFixed(2)}`; if (key.includes("days")) return value.toFixed(1); if (key.includes("price") || key.includes("margin") || key.includes("tax") || key.includes("profit") || key.includes("capital") || key.includes("mid")) return `${gpShort(value)} gp`; if (Math.abs(value) >= 1000) return gpShort(value); return value.toFixed(1); } function CustomTooltip({ active, payload }) { if (!active || !payload || !payload.length) return null; const r = payload[0].payload; const preferred = ["capital_required", "expected_roic_pct", "portfolio_roic_pct", "blended_roic_pct", "practical_profit", "limit_constrained_profit", "limit_constrained_units", "candidates", "items", "real_margin", "ge_tax", "naive_margin", "tax_take_pct", "vol_1h", "buy_limit", "avg_active_items", "active_item_share_pct", "bond_mid_gp", "membership_days_per_1m_gp", "usd_per_1m_gp", "mid_price", "daily_volatility", "avg_daily_volume_signal"]; const keys = preferred.filter((k) => r[k] !== undefined).slice(0, 7); return (

{r.name || r.week || r.day || r.month}

{keys.map((k) => (

{labelFor[k] || k} {prettyValue(k, r[k])}

))}

); } export default function GrandExchangeAlpha() { const [tab, setTab] = useDiveState("tab", "overview"); const [selectedItem, setSelectedItem] = useDiveState("selectedItem", 13190); const safeItem = Number.isFinite(Number(selectedItem)) ? Math.round(Number(selectedItem)) : 13190; const heroQ = useSQLQuery(` WITH live AS ( SELECT COUNT(*) AS live_priced_items, MAX(strftime(snapshot_refreshed_at, '%Y-%m-%d %H:%M UTC')) AS refreshed_at, SUM(CASE WHEN vol_1h > 0 THEN 1 ELSE 0 END) AS items_with_1h_volume, SUM(CASE WHEN real_margin > 0 AND vol_1h >= 10 THEN 1 ELSE 0 END) AS active_flip_candidates, SUM(CASE WHEN high > low AND (real_margin <= 0 OR vol_1h < 10) THEN 1 ELSE 0 END) AS traps, AVG(CASE WHEN low > 0 THEN (high - low) * 100.0 / low ELSE NULL END) AS avg_spread_pct FROM "osrs_data"."curated"."live_market_snapshot" ), archive AS ( SELECT COUNT(*) AS historical_rows, COUNT(DISTINCT item_id) AS historical_items, MIN(substr(fetched_at, 1, 10)) AS archive_start, MAX(substr(fetched_at, 1, 10)) AS archive_end FROM "osrs_data"."ge_tracker"."prices" ) SELECT * FROM live CROSS JOIN archive `); const bondQ = useSQLQuery(` SELECT item_id, name, high, low, (high + low) / 2.0 AS bond_mid_gp, ge_tax, naive_margin, real_margin, vol_1h, strftime(snapshot_refreshed_at, '%Y-%m-%d %H:%M UTC') AS snapshot_refreshed_at, 9.99::DOUBLE AS bond_usd_price, ((high + low) / 2.0) / 14.0 AS gp_per_membership_day, 1000000.0 * 14.0 / NULLIF(((high + low) / 2.0), 0) AS membership_days_per_1m_gp, 9.99 / NULLIF(((high + low) / 2.0) / 1000000.0, 0) AS usd_per_1m_gp, (((high + low) / 2.0) / 1000000.0) / 9.99 AS million_gp_per_usd, 30.0 * (((high + low) / 2.0) / 14.0) AS gp_needed_for_30_days_membership FROM "osrs_data"."curated"."live_market_snapshot" WHERE item_id = 13190 `); const radarQ = useSQLQuery(` WITH base AS ( SELECT r.name AS name, r.item_id AS item_id, r.high AS high, r.low AS low, r.buy_limit AS buy_limit, r.ge_tax AS ge_tax, r.real_margin AS real_margin, r.vol_1h AS vol_1h, r.roi_pct AS roi_pct, r.opportunity_value AS opportunity_value, r.flip_score AS flip_score, CASE WHEN r.merchant_category = 'Whale Items' THEN 'Capital-intensive rares' ELSE r.merchant_category END AS merchant_category, r.merchant_persona AS merchant_persona, r.liquidity_bucket AS liquidity_bucket, COALESCE(v.daily_volatility, 0) * 100.0 AS daily_volatility, LEAST(r.vol_1h, COALESCE(r.buy_limit, r.vol_1h)) AS limit_constrained_units, r.real_margin * LEAST(r.vol_1h, COALESCE(r.buy_limit, r.vol_1h)) AS limit_constrained_profit, r.low * LEAST(r.vol_1h, COALESCE(r.buy_limit, r.vol_1h)) AS capital_required, r.real_margin * 100.0 / NULLIF(r.low, 0) AS expected_roic_pct FROM "osrs_data"."curated"."merchant_radar" r LEFT JOIN "osrs_data"."curated"."item_volatility_90d" v ON r.item_id = v.item_id WHERE r.real_margin > 0 AND r.vol_1h >= 10 ), bounds AS ( SELECT quantile_cont(capital_required, 0.98) AS capital_cap, quantile_cont(expected_roic_pct, 0.98) AS roic_cap FROM base ) SELECT b.* FROM base b CROSS JOIN bounds q WHERE b.capital_required <= q.capital_cap AND b.expected_roic_pct <= q.roic_cap ORDER BY limit_constrained_profit DESC LIMIT 500 `); const selectorQ = useSQLQuery(` SELECT item_id, name FROM "osrs_data"."curated"."live_market_snapshot" ORDER BY lower(name) `); const economyQ = useSQLQuery(` WITH live AS ( SELECT COUNT(*) AS live_priced_items, SUM(CASE WHEN vol_1h > 0 THEN 1 ELSE 0 END) AS current_items_with_1h_flow FROM "osrs_data"."curated"."live_market_snapshot" ), archive_daily AS ( SELECT DATE_TRUNC('day', TRY_CAST(fetched_at AS TIMESTAMP))::DATE AS day, COUNT(DISTINCT item_id) AS archived_priced_items, COUNT(DISTINCT CASE WHEN COALESCE(high_vol_1h, 0) + COALESCE(low_vol_1h, 0) > 0 THEN item_id END) AS archived_active_items FROM "osrs_data"."ge_tracker"."prices" WHERE high > 0 AND low > 0 AND TRY_CAST(fetched_at AS TIMESTAMP) >= TIMESTAMP '2025-09-01' GROUP BY 1 ), archive AS ( SELECT AVG(archived_priced_items) AS avg_archived_priced_items, AVG(archived_active_items) AS avg_archived_active_items, MAX(archived_active_items) AS max_archived_active_items FROM archive_daily ) SELECT 'Current live priced universe' AS name, live_priced_items AS value FROM live UNION ALL SELECT 'Current items with 1h flow', current_items_with_1h_flow FROM live UNION ALL SELECT 'Archive avg priced items/day', avg_archived_priced_items FROM archive UNION ALL SELECT 'Archive avg active items/day', avg_archived_active_items FROM archive UNION ALL SELECT 'Archive best active day', max_archived_active_items FROM archive `); const categoryQ = useSQLQuery(` WITH base AS ( SELECT CASE WHEN merchant_category = 'Whale Items' THEN 'Capital-intensive rares' ELSE merchant_category END AS merchant_category, low, buy_limit, vol_1h, real_margin, ge_tax, naive_margin, LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS practical_units, low * LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS capital_required, real_margin * LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS practical_profit, real_margin * 100.0 / NULLIF(low, 0) AS expected_roic_pct, ge_tax * 100.0 / NULLIF(naive_margin, 0) AS tax_take_pct FROM "osrs_data"."curated"."merchant_radar" WHERE real_margin > 0 AND vol_1h >= 10 AND low > 0 ) SELECT merchant_category AS name, COUNT(*) AS candidates, SUM(practical_profit) AS practical_profit, SUM(capital_required) AS capital_required, SUM(practical_profit) / NULLIF(SUM(capital_required), 0) * 100.0 AS portfolio_roic_pct, AVG(tax_take_pct) AS tax_take_pct FROM base GROUP BY 1 HAVING COUNT(*) >= 5 ORDER BY portfolio_roic_pct DESC LIMIT 10 `); const diagnosticQ = useSQLQuery(` WITH base AS ( SELECT name, low, buy_limit, vol_1h, real_margin, ge_tax, naive_margin, LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS practical_units, low * LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS capital_required, real_margin * LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) AS practical_profit, real_margin * 100.0 / NULLIF(low, 0) AS expected_roic_pct, ge_tax * 100.0 / NULLIF(naive_margin, 0) AS tax_take_pct, CASE WHEN ge_tax * 100.0 / NULLIF(naive_margin, 0) >= 80 THEN 'Tax wall' WHEN low * LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) >= 100000000 THEN 'Capital intensive' WHEN vol_1h < 25 THEN 'Thin but quoted' WHEN real_margin * 100.0 / NULLIF(low, 0) >= 5 THEN 'High ROIC micro-yield' WHEN LEAST(vol_1h, COALESCE(buy_limit, vol_1h)) >= 1000 THEN 'Scale via volume' ELSE 'Balanced' END AS diagnostic FROM "osrs_data"."curated"."merchant_radar" WHERE real_margin > 0 AND vol_1h >= 10 AND low > 0 ) SELECT diagnostic AS name, COUNT(*) AS items, SUM(practical_profit) AS practical_profit, SUM(capital_required) AS capital_required, SUM(practical_profit) / NULLIF(SUM(capital_required), 0) * 100.0 AS blended_roic_pct, AVG(expected_roic_pct) AS expected_roic_pct, AVG(tax_take_pct) AS tax_take_pct FROM base GROUP BY 1 ORDER BY practical_profit DESC `); const trapQ = useSQLQuery(` SELECT l.name, l.item_id, l.high, l.low, (l.high - l.low) AS naive_margin, l.ge_tax, l.real_margin, l.vol_1h, COALESCE(v.daily_volatility, 0) * 100.0 AS daily_volatility, CASE WHEN l.vol_1h = 0 THEN 'No recent trades' WHEN l.vol_1h < 10 THEN 'Thin recent market' WHEN l.real_margin <= 0 THEN 'Tax removes margin' ELSE 'Execution risk' END AS trap_reason FROM "osrs_data"."curated"."live_market_snapshot" l LEFT JOIN "osrs_data"."curated"."item_volatility_90d" v ON l.item_id = v.item_id WHERE l.high > l.low AND (l.real_margin <= 0 OR l.vol_1h < 10) ORDER BY (l.high - l.low) DESC LIMIT 40 `); const bondHistQ = useSQLQuery(` WITH daily_bond AS ( SELECT DATE_TRUNC('month', TRY_CAST(fetched_at AS TIMESTAMP))::DATE AS month, AVG((high + low) / 2.0) AS bond_mid_gp FROM "osrs_data"."ge_tracker"."prices" WHERE item_id = 13190 AND high > 0 AND low > 0 GROUP BY 1 ), priced AS ( SELECT month, bond_mid_gp, CASE WHEN month BETWEEN DATE '2020-01-01' AND DATE '2022-05-03' THEN 6.99 WHEN month BETWEEN DATE '2022-05-04' AND DATE '2024-06-24' THEN 7.99 WHEN month BETWEEN DATE '2024-06-25' AND DATE '2026-03-09' THEN 8.99 ELSE 9.99 END AS bond_usd_price FROM daily_bond ) SELECT strftime(month, '%Y-%m') AS month, bond_mid_gp, 1000000.0 * 14.0 / NULLIF(bond_mid_gp, 0) AS membership_days_per_1m_gp, bond_usd_price / NULLIF(bond_mid_gp / 1000000.0, 0) AS usd_per_1m_gp, 30.0 * (bond_mid_gp / 14.0) AS gp_needed_for_30_days_membership FROM priced ORDER BY month `); const volQ = useSQLQuery(` WITH base AS ( SELECT item_id, name, days_observed, avg_mid_price, daily_volatility * 100.0 AS daily_volatility, avg_abs_move, avg_real_margin_90d, avg_daily_volume_signal, volatility_bucket, CASE WHEN avg_daily_volume_signal >= 1000 AND daily_volatility >= 0.05 THEN 'Active, high-movement market' WHEN avg_daily_volume_signal >= 1000 THEN 'Active, steadier market' WHEN daily_volatility >= 0.05 THEN 'Thin, high-movement market' ELSE 'Quiet market' END AS volatility_label FROM "osrs_data"."curated"."item_volatility_90d" WHERE days_observed >= 30 AND avg_daily_volume_signal > 0 ), bounds AS ( SELECT quantile_cont(avg_daily_volume_signal, 0.98) AS volume_cap, quantile_cont(daily_volatility, 0.98) AS volatility_cap FROM base ) SELECT b.* FROM base b CROSS JOIN bounds q WHERE b.avg_daily_volume_signal <= q.volume_cap AND b.daily_volatility <= q.volatility_cap ORDER BY avg_daily_volume_signal DESC, daily_volatility DESC LIMIT 500 `); const weatherQ = useSQLQuery(` SELECT strftime(day, '%Y-%m-%d') AS day, observations, items_observed, avg_real_margin, median_real_margin, avg_spread_pct, volume_signal, spread_7d, volume_7d, market_weather FROM "osrs_data"."curated"."market_weather_daily" ORDER BY day `); const itemQ = useSQLQuery(` SELECT l.item_id, l.name, l.examine, l.members, l.buy_limit, l.high, l.low, l.ge_tax, l.naive_margin, l.real_margin, l.vol_5m, l.vol_1h, LEAST(l.vol_1h, COALESCE(l.buy_limit, l.vol_1h)) AS limit_constrained_units, l.real_margin * LEAST(l.vol_1h, COALESCE(l.buy_limit, l.vol_1h)) AS limit_constrained_profit, l.low * LEAST(l.vol_1h, COALESCE(l.buy_limit, l.vol_1h)) AS capital_required, l.real_margin * 100.0 / NULLIF(l.low, 0) AS expected_roic_pct, strftime(l.high_time, '%Y-%m-%d %H:%M UTC') AS high_time, strftime(l.low_time, '%Y-%m-%d %H:%M UTC') AS low_time, m.roi_pct, m.spread_pct, CASE WHEN m.merchant_category = 'Whale Items' THEN 'Capital-intensive rares' ELSE m.merchant_category END AS merchant_category, m.merchant_persona, v.daily_volatility, v.avg_abs_move, v.volatility_bucket, CASE WHEN l.item_id = 13190 THEN 'Bond-linked item: this is the official USD, GP, and membership benchmark.' WHEN l.real_margin <= 0 THEN 'The listed spread does not survive the Grand Exchange tax.' WHEN l.vol_1h = 0 THEN 'No recent market flow; the quote may be hard to execute.' WHEN l.vol_1h < 10 THEN 'Thin recent market; execution risk is high.' WHEN l.real_margin > 0 AND l.vol_1h >= 100 THEN 'Liquid positive-margin candidate. Buy limits still cap how much one account can realistically capture per limit window.' WHEN l.real_margin > 0 THEN 'Positive-margin candidate with moderate market flow. Buy limits and available volume determine whether this scales.' ELSE 'Monitor only.' END AS plain_english_signal FROM "osrs_data"."curated"."live_market_snapshot" l LEFT JOIN "osrs_data"."curated"."merchant_radar" m ON l.item_id = m.item_id LEFT JOIN "osrs_data"."curated"."item_volatility_90d" v ON l.item_id = v.item_id WHERE l.item_id = ${safeItem} LIMIT 1 `, { enabled: !!safeItem }); const itemHistQ = useSQLQuery(` SELECT strftime(DATE_TRUNC('month', TRY_CAST(fetched_at AS TIMESTAMP)), '%Y-%m') AS month, AVG((high + low) / 2.0) AS mid_price, AVG(real_margin) AS avg_real_margin, SUM(COALESCE(high_vol_1h, 0) + COALESCE(low_vol_1h, 0)) AS volume_signal FROM "osrs_data"."ge_tracker"."prices" WHERE item_id = ${safeItem} AND high > 0 AND low > 0 GROUP BY 1 ORDER BY 1 `, { enabled: !!safeItem }); const hero = Array.isArray(heroQ.data) ? heroQ.data[0] || {} : {}; const bond = Array.isArray(bondQ.data) ? bondQ.data[0] || {} : {}; const radar = Array.isArray(radarQ.data) ? radarQ.data : []; const traps = Array.isArray(trapQ.data) ? trapQ.data : []; const categories = Array.isArray(categoryQ["data"]) ? categoryQ["data"].map(r => ({ ...r, candidates: N(r.candidates), practical_profit: N(r.practical_profit), capital_required: N(r.capital_required), portfolio_roic_pct: N(r.portfolio_roic_pct), tax_take_pct: N(r.tax_take_pct) })) : []; const diagnostics = Array.isArray(diagnosticQ["data"]) ? diagnosticQ["data"].map(r => ({ ...r, items: N(r.items), practical_profit: N(r.practical_profit), capital_required: N(r.capital_required), blended_roic_pct: N(r.blended_roic_pct), expected_roic_pct: N(r.expected_roic_pct), tax_take_pct: N(r.tax_take_pct) })) : []; const bondHist = Array.isArray(bondHistQ["data"]) ? bondHistQ["data"].map(r => ({ ...r, membership_days_per_1m_gp: N(r.membership_days_per_1m_gp), usd_per_1m_gp: N(r.usd_per_1m_gp), bond_mid_gp: N(r.bond_mid_gp) })) : []; const volRows = Array.isArray(volQ.data) ? volQ.data : []; const weather = Array.isArray(weatherQ.data) ? weatherQ.data : []; const item = Array.isArray(itemQ.data) ? itemQ.data[0] || {} : {}; const selectorItems = Array.isArray(selectorQ.data) ? selectorQ.data : []; const itemHist = Array.isArray(itemHistQ["data"]) ? itemHistQ["data"].map(r => ({ ...r, mid_price: N(r.mid_price), avg_real_margin: N(r.avg_real_margin), volume_signal: N(r.volume_signal) })) : []; const economyRows = Array.isArray(economyQ["data"]) ? economyQ["data"].map(r => ({ ...r, value: N(r.value) })) : []; const radarPlot = useMemo(() => radar.map(r => ({ ...r, vol_1h: N(r.vol_1h), buy_limit: N(r.buy_limit), real_margin: N(r.real_margin), daily_volatility: N(r.daily_volatility), limit_constrained_units: N(r.limit_constrained_units), limit_constrained_profit: N(r.limit_constrained_profit), capital_required: N(r.capital_required), expected_roic_pct: N(r.expected_roic_pct), opportunity_value: Math.max(1, N(r.limit_constrained_profit)), roi_pct: N(r.roi_pct), flip_score: N(r.flip_score) })), [radar]); const trapRows = useMemo(() => traps.slice(0, 12).map(r => ({ name: r.name, naive_margin: N(r.naive_margin), real_margin: N(r.real_margin), ge_tax: N(r.ge_tax), vol_1h: N(r.vol_1h), daily_volatility: N(r.daily_volatility), trap_reason: r.trap_reason, item_id: N(r.item_id) })), [traps]); const volPlot = useMemo(() => volRows.map(r => ({ ...r, daily_volatility: N(r.daily_volatility), avg_daily_volume_signal: N(r.avg_daily_volume_signal), avg_mid_price: N(r.avg_mid_price) })), [volRows]); const latestWeather = weather.length ? weather[weather.length - 1] : {}; const tabs = [ ["overview", "Guidebook"], ["alpha", "Trade Desk"], ["fx", "Bond Counter"], ["risk", "Market Lessons"], ["item", "Order Ledger"] ]; return (

{tabs.map(([id, label]) => setTab(id)}>{label})}

{tab === "overview" && (

Old School RuneScape is a game where players grind monsters, skills, and bosses for gold pieces. But once that gold enters the Grand Exchange, it starts behaving like capital: it can chase yield, absorb fees, hit position limits, lose purchasing power, or buy membership time through Bonds. This Dive uses that market to teach one question: when does playtime become an asset?

Why this matters

Players pay dollars to enter Gielinor. The best players build GP stacks that can buy the game back.

Old School RuneScape turns time, skill, luck, speculation, and market knowledge into gold pieces. Bonds turn those gold pieces into official membership days. The result is a fantasy economy with real trading fundamentals: turnover, liquidity, fees, position limits, volatility, and purchasing power.

Core thesis

Profit is not where the biggest spread is. Profit is where margin survives tax, buy limits, market depth, and time.

{heroQ.isLoading || bondQ.isLoading ? : (

)}

First-time reading: a spread is the gap between the current high and low prices. It looks like a possible flip, but it is not profit yet. The rest of the Dive keeps subtracting reality: tax, volume, buy limits, and stale markets.

Spread

Gap between buy and sell prices.

Tax

Trading friction that reduces margin.

Liquidity

Recent market flow; decides whether a quote can execute.

The Old School Bond is the sanctioned bridge between USD, GP, and membership days. {bondQ.isLoading ? : (

)}

{economyQ["isLoading"] ? : ( } /> )} Live opportunities come from the current curated market layer. The historical archive currently runs from {hero.archive_start || "..."} to {hero.archive_end || "..."} across {fmt(hero.historical_rows)} price rows.

)} {tab === "alpha" && (

Real trading concept: capacity. A strategy is only useful if it can absorb capital. This section converts a fantasy flip into a trading-capacity problem: after tax, recent volume, and GE buy limits, which items still have practical scale? {radarQ.isLoading ? : ( pct(v, 1)} /> } /> { if (p && p.item_id) { setSelectedItem(N(p.item_id)); setTab("item"); } }} /> )}

{categoryQ["isLoading"] ? : ( pct(v, 1)} /> } /> )} {diagnosticQ["isLoading"] ? : ( } /> )}

Read this page like a trade desk. A flip with 500K gp profit may be weak if it requires 200M gp of capital; a smaller profit can be better if it turns over quickly on less capital. Expected ROIC (quoted) is after GE tax and before slippage; it assumes current prices are executable. Capacity is capped by the smaller of recent volume and buy limit.

Return

After-tax margin as a percent of the low price.

Capital

Entry price multiplied by practical units.

Risk

Thin volume, stale quotes, and limits prevent paper returns from scaling.

{radarQ.isLoading ? : radar.slice(0, 12).map((r, i) => ( { setSelectedItem(N(r.item_id)); setTab("item"); }}> {i + 1}. {r.name}
{gpShort(r.capital_required)} capital at risk → spread - {gpShort(r.ge_tax)} tax ± {pct(r.daily_volatility, 1)} price movement = {gpShort(r.limit_constrained_profit)} expected
units {fmt(r.limit_constrained_units)} · Expected ROIC (quoted) {pct(r.expected_roic_pct, 1)} · limit {fmt(r.buy_limit)} {gpShort(r.limit_constrained_profit)} ))} Real trading concept: false alpha. These are not opportunities. They are examples where the displayed spread is misleading because fees erase the margin, volume is thin, or execution would be unreliable. {trapQ.isLoading ? : trapRows.map((r) => ( { setSelectedItem(N(r.item_id)); setTab("item"); }}> {r.name}
{gpShort(r.naive_margin)} paper spread ± {pct(r.daily_volatility, 1)} price movement - {gpShort(r.ge_tax)} tax = {gpShort(r.real_margin)} outcome
failure mode: {r.trap_reason} · 1h volume {fmt(r.vol_1h)} {gpShort(r.real_margin)} ))}

)} {tab === "fx" && (

Real trading concept: purchasing power. By now, the Dive has shown that GP behaves like market money inside the game. Bonds make that money measurable against the real world: dollars buy Bonds, Bonds sell for GP, and GP can buy membership time. No black-market gold prices are used. {bondQ.isLoading ? : (

)} {bondHistQ["isLoading"] ? : ( } /> )}

)} {tab === "risk" && (

Real trading concept: volatility without depth is not automatically opportunity. At this point, you have seen market size, spreads, taxes, buy limits, and Bonds. This section asks whether price movement is paired with enough market depth to matter. {volQ.isLoading ? : ( pct(v, 1)} /> } /> { if (p && p.item_id) { setSelectedItem(N(p.item_id)); setTab("item"); } }} /> )}

Runes, herbs, bones, sharks, and logs behave like consumed commodities: constant demand, high turnover, smaller margins. Weapons and armor behave like capital equipment: expensive assets players use to produce PvM income. Capital-intensive rares behave more like art or collectibles: status, scarcity, bigger tickets, and lower liquidity. Historical regime labels summarize spread width, volume signal, and observed market breadth. {weatherQ.isLoading ? : (

)}

)} {tab === "item" && (

This is the final drilldown. After learning the market concepts section by section, choose any Grand Exchange item from the dropdown or click a row/point elsewhere to inspect its live quote, tax drag, buy limit, practical unit cap, and historical path. {selectorQ.isLoading ? : (

Select any item in the live Grand Exchange universe:

{selectorItems.map(r => )}

)} {itemQ.isLoading ? : (

0 ? GREEN : RED} />

)}

Plain-English signal

{item.plain_english_signal || "Loading item signal..."}

{item.examine || "No examine text available."}

Buy limit
{fmt(item.buy_limit)}

1h volume
{fmt(item.vol_1h)}

Practical units
{fmt(item.limit_constrained_units)}

Expected ROIC (quoted)
{pct(item.expected_roic_pct, 1)}

Capital required
{gpShort(item.capital_required)}

Category
{item.merchant_category || "Unclassified"}

Movement bucket
{item.volatility_bucket || "n/a"}

{itemHistQ["isLoading"] ? : ( } /> )}

)}

Live opportunities use curated current market data; historical views use the archive layer. Official Bond benchmark only — no black-market RWT data.

); }

Grand Exchange Alpha: A Field Guide to Gielinor's Markets

Comments