{ "name": "Regime Model (sanitized template)", "nodes": [ { "parameters": { "rule": { "interval": [ { "triggerAtHour": 9, "triggerAtMinute": 15 } ] } }, "type": "n8n-nodes-base.scheduleTrigger", "typeVersion": 1.3, "position": [ 3328, 4288 ], "id": "aef98cf1-c3c2-49dc-af0d-df0132be94ab", "name": "Schedule Trigger" }, { "parameters": { "httpMethod": "POST", "path": "regime-model", "responseMode": "responseNode", "options": {} }, "type": "n8n-nodes-base.webhook", "typeVersion": 2.1, "position": [ 3312, 3984 ], "id": "a95cb373-2e2e-4ac3-a2c6-70edca5c7eaa", "name": "Webhook" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "fb91d733-aa5e-4374-b717-a5239b402d99", "leftValue": "={{ $json.is_working_day }}", "rightValue": true, "operator": { "type": "boolean", "operation": "equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 3984, 4288 ], "id": "4ee75aa5-a47b-49b3-97cb-1f6dd7abc2a1", "name": "If" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "wv-if2-cond-01", "leftValue": "={{ $json.route }}", "rightValue": "execute", "operator": { "type": "string", "operation": "equals", "name": "filter.operator.equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 3968, 3984 ], "id": "28dbed1d-ffea-4ef4-9457-b7f6348366eb", "name": "Webhook Validation" }, { "parameters": { "respondWith": "text", "responseBody": "=={{ JSON.stringify($json) }}", "options": { "responseHeaders": { "entries": [ { "name": "Content-Type", "value": "application/json" } ] } } }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 4448, 3808 ], "id": "03c820e7-abeb-45d1-a5ee-f067596635da", "name": "Respond Error", "onError": "continueRegularOutput" }, { "parameters": {}, "type": "n8n-nodes-base.merge", "typeVersion": 3.2, "position": [ 4368, 3952 ], "id": "6d55709c-b185-434f-b42d-45aa96ec0acd", "name": "Merge Triggers" }, { "parameters": { "jsCode": "const j = $input.first().json;\nreturn [{ json: {\n tickers: j.tickers || ['SPY'],\n start_date: j.start_date || '2019-01-01',\n end_date: j.end_date || null,\n jump_penalty: j.jump_penalty != null ? j.jump_penalty : 5.0,\n n_components: j.n_components != null ? j.n_components : 2,\n n_init: j.n_init != null ? j.n_init : 20,\n trigger_source: j.route === 'execute' ? 'webhook' : 'schedule',\n has_csv: j.has_csv || false,\n csv_data: j.csv_data || null\n}}];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 4512, 3952 ], "id": "5ceff252-cf1a-4c5e-98f8-a893d46afa84", "name": "Set Parameters" }, { "parameters": { "endpointUrl": "", "tool": { "__rl": true, "value": "fetch-ohlcvs", "mode": "list", "cachedResultName": "fetch-ohlcvs" }, "parameters": { "mappingMode": "defineBelow", "value": { "request": "={{ {\n \"tickers\": $('Set Parameters').first().json.tickers,\n \"timeframe\": \"1d\",\n \"start_date\": $('Set Parameters').first().json.start_date,\n \"end_date\": $('Set Parameters').first().json.end_date || $now.toFormat('yyyy-MM-dd'),\n \"_skill_contract_acknowledged\": \"read-and-understood\"\n} }}" }, "matchingColumns": [ "request" ], "schema": [ { "id": "request", "displayName": "request", "defaultMatch": false, "required": true, "display": true, "type": "object", "defaultValue": "{\n \"tickers\": [\n \"string\"\n ],\n \"timeframe\": \"string\",\n \"start_date\": \"string\",\n \"end_date\": \"string\",\n \"source\": \"string\",\n \"interval\": \"string\"\n}", "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "@n8n/n8n-nodes-langchain.mcpClient", "typeVersion": 1, "position": [ 4464, 4272 ], "id": "1c998b33-bf74-4b09-8f0e-56600c31cee7", "name": "Data extraction" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" } ] }, "sendBody": true, "specifyBody": "json", "jsonBody": "{\n \"jsonrpc\": \"2.0\",\n \"id\": 1,\n \"method\": \"initialize\",\n \"params\": {\n \"protocolVersion\": \"2024-11-05\",\n \"capabilities\": {},\n \"clientInfo\": { \"name\": \"n8n\", \"version\": \"1.0.0\" }\n }\n}", "options": { "response": { "response": { "fullResponse": true } } } }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4688, 4272 ], "id": "19005181-1a98-4614-b100-037da08e38b2", "name": "DataUnpack" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" }, { "name": "mcp-session-id", "value": "={{ $('DataUnpack').first().json.headers['mcp-session-id'] }}" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={{ JSON.stringify({ \"jsonrpc\": \"2.0\", \"method\": \"notifications/initialized\" }) }}", "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 5168, 4272 ], "id": "33ca40d9-7fda-42e3-b596-ac052795f81a", "name": "Connection Handshake" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" }, { "name": "mcp-session-id", "value": "={{ $('DataUnpack').first().json.headers['mcp-session-id'] }}" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={{ JSON.stringify({ \"jsonrpc\": \"2.0\", \"id\": 2, \"method\": \"tools/call\", \"params\": { \"name\": \"result_get\", \"arguments\": { \"request\": { \"result_id\": $('Data extraction').first().json.result_id } } } }) }}", "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4080, 4528 ], "id": "500fb5d4-3216-4be0-bd78-09d7f749aad3", "name": "DataExtracted" }, { "parameters": { "jsCode": "// --- Determine data source: CSV or SSE from data extraction ---\nconst inputJson = $input.first().json;\nlet allDates, allCloses;\n\nif (inputJson.csv_rows) {\n // === CSV PATH ===\n const sorted = [...inputJson.csv_rows]\n .sort((a, b) => a.timestamp.localeCompare(b.timestamp))\n .filter(r => { const v = parseFloat(r.close); return !isNaN(v) && v > 0; });\n allDates = sorted.map(r => r.timestamp.substring(0, 10));\n allCloses = sorted.map(r => parseFloat(r.close));\n} else {\n // === DATA EXTRACTION PATH (SSE) ===\n const raw = inputJson.data;\n const dataIdx = raw.indexOf('data: {');\n if (dataIdx === -1) throw new Error('No \"data: {\" found in response. Raw: ' + raw.substring(0, 200));\n const jsonStr = raw.slice(dataIdx + 6).trim();\n const outer = JSON.parse(jsonStr);\n const text = outer?.result?.content?.[0]?.text;\n const rows = JSON.parse(text)?.result?.payload?.ohlcv_df?.rows;\n if (!rows) throw new Error('No rows. text keys: ' + JSON.stringify(Object.keys(JSON.parse(text)?.result ?? {})));\n const sorted = [...rows]\n .sort((a, b) => a.timestamp.localeCompare(b.timestamp))\n .filter(r => { const v = parseFloat(r.close); return r.close != null && !isNaN(v) && v > 0; });\n allDates = sorted.map(r => r.timestamp.substring(0, 10));\n allCloses = sorted.map(r => parseFloat(r.close));\n}\nconst n = allCloses.length;\n\nconst lr = [0.0];\nfor (let i = 1; i < n; i++) lr.push(Math.log(allCloses[i] / allCloses[i-1]));\n\nfunction rollingVol(rets, w) {\n const out = new Array(rets.length).fill(0);\n for (let i = w-1; i < rets.length; i++) {\n const chunk = rets.slice(i-w+1, i+1);\n const mu = chunk.reduce((a,b)=>a+b,0)/w;\n const v = chunk.reduce((a,b)=>a+(b-mu)**2,0)/Math.max(w-1,1);\n out[i] = Math.sqrt(v*252);\n }\n return out;\n}\n\nfunction rollingSum(rets, w) {\n const out = new Array(rets.length).fill(0);\n for (let i = w-1; i < rets.length; i++)\n out[i] = rets.slice(i-w+1, i+1).reduce((a,b)=>a+b,0);\n return out;\n}\n\nfunction zscore(v) {\n const mu = v.reduce((a,b)=>a+b,0)/v.length;\n const std = Math.sqrt(v.reduce((a,b)=>a+(b-mu)**2,0)/Math.max(v.length-1,1)) || 1e-8;\n return v.map(x=>(x-mu)/std);\n}\n\nconst START = 63;\nconst lr_f = lr.slice(START);\nconst rv21_f = rollingVol(lr, 21).slice(START);\nconst rv63_f = rollingVol(lr, 63).slice(START);\nconst m10_f = rollingSum(lr, 10).slice(START);\nconst featDates = allDates.slice(START);\nconst m = lr_f.length;\nconst idx = Array.from({length: m}, (_, i) => i);\n\nconst ret_z = zscore(lr_f);\nconst rvol21_z = zscore(rv21_f);\nconst rvol63_z = zscore(rv63_f);\nconst mom10_z = zscore(m10_f);\n\nconst hasNaN = idx.some(i => isNaN(ret_z[i]) || isNaN(rvol21_z[i]) || isNaN(rvol63_z[i]) || isNaN(mom10_z[i]));\nif (hasNaN) throw new Error('NaN detected in features after z-scoring');\n\nconst X = {\n index: idx,\n columns: [\"ret_z\",\"rvol21_z\",\"rvol63_z\",\"mom10_z\"],\n data: idx.map(i => [ret_z[i], rvol21_z[i], rvol63_z[i], mom10_z[i]])\n};\n\nconst ret_ser = { index: idx, data: lr_f.map(v => parseFloat(v.toFixed(8))) };\n\nreturn [{ json: {\n X, ret_ser,\n feat_dates: featDates,\n all_dates: allDates,\n all_closes: allCloses,\n row_count: m,\n date_first: featDates[0],\n date_last: featDates[m-1]\n}}];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 4896, 4272 ], "id": "f4a65083-b338-487d-a23f-1b4a0ac06e06", "name": "Generate features" }, { "parameters": { "endpointUrl": "", "tool": { "__rl": true, "value": "jump-model-create", "mode": "list", "cachedResultName": "jump-model-create" }, "parameters": { "mappingMode": "defineBelow", "value": { "request": "={{ { \n \"init_kwargs\": { \n \"n_components\": $('Set Parameters').first().json.n_components, \n \"jump_penalty\": $('Set Parameters').first().json.jump_penalty, \n \"cont\": true, \n \"n_init\": $('Set Parameters').first().json.n_init\n }, \n \"_skill_contract_acknowledged\": \"read-and-understood\" \n} }}" }, "matchingColumns": [ "request" ], "schema": [ { "id": "request", "displayName": "request", "defaultMatch": false, "required": true, "display": true, "type": "string", "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "@n8n/n8n-nodes-langchain.mcpClient", "typeVersion": 1.1, "position": [ 4480, 4576 ], "id": "585fd72f-c21e-4c2e-831b-6a2c3f9e4b8e", "name": "Create Jump Model" }, { "parameters": { "endpointUrl": "=", "tool": { "__rl": true, "value": "jump-model-fit", "mode": "list", "cachedResultName": "jump-model-fit" }, "parameters": { "mappingMode": "defineBelow", "value": { "request": "={{ { \n \"handle\": $('Create Jump Model').first().json.structuredContent.result.handle, \n \"X\": $('Generate features').first().json.X, \n \"ret_ser\": $('Generate features').first().json.ser, \n \"sort_by\": \"cumret\",\n \"_skill_contract_acknowledged\": \"read-and-understood\"\n} }}" }, "matchingColumns": [ "request" ], "schema": [ { "id": "request", "displayName": "request", "defaultMatch": false, "required": true, "display": true, "type": "string", "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "@n8n/n8n-nodes-langchain.mcpClient", "typeVersion": 1.1, "position": [ 4704, 4576 ], "id": "f7de78fa-9bfb-49b3-a804-9348f9b550b8", "name": "Fit Model", "retryOnFail": false, "alwaysOutputData": false, "executeOnce": true, "notesInFlow": false }, { "parameters": { "endpointUrl": "", "tool": { "__rl": true, "value": "jump-model-predict-proba-online", "mode": "list", "cachedResultName": "jump-model-predict-proba-online" }, "parameters": { "mappingMode": "defineBelow", "value": { "request": "={{ { \"handle\": $('Create Jump Model').first().json.structuredContent.result.handle, \"X\": $('Generate features').first().json.X,\n\"_skill_contract_acknowledged\": \"read-and-understood\"\n} }}" }, "matchingColumns": [ "request" ], "schema": [ { "id": "request", "displayName": "request", "defaultMatch": false, "required": true, "display": true, "type": "string", "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "@n8n/n8n-nodes-langchain.mcpClient", "typeVersion": 1.1, "position": [ 4896, 4576 ], "id": "66ff8005-3e72-4e18-9ee3-c7a2ba4a4a93", "name": "Predict Online Probabilities" }, { "parameters": { "endpointUrl": "", "tool": { "__rl": true, "value": "jump-model-predict", "mode": "list", "cachedResultName": "jump-model-predict" }, "parameters": { "mappingMode": "defineBelow", "value": { "request": "={{ { \"handle\": $('Create Jump Model').first().json.structuredContent.result.handle, \"X\": $('Generate features').first().json.X,\n\"_skill_contract_acknowledged\": \"read-and-understood\"} }}" }, "matchingColumns": [ "request" ], "schema": [ { "id": "request", "displayName": "request", "defaultMatch": false, "required": true, "display": true, "type": "string", "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "@n8n/n8n-nodes-langchain.mcpClient", "typeVersion": 1.1, "position": [ 4080, 4816 ], "id": "6488352e-373a-48a6-9f1e-a78b94c57c3e", "name": "Predict Hard Labels" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"initialize\",\"params\":{\"protocolVersion\":\"2024-11-05\",\"capabilities\":{},\"clientInfo\":{\"name\":\"n8n\",\"version\":\"1.0.0\"}}}", "options": { "response": { "response": { "fullResponse": true } } } }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4272, 4816 ], "id": "0ca8e65e-4061-45db-a411-c825f335cc1a", "name": "Node A" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" }, { "name": "mcp-session-id", "value": "={{ $('Node A').first().json.headers['mcp-session-id'] }}" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "{\"jsonrpc\":\"2.0\",\"method\":\"notifications/initialized\"}", "options": { "response": { "response": {} } } }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4416, 4816 ], "id": "c76c5d86-1211-49bc-bfe1-eee39c406879", "name": "Node B" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" }, { "name": "mcp-session-id", "value": "={{ $('Node A').first().json.headers['mcp-session-id'] }}" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={{ JSON.stringify({ \n \"jsonrpc\": \"2.0\", \n \"id\": 3, \n \"method\": \"tools/call\", \n \"params\": { \n \"name\": \"result_get\", \n \"arguments\": { \n \"request\": { \n \"result_id\": $('Predict Online Probabilities').first().json.structuredContent.result_id,\n \"_skill_contract_acknowledged\": \"read-and-understood\"\n } \n } \n } \n}) }}", "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4560, 4816 ], "id": "83dad748-7727-4b67-bb1d-9af18b9e76eb", "name": "Node C" }, { "parameters": { "method": "POST", "url": "", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Accept", "value": "application/json, text/event-stream" }, { "name": "mcp-session-id", "value": "={{ $('Node A').first().json.headers['mcp-session-id'] }}" } ] }, "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={{ JSON.stringify({ \"jsonrpc\": \"2.0\", \"id\": 3, \"method\": \"tools/call\", \"params\": { \"name\": \"result_get\", \"arguments\": { \"request\": { \"result_id\": $('Predict Hard Labels').first().json.structuredContent.result_id,\"_skill_contract_acknowledged\": \"read-and-understood\" } } } }) }}", "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.4, "position": [ 4704, 4816 ], "id": "ecc08cfd-95d1-469e-ad0a-6485492c0be2", "name": "Node D" }, { "parameters": { "jsCode": "function parseSSE(raw) {\n const idx = raw.indexOf('data: {');\n if (idx === -1) throw new Error('No data found: ' + raw.slice(0, 100));\n const outer = JSON.parse(raw.slice(idx + 6).trim());\n const text = outer?.result?.content?.[0]?.text;\n return JSON.parse(text);\n}\n\nconst rawProba = $('Node C').first().json.data;\nconst rawLabels = $('Node D').first().json.data;\n\nconst probaPayload = parseSSE(rawProba);\nconst labelsPayload = parseSSE(rawLabels);\n\nconst probaRows = probaPayload?.result?.payload?.rows ?? probaPayload?.payload?.rows;\nconst labelRows = labelsPayload?.result?.payload?.rows ?? labelsPayload?.payload?.rows;\n\nif (!probaRows) throw new Error('No proba rows. Keys: ' + JSON.stringify(Object.keys(probaPayload)));\nif (!labelRows) throw new Error('No label rows. Keys: ' + JSON.stringify(Object.keys(labelsPayload)));\n\nprobaRows.sort((a, b) => parseInt(a.index) - parseInt(b.index));\nlabelRows.sort((a, b) => parseInt(a.index) - parseInt(b.index));\n\nconst labels = labelRows.map(r => parseInt(r.value));\nconst probas = probaRows.map(r => [parseFloat(r['0']), parseFloat(r['1'])]);\n\nconst featDates = $('Generate features').first().json.feat_dates;\nconst retData = $('Generate features').first().json.ret_ser.data;\n\nconst sum0 = retData.reduce((a, r, i) => a + (labels[i] === 0 ? r : 0), 0);\nconst sum1 = retData.reduce((a, r, i) => a + (labels[i] === 1 ? r : 0), 0);\nconst bullComp = sum0 >= sum1 ? 0 : 1;\nconst bearComp = 1 - bullComp;\nconst stateMap = { [bullComp]: 'Bull', [bearComp]: 'Bear' };\n\nconst m = labels.length;\nconst nBull = labels.filter(l => l === bullComp).length;\nconst nBear = m - nBull;\nconst nTrans = labels.filter((l, i) => i > 0 && l !== labels[i-1]).length;\nconst curState = stateMap[labels[m-1]];\n\nlet streak = 1;\nfor (let i = m-2; i >= 0 && labels[i] === labels[m-1]; i--) streak++;\n\nconst pBull = (probas[m-1][bullComp] * 100).toFixed(1);\nconst pBear = (probas[m-1][bearComp] * 100).toFixed(1);\n\nconst last10 = Array.from({length: 10}, (_, i) => {\n const idx = m - 10 + i;\n return ` ${featDates[idx]} ${stateMap[labels[idx]].padEnd(5)} ${(probas[idx][bullComp]*100).toFixed(1).padStart(6)}% ${(probas[idx][bearComp]*100).toFixed(1).padStart(6)}%`;\n}).join('\\n');\n\nconst tickers = $('Set Parameters').first().json.tickers;\nconst tickerStr = Array.isArray(tickers) ? tickers.join('/') : String(tickers);\nconst jumpPenalty = $('Set Parameters').first().json.jump_penalty;\n\nconst report = `\n=================================================================\n JUMP MODEL — REGIME FORECAST ${tickerStr} | λ=${jumpPenalty}\n=================================================================\n Analysis date : ${new Date().toISOString().split('T')[0]}\n Sample : ${featDates[0]} → ${featDates[m-1]} (${m} days)\n State mapping : comp ${bullComp}=Bull comp ${bearComp}=Bear\n Regime stats : Bull ${(100*nBull/m).toFixed(1)}% (${nBull}d) Bear ${(100*nBear/m).toFixed(1)}% (${nBear}d) Transitions ${nTrans}\n\n Date State P(Bull) P(Bear)\n ---------- ----- -------- --------\n${last10}\n\n Current regime : ${curState} (${streak} consecutive days)\n Next-day forecast : P(Bull) = ${pBull}% P(Bear) = ${pBear}%\n=================================================================`;\n\nreturn [{ json: {\n report,\n current_state: curState,\n p_bull: parseFloat(pBull),\n p_bear: parseFloat(pBear),\n streak_days: streak,\n bull_pct: parseFloat((100*nBull/m).toFixed(1)),\n bear_pct: parseFloat((100*nBear/m).toFixed(1)),\n n_transitions: nTrans,\n analysis_date: new Date().toISOString().split('T')[0]\n}}];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 4864, 4816 ], "id": "6b02516c-dc70-4705-a154-ee69d2518a8b", "name": "TextReport" }, { "parameters": { "jsCode": "const featDates = $('Generate features').first().json.feat_dates;\nconst allDates = $('Generate features').first().json.all_dates;\nconst allCloses = $('Generate features').first().json.all_closes;\nconst retData = $('Generate features').first().json.ret_ser.data;\n\nfunction parseSSE(raw) {\n const idx = raw.indexOf('data: {');\n const outer = JSON.parse(raw.slice(idx + 6).trim());\n return JSON.parse(outer?.result?.content?.[0]?.text);\n}\nconst probaRows = parseSSE($('Node C').first().json.data)?.result?.payload?.rows;\nconst labelRows = parseSSE($('Node D').first().json.data)?.result?.payload?.rows;\n\nprobaRows.sort((a, b) => parseInt(a.index) - parseInt(b.index));\nlabelRows.sort((a, b) => parseInt(a.index) - parseInt(b.index));\n\nconst labels = labelRows.map(r => parseInt(r.value));\nconst probas = probaRows.map(r => [parseFloat(r['0']), parseFloat(r['1'])]);\n\nconst sum0 = retData.reduce((a,r,i) => a + (labels[i]===0 ? r : 0), 0);\nconst bullComp = sum0 >= retData.reduce((a,r,i) => a+(labels[i]===1?r:0),0) ? 0 : 1;\nconst bearComp = 1 - bullComp;\n\nconst startIdx = allDates.indexOf(featDates[0]);\n\nconst bands = [];\nlet bandStart = 0;\nfor (let i = 1; i <= labels.length; i++) {\n if (i === labels.length || labels[i] !== labels[i-1]) {\n bands.push({ from: featDates[bandStart], to: featDates[Math.min(i, labels.length-1)], bull: labels[bandStart] === bullComp });\n bandStart = i;\n }\n}\n\nconst pBullSeries = probas.map(p => parseFloat((p[bullComp]*100).toFixed(2)));\n\nconst bandsJson = JSON.stringify(bands);\nconst datesJson = JSON.stringify(allDates);\nconst closesJson = JSON.stringify(allCloses);\nconst featJson = JSON.stringify(featDates);\nconst pBullJson = JSON.stringify(pBullSeries);\nconst today = new Date().toISOString().split('T')[0];\n\nconst tickers = $('Set Parameters').first().json.tickers;\nconst tickerStr = Array.isArray(tickers) ? tickers.join('/') : String(tickers);\nconst jumpPenalty = $('Set Parameters').first().json.jump_penalty;\n\nconst html = `\n\n\n \n ${tickerStr} Jump Model Regimes\n \n \n \n\n\n

${tickerStr} — Jump Model 2-State Regime | λ = ${jumpPenalty}

\n

Analysis date: ${today}  |  Sample: ${featDates[0]} → ${featDates[featDates.length-1]}

\n
\n
\n\n\n`;\n\nreturn [{ json: { html, filename: tickerStr.toLowerCase().replace(/[^a-z0-9]/g,'_') + '_regime_' + today + '.html' } }];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 5024, 4816 ], "id": "06327778-5c12-4750-b350-bd04fab37c45", "name": "GraphReport" }, { "parameters": { "jsCode": "const r = $('TextReport').first().json;\nconst featDates = $('Generate features').first().json.feat_dates;\nconst retData = $('Generate features').first().json.ret_ser.data;\n\nfunction parseSSE(raw) {\n const idx = raw.indexOf('data: {');\n const outer = JSON.parse(raw.slice(idx + 6).trim());\n return JSON.parse(outer?.result?.content?.[0]?.text);\n}\nconst probaRows = parseSSE($('Node C').first().json.data)?.result?.payload?.rows;\nconst labelRows = parseSSE($('Node D').first().json.data)?.result?.payload?.rows;\n\nprobaRows.sort((a,b) => parseInt(a.index)-parseInt(b.index));\nlabelRows.sort((a,b) => parseInt(a.index)-parseInt(b.index));\n\nconst labels = labelRows.map(r => parseInt(r.value));\nconst probas = probaRows.map(r => [parseFloat(r['0']), parseFloat(r['1'])]);\nconst sum0 = retData.reduce((a,v,i) => a+(labels[i]===0?v:0), 0);\nconst bullComp = sum0 >= retData.reduce((a,v,i) => a+(labels[i]===1?v:0), 0) ? 0 : 1;\nconst bearComp = 1 - bullComp;\nconst stateMap = { [bullComp]:'Bull', [bearComp]:'Bear' };\nconst m = labels.length;\n\nconst monthMap = {};\nfeatDates.forEach((d, i) => {\n const mo = d.substring(0, 7);\n if (!monthMap[mo]) monthMap[mo] = { bull:0, bear:0 };\n labels[i] === bullComp ? monthMap[mo].bull++ : monthMap[mo].bear++;\n});\n\nconst monthCells = Object.entries(monthMap).map(([mo, v]) => {\n const pct = v.bull / (v.bull + v.bear);\n const label = mo.substring(2);\n let bg, text;\n if (pct >= 0.7) { bg='#1a6e3c'; text='#7fffb0'; }\n else if (pct >= 0.5) { bg='#2d5a3d'; text='#a8e6c3'; }\n else if (pct >= 0.3) { bg='#5a2d2d'; text='#e6a8a8'; }\n else { bg='#6e1a1a'; text='#ffb0b0'; }\n return `${label}`;\n}).join('');\n\nconst last10Rows = Array.from({length:10}, (_,i) => {\n const idx = m - 10 + i;\n const state = stateMap[labels[idx]];\n const pb = (probas[idx][bullComp]*100).toFixed(1);\n const pbr = (probas[idx][bearComp]*100).toFixed(1);\n const isLast = i === 9;\n const rowBg = isLast ? (state==='Bull'?'#1a3a1a':'#3a1a1a') : (i%2===0?'#1a1a2e':'#14142a');\n const stateColor = state==='Bull' ? '#27ae60' : '#e74c3c';\n return `${featDates[idx]}${isLast?'▶ ':''}${state}${pb}%${pbr}%`;\n}).join('');\n\nconst tickers = $('Set Parameters').first().json.tickers;\nconst tickerStr = Array.isArray(tickers) ? tickers.join('/') : String(tickers);\nconst jumpPenalty = $('Set Parameters').first().json.jump_penalty;\n\nconst bannerBg = r.current_state==='Bull' ? '#0d3320' : '#3a0d0d';\nconst bannerBorder= r.current_state==='Bull' ? '#27ae60' : '#e74c3c';\nconst bannerColor = r.current_state==='Bull' ? '#27ae60' : '#e74c3c';\nconst emoji = r.current_state==='Bull' ? '🟢' : '🔴';\n\nconst html = `

${tickerStr} Jump Model — Regime Forecast

${r.analysis_date}  |  λ=${jumpPenalty}  |  Sample: ${featDates[0]} → ${featDates[m-1]}  (${m} days)

${emoji}
${r.current_state.toUpperCase()} REGIME
${r.streak_days} consecutive trading days  |  P(Bull) = ${r.p_bull}%   P(Bear) = ${r.p_bear}%
${[['Bull Days',r.bull_pct+'% ('+Math.round(m*r.bull_pct/100)+'d)','#27ae60'],['Bear Days',r.bear_pct+'% ('+Math.round(m*r.bear_pct/100)+'d)','#e74c3c'],['Transitions',r.n_transitions,'#f39c12'],['Streak',r.streak_days+' days',bannerColor]].map(([label,val,col])=>``).join('')}
${label}
${val}
📅 MONTHLY REGIME TIMELINE █ Bull█ Bear
${monthCells}
🕐 LAST 10 TRADING DAYS
${last10Rows}
DateStateP(Bull)P(Bear)
📋 FULL REPORT
${r.report}

QuantAssistant  |  Jump Model 2-State Regime  |  ${tickerStr}  |  λ=${jumpPenalty}

`;\n\nreturn [{ json: {\n html,\n subject: `${emoji} ${tickerStr} ${r.current_state.toUpperCase()} — P(Bull)=${r.p_bull}% | ${r.streak_days}d streak | ${r.analysis_date}`\n}}];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 5200, 4816 ], "id": "3796240e-5210-478d-b6b3-d06310d00364", "name": "BuildEmail" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "route-by-trigger-cond", "leftValue": "={{ $('Set Parameters').first().json.trigger_source }}", "rightValue": "webhook", "operator": { "type": "string", "operation": "equals", "name": "filter.operator.equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 5392, 4816 ], "id": "ecf31d69-dfdc-4666-84a7-8f2444e89b0e", "name": "Route by Trigger" }, { "parameters": { "respondWith": "json", "responseBody": "={{ $('TextReport').first().json }}", "options": {} }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 5600, 4528 ], "id": "c5dcac33-bed2-4183-93f8-f3d01f3f96b6", "name": "Respond to Webhook Success" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "has-csv-cond-01", "leftValue": "={{ $json.has_csv }}", "rightValue": true, "operator": { "type": "boolean", "operation": "equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 4672, 3952 ], "id": "dba67225-8bd1-458c-bebd-6815212a93bd", "name": "Has CSV?" }, { "parameters": { "jsCode": "const setParams = $('Set Parameters').first().json;\nconst csvData = setParams.csv_data;\n\nif (!csvData || !csvData.trim()) throw new Error('csv_data is empty');\n\nconst lines = csvData.trim().split(/\\r?\\n/).map(l => l.trim()).filter(l => l);\nconst headers = lines[0].split(',').map(h => h.trim());\n\n// Find Date column (accepts: date, Date, DATE, timestamp, Timestamp)\nconst dateIdx = headers.findIndex(h => /^date$/i.test(h) || /^timestamp$/i.test(h));\nconst valIdx = headers.findIndex((_, i) => i !== dateIdx);\n\nif (dateIdx === -1) throw new Error('No Date/Timestamp column found. Headers: ' + headers.join(', '));\nif (valIdx === -1) throw new Error('CSV must have at least 2 columns (Date + value).');\n\nconst rows = [];\nfor (const line of lines.slice(1)) {\n const cols = line.split(',').map(c => c.trim());\n const ts = (cols[dateIdx] || '').substring(0, 10);\n const val = parseFloat(cols[valIdx]);\n if (ts.length === 10 && !isNaN(val) && val > 0) rows.push({ timestamp: ts, close: val });\n}\n\nif (rows.length < 70) throw new Error('Too few rows after parsing: ' + rows.length + '. Need at least 70 to compute features (63-bar warmup + data).');\n\nreturn [{ json: { csv_rows: rows, value_col: headers[valIdx], row_count: rows.length } }];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 4992, 3936 ], "id": "e6372c7f-e095-4678-8752-cbc31feca248", "name": "Parse CSV" }, { "parameters": {}, "type": "n8n-nodes-base.merge", "typeVersion": 3.2, "position": [ 5584, 3920 ], "id": "cb4de546-7c25-4c34-af36-fbd2a3bd19a7", "name": "Merge Pre-Features" }, { "parameters": { "language": "pythonNative", "pythonCode": "import json\n\nitem = _items[0]\njson_data = item.get('json', item)\nbody = json_data.get('body', {}) or {}\n\nif isinstance(body, str):\n try:\n body = json.loads(body)\n except Exception:\n body = {}\n\ntickers = body.get('tickers', None)\nstart_date = body.get('start_date', None)\nend_date = body.get('end_date', None)\njump_penalty = body.get('jump_penalty', None)\nn_components = body.get('n_components', None)\nn_init = body.get('n_init', None)\n\ncsv_data = body.get('csv_data', None)\nif isinstance(csv_data, str) and not csv_data.strip():\n csv_data = None\n\nif tickers is not None and not isinstance(tickers, list):\n return [{'json': {'route': 'error', 'reason': 'tickers must be a list, e.g. [\"SPY\"]'}}]\n\nreturn [{'json': {\n 'route': 'execute',\n 'tickers': tickers or ['SPY'],\n 'start_date': start_date or '2019-01-01',\n 'end_date': end_date or None,\n 'jump_penalty': float(jump_penalty) if jump_penalty is not None else 5.0,\n 'n_components': int(n_components) if n_components is not None else 2,\n 'n_init': int(n_init) if n_init is not None else 20,\n 'csv_data': csv_data,\n 'has_csv': csv_data is not None\n}}]" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 3632, 3984 ], "id": "1d00e7a4-e02f-4af6-ac46-7bdb7959cafa", "name": "ExtractCSVbody" }, { "parameters": { "language": "pythonNative", "pythonCode": "import pandas as pd\nfrom pandas.tseries.holiday import USFederalHolidayCalendar\n\ntoday = pd.Timestamp.today().normalize()\ncal = USFederalHolidayCalendar()\nholidays = cal.holidays(start=today.replace(month=1, day=1), end=today.replace(month=12, day=31))\nis_weekend = today.dayofweek >= 5\nis_holiday = today in holidays\nreturn {\"is_working_day\": not (is_weekend or is_holiday)}" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 3648, 4288 ], "id": "978302c9-c4d7-4a5f-a2ce-ae44700d7534", "name": "IsHoliday" }, { "parameters": { "jsCode": "const reason = $input.first().json.reason || 'Invalid request';\n\nreturn [{ json: {\n status: 'error',\n reason: reason,\n schema: {\n description: 'POST a JSON body to run Jump Model regime analysis. All fields are optional.',\n fields: {\n tickers: { type: 'array', default: ['SPY'], example: ['QQQ'], note: 'Must be an array, not a string.' },\n start_date: { type: 'YYYY-MM-DD', default: '2019-01-01', example: '2020-01-01' },\n end_date: { type: 'YYYY-MM-DD', default: 'today', example: '2024-12-31' },\n jump_penalty: { type: 'number', default: 5.0, example: 10, note: 'Regime-switching cost. Higher = fewer transitions. Typical range: 1–100.' },\n n_components: { type: 'integer', default: 2, example: 2, note: 'Number of regimes. Typically 2 (Bull/Bear).' },\n n_init: { type: 'integer', default: 20, example: 30, note: 'Random restarts for fitting. Higher = more stable.' },\n csv_data: { type: 'string (CSV)', default: null, note: 'Optional. If provided, skips market-data fetch. Must have a Date column + one price column. Minimum 70 rows.', csv_format: 'Date,Close\\n2024-01-02,469.42\\n2024-01-03,468.69\\n...' }\n },\n validation_rules: [\n 'tickers must be an array — e.g. [\"SPY\"], not \"SPY\"',\n 'csv_data must contain at least 70 rows (63-bar warmup + data)',\n 'csv_data must have a column named Date or Timestamp (case-insensitive)'\n ],\n example_requests: {\n minimal: {},\n custom_ticker: { tickers: ['QQQ'] },\n date_range: { tickers: ['SPY'], start_date: '2020-01-01', end_date: '2024-12-31' },\n custom_model: { tickers: ['SPY'], jump_penalty: 10, n_components: 2, n_init: 30 },\n csv_upload: { tickers: ['CUSTOM'], csv_data: 'Date,Close\\n2024-01-02,469.42\\n...' }\n },\n curl_example: \"curl -X POST https://n8n.limex.pro/webhook/regime-model -H 'Content-Type: application/json' -d '{\\\"tickers\\\":[\\\"QQQ\\\"],\\\"jump_penalty\\\":10}'\"\n }\n}}];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 4096, 3808 ], "id": "25715ec3-e79f-4447-b17d-5093cf20ad15", "name": "Build Error Response" } ], "connections": { "Schedule Trigger": { "main": [ [ { "node": "IsHoliday", "type": "main", "index": 0 } ] ] }, "Webhook": { "main": [ [ { "node": "ExtractCSVbody", "type": "main", "index": 0 } ] ] }, "If": { "main": [ [ { "node": "Merge Triggers", "type": "main", "index": 0 } ] ] }, "Webhook Validation": { "main": [ [ { "node": "Merge Triggers", "type": "main", "index": 1 } ], [ { "node": "Build Error Response", "type": "main", "index": 0 } ] ] }, "Merge Triggers": { "main": [ [ { "node": "Set Parameters", "type": "main", "index": 0 } ] ] }, "Set Parameters": { "main": [ [ { "node": "Has CSV?", "type": "main", "index": 0 } ] ] }, "Has CSV?": { "main": [ [ { "node": "Parse CSV", "type": "main", "index": 0 } ], [ { "node": "Data extraction", "type": "main", "index": 0 } ] ] }, "Parse CSV": { "main": [ [ { "node": "Merge Pre-Features", "type": "main", "index": 1 } ] ] }, "Data extraction": { "main": [ [ { "node": "DataUnpack", "type": "main", "index": 0 } ] ] }, "DataUnpack": { "main": [ [ { "node": "Connection Handshake", "type": "main", "index": 0 } ] ] }, "Connection Handshake": { "main": [ [ { "node": "DataExtracted", "type": "main", "index": 0 } ] ] }, "DataExtracted": { "main": [ [ { "node": "Merge Pre-Features", "type": "main", "index": 0 } ] ] }, "Merge Pre-Features": { "main": [ [ { "node": "Generate features", "type": "main", "index": 0 } ] ] }, "Generate features": { "main": [ [ { "node": "Create Jump Model", "type": "main", "index": 0 } ] ] }, "Create Jump Model": { "main": [ [ { "node": "Fit Model", "type": "main", "index": 0 } ] ] }, "Fit Model": { "main": [ [ { "node": "Predict Online Probabilities", "type": "main", "index": 0 } ] ] }, "Predict Online Probabilities": { "main": [ [ { "node": "Predict Hard Labels", "type": "main", "index": 0 } ] ] }, "Predict Hard Labels": { "main": [ [ { "node": "Node A", "type": "main", "index": 0 } ] ] }, "Node A": { "main": [ [ { "node": "Node B", "type": "main", "index": 0 } ] ] }, "Node B": { "main": [ [ { "node": "Node C", "type": "main", "index": 0 } ] ] }, "Node C": { "main": [ [ { "node": "Node D", "type": "main", "index": 0 } ] ] }, "Node D": { "main": [ [ { "node": "TextReport", "type": "main", "index": 0 } ] ] }, "TextReport": { "main": [ [ { "node": "GraphReport", "type": "main", "index": 0 } ] ] }, "GraphReport": { "main": [ [ { "node": "BuildEmail", "type": "main", "index": 0 } ] ] }, "BuildEmail": { "main": [ [ { "node": "Route by Trigger", "type": "main", "index": 0 } ] ] }, "Route by Trigger": { "main": [ [ { "node": "Respond to Webhook Success", "type": "main", "index": 0 } ], [] ] }, "ExtractCSVbody": { "main": [ [ { "node": "Webhook Validation", "type": "main", "index": 0 } ] ] }, "IsHoliday": { "main": [ [ { "node": "If", "type": "main", "index": 0 } ] ] }, "Build Error Response": { "main": [ [ { "node": "Respond Error", "type": "main", "index": 0 } ] ] } }, "settings": { "executionOrder": "v1", "binaryMode": "separate", "availableInMCP": false }, "nodeGroups": [] }