Credit Spreads

What Is a Credit Spread?

When a company borrows money by issuing bonds, it has to offer a higher interest rate than the US government — because there's more risk that a company might not pay back the loan. The difference between what a company pays and what the government pays is called the credit spread.

Credit spreads are quoted in basis points because the differences are usually small. 100 bps = 1%. So when you hear "spreads blew out by 150 bps," that means they widened by 1.5 percentage points.

Think of it this way: when the economy is strong and investors feel safe, companies can borrow cheaply — spreads stay tight. When recession fears hit or companies report bad earnings, investors demand more yield to compensate for the risk — spreads widen.

Investment Grade vs High Yield

Not all companies are equally risky. Rating agencies (Moody's, S&P, Fitch) rate corporate bonds on their creditworthiness. The higher the rating, the lower the spread:

The gap between IG and HY spreads tells you something important: it's the market's assessment of how different the risk outlook is for stable vs. speculative companies. When that gap widens, it means investors are getting picky about risk — they're demanding much higher yields for shaky credits.

Why Credit Spreads Matter

Credit spreads are often called the bond market's "fear gauge" — more sensitive than stocks in some ways because bond investors tend to be institutional and sophisticated. They spot trouble early.

Two Key Signals

Historical Context

During the 2008 financial crisis, high yield spreads blew out to over 2,000 bps (20%). In normal markets they're 300–500 bps. When COVID hit in March 2020, HY spreads spiked to over 1,100 bps in days — a leading indicator that the equity market was about to crater.

The fi-config.yaml Credit Spread Settings

Here's how OpenClaw is configured to monitor and alert on credit spreads:

Copy# fi-config.yaml — credit spread section
fred:
  api_key: "your_fred_api_key_here"

credit_spreads:
  # FRED series for credit spreads
  investment_grade: "BAMLC0A0CM"    # ICE BofA US Corporate (IG) OAS
  high_yield:       "BAMLH0A0HYM2"  # ICE BofA US High Yield OAS

  alerts:
    # Alert if spreads widen by this many basis points in a single week
    ig_weekly_move:  50    # 50 bps move in IG is meaningful
    hy_weekly_move: 150    # 150 bps move in HY is meaningful

    # Alert if spreads exceed absolute levels (danger zones)
    ig_danger_level: 200   # IG above 200 bps = elevated stress
    hy_danger_level: 700   # HY above 700 bps = serious stress

alerts:
  email: "you@example.com"
  daily_digest: true

The beauty of FRED's free API is that you get professional-grade data — the same spreads that fund managers and traders watch — without paying thousands per month for Bloomberg or Refinitiv.

The Credit Spread Script

Here's the Python script that OpenClaw runs daily to fetch spreads, calculate changes, and fire alerts:

Copy# fi_credit_spreads.py — OpenClaw Credit Spread Monitor

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

# ── Load config ───────────────────────────────────────────────────
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"])
CS   = cfg["credit_spreads"]

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

# ── Fetch current spread levels ───────────────────────────────────
def fetch_spreads() -> dict:
    """
    Fetches the latest IG and HY option-adjusted spreads.
    OAS (option-adjusted spread) is the most comparable measure
    across bonds with different embedded options.
    Returns values in basis points.
    """
    spreads = {}
    for name, series_id in [
        ("Investment Grade (IG)", CS["investment_grade"]),
        ("High Yield (HY)",        CS["high_yield"]),
    ]:
        series = fred.get_series(series_id, observation_start="2020-01-01").dropna()
        current = float(series.iloc[-1])
        week_ago = float(series.iloc[-6]) if len(series) >= 6 else current
        weekly_move = round(current - week_ago, 2)

        spreads[name] = {
            "current_bps": round(current * 100, 1),   # FRED stores as %, convert to bps
            "week_ago_bps": round(week_ago * 100, 1),
            "weekly_move_bps": round(weekly_move * 100, 1),
            "series_id": series_id,
        }

        move_arrow = "▲" if weekly_move > 0 else "▼"
        print(f"   {name:<26} {current*100:>6.1f} bps  "
              f"({move_arrow}{abs(weekly_move*100):.1f} bps this week)")

    return spreads

spreads = fetch_spreads()

# ── Check alert conditions ────────────────────────────────────────
def check_spread_alerts(spreads: dict) -> list:
    """Check for meaningful moves or dangerous absolute levels."""
    alerts_cfg = CS.get("alerts", {})
    fired = []

    ig = spreads["Investment Grade (IG)"]
    hy = spreads["High Yield (HY)"]

    # Weekly move alerts
    if abs(ig["weekly_move_bps"]) >= alerts_cfg.get("ig_weekly_move", 50):
        direction = "widened" if ig["weekly_move_bps"] > 0 else "tightened"
        fired.append({
            "severity": "MEDIUM",
            "message": f"IG spreads {direction} {abs(ig['weekly_move_bps']):.0f} bps this week "
                      f"(now {ig['current_bps']:.0f} bps)"
        })

    if abs(hy["weekly_move_bps"]) >= alerts_cfg.get("hy_weekly_move", 150):
        direction = "widened" if hy["weekly_move_bps"] > 0 else "tightened"
        fired.append({
            "severity": "HIGH",
            "message": f"HY spreads {direction} {abs(hy['weekly_move_bps']):.0f} bps this week "
                      f"(now {hy['current_bps']:.0f} bps) — significant risk move"
        })

    # Absolute danger levels
    if ig["current_bps"] >= alerts_cfg.get("ig_danger_level", 200):
        fired.append({
            "severity": "HIGH",
            "message": f"IG spreads at {ig['current_bps']:.0f} bps — above elevated stress threshold"
        })

    if hy["current_bps"] >= alerts_cfg.get("hy_danger_level", 700):
        fired.append({
            "severity": "HIGH",
            "message": f"HY spreads at {hy['current_bps']:.0f} bps — above serious stress threshold"
        })

    return fired

alerts = check_spread_alerts(spreads)
if alerts:
    print(f"\n   🚨 {len(alerts)} alert(s):")
    for a in alerts:
        print(f"   [{a['severity']}] {a['message']}")
else:
    print(f"\n   ✓ No spread alerts today — markets within normal range")

Reading Spread Levels

What do different spread levels actually mean for market conditions? Here's a quick reference:

The IG and HY relationship is important: when spreads are rising together, it signals economy-wide stress (rate hikes, recession fears). When only HY widens while IG stays flat, it's usually a company-specific or sector issue.

Historical Context: Where Have Spreads Been?

To calibrate what "normal" feels like, here's a simplified view of how high yield spreads have behaved over the past 20 years:

Key takeaway: Large, fast moves in HY spreads are one of the most reliable leading indicators of equity market stress. OpenClaw tracks the week-over-week change so you catch the move early — not after it's already in the headlines.

Notice how:

• The 2008 crisis took spreads to extreme levels (2000+ bps) — but the move happened over months as liquidity dried up
• COVID in March 2020 was almost as violent in spread terms (1100 bps) but reversed faster because the Fed intervened immediately
• Post-2010, spreads spent most of the time in the 300–500 bps "normal" range
• The wider the spread, the more fear is priced in — and usually, that fear precedes equity losses

Sample Output: What a Day of Monitoring Looks Like

Copy🦞 OpenClaw Credit Spread Monitor
   2026-03-28 09:15
──────────────────────────────────────────────────
   Investment Grade (IG)     112.4 bps  (▲ 8.2 bps this week)
   High Yield (HY)           385.6 bps  (▲ 31.5 bps this week)

Context:
  IG at 112 bps — Normal range (comfortable)
  HY at 386 bps — Low end of normal range

  Both spreads widening slightly — risk-off sentiment
  is picking up, but not at alert-level movement yet.

✓ No alerts triggered today
────────────────────────────────────────────────────

This is what you'd see on a normal day. On a day with meaningful spread moves, you'd see alerts like:

Copy🚨 2 alert(s):
   [HIGH] HY spreads widened 187 bps this week (now 524 bps) — significant risk move
   [MEDIUM] IG spreads widened 62 bps this week (now 156 bps)

That would be a signal to check the news, look at equity volatility, and consider whether your portfolio is positioned defensively.

Why OpenClaw Watches This

Credit spreads are one of the most underrated early warning systems for market stress. Equity traders often miss the move until it's too late, but the bond market — where the real smart money sits — tends to see it first.

• Leading indicator: Spreads often widen days or weeks before stocks fall hard
• Objective: You can't argue with yield — spreads are data, not opinion
• Free: FRED publishes these daily, with historical data back 20+ years
• Quantifiable: You can set rules (alert on 150 bps HY weekly move) and stick to them

OpenClaw's approach is to mix this early warning system with yield curve analysis and rates momentum. Together, they paint a picture of what the bond market is really thinking — which often diverges sharply from what the financial media is saying.