Inflation Breakevens

fred:
  api_key: "your_fred_api_key_here"

breakevens:
  five_year:  "T5YIE"   # 5-Year Breakeven Inflation Rate
  ten_year:   "T10YIE"  # 10-Year Breakeven Inflation Rate
  forward:    "T5YIFR"  # 5yr/5yr Forward Inflation Expectation

  # Also compare to recent actual CPI
  cpi_series: "CPIAUCSL"  # CPI for All Urban Consumers (monthly)

  alerts:
    weekly_move: 0.15     # Alert if any breakeven moves more than 15 bps in a week
    above_fed_target: 2.75  # Alert if 10yr breakeven exceeds this (Fed target is 2%)
    below_concern: 1.75   # Alert if 10yr breakeven drops below this (deflation risk)

import yaml
from fredapi import Fred
import pandas as pd
from datetime import datetime, timedelta

def load_config(path: str = "fi-config.yaml") -> dict:
    with open(path) as f:
        return yaml.safe_load(f)

cfg  = load_config()
fred = Fred(api_key=cfg["fred"]["api_key"])
BE   = cfg["breakevens"]

print(f"🦞 OpenClaw Inflation Breakeven Monitor")
print(f"   {datetime.now().strftime('%Y-%m-%d %H:%M')}")
print("─" * 50)

# ── Fetch breakeven series ────────────────────────────────────────
def fetch_breakevens() -> dict:
    """
    Fetches the three breakeven series from FRED.
    All three are daily and highly liquid market-based measures.
    """
    series_map = {
        "5yr Breakeven":     BE["five_year"],
        "10yr Breakeven":    BE["ten_year"],
        "5yr/5yr Forward":   BE["forward"],
    }

    results = {}
    for label, series_id in series_map.items():
        series = fred.get_series(series_id, observation_start="2022-01-01").dropna()
        current   = float(series.iloc[-1])
        week_ago  = float(series.iloc[-6]) if len(series) >= 6 else current
        month_ago = float(series.iloc[-22]) if len(series) >= 22 else current

        results[label] = {
            "current":    round(current, 3),
            "week_ago":   round(week_ago, 3),
            "month_ago":  round(month_ago, 3),
            "weekly_chg": round(current - week_ago, 3),
            "monthly_chg":round(current - month_ago, 3),
        }

    return results

data = fetch_breakevens()

# ── Print snapshot ────────────────────────────────────────────────
print(f"\n  {'Breakeven':<22} {'Current':>8} {'Wk Chg':>9} {'Mo Chg':>9}")
print("  " + "─" * 52)
for label, d in data.items():
    wk_arrow = "▲" if d["weekly_chg"] > 0 else "▼"
    mo_arrow = "▲" if d["monthly_chg"] > 0 else "▼"
    print(f"  {label:<22} {d['current']:>7.3f}%"
          f"  {wk_arrow}{abs(d['weekly_chg']):.3f}%"
          f"  {mo_arrow}{abs(d['monthly_chg']):.3f}%")

# ── Fetch latest CPI for comparison ──────────────────────────────
def get_latest_cpi_yoy() -> float | None:
    """
    Fetches CPI and calculates year-over-year change.
    CPI updates monthly — we use the most recent available.
    """
    try:
        cpi = fred.get_series(BE["cpi_series"], observation_start="2022-01-01").dropna()
        if len(cpi) < 13:
            return None
        yoy = (cpi.iloc[-1] - cpi.iloc[-13]) / cpi.iloc[-13] * 100
        return round(float(yoy), 2)
    except Exception:
        return None

cpi_yoy = get_latest_cpi_yoy()
ten_yr_be = data["10yr Breakeven"]["current"]

print(f"\n  Market vs Actual Inflation:")
if cpi_yoy:
    gap = ten_yr_be - cpi_yoy
    print(f"  Latest CPI (YoY):    {cpi_yoy:.2f}%")
    print(f"  10yr Breakeven:      {ten_yr_be:.3f}%")
    print(f"  Gap:                 {gap:+.3f}%  ", end="")
    if gap > 0.5:
        print("(Market expects inflation to rise from here)")
    elif gap < -0.5:
        print("(Market expects inflation to fall from here)")
    else:
        print("(Market broadly in line with current inflation)")

# ── Check alerts ──────────────────────────────────────────────────
def check_breakeven_alerts(data: dict) -> list:
    alerts_cfg = BE.get("alerts", {})
    fired = []
    move_threshold = alerts_cfg.get("weekly_move", 0.15)

    for label, d in data.items():
        if abs(d["weekly_chg"]) >= move_threshold:
            direction = "rose" if d["weekly_chg"] > 0 else "fell"
            fired.append(f"{label} {direction} {abs(d['weekly_chg']):.3f}% this week → {d['current']:.3f}%")

    ten_yr = data["10yr Breakeven"]["current"]
    if ten_yr > alerts_cfg.get("above_fed_target", 2.75):
        fired.append(f"10yr breakeven {ten_yr:.3f}% above Fed's 2% target + 0.75% buffer — elevated inflation expectations")
    if ten_yr < alerts_cfg.get("below_concern", 1.75):
        fired.append(f"10yr breakeven {ten_yr:.3f}% — below 1.75%, deflation concerns building")

    return fired

alerts = check_breakeven_alerts(data)
if alerts:
    print(f"\n  🚨 {len(alerts)} alert(s):")
    for a in alerts: print(f"  • {a}")
else:
    print(f"\n  ✓ Breakevens within normal range — no alerts today")

🦞 OpenClaw Inflation Breakeven Monitor
   2025-03-27 14:32
─────────────────────────────────────────────────

  Breakeven               Current   Wk Chg   Mo Chg
  ────────────────────────────────────────────────
  5yr Breakeven           2.418%   ▲0.031%  ▼0.082%
  10yr Breakeven          2.313%   ▲0.027%  ▼0.094%
  5yr/5yr Forward         2.218%   ▲0.019%  ▼0.107%

  Market vs Actual Inflation:
  Latest CPI (YoY):    2.80%
  10yr Breakeven:      2.313%
  Gap:                 -0.487%  (Market expects inflation to fall from here)

  ✓ Breakevens within normal range — no alerts today