44:["$","title",null,{"children":"AI Stock Performance | Bobby Reedy | Observable"}] 4c:Tc96,display((() => { const members = latest.filter(d => d.group !== "S&P 500"); const dateFmt = d3.utcFormat("%b %-d, %Y"); const lo = Math.min(0, d3.min(members, d => d.ret), spyRet); const hi = Math.max(0, d3.max(members, d => d.ret), spyRet); const render = w => { const mobile = w < 600; const outer = Math.min(900, w); const padPx = mobile ? 14 : 24; const inner = outer - 2 * padPx; const ml = mobile ? 96 : 120, mr = mobile ? 60 : 20; const rowH = mobile ? 30 : 30; const pad = (hi - lo) * (mobile ? 0.04 : 0.14); const domain = [lo - pad, hi + pad]; const panel = (group, first, last) => { const rows = members.filter(d => d.group === group).sort((a, b) => d3.descending(a.ret, b.ret)); const valueMarks = mobile ? [Plot.text(rows, {y: "name", text: d => fmt(d.ret), frameAnchor: "right", textAnchor: "start", dx: 10, fontSize: 14, fontWeight: 600})] : [ Plot.text(rows.filter(d => d.ret >= 0), {y: "name", x: "ret", text: d => fmt(d.ret), textAnchor: "start", dx: 6}), Plot.text(rows.filter(d => d.ret < 0), {y: "name", x: "ret", text: d => fmt(d.ret), textAnchor: "end", dx: -6}) ]; return Plot.plot({ width: inner, height: rows.length * rowH + 34 + (last ? 40 : 6), marginLeft: ml, marginRight: mr, marginTop: 34, marginBottom: last ? 40 : 6, style: {fontSize: mobile ? "13px" : "14px", background: "transparent", color: "#1a1a1a"}, x: {domain, grid: true, label: null, ticks: mobile ? 4 : 8, tickFormat: d3.format(".0%"), axis: last ? "bottom" : null}, y: {domain: rows.map(d => d.name), label: null, padding: 0.25}, marks: [ Plot.barX(rows, {y: "name", x: "ret", fill: palette.get(group)}), Plot.ruleX([0]), Plot.ruleX([spyRet], {stroke: "#777", strokeDasharray: "4,3"}), ...valueMarks, Plot.text([group], {frameAnchor: "top-left", lineAnchor: "bottom", dx: -ml, dy: -8, fontWeight: "bold", fontSize: mobile ? 16 : 15, fill: "#1a1a1a"}), first ? Plot.text([`S&P 500 ${fmt(spyRet)}`], {x: spyRet, frameAnchor: "top", lineAnchor: "bottom", dy: -8, fill: "#555", fontSize: 12}) : null ] }); }; return html`

The AI divide

Selected AI-related stock returns | ${dateFmt(d3.min(stocks, d => d.Date))} – ${dateFmt(win.end)}

${groups.map((g, i) => panel(g, i === 0, i === groups.length - 1))}

Adjusted-close returns, base close to latest close. Dashed line = S&P 500 (SPY).

`; }; const box = html`

`; let last = 0; new ResizeObserver(() => { const w = Math.floor(box.clientWidth); if (!w || Math.abs(w - last) < 2) return; last = w; box.replaceChildren(render(w)); }).observe(box); return box; })()); 4d:T653,display((() => { const render = w => { const mobile = w < 600; return Plot.plot({ width: Math.min(w, 960), height: mobile ? Math.max(440) : 500, marginLeft: mobile ? 46 : 50, marginRight: mobile ? 64 : 210, marginTop: 20, marginBottom: 50, style: {fontSize: mobile ? "13px" : "13px"}, x: {type: "utc", label: null, ticks: mobile ? 4 : 8}, y: {grid: true, label: mobile ? "Index (100 = start)" : "Indexed (100 = window start)"}, color: {legend: true, domain: [...palette.keys()], range: [...palette.values()]}, marks: [ Plot.ruleY([100]), Plot.lineY(groupSeries.filter(d => d.group !== "S&P 500"), {x: "Date", y: "idx", stroke: "group", strokeWidth: 2.5}), Plot.lineY(groupSeries.filter(d => d.group === "S&P 500"), {x: "Date", y: "idx", stroke: "group", strokeWidth: 2, strokeDasharray: "5,4"}), Plot.text(groupSeries, Plot.selectLast({ x: "Date", y: "idx", z: "group", fill: "group", text: d => mobile ? fmt(d.ret) : `${d.group} ${fmt(d.ret)}`, textAnchor: "start", dx: 6, fontWeight: 700, fontSize: mobile ? 14 : 13 })), Plot.tip(groupSeries, Plot.pointerX({ x: "Date", y: "idx", z: "group", title: d => `${d.group}\n${fmt(d.ret)}` })) ] }); }; const box = html`

`; let last = 0; new ResizeObserver(() => { const w = Math.floor(box.clientWidth); if (!w || Math.abs(w - last) < 2) return; last = w; box.replaceChildren(render(w)); }).observe(box); return box; })()); 4e:T11fc,display((() => { const members = stocks.filter(d => d.group !== "S&P 500"); const xDomain = d3.extent(members, d => d.Date); let selected = null; // ticker locked by click/tap; survives resizes const render = w => { const mobile = w < 600; const panelH = mobile ? 280 : 280; const width = Math.min(w, 960); // One chart per group, so each group gets its own y-axis min/max. const panel = group => Plot.plot({ width, height: panelH + 30 + 34, marginTop: 30, marginBottom: 34, marginLeft: mobile ? 42 : 60, marginRight: mobile ? 56 : 80, style: {fontSize: mobile ? "13px" : "12px"}, x: {type: "utc", domain: xDomain, label: null, ticks: mobile ? 4 : 8}, y: {grid: true, nice: true, label: mobile ? "Index (100 = start)" : "Indexed (100 = window start)"}, color: {domain: [...palette.keys()], range: [...palette.values()]}, marks: [ Plot.ruleY([100]), Plot.lineY(members.filter(d => d.group === group), {x: "Date", y: "idx", z: "ticker", stroke: "group", strokeWidth: 1.5, title: "ticker"}), Plot.text(members.filter(d => d.group === group), Plot.selectLast({x: "Date", y: "idx", z: "ticker", text: "ticker", fill: "group", textAnchor: "start", dx: 5, fontWeight: 600})), Plot.text([group], {frameAnchor: "top-left", dx: 6, dy: 6, fontWeight: "bold", fontSize: mobile ? 15 : 14}), Plot.tip(members.filter(d => d.group === group), Plot.pointer({x: "Date", y: "idx", title: d => `${d.name}\n${fmt(d.ret)}`})) ] }); const wrap = html`

${mobile ? "Tap" : "Hover or click"} a line or ticker to highlight it. ${mobile ? "Tap" : "Click"} it again or empty space to clear.

${groups.map(g => panel(g))}

`; // Focus: highlighted stock keeps its color; everything else (in every panel) turns gray and semi-transparent. const lines = [...wrap.querySelectorAll('g[aria-label="line"] path')]; const labels = [...wrap.querySelectorAll('g[aria-label="text"] text')].filter(l => !groups.includes(l.textContent)); const focus = ticker => { for (const p of lines) { const on = ticker == null || p.dataset.ticker === ticker; p.setAttribute("stroke", on ? p.dataset.stroke : "#9a9a9a"); p.setAttribute("stroke-opacity", ticker == null || on ? 1 : 0.3); p.setAttribute("stroke-width", ticker != null && on ? 3 : 1.5); if (ticker != null && on) p.parentNode.appendChild(p); // bring to front } for (const l of labels) { const on = ticker == null || l.textContent === ticker; l.style.fill = on ? "" : "#9a9a9a"; l.style.opacity = ticker == null || on ? 1 : 0.3; l.style.fontWeight = ticker != null && on ? "800" : "600"; } }; for (const p of lines) { const t = p.querySelector("title"); p.dataset.ticker = t ? t.textContent : ""; t?.remove(); // avoid the native browser tooltip p.dataset.stroke = p.getAttribute("stroke"); p.style.pointerEvents = "none"; // wide invisible copy so thin lines are easy to hover or tap const hit = p.cloneNode(false); hit.setAttribute("stroke", "transparent"); hit.setAttribute("stroke-width", mobile ? 22 : 14); hit.setAttribute("fill", "none"); hit.dataset.hit = "1"; hit.dataset.ticker = p.dataset.ticker; hit.style.pointerEvents = "stroke"; hit.style.cursor = "pointer"; // mouse hover previews; touch is handled by click only (touch "leave" would otherwise reset it) hit.addEventListener("pointerenter", e => { if (e.pointerType !== "touch") focus(p.dataset.ticker); }); p.after(hit); } for (const l of labels) { l.style.pointerEvents = "all"; l.style.cursor = "pointer"; } wrap.addEventListener("pointerleave", e => { if (e.pointerType !== "touch") focus(selected); }); wrap.addEventListener("click", e => { const t = e.target?.dataset?.hit ? e.target.dataset.ticker : labels.includes(e.target) ? e.target.textContent : null; selected = t == null || t === selected ? null : t; // tap same stock or empty space to clear focus(selected); }); focus(selected); return wrap; }; const box = html`

`; let last = 0; new ResizeObserver(() => { const w = Math.floor(box.clientWidth); if (!w || Math.abs(w - last) < 2) return; last = w; box.replaceChildren(render(w)); }).observe(box); return box; })());4f:T1485,display((() => { const order = ["Big Tech", "AI semis", "AI cloud & data-center", "S&P 500"]; const short = {"Big Tech": "Big Tech", "AI semis": "AI semis", "AI cloud & data-center": "AI cloud", "S&P 500": "S&P 500"}; const labels = order.map(g => short[g]); const WINDOW = 30; // trading days for the rolling view // Daily return per ticker, then equal-weight average per group per day. const dayRet = []; for (const [, rows] of d3.group(raw, d => d.ticker)) { rows.sort((a, b) => a.Date - b.Date); for (let i = 1; i < rows.length; i++) dayRet.push({ts: +rows[i].Date, group: rows[i].group, r: rows[i].close / rows[i - 1].close - 1}); } const byDate = d3.rollup(dayRet, v => d3.mean(v, d => d.r), d => d.ts, d => d.group); const daily = Array.from(byDate, ([ts, m]) => ({ts, vals: order.map(g => m.get(g))})) .filter(d => d.vals.every(v => v != null)) .sort((a, b) => a.ts - b.ts); const corr = (x, y) => { const mx = d3.mean(x), my = d3.mean(y); let sxy = 0, sxx = 0, syy = 0; for (let i = 0; i < x.length; i++) { const a = x[i] - mx, b = y[i] - my; sxy += a * b; sxx += a * a; syy += b * b; } return sxy / Math.sqrt(sxx * syy); }; const col = i => daily.map(d => d.vals[i]); const matrix = order.flatMap((a, i) => order.map((b, j) => ({a: labels[i], b: labels[j], r: corr(col(i), col(j))}))); const pairs = [[0, 1], [0, 2], [1, 2]]; const pairName = ([i, j]) => `${labels[i]} / ${labels[j]}`; const rolling = pairs.flatMap(p => { const out = []; for (let k = WINDOW - 1; k < daily.length; k++) { const s = daily.slice(k - WINDOW + 1, k + 1); out.push({Date: new Date(daily[k].ts), pair: pairName(p), r: corr(s.map(d => d.vals[p[0]]), s.map(d => d.vals[p[1]]))}); } return out; }); const pairR = pairs.map(p => ({name: pairName(p), r: corr(col(p[0]), col(p[1]))})).sort((a, b) => b.r - a.r); const dateFmt = d3.utcFormat("%b %-d, %Y"); const pairColors = ["#4e79a7", "#f28e2b", "#59a14f"]; const render = w => { const mobile = w < 600; const outer = Math.min(w, 900); const cell = mobile ? Math.floor((outer - 28 - 80) / 4) : 100; const ml = mobile ? 72 : 90; const heat = Plot.plot({ width: ml + 4 * cell + 10, height: 4 * cell + 44, marginLeft: ml, marginTop: 34, marginRight: 10, marginBottom: 10, style: {fontSize: mobile ? "13px" : "14px", background: "transparent"}, x: {domain: labels, axis: "top", label: null}, y: {domain: labels, label: null}, color: {type: "diverging", scheme: "rdbu", domain: [-1, 1]}, marks: [ Plot.cell(matrix, {x: "b", y: "a", fill: "r", inset: 1}), Plot.text(matrix, {x: "b", y: "a", text: d => d.r.toFixed(2), fill: d => Math.abs(d.r) > 0.6 ? "#fff" : "#1a1a1a", fontSize: mobile ? 14 : 16, fontWeight: 700}) ] }); const lo = Math.min(0, Math.floor(d3.min(rolling, d => d.r) * 10) / 10); const roll = Plot.plot({ width: outer - 28, height: mobile ? 340 : 360, marginLeft: mobile ? 40 : 46, marginRight: 50, marginTop: 20, style: {fontSize: "13px", background: "transparent"}, x: {type: "utc", label: null, ticks: mobile ? 4 : 8}, y: {grid: true, domain: [lo, 1], label: `${WINDOW}-day correlation`}, color: {legend: true, domain: pairs.map(pairName), range: pairColors}, marks: [ Plot.ruleY([0]), Plot.lineY(rolling, {x: "Date", y: "r", stroke: "pair", strokeWidth: 2}), Plot.text(rolling, Plot.selectLast({x: "Date", y: "r", z: "pair", text: d => d.r.toFixed(2), fill: "pair", textAnchor: "start", dx: 6, fontWeight: 700})), Plot.tip(rolling, Plot.pointerX({x: "Date", y: "r", z: "pair", title: d => `${d.pair}\n${d.r.toFixed(2)}`})) ] }); const hi = pairR[0], low = pairR.at(-1); return html`

How tightly do the groups move together?

Correlation of daily returns (equal-weight group averages), ${dateFmt(new Date(daily[0].ts))} – ${dateFmt(new Date(daily.at(-1).ts))}. 1.00 = move in lockstep, 0 = unrelated.

${heat}

Most correlated: ${hi.name} (${hi.r.toFixed(2)}). Least correlated: ${low.name} (${low.r.toFixed(2)}).

Rolling ${WINDOW}-day correlation

Correlations tend to rise in sell-offs, so a jump here signals the groups trading as one theme.

${roll}

`; }; const box = html`

`; let last = 0; new ResizeObserver(() => { const w = Math.floor(box.clientWidth); if (!w || Math.abs(w - last) < 2) return; last = w; box.replaceChildren(render(w)); }).observe(box); return box; })());50:Tda6,(() => { const colors = {"Big Tech": "#f24e2a", "AI semis": "#e5b50a", "AI cloud & data-center": "#008c68", "S&P 500": "#6b6b6b"}; const groupNames = ["Big Tech", "AI semis", "AI cloud & data-center"]; const pct = d3.format("+.1%"); const end = d3.max(raw, d => d.Date); const periods = [["1W", 7], ["1M", 30], ["3M", 90], ["6M", 180], ["YTD", "ytd"], ["1Y", 365]]; const startFor = p => p === "ytd" ? new Date(Date.UTC(end.getUTCFullYear(), 0, 1)) : d3.utcDay.offset(end, -p); // Return per ticker for one window: latest close vs. last close on or before the start. const periodReturns = start => { const bisect = d3.bisector(d => d.Date); const m = new Map(); for (const [t, all] of d3.group(raw, d => d.ticker)) { const rows = all.filter(d => d.Date <= end).sort((a, b) => a.Date - b.Date); if (!rows.length) continue; const i = Math.max(0, bisect.right(rows, start) - 1); m.set(t, rows.at(-1).close / rows[i].close - 1); } return m; }; const byPeriod = periods.map(([label, p]) => [label, periodReturns(startFor(p))]); const meta = d3.groups(raw, d => d.ticker).map(([, v]) => v[0]); const rows = meta.map(m => ({ ticker: m.ticker, name: m.name, group: m.group, vals: byPeriod.map(([, mp]) => mp.get(m.ticker)) })); const avgOf = g => periods.map((_, i) => d3.mean(rows.filter(r => r.group === g), r => r.vals[i])); const num = x => x == null ? html`` : html`${pct(x)}`; const dataRow = (r, cls = "") => html` ${r.ticker}${r.name}${r.vals.map(num)}`; const spy = rows.find(r => r.ticker === "SPY"); const body = [ spy && dataRow({...spy, ticker: "SPY", name: "S&P 500 (benchmark)"}, "aiq-avg"), ...groupNames.flatMap(g => [ html`${g}`, dataRow({ticker: "AVG", name: "Equal-weight average", vals: avgOf(g)}, "aiq-avg"), ...rows.filter(r => r.group === g).map(r => dataRow(r)) ]) ]; return display(html`

${periods.map(([l]) => html``)}${body}

Ticker	Name	${l}

`); })(); 51:[] 48:{"id":"433cfae2b1374d4b","slug":"ai-stock-performance","title":"AI Stock Performance","thumbnail":"dc0daa34bc9a7174fbff5326aabeeb2cdcc94a4abc7e5cb5597c8e899ea07b0a","access_level":"public","create_time":"$D2026-11-14T03:20:35.430Z","update_time":"$D2026-11-14T14:19:13.799Z","view_time":null,"first_public_time":"$D2026-11-14T03:55:10.855Z","has_unpublished_edits":null,"fork":{"id":"659d496cda366132","slug":"sp-500-sector-performance","title":"S&P 500 Sector Performance","owner":{"id":"3b88b27becc4bbe6","login":"robertmreedy","name":"Bobby Reedy"}},"stars":0,"starred":false,"owner":{"type":"team","id":"3b88b27becc4bbe6","login":"robertmreedy","name":"Bobby Reedy","avatar_url":"https://avatars-next.observableusercontent.com/90f1a7d743c3a2110c947721108b59ac8dcf7901079833e3803e54258687e7a4","tier":"starter_2024","bio":"All Things Data","followed_by_you":false,"follows_you":false},"version":292,"publish_version":292,"role":null,"authored":false,"authors":[{"type":"individual","id":"78c022c35bbdd3b7","login":"robertmreedy","name":"Bobby Reedy","avatar_url":"https://avatars-next.observableusercontent.com/90f1a7d743c3a2110c947721108b59ac8dcf7901079833e3803e54258687e7a4","tier":null,"bio":"All Things Data","followed_by_you":false,"follows_you":false}],"members":[{"type":"team","id":"3b88b27becc4bbe6","login":"robertmreedy","name":"Bobby Reedy","avatar_url":"https://avatars-next.observableusercontent.com/90f1a7d743c3a2110c947721108b59ac8dcf7901079833e3803e54258687e7a4","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"AI Stock Performance","cells":[{"id":0,"value":"# AI Stock Performance\n\n*Data source: [Yahoo Finance](https://finance.yahoo.com) (updated daily: [GitHub](https://github.com/robertmreedy/AI-Stock-Groups))*\n\n*Inspired by a chart posted on LinkedIn by Wei Li, Global Chief Investment Strategist at BlackRock ([post](https://lnkd.in/p/gvqVReA5)).*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":108,"value":"const preset = view(Inputs.radio(\n new Map([[\"1D\", 1],[\"1W\", 7], [\"1M\", 30], [\"3M\", 90], [\"6M\", 180], [\"YTD\", \"ytd\"], [\"1Y\", 365], [\"Custom\", \"custom\"]]),\n {label: \"Window\", value: 7}\n));","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":109,"value":"const customRange = view(\n preset === \"custom\"\n ? Inputs.form([\n Inputs.date({label: \"Start\", value: d3.utcDay.offset(lastDate, -30), min: firstDate, max: lastDate}),\n Inputs.date({label: \"End\", value: lastDate, min: firstDate, max: lastDate})\n ])\n : Object.assign(html``, {value: [d3.utcDay.offset(lastDate, -30), lastDate]})\n);","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":115,"value":"$4c","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":118,"value":"$4d","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":119,"value":"$4e","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":124,"value":"$4f","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":120,"value":"$50","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"

\n## Code and Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"raw = d3.csv(\"https://raw.githubusercontent.com/robertmreedy/AI-Stock-Groups/main/data/ai_stocks.csv\", d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":121,"value":"const palette = new Map([\n [\"Big Tech\", \"#f24e2a\"],\n [\"AI semis\", \"#e5b50a\"],\n [\"AI cloud & data-center\", \"#008c68\"],\n [\"S&P 500\", \"#6b6b6b\"]\n]);\nconst groups = [\"Big Tech\", \"AI semis\", \"AI cloud & data-center\"];\nconst lastDate = d3.max(raw, d => d.Date);\nconst firstDate = d3.min(raw, d => d.Date);\nconst fmt = d3.format(\"+.1%\");","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"const win = (() => {\n const custom = preset === \"custom\";\n const end = custom ? customRange[1] : lastDate;\n const start = custom ? customRange[0]\n : preset === \"ytd\" ? new Date(Date.UTC(lastDate.getUTCFullYear(), 0, 1))\n : d3.utcDay.offset(lastDate, -preset);\n return {start, end};\n})();","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":117,"value":"function rebase(data, start, end) {\n const bisect = d3.bisector(d => d.Date);\n const out = [];\n for (const [, rows] of d3.group(data, d => d.ticker)) {\n rows.sort((a, b) => a.Date - b.Date);\n const upto = rows.filter(d => d.Date <= end);\n if (!upto.length) continue;\n let i = bisect.right(upto, start) - 1;\n if (i < 0) i = 0;\n const base = upto[i].close;\n for (const r of upto.slice(i)) out.push({...r, ret: r.close / base - 1, idx: 100 * r.close / base});\n }\n return out;\n}","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"const stocks = rebase(raw, win.start, win.end);\nconst latest = Array.from(d3.group(stocks, d => d.ticker).values(), v => d3.greatest(v, d => d.Date));\nconst spyRet = latest.find(d => d.ticker === \"SPY\")?.ret ?? 0;","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"const groupSeries = (() => {\n const members = stocks.filter(d => d.group !== \"S&P 500\");\n const avg = Array.from(\n d3.rollup(members, v => d3.mean(v, d => d.ret), d => d.group, d => +d.Date),\n ([group, m]) => Array.from(m, ([t, ret]) => ({group, Date: new Date(t), ret, idx: 100 * (1 + ret)}))\n ).flat();\n const spy = stocks.filter(d => d.group === \"S&P 500\")\n .map(d => ({group: \"S&P 500\", Date: d.Date, ret: d.ret, idx: d.idx}));\n return [...avg, ...spy];\n})();","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W51","stdlib":"1"}} 24:null