economic-indicator-tracker
Track leading, lagging, and coincident economic indicators systematically. Use for "economic indicators", "leading indicator", "lagging indicator", "PMI tracker", "GDP tracker", "jobs data", "inflation tracker", "economic cycle", "recession indicator", "expansion indicator", "economic health", or any systematic macro indicator tracking. Works with macro-economic-dashboard.
Quellinformationen
- Repository
- mahmoud20138/Tradecraft
- Letzte Quellaktivität
- 23. April 2026 um 08:40
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 15
- Forks
- 4
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
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Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- economic-indicator-tracker
- description
- Track leading, lagging, and coincident economic indicators systematically. Use for "economic indicators", "leading indicator", "lagging indicator", "PMI tracker", "GDP tracker", "jobs data", "inflation tracker", "economic cycle", "recession indicator", "expansion indicator", "economic health", or any systematic macro indicator tracking. Works with macro-economic-dashboard.
- kind
- tool
- category
- trading/data
- status
- active
- tags
- ["economic","indicator","market-context","tracker","trading"]
- related_skills
- ["economic-calendar","market-data-ingestion","alternative-data-integrator","macro-economic-dashboard","market-intelligence"]
# Economic Indicator Tracker
```python
INDICATORS = {
"leading": [
{"name": "PMI Manufacturing", "frequency": "monthly", "impact": "HIGH", "pairs": ["USD", "EUR", "GBP"]},
{"name": "Building Permits", "frequency": "monthly", "impact": "MEDIUM", "pairs": ["USD"]},
{"name": "Consumer Confidence", "frequency": "monthly", "impact": "MEDIUM", "pairs": ["USD", "EUR"]},
{"name": "Yield Curve 2-10", "frequency": "daily", "impact": "HIGH", "pairs": ["USD"]},
{"name": "New Orders Index", "frequency": "monthly", "impact": "MEDIUM", "pairs": ["USD"]},
{"name": "Stock Market (SPX)", "frequency": "daily", "impact": "HIGH", "pairs": ["ALL"]},
{"name": "Initial Jobless Claims", "frequency": "weekly", "impact": "MEDIUM", "pairs": ["USD"]}],
"coincident": [
{"name": "Non-Farm Payrolls", "frequency": "monthly", "impact": "HIGH", "pairs": ["USD"]},
{"name": "Industrial Production", "frequency": "monthly", "impact": "MEDIUM", "pairs": ["USD", "EUR"]},
{"name": "Retail Sales", "frequency": "monthly", "impact": "HIGH", "pairs": ["USD", "GBP"]},
{"name": "GDP", "frequency": "quarterly", "impact": "HIGH", "pairs": ["ALL"]}],
"lagging": [
{"name": "CPI / Inflation", "frequency": "monthly", "impact": "HIGH", "pairs": ["ALL"]},
{"name": "Unemployment Rate", "frequency": "monthly", "impact": "HIGH", "pairs": ["USD"]},
{"name": "Core PCE", "frequency": "monthly", "impact": "HIGH", "pairs": ["USD"]},
{"name": "Average Hourly Earnings", "frequency": "monthly", "impact": "MEDIUM", "pairs": ["USD"]}],
}
class EconomicIndicatorTracker:
@staticmethod
def cycle_position(leading_trend: str, coincident_trend: str, lagging_trend: str) -> dict:
if leading_trend == "improving" and coincident_trend == "improving":
phase = "EXPANSION — risk-on currencies favored (AUD, NZD, CAD)"
elif leading_trend == "deteriorating" and coincident_trend == "improving":
phase = "LATE CYCLE — be cautious, peak may be near"
elif leading_trend == "deteriorating" and coincident_trend == "deteriorating":
phase = "CONTRACTION — safe havens favored (JPY, CHF, USD, Gold)"
elif leading_trend == "improving" and coincident_trend == "deteriorating":
phase = "EARLY RECOVERY — selective risk-on, high-beta currencies"
else:
phase = "TRANSITION — mixed signals"
return {"phase": phase, "leading": leading_trend, "coincident": coincident_trend, "lagging": lagging_trend}
@staticmethod
def surprise_index(actual: float, forecast: float, previous: float) -> dict:
surprise = actual - forecast
beat = actual > forecast
return {
"surprise": round(surprise, 3),
"beat_expectations": beat,
"vs_previous": "improving" if actual > previous else "deteriorating",
"market_impact": "Positive surprise — currency should strengthen" if beat else "Negative surprise — currency weakens",
}
```
Auf GitHub ansehen