29:null 2a:["$","title",null,{"children":"Is a U.S. recession coming? | Adjacent | Observable"}] 2f:T804,// Updated function to fetch Polymarket price history for a given market ID async function fetchMarketPriceHistory(marketId) { try { // Set up the request parameters using the format from the working example const interval = "1d"; // "1m" for 1 month const fidelity = "10"; // Include fidelity parameter as shown in the example const url = `https://clob.polymarket.com/prices-history?market=${marketId}&interval=${interval}&fidelity=${fidelity}`; console.log("Requesting URL:", url); // Add appropriate headers const options = { headers: { "Content-Type": "application/json", "Cache-Control": "no-cache" } }; // Fetch the market history const response = await fetch(url, options); // Check if the request was successful if (!response.ok) { throw new Error(`HTTP error! Status: ${response.status}`); } // Parse the JSON response const priceHistory = await response.json(); // Process the data to make it easier to work with if (priceHistory.history && priceHistory.history.length > 0) { // Convert Unix timestamps to JavaScript Date objects and format the data const formattedHistory = priceHistory.history.map(point => ({ date: new Date(point.t * 1000), price: point.p, rawTimestamp: point.t })); // Sort the data by date (oldest to newest) const sortedHistory = formattedHistory.sort((a, b) => a.rawTimestamp - b.rawTimestamp); return { marketId, priceHistory: sortedHistory, firstPoint: sortedHistory[0], lastPoint: sortedHistory[sortedHistory.length - 1], totalPoints: sortedHistory.length }; } else { return { marketId, priceHistory: [], error: "No price history data found" }; } } catch (error) { console.error(`Error fetching price history for market ${marketId}:`, error); return { marketId, error: error.message }; } }30:T1f69,// Improved function to fetch and process price histories for multiple markets async function fetchProcessedMarketHistories(marketIds, marketNames) { try { // Validate inputs if (!Array.isArray(marketIds) || !Array.isArray(marketNames) || marketIds.length !== marketNames.length) { throw new Error("marketIds and marketNames must be arrays of the same length"); } // Create a mapping between market IDs and their display names const marketNameMap = {}; marketIds.forEach((id, index) => { marketNameMap[id] = marketNames[index]; }); console.log("Fetching data for markets:", marketNames.join(", ")); // Fetch raw data for all markets - use max interval to ensure we get all available data const fetchPromises = marketIds.map(marketId => { // Using "max" interval to get all available data for this market const interval = "max"; const url = `https://clob.polymarket.com/prices-history?market=${marketId}&interval=${interval}`; return fetch(url, { headers: { "Content-Type": "application/json", "Cache-Control": "no-cache" } }) .then(response => { if (!response.ok) { throw new Error(`HTTP error! Status: ${response.status} for market ${marketId}`); } return response.json(); }) .then(data => ({ marketId, data })) .catch(error => { console.error(`Error fetching market ${marketId}:`, error); return { marketId, error: error.message }; }); }); // Wait for all fetches to complete const results = await Promise.all(fetchPromises); // Process each market's data to get daily closing prices const marketDailyPrices = {}; const marketCreationDates = {}; results.forEach(result => { const marketName = marketNameMap[result.marketId]; if (result.error || !result.data?.history || result.data.history.length === 0) { console.warn(`No valid data for market ${marketName}`); marketDailyPrices[marketName] = new Map(); return; } console.log(`Processing ${result.data.history.length} price points for ${marketName}`); // Find market creation date from earliest data point if (result.data.history.length > 0) { const timestamps = result.data.history.map(point => point.t); const earliestTimestamp = Math.min(...timestamps); const creationDate = new Date(earliestTimestamp * 1000); // Store creation date with no time component (UTC date) const creationDateUTC = new Date(Date.UTC( creationDate.getUTCFullYear(), creationDate.getUTCMonth(), creationDate.getUTCDate() )); marketCreationDates[marketName] = creationDateUTC; console.log(`Market ${marketName} creation date:`, creationDateUTC.toISOString().split('T')[0]); } // Group prices by day and get closing price for each day const pricesByDay = {}; result.data.history.forEach(point => { // Convert timestamp to date (assuming timestamp is in seconds) const date = new Date(point.t * 1000); // Create a UTC date key for consistent timezone handling const dayKey = `${date.getUTCFullYear()}-${String(date.getUTCMonth() + 1).padStart(2, '0')}-${String(date.getUTCDate()).padStart(2, '0')}`; if (!pricesByDay[dayKey]) { pricesByDay[dayKey] = []; } pricesByDay[dayKey].push({ timestamp: point.t, price: point.p }); }); // For each day, get the closing price (last price of the day) const dailyClosingPrices = new Map(); Object.entries(pricesByDay).forEach(([day, prices]) => { // Sort by timestamp (latest last) const sortedPrices = prices.sort((a, b) => a.timestamp - b.timestamp); // Take the latest price of the day const latestPrice = sortedPrices[sortedPrices.length - 1]; dailyClosingPrices.set(day, latestPrice.price); }); // Store the daily prices for this market marketDailyPrices[marketName] = dailyClosingPrices; console.log(`Processed ${dailyClosingPrices.size} daily prices for ${marketName}`); }); // Determine the full date range const today = new Date(); const todayUTC = new Date(Date.UTC(today.getUTCFullYear(), today.getUTCMonth(), today.getUTCDate())); // Find the earliest market creation date let startDate = todayUTC; Object.values(marketCreationDates).forEach(date => { if (date < startDate) { startDate = date; } }); console.log("Start date:", startDate.toISOString().split('T')[0]); console.log("End date (today):", todayUTC.toISOString().split('T')[0]); // Generate all dates in the range const allDates = []; const currentDate = new Date(startDate); while (currentDate <= todayUTC) { const dateStr = currentDate.toISOString().split('T')[0]; allDates.push(dateStr); // Move to next day currentDate.setUTCDate(currentDate.getUTCDate() + 1); } console.log(`Generated ${allDates.length} days in date range`); // Fill in missing prices by carrying forward the last known price const filledMarketPrices = {}; Object.entries(marketDailyPrices).forEach(([marketName, priceMap]) => { filledMarketPrices[marketName] = new Map(); const creationDate = marketCreationDates[marketName]; // If empty market, skip if (priceMap.size === 0) { console.warn(`No price data to fill for ${marketName}`); return; } // Sort the existing dates const existingDates = Array.from(priceMap.keys()).sort(); console.log(`${marketName} has data for ${existingDates.length} days, first:`, existingDates[0], "last:", existingDates[existingDates.length - 1]); // If we have no data, skip if (existingDates.length === 0) return; let lastPrice = null; // Fill in prices for all dates in our range allDates.forEach(dateStr => { const currentDate = new Date(dateStr); if (priceMap.has(dateStr)) { // We have data for this day lastPrice = priceMap.get(dateStr); filledMarketPrices[marketName].set(dateStr, lastPrice); } else if (lastPrice !== null && currentDate >= creationDate) { // Carry forward last known price if after market creation filledMarketPrices[marketName].set(dateStr, lastPrice); } else { // No data yet for this market filledMarketPrices[marketName].set(dateStr, null); } }); console.log(`Filled in prices for ${marketName}, now have ${filledMarketPrices[marketName].size} days`); }); // Create the final dataset in the requested format const processedHistory = allDates.map(dateStr => { // Create Date object for midnight UTC, then adjust to local time for display const utcDate = new Date(dateStr); // For display in Observable, adjust to local timezone const date = new Date(utcDate.getTime()); const result = { date: date }; // Add each market's price for this date Object.keys(filledMarketPrices).forEach(marketName => { const price = filledMarketPrices[marketName].get(dateStr); // Multiply by 100 to match your format result[marketName] = price !== null ? price * 100 : null; }); return result; }); console.log(`Final processed dataset has ${processedHistory.length} days`); return processedHistory; } catch (error) { console.error("Error in fetchProcessedMarketHistories:", error); return { error: error.message }; } }31:T17e1,// Create the recession prediction chart with watermark and improved label positioning viewof recessionPredictionChart = { // Function to determine width based on container size const getResponsiveWidth = () => { // Get the container width (default to 800 if not available) const containerWidth = width || 800; return Math.min(containerWidth, 800); // Cap at 800px max }; // Calculate responsive dimensions const chartWidth = getResponsiveWidth(); const chartHeight = chartWidth * 0.625; // Maintain aspect ratio (500/800 = 0.625) // Adjust font sizes based on width const titleSize = chartWidth < 500 ? 14 : 16; const subtitleSize = chartWidth < 500 ? 12 : 14; const labelSize = chartWidth < 500 ? 10 : 12; // Adjust margins for smaller screens const rightMargin = chartWidth < 500 ? 80 : 120; const leftMargin = chartWidth < 500 ? 40 : 60; const bottomMargin = chartWidth < 500 ? 30 : 40; const topMargin = chartWidth < 500 ? 30 : 40; // Adjust tick count for smaller screens const tickCount = chartWidth < 500 ? 4 : 8; // Create the basic chart using Plot const chart = Plot.plot({ title: "US Recession Probabilities by Quarter", subtitle: "Based on prediction markets for negative GDP growth", width: chartWidth, height: chartHeight, style: { fontSize: labelSize, ".plot-title": { fontSize: titleSize + "px" }, ".plot-subtitle": { fontSize: subtitleSize + "px" } }, x: { label: "Date", tickFormat: "%b %d", tickCount: tickCount, grid: true }, y: { label: "Probability (%)", domain: [0, 100], grid: true }, // Use responsive margins marginRight: rightMargin, marginLeft: leftMargin, marginBottom: bottomMargin, marginTop: topMargin, marks: [ Plot.ruleY([0, 25, 50, 75, 100], { stroke: "#ccc", strokeDasharray: "3,3" }), // Dynamically generate lines for each market ...marketNames.map((marketName, index) => { const colors = ["red", "blue", "green"]; return Plot.line(processedData, { x: "date", y: marketName, stroke: colors[index % colors.length], strokeWidth: chartWidth < 500 ? 1.5 : 2 }); }), // Dynamically generate dots for each market (show fewer dots on small screens) ...marketNames.map((marketName, index) => { const colors = ["red", "blue", "green"]; const dotFrequency = chartWidth < 500 ? 14 : 7; // Show fewer dots on small screens return Plot.dot( processedData.filter((d, i) => i % dotFrequency === 0), { x: "date", y: marketName, fill: colors[index % colors.length], r: chartWidth < 500 ? 2 : 3, opacity: 0.7 } ); }), // Dynamically generate end labels for each market ...marketNames.map((marketName, index) => { const colors = ["red", "blue", "green"]; // Only show end labels if screen is wide enough if (chartWidth >= 500) { return Plot.text( processedData.filter((d, i) => i === processedData.length - 1), { x: "date", y: marketName, text: (d) => `${d[marketName]?.toFixed(1)}%`, dx: 50, fill: colors[index % colors.length], fontWeight: "bold", fontSize: chartWidth < 600 ? 12 : 14 } ); } else { return Plot.text([]); // Empty plot for small screens } }) ] }); // Calculate legend position based on chart size const legendTop = chartWidth < 500 ? 50 : 70; const legendLeft = chartWidth < 500 ? 70 : 130; const legendFontSize = chartWidth < 500 ? 10 : 12; // Calculate watermark position and size const watermarkTop = chartHeight / 2 + topMargin; const watermarkLeft = chartWidth / 2; const watermarkSize = chartWidth < 500 ? 30 : 60; // Create the container with legend and watermark const container = html`

${chart}

${marketNames.map((name, index) => { const colors = ["red", "blue", "green"]; // Remove the question mark from the display name const displayName = name.replace("?", "") + " 2025"; return html`

${displayName}

`; })}

ADJACENT

${chart}

${marketNames2.map((name, index) => { const colors = ["red", "blue", "green"]; // Remove the question mark from the display name const displayName = name.replace("?", "") + " 2025"; return html`

${displayName}

`; })}

ADJACENT

`; // Add resize event listener to make the chart responsive to window resizing container.value = chart; // Create a resize observer to update chart on container size changes if (typeof ResizeObserver !== "undefined") { const observer = new ResizeObserver((entries) => { // Get the container's new width const containerWidth = entries[0].contentRect.width; // Only redraw if width has changed significantly if (Math.abs(containerWidth - chartWidth) > 20) { // This will trigger a redraw with the new container width invalidation.then(() => observer.disconnect()); return container; } }); // Start observing the container observer.observe(container); } return container; }33:[] 2d:{"id":"f865af4ad0d9d085","slug":null,"title":"Is a U.S. recession coming?","thumbnail":"1fdc8cc32a6ca435c3498bb8922b18ab96a4b0b58690ae88365a7215ddba7baa","access_level":"public","create_time":"$D2025-04-29T12:20:14.354Z","update_time":"$D2025-05-01T17:57:33.220Z","view_time":null,"first_public_time":"$D2025-04-29T14:05:44.767Z","fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"59b2aaa9189b56d4","login":"adjacent","name":"Adjacent","avatar_url":"https://avatars-next.observableusercontent.com/e34bfda26f2a3e11bf04364a685b422fda7ad5630974dadb7c20559fdf8ea883","tier":"pro_2024"},"version":123,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"4d75e52b48086387","login":"dougiebuckets","name":"dougiebuckets","avatar_url":"https://avatars-next.observableusercontent.com/d55596be54f2db1cfdf1dd98b171dbdcc2e8c228c20ce7d20d50902a10772d44","tier":null}],"members":[{"type":"team","id":"59b2aaa9189b56d4","login":"adjacent","name":"Adjacent","avatar_url":"https://avatars-next.observableusercontent.com/e34bfda26f2a3e11bf04364a685b422fda7ad5630974dadb7c20559fdf8ea883","tier":"pro_2024","role":"editor"},{"type":"individual","id":"4d75e52b48086387","login":"dougiebuckets","name":"dougiebuckets","avatar_url":"https://avatars-next.observableusercontent.com/d55596be54f2db1cfdf1dd98b171dbdcc2e8c228c20ce7d20d50902a10772d44","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"1b9a0609907383f3","slug":"adjacent-news","title":"Adjacent News","owner":{"id":"59b2aaa9189b56d4","login":"adjacent","name":"Adjacent"}},"type":"notebook","body":{"title":"Is a U.S. recession coming?","cells":[{"id":0,"value":"# Is a U.S. recession coming?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"There's been a lot of speculation regarding a forthcoming recession for the U.S. Much of this is fueled by the impacts of the trade/tariff war, as U.S. companies dependent upon global supply chains will be impacted until the trade/tariff war is resolved. The goal of this notebook is to look at prediction market data that might provide more insight into the likelihood of a recession. A common rule of thumb is that two consecutive quarters of negative gross domestic product (GDP) growth indicate a recession.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"Let's look how how markets concerning \"Negative GDP growth in Q1, Q2, and Q3 2025?\" have looked over the last month.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":17,"value":"First, let's get the IDs for each of these markets and set them as variables:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"q1Market = \"89739903755687214104992659432952221759399066860582700099347588931624601910371\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"q2Market = \"71761415495894786779765163166908058066219113038864782309892208702213111224732\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"q3Market = \"79734015532749181794094939197404065485307749197084575709383670281000269283430\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"marketIds = [q1Market, q2Market, q3Market]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":57,"value":"marketNames = [\"Negative GDP in Q1?\", \"Negative GDP in Q2?\", \"Negative GDP in Q3?\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":75,"value":"processedData = {\n return await fetchProcessedMarketHistories(marketIds, marketNames);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":78,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":84,"value":"As we can see, of late negative GDP forecasts have increased sharply for Q1 as well as Q2. Q3 hs remained relatively static over the last week or so.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":88,"value":"Now I'm going to chart out the price histories for the following markets - 1) Negative GDP growth in 2025?, 2), US recession in 2025?, and 3) 5% GDP contraction in Q3 2025?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":90,"value":"negativeGDP = \"65570440056117077542463878494177612662140785434913628124381440406242436241630\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":96,"value":"gdpContraction = \"40902209963355115759331536205214853537622056896514703594538648494237557365925\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":92,"value":"recession2025 = \"104173557214744537570424345347209544585775842950109756851652855913015295701992\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":102,"value":"marketIds2 = [negativeGDP, gdpContraction, recession2025]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":105,"value":"marketNames2 = [\"Negative GDP growth?\", \"5% GDP contraction in Q3?\", \"US recession in?\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":108,"value":"processedData2 = {\n return await fetchProcessedMarketHistories(marketIds2, marketNames2);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 2e:"$2d:body"