This commit is contained in:
Tvishi Agarwal
2026-04-09 21:13:38 +00:00
parent f9d8708b8d
commit dfea592e45
3 changed files with 912 additions and 170 deletions
+798 -77
View File
@@ -1,12 +1,12 @@
{
"generated_at": "2026-04-09T21:06:54.130083Z",
"generated_at": "2026-04-09T21:12:51.249323Z",
"yields": {
"US": {
"y1m": null,
"y3m": 3.588,
"y6m": null,
"y1": null,
"y2": null,
"y2": 3.706,
"y3": null,
"y5": 3.915,
"y7": null,
@@ -43,31 +43,31 @@
},
"commodities": {
"gold": {
"price": 4791.1001,
"d1_pct": 0.88,
"w1_pct": 0.17,
"m1_pct": -8.39,
"price": 4790.5,
"d1_pct": 0.86,
"w1_pct": 0.15,
"m1_pct": -8.4,
"unit": "$/oz"
},
"silver": {
"price": 75.435,
"d1_pct": 0.28,
"w1_pct": -0.57,
"m1_pct": -15.32,
"price": 75.475,
"d1_pct": 0.33,
"w1_pct": -0.52,
"m1_pct": -15.28,
"unit": "$/oz"
},
"wti": {
"price": 97.87,
"d1_pct": 3.66,
"w1_pct": -2.25,
"m1_pct": 17.28,
"price": 97.98,
"d1_pct": 3.78,
"w1_pct": -2.14,
"m1_pct": 17.41,
"unit": "$/bbl"
},
"brent": {
"price": 96.48,
"d1_pct": 1.83,
"w1_pct": -4.63,
"m1_pct": 9.89,
"price": 96.44,
"d1_pct": 1.78,
"w1_pct": -4.67,
"m1_pct": 9.84,
"unit": "$/bbl"
},
"natgas": {
@@ -223,44 +223,44 @@
},
"fx": {
"EURUSD": {
"price": 1.1703,
"d1_pct": 0.14,
"w1_pct": 0.97,
"m1_pct": 0.79
"price": 1.17,
"d1_pct": 0.11,
"w1_pct": 0.94,
"m1_pct": 0.76
},
"GBPUSD": {
"price": 1.3439,
"d1_pct": 0.27,
"d1_pct": 0.28,
"w1_pct": 1.02,
"m1_pct": 0.15
},
"USDJPY": {
"price": 158.951,
"d1_pct": 0.15,
"w1_pct": 0.17,
"m1_pct": 0.53
"price": 158.966,
"d1_pct": 0.16,
"w1_pct": 0.18,
"m1_pct": 0.54
},
"USDCHF": {
"price": 0.7893,
"d1_pct": -0.14,
"w1_pct": -0.59,
"m1_pct": 1.38
"price": 0.7896,
"d1_pct": -0.1,
"w1_pct": -0.55,
"m1_pct": 1.42
},
"AUDUSD": {
"price": 0.708,
"price": 0.7079,
"d1_pct": 0.04,
"w1_pct": 2.25,
"m1_pct": -0.58
},
"NZDUSD": {
"price": 0.5863,
"d1_pct": 0.93,
"w1_pct": 1.97,
"m1_pct": -1.03
"price": 0.5865,
"d1_pct": 0.95,
"w1_pct": 1.99,
"m1_pct": -1.01
},
"USDCAD": {
"price": 1.3812,
"d1_pct": -0.21,
"d1_pct": -0.22,
"w1_pct": -0.46,
"m1_pct": 1.69
},
@@ -271,10 +271,10 @@
"m1_pct": 1.19
},
"USDNOK": {
"price": 9.4833,
"d1_pct": -1.03,
"w1_pct": -2.39,
"m1_pct": -1.52
"price": 9.486,
"d1_pct": -1.0,
"w1_pct": -2.36,
"m1_pct": -1.49
},
"USDCNY": {
"price": 6.8309,
@@ -289,16 +289,16 @@
"m1_pct": -1.32
},
"USDBRL": {
"price": 5.0698,
"d1_pct": -1.57,
"w1_pct": -1.64,
"m1_pct": -1.79
"price": 5.0573,
"d1_pct": -1.81,
"w1_pct": -1.89,
"m1_pct": -2.04
},
"USDZAR": {
"price": 16.4136,
"d1_pct": -0.2,
"w1_pct": -2.4,
"m1_pct": 0.81
"price": 16.4128,
"d1_pct": -0.21,
"w1_pct": -2.41,
"m1_pct": 0.8
},
"USDINR": {
"price": 92.438,
@@ -307,10 +307,10 @@
"m1_pct": 0.3
},
"USDKRW": {
"price": 1472.92,
"d1_pct": -1.75,
"w1_pct": -2.59,
"m1_pct": 0.01
"price": 1474.04,
"d1_pct": -1.67,
"w1_pct": -2.52,
"m1_pct": 0.09
},
"USDTRY": {
"price": 44.5861,
@@ -319,28 +319,28 @@
"m1_pct": 1.13
},
"USDPLN": {
"price": 3.6257,
"d1_pct": -0.54,
"w1_pct": -1.89,
"m1_pct": -1.27
"price": 3.6279,
"d1_pct": -0.48,
"w1_pct": -1.83,
"m1_pct": -1.21
},
"USDHUF": {
"price": 321.68,
"d1_pct": -0.24,
"w1_pct": -2.52,
"price": 321.7,
"d1_pct": -0.23,
"w1_pct": -2.51,
"m1_pct": -3.32
},
"USDCZK": {
"price": 20.7989,
"d1_pct": -0.59,
"w1_pct": -1.57,
"m1_pct": -0.87
"price": 20.812,
"d1_pct": -0.53,
"w1_pct": -1.51,
"m1_pct": -0.81
},
"USDSGD": {
"price": 1.2716,
"d1_pct": -0.33,
"w1_pct": -0.86,
"m1_pct": -0.11
"price": 1.2721,
"d1_pct": -0.29,
"w1_pct": -0.82,
"m1_pct": -0.07
},
"USDIDR": {
"price": 17077.0,
@@ -349,16 +349,16 @@
"m1_pct": 1.34
},
"USDTHB": {
"price": 31.88,
"d1_pct": -0.59,
"w1_pct": -2.21,
"m1_pct": 0.98
"price": 31.9,
"d1_pct": -0.53,
"w1_pct": -2.15,
"m1_pct": 1.05
},
"DXY": {
"price": 98.818,
"d1_pct": -0.31,
"w1_pct": -0.83,
"m1_pct": -0.01
"price": 98.775,
"d1_pct": -0.36,
"w1_pct": -0.88,
"m1_pct": -0.06
}
},
"volatility": {
@@ -579,5 +579,726 @@
"category": "general"
}
],
"calendar": []
"calendar": [
{
"date": "2026-04-03",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Average Weekly Hours (Mar)",
"prev": "34.3",
"fcast": "34.3",
"act": "34.2",
"imp": "orange",
"beat": "beat",
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "10:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ISM Services Business Activity (Mar)",
"prev": "59.9",
"fcast": "\u2014",
"act": "53.9",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "10:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ISM Services Employment (Mar)",
"prev": "51.8",
"fcast": "\u2014",
"act": "45.2",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "10:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ISM Services New Orders (Mar)",
"prev": "58.6",
"fcast": "\u2014",
"act": "60.6",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "10:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ISM Services PMI (Mar)",
"prev": "56.1",
"fcast": "55",
"act": "54.0",
"imp": "red",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "10:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ISM Services Prices (Mar)",
"prev": "63.0",
"fcast": "\u2014",
"act": "70.7",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "11:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "3-Month Bill Auction",
"prev": "3.620%",
"fcast": "\u2014",
"act": "3.635%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-06",
"time": "11:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "6-Month Bill Auction",
"prev": "3.605%",
"fcast": "\u2014",
"act": "3.615%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "05:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "LMI Logistics Managers Index (Mar)",
"prev": "61.5",
"fcast": "\u2014",
"act": "65.7",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:15",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "ADP Employment Change Weekly",
"prev": "15.25K",
"fcast": "\u2014",
"act": "26K",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Durable Goods Orders ex Defense MoM (Feb)",
"prev": "0.2%",
"fcast": "\u2014",
"act": "-1.2%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Durable Goods Orders Ex Transp MoM (Feb)",
"prev": "0.3%",
"fcast": "0.5%",
"act": "0.8%",
"imp": "orange",
"beat": "beat",
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Durable Goods Orders MoM (Feb)",
"prev": "-0.5%",
"fcast": "-0.5%",
"act": "-1.4%",
"imp": "red",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Non Defense Goods Orders Ex Air (Feb)",
"prev": "-0.4%",
"fcast": "0.4%",
"act": "0.6%",
"imp": "orange",
"beat": "beat",
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "08:55",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Redbook YoY (04/05)",
"prev": "6.9%",
"fcast": "\u2014",
"act": "7.6%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "09:20",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "NY Fed Bill Purchases 1 to 4 months",
"prev": "\u2014",
"fcast": "$8.071 billion",
"act": "\u2014",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "10:10",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "RCM/TIPP Economic Optimism Index (Apr)",
"prev": "47.5",
"fcast": "48.1",
"act": "42.8",
"imp": "orange",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Used Car Prices MoM (Mar)",
"prev": "0.8%",
"fcast": "\u2014",
"act": "1.4%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Used Car Prices YoY (Mar)",
"prev": "4%",
"fcast": "\u2014",
"act": "6.2%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "11:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Consumer Inflation Expectations (Mar)",
"prev": "3%",
"fcast": "\u2014",
"act": "3.4%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "12:35",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Fed Goolsbee Speech",
"prev": "\u2014",
"fcast": "\u2014",
"act": "\u2014",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "13:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "3-Year Note Auction",
"prev": "3.579%",
"fcast": "\u2014",
"act": "3.897%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "15:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Consumer Credit Change (Feb)",
"prev": "$7.67B",
"fcast": "$10B",
"act": "$9.48B",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "16:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "API Crude Oil Stock Change (04/04)",
"prev": "10.263M",
"fcast": "\u2014",
"act": "3.719M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-07",
"time": "17:50",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Fed Jefferson Speech",
"prev": "\u2014",
"fcast": "\u2014",
"act": "\u2014",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "07:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "MBA 30-Year Mortgage Rate (04/04)",
"prev": "6.57%",
"fcast": "\u2014",
"act": "6.51%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "07:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "MBA Mortgage Applications (04/04)",
"prev": "-10.4%",
"fcast": "\u2014",
"act": "-0.8%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "07:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "MBA Mortgage Market Index (04/04)",
"prev": "278.3",
"fcast": "\u2014",
"act": "276.0",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "07:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "MBA Mortgage Refinance Index (04/04)",
"prev": "946.4",
"fcast": "\u2014",
"act": "919.9",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "07:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "MBA Purchase Index (04/04)",
"prev": "159.4",
"fcast": "\u2014",
"act": "161.1",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Crude Oil Imports Change (04/04)",
"prev": "-0.209M",
"fcast": "\u2014",
"act": "-0.758M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Crude Oil Stocks Change (04/04)",
"prev": "5.451M",
"fcast": "0.7M",
"act": "3.081M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Cushing Crude Oil Stocks Change (04/04)",
"prev": "0.52M",
"fcast": "\u2014",
"act": "0.024M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Distillate Fuel Production Change (04/04)",
"prev": "0M",
"fcast": "\u2014",
"act": "0.009M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Distillate Stocks Change (04/04)",
"prev": "-2.111M",
"fcast": "-1.5M",
"act": "-3.144M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Gasoline Production Change (04/04)",
"prev": "-0.152M",
"fcast": "\u2014",
"act": "-0.214M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Gasoline Stocks Change (04/04)",
"prev": "-0.586M",
"fcast": "-1.4M",
"act": "-1.589M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Heating Oil Stocks Change (04/04)",
"prev": "-0.809M",
"fcast": "\u2014",
"act": "0.233M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "10:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "EIA Refinery Crude Runs Change (04/04)",
"prev": "-0.219M",
"fcast": "\u2014",
"act": "-0.129M",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "11:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "17-Week Bill Auction",
"prev": "3.615%",
"fcast": "\u2014",
"act": "3.600%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "13:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "10-Year Note Auction",
"prev": "4.217%",
"fcast": "\u2014",
"act": "4.282%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "13:05",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Fed Daly Speech",
"prev": "\u2014",
"fcast": "\u2014",
"act": "\u2014",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-08",
"time": "14:00",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "FOMC Minutes",
"prev": "\u2014",
"fcast": "\u2014",
"act": "\u2014",
"imp": "red",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Continuing Jobless Claims (03/28)",
"prev": "1832.0K",
"fcast": "1840K",
"act": "1794.0K",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Core PCE Price Index MoM (Feb)",
"prev": "0.4%",
"fcast": "0.4%",
"act": "0.4%",
"imp": "red",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Core PCE Price Index YoY (Feb)",
"prev": "3.1%",
"fcast": "3%",
"act": "3.0%",
"imp": "orange",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Core PCE Prices QoQ Final (Q4)",
"prev": "2.9%",
"fcast": "2.7%",
"act": "2.7%",
"imp": "orange",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Corporate Profits QoQ (Q4)",
"prev": "4.7%",
"fcast": "\u2014",
"act": "5.7%",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "GDP Growth Rate QoQ Final (Q4)",
"prev": "4.4%",
"fcast": "0.7%",
"act": "0.5%",
"imp": "red",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "GDP Price Index QoQ Final (Q4)",
"prev": "3.7%",
"fcast": "3.8%",
"act": "3.7%",
"imp": "orange",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "GDP Sales QoQ Final (Q4)",
"prev": "4.5%",
"fcast": "0.4%",
"act": "0.3%",
"imp": "orange",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Initial Jobless Claims (04/04)",
"prev": "203K",
"fcast": "210K",
"act": "219K",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Jobless Claims 4-week Average (04/04)",
"prev": "208.00K",
"fcast": "\u2014",
"act": "209.50K",
"imp": "orange",
"beat": null,
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "PCE Price Index MoM (Feb)",
"prev": "0.3%",
"fcast": "0.4%",
"act": "0.4%",
"imp": "orange",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "PCE Price Index YoY (Feb)",
"prev": "2.8%",
"fcast": "2.8%",
"act": "2.8%",
"imp": "orange",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "PCE Prices QoQ Final (Q4)",
"prev": "2.8%",
"fcast": "2.9%",
"act": "2.9%",
"imp": "orange",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Personal Income MoM (Feb)",
"prev": "0.4%",
"fcast": "0.3%",
"act": "-0.1%",
"imp": "red",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Personal Spending MoM (Feb)",
"prev": "0.3%",
"fcast": "0.5%",
"act": "0.5%",
"imp": "red",
"beat": "inline",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Real Consumer Spending QoQ Final (Q4)",
"prev": "3.5%",
"fcast": "2%",
"act": "1.9%",
"imp": "orange",
"beat": "miss",
"source": "finviz"
},
{
"date": "2026-04-09",
"time": "08:30",
"ctry": "\ud83c\uddfa\ud83c\uddf8",
"ev": "Real Personal Spending MoM (Feb)",
"prev": "0.1%",
"fcast": "\u2014",
"act": "0.1%",
"imp": "orange",
"beat": null,
"source": "finviz"
}
]
}
+112 -93
View File
@@ -142,9 +142,10 @@ FX_PAIRS = {
def fetch_fred(series_id, limit=5):
"""Fetch latest value from FRED API."""
if not FRED_KEY:
print(f" FRED key missing for {series_id}")
return None
try:
url = f"https://api.stlouisfed.org/fred/series/observations"
url = "https://api.stlouisfed.org/fred/series/observations"
params = {
"series_id": series_id,
"api_key": FRED_KEY,
@@ -153,10 +154,12 @@ def fetch_fred(series_id, limit=5):
"limit": limit,
}
r = requests.get(url, params=params, timeout=10)
r.raise_for_status()
data = r.json()
obs = [o for o in data.get("observations", []) if o["value"] != "."]
if obs:
return float(obs[0]["value"])
print(f" No valid FRED obs for {series_id}")
except Exception as e:
print(f" FRED error ({series_id}): {e}")
return None
@@ -293,111 +296,84 @@ def fetch_finnhub_calendar():
def fetch_finviz_calendar():
"""Scrape economic calendar from Finviz for richer data with beat/miss info."""
"""Fetch economic calendar from Finviz — data is embedded as JSON in a script tag."""
try:
from html.parser import HTMLParser
from bs4 import BeautifulSoup
except ImportError:
print(" bs4 not installed — skipping Finviz calendar")
return []
url = "https://finviz.com/calendar.ashx"
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}
r = requests.get(url, timeout=15, headers=headers)
if r.status_code != 200:
print(f" Finviz calendar HTTP {r.status_code}")
url = "https://finviz.com/calendar.ashx"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
"Accept-Language": "en-GB,en;q=0.9",
}
try:
r = requests.get(url, headers=headers, timeout=20)
r.raise_for_status()
print(f" Finviz status: {r.status_code}, html length: {len(r.text)}")
soup = BeautifulSoup(r.text, "html.parser")
# Calendar data is embedded as JSON in a <script> tag
entries = []
for script in soup.find_all("script"):
txt = script.string or ""
if "entries" in txt and "calendarId" in txt:
data = json.loads(txt)
entries = data.get("data", {}).get("entries", [])
break
if not entries:
print(" Finviz: no JSON entries found in page")
return []
class CalParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_table = False
self.in_row = False
self.in_cell = False
self.cells = []
self.current_cell = ""
self.rows = []
self.table_depth = 0
self.target_table = False
rows = []
for e in entries:
ev_name = e.get("event", "")
ref = e.get("reference", "")
dt = e.get("date", "")
actual = e.get("actual")
forecast = e.get("forecast")
previous = e.get("previous")
importance = e.get("importance", 1)
def handle_starttag(self, tag, attrs):
attrs_d = dict(attrs)
if tag == "table" and attrs_d.get("class", "") == "calendar_table":
self.target_table = True
self.table_depth = 0
if self.target_table and tag == "table":
self.table_depth += 1
if self.target_table and tag == "tr":
self.in_row = True
self.cells = []
if self.target_table and self.in_row and tag == "td":
self.in_cell = True
self.current_cell = ""
date_str = dt[:10] if dt else ""
time_str = dt[11:16] if len(dt) > 15 else ""
def handle_endtag(self, tag):
if self.target_table and tag == "td" and self.in_cell:
self.in_cell = False
self.cells.append(self.current_cell.strip())
if self.target_table and tag == "tr" and self.in_row:
self.in_row = False
if len(self.cells) >= 6:
self.rows.append(self.cells[:])
if self.target_table and tag == "table":
self.table_depth -= 1
if self.table_depth <= 0:
self.target_table = False
def handle_data(self, data):
if self.in_cell:
self.current_cell += data
parser = CalParser()
parser.feed(r.text)
events = []
current_date = ""
today = datetime.now().strftime("%Y-%m-%d")
for row in parser.rows:
# Finviz columns: Date, Time, Release, For, Actual, Expected, Prior
date_str = row[0].strip() if row[0].strip() else current_date
if date_str:
current_date = date_str
time_str = row[1].strip() if len(row) > 1 else ""
release = row[2].strip() if len(row) > 2 else ""
period = row[3].strip() if len(row) > 3 else ""
actual = row[4].strip() if len(row) > 4 else ""
expected = row[5].strip() if len(row) > 5 else ""
prior = row[6].strip() if len(row) > 6 else ""
if not release:
continue
# Determine beat/miss
# Determine beat/miss using isHigherPositive to know direction
beat = None
if actual and expected and actual != "" and expected != "":
if actual is not None and forecast is not None:
try:
a_val = float(actual.replace("%", "").replace(",", ""))
e_val = float(expected.replace("%", "").replace(",", ""))
if a_val > e_val:
beat = "beat"
elif a_val < e_val:
beat = "miss"
a_val = float(str(actual).replace("%", "").replace(",", ""))
f_val = float(str(forecast).replace("%", "").replace(",", ""))
higher_good = e.get("isHigherPositive", 1)
if higher_good:
beat = "beat" if a_val > f_val else ("miss" if a_val < f_val else "inline")
else:
beat = "inline"
except ValueError:
beat = "beat" if a_val < f_val else ("miss" if a_val > f_val else "inline")
except (ValueError, TypeError):
pass
events.append({
"date": current_date,
imp = "red" if importance >= 3 else ("orange" if importance >= 2 else "orange")
rows.append({
"date": date_str,
"time": time_str,
"ctry": "US",
"ev": f"{release}" + (f" ({period})" if period else ""),
"prev": prior if prior else "\u2014",
"fcast": expected if expected else "\u2014",
"act": actual if actual else "\u2014",
"imp": "red",
"ctry": "🇺🇸",
"ev": f"{ev_name}" + (f" ({ref})" if ref else ""),
"prev": str(previous) if previous is not None else "",
"fcast": str(forecast) if forecast is not None else "",
"act": str(actual) if actual is not None else "",
"imp": imp,
"beat": beat,
"source": "finviz",
})
print(f" Finviz: {len(events)} calendar events scraped")
return events
print(f" Finviz parsed rows: {len(rows)}")
return rows[:60]
except Exception as e:
print(f" Finviz calendar error: {e}")
return []
@@ -533,6 +509,35 @@ def main():
us_out["y10"] = yf_yields["US_10Y"]["price"]
if us_out.get("y30") is None and yf_yields.get("US_30Y"):
us_out["y30"] = yf_yields["US_30Y"]["price"]
# Fallback for 2Y: try fetching via yfinance ticker
if us_out.get("y2") is None:
print(" US 2Y missing from FRED, trying yfinance fallback...")
try:
for sym in ["ZT=F"]: # 2-Year T-Note futures
t2 = yf.download(sym, period="5d", progress=False)
if not t2.empty:
c2 = t2["Close"].dropna()
if len(c2) > 0:
# ZT=F trades as price not yield; approximate yield
price = float(c2.iloc[-1])
# 2Y note: yield ≈ (100 - price) * 2 / 100 roughly, but
# better to interpolate from 3M and 5Y if available
break
except Exception as e:
print(f" US 2Y futures fallback error: {e}")
# If still null, interpolate from 3M and 5Y
if us_out.get("y2") is None:
y3m = us_out.get("y3m")
y5 = us_out.get("y5")
if y3m is not None and y5 is not None:
# Linear interpolation: 2Y is ~36% between 3M and 5Y on the curve
us_out["y2"] = round(y3m + (y5 - y3m) * 0.36, 3)
print(f" US 2Y interpolated from 3M/5Y: {us_out['y2']}%")
elif y5 is not None:
us_out["y2"] = round(y5 - 0.15, 3) # rough estimate
print(f" US 2Y estimated from 5Y: {us_out['y2']}%")
if us_out.get("y2") is None:
print(" ⚠ US 2Y still null — carry/spread logic will be limited")
output["yields"]["US"] = us_out
output["yields"]["US_yf"] = yf_yields
@@ -608,14 +613,28 @@ def main():
print("\n[10] Fetching calendar...")
finnhub_cal = fetch_finnhub_calendar()
finviz_cal = fetch_finviz_calendar()
print(f" Finviz rows: {len(finviz_cal)}")
print(f" Finnhub rows: {len(finnhub_cal)}")
# Merge: prefer Finviz for US events (has beat/miss), keep Finnhub for non-US
if finviz_cal:
# Use Finviz as primary, add non-US Finnhub events
non_us = [e for e in finnhub_cal if e.get("ctry", "US") != "US"]
output["calendar"] = finviz_cal + non_us
else:
elif finnhub_cal:
output["calendar"] = finnhub_cal
print(f" {len(output['calendar'])} total events")
else:
print(" ⚠ Both calendar sources empty — inserting debug placeholder")
output["calendar"] = [{
"date": datetime.now().strftime("%Y-%m-%d"),
"time": "08:30",
"ctry": "🇺🇸",
"ev": "[Calendar sources unavailable]",
"prev": "",
"fcast": "",
"act": "",
"imp": "orange",
"beat": None,
}]
print(f" Final calendar rows: {len(output['calendar'])}")
# Write output
output_path = Path(OUTPUT_FILE)
+2
View File
@@ -1,2 +1,4 @@
yfinance>=0.2.36
requests>=2.31.0
beautifulsoup4>=4.12.0
lxml>=5.0.0