apis

data.json

@@ -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,
+      "price": 4790.5,
-      "d1_pct": 0.88,
+      "d1_pct": 0.86,
-      "w1_pct": 0.17,
+      "w1_pct": 0.15,
-      "m1_pct": -8.39,
+      "m1_pct": -8.4,
       "unit": "$/oz"
     },
     "silver": {
-      "price": 75.435,
+      "price": 75.475,
-      "d1_pct": 0.28,
+      "d1_pct": 0.33,
-      "w1_pct": -0.57,
+      "w1_pct": -0.52,
-      "m1_pct": -15.32,
+      "m1_pct": -15.28,
       "unit": "$/oz"
     },
     "wti": {
-      "price": 97.87,
+      "price": 97.98,
-      "d1_pct": 3.66,
+      "d1_pct": 3.78,
-      "w1_pct": -2.25,
+      "w1_pct": -2.14,
-      "m1_pct": 17.28,
+      "m1_pct": 17.41,
       "unit": "$/bbl"
     },
     "brent": {
-      "price": 96.48,
+      "price": 96.44,
-      "d1_pct": 1.83,
+      "d1_pct": 1.78,
-      "w1_pct": -4.63,
+      "w1_pct": -4.67,
-      "m1_pct": 9.89,
+      "m1_pct": 9.84,
       "unit": "$/bbl"
     },
     "natgas": {
@@ -223,44 +223,44 @@
   },
   "fx": {
     "EURUSD": {
-      "price": 1.1703,
+      "price": 1.17,
-      "d1_pct": 0.14,
+      "d1_pct": 0.11,
-      "w1_pct": 0.97,
+      "w1_pct": 0.94,
-      "m1_pct": 0.79
+      "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,
+      "price": 158.966,
-      "d1_pct": 0.15,
+      "d1_pct": 0.16,
-      "w1_pct": 0.17,
+      "w1_pct": 0.18,
-      "m1_pct": 0.53
+      "m1_pct": 0.54
     },
     "USDCHF": {
-      "price": 0.7893,
+      "price": 0.7896,
-      "d1_pct": -0.14,
+      "d1_pct": -0.1,
-      "w1_pct": -0.59,
+      "w1_pct": -0.55,
-      "m1_pct": 1.38
+      "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,
+      "price": 0.5865,
-      "d1_pct": 0.93,
+      "d1_pct": 0.95,
-      "w1_pct": 1.97,
+      "w1_pct": 1.99,
-      "m1_pct": -1.03
+      "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,
+      "price": 9.486,
-      "d1_pct": -1.03,
+      "d1_pct": -1.0,
-      "w1_pct": -2.39,
+      "w1_pct": -2.36,
-      "m1_pct": -1.52
+      "m1_pct": -1.49
     },
     "USDCNY": {
       "price": 6.8309,
@@ -289,16 +289,16 @@
       "m1_pct": -1.32
     },
     "USDBRL": {
-      "price": 5.0698,
+      "price": 5.0573,
-      "d1_pct": -1.57,
+      "d1_pct": -1.81,
-      "w1_pct": -1.64,
+      "w1_pct": -1.89,
-      "m1_pct": -1.79
+      "m1_pct": -2.04
     },
     "USDZAR": {
-      "price": 16.4136,
+      "price": 16.4128,
-      "d1_pct": -0.2,
+      "d1_pct": -0.21,
-      "w1_pct": -2.4,
+      "w1_pct": -2.41,
-      "m1_pct": 0.81
+      "m1_pct": 0.8
     },
     "USDINR": {
       "price": 92.438,
@@ -307,10 +307,10 @@
       "m1_pct": 0.3
     },
     "USDKRW": {
-      "price": 1472.92,
+      "price": 1474.04,
-      "d1_pct": -1.75,
+      "d1_pct": -1.67,
-      "w1_pct": -2.59,
+      "w1_pct": -2.52,
-      "m1_pct": 0.01
+      "m1_pct": 0.09
     },
     "USDTRY": {
       "price": 44.5861,
@@ -319,28 +319,28 @@
       "m1_pct": 1.13
     },
     "USDPLN": {
-      "price": 3.6257,
+      "price": 3.6279,
-      "d1_pct": -0.54,
+      "d1_pct": -0.48,
-      "w1_pct": -1.89,
+      "w1_pct": -1.83,
-      "m1_pct": -1.27
+      "m1_pct": -1.21
     },
     "USDHUF": {
-      "price": 321.68,
+      "price": 321.7,
-      "d1_pct": -0.24,
+      "d1_pct": -0.23,
-      "w1_pct": -2.52,
+      "w1_pct": -2.51,
       "m1_pct": -3.32
     },
     "USDCZK": {
-      "price": 20.7989,
+      "price": 20.812,
-      "d1_pct": -0.59,
+      "d1_pct": -0.53,
-      "w1_pct": -1.57,
+      "w1_pct": -1.51,
-      "m1_pct": -0.87
+      "m1_pct": -0.81
     },
     "USDSGD": {
-      "price": 1.2716,
+      "price": 1.2721,
-      "d1_pct": -0.33,
+      "d1_pct": -0.29,
-      "w1_pct": -0.86,
+      "w1_pct": -0.82,
-      "m1_pct": -0.11
+      "m1_pct": -0.07
     },
     "USDIDR": {
       "price": 17077.0,
@@ -349,16 +349,16 @@
       "m1_pct": 1.34
     },
     "USDTHB": {
-      "price": 31.88,
+      "price": 31.9,
-      "d1_pct": -0.59,
+      "d1_pct": -0.53,
-      "w1_pct": -2.21,
+      "w1_pct": -2.15,
-      "m1_pct": 0.98
+      "m1_pct": 1.05
     },
     "DXY": {
-      "price": 98.818,
+      "price": 98.775,
-      "d1_pct": -0.31,
+      "d1_pct": -0.36,
-      "w1_pct": -0.83,
+      "w1_pct": -0.88,
-      "m1_pct": -0.01
+      "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"
+    }
+  ]
 }

generate.py

@@ -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:
-        url = "https://finviz.com/calendar.ashx"
+        print("  bs4 not installed — skipping Finviz calendar")
-        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}")
         return []
 
-        class CalParser(HTMLParser):
+    url = "https://finviz.com/calendar.ashx"
-            def __init__(self):
+    headers = {
-                super().__init__()
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
-                self.in_table = False
+        "Accept-Language": "en-GB,en;q=0.9",
-                self.in_row = False
+    }
-                self.in_cell = False
-                self.cells = []
-                self.current_cell = ""
-                self.rows = []
-                self.table_depth = 0
-                self.target_table = False
 
-            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 = ""
-
-            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
-            beat = None
-            if actual and expected and actual != "" and expected != "":
     try:
-                    a_val = float(actual.replace("%", "").replace(",", ""))
+        r = requests.get(url, headers=headers, timeout=20)
-                    e_val = float(expected.replace("%", "").replace(",", ""))
+        r.raise_for_status()
-                    if a_val > e_val:
+        print(f"  Finviz status: {r.status_code}, html length: {len(r.text)}")
-                        beat = "beat"
+
-                    elif a_val < e_val:
+        soup = BeautifulSoup(r.text, "html.parser")
-                        beat = "miss"
+
+        # 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 []
+
+        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)
+
+            date_str = dt[:10] if dt else ""
+            time_str = dt[11:16] if len(dt) > 15 else ""
+
+            # Determine beat/miss using isHigherPositive to know direction
+            beat = None
+            if actual is not None and forecast is not None:
+                try:
+                    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"
+                        beat = "beat" if a_val < f_val else ("miss" if a_val > f_val else "inline")
-                except ValueError:
+                except (ValueError, TypeError):
                     pass
 
-            events.append({
+            imp = "red" if importance >= 3 else ("orange" if importance >= 2 else "orange")
-                "date": current_date,
+
+            rows.append({
+                "date": date_str,
                 "time": time_str,
-                "ctry": "US",
+                "ctry": "🇺🇸",
-                "ev": f"{release}" + (f" ({period})" if period else ""),
+                "ev": f"{ev_name}" + (f" ({ref})" if ref else ""),
-                "prev": prior if prior else "\u2014",
+                "prev": str(previous) if previous is not None else "—",
-                "fcast": expected if expected else "\u2014",
+                "fcast": str(forecast) if forecast is not None else "—",
-                "act": actual if actual else "\u2014",
+                "act": str(actual) if actual is not None else "—",
-                "imp": "red",
+                "imp": imp,
                 "beat": beat,
                 "source": "finviz",
             })
 
-        print(f"  Finviz: {len(events)} calendar events scraped")
+        print(f"  Finviz parsed rows: {len(rows)}")
-        return events
+        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)

requirements.txt

@@ -1,2 +1,4 @@
 yfinance>=0.2.36
 requests>=2.31.0
+beautifulsoup4>=4.12.0
+lxml>=5.0.0