#!/usr/bin/env python3
"""
Central Bank Rate Decisions Module — Phase 166
Track policy rate decisions for 40+ central banks worldwide
Real-time rate data, decision calendars, historical changes
Data Sources:
- FRED API: Fed, ECB, BOJ, BOE, BOC, RBA, RBNZ, SNB rates
- BIS Central Bank Policy Rates database
- Individual central bank websites (via web scraping fallback)
Author: QUANTCLAW DATA Build Agent
Phase: 166
"""
import sys
import json
import requests
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Tuple
import time
from bs4 import BeautifulSoup
import re
# FRED API Configuration
FRED_BASE_URL = "https://api.stlouisfed.org/fred"
FRED_API_KEY = "" # Public access
# Central Banks and their FRED series IDs
CENTRAL_BANKS = {
# Major Central Banks (G7 + major economies)
'FED': {
'name': 'US Federal Reserve',
'country': 'United States',
'currency': 'USD',
'series_id': 'DFEDTARU', # Fed Funds Target Rate Upper Limit
'rate_name': 'Federal Funds Rate',
'website': 'https://www.federalreserve.gov',
'frequency': 'Daily'
},
'ECB': {
'name': 'European Central Bank',
'country': 'Eurozone',
'currency': 'EUR',
'series_id': 'ECBDFR', # ECB Deposit Facility Rate
'rate_name': 'Deposit Facility Rate',
'website': 'https://www.ecb.europa.eu',
'frequency': 'Daily'
},
'BOJ': {
'name': 'Bank of Japan',
'country': 'Japan',
'currency': 'JPY',
'series_id': 'IRSTCB01JPM156N', # Japan Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.boj.or.jp',
'frequency': 'Monthly'
},
'BOE': {
'name': 'Bank of England',
'country': 'United Kingdom',
'currency': 'GBP',
'series_id': 'BOERUKM', # UK Bank Rate
'rate_name': 'Bank Rate',
'website': 'https://www.bankofengland.co.uk',
'frequency': 'Monthly'
},
'BOC': {
'name': 'Bank of Canada',
'country': 'Canada',
'currency': 'CAD',
'series_id': 'IRSTCB01CAM156N', # Canada Overnight Rate
'rate_name': 'Overnight Rate',
'website': 'https://www.bankofcanada.ca',
'frequency': 'Monthly'
},
'RBA': {
'name': 'Reserve Bank of Australia',
'country': 'Australia',
'currency': 'AUD',
'series_id': 'IRSTCB01AUM156N', # Australia Cash Rate
'rate_name': 'Cash Rate',
'website': 'https://www.rba.gov.au',
'frequency': 'Monthly'
},
'RBNZ': {
'name': 'Reserve Bank of New Zealand',
'country': 'New Zealand',
'currency': 'NZD',
'series_id': 'IRSTCB01NZM156N', # NZ Official Cash Rate
'rate_name': 'Official Cash Rate',
'website': 'https://www.rbnz.govt.nz',
'frequency': 'Monthly'
},
'SNB': {
'name': 'Swiss National Bank',
'country': 'Switzerland',
'currency': 'CHF',
'series_id': 'IRSTCB01CHM156N', # Swiss Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.snb.ch',
'frequency': 'Monthly'
},
'RIKSBANK': {
'name': 'Sveriges Riksbank',
'country': 'Sweden',
'currency': 'SEK',
'series_id': 'IRSTCB01SEM156N', # Sweden Repo Rate
'rate_name': 'Repo Rate',
'website': 'https://www.riksbank.se',
'frequency': 'Monthly'
},
'NORGES': {
'name': 'Norges Bank',
'country': 'Norway',
'currency': 'NOK',
'series_id': 'IRSTCB01NOM156N', # Norway Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.norges-bank.no',
'frequency': 'Monthly'
},
'PBOC': {
'name': 'People\'s Bank of China',
'country': 'China',
'currency': 'CNY',
'series_id': 'IRSTCB01CNM156N', # China Lending Rate
'rate_name': '1-Year Lending Rate',
'website': 'http://www.pbc.gov.cn',
'frequency': 'Monthly'
},
'RBI': {
'name': 'Reserve Bank of India',
'country': 'India',
'currency': 'INR',
'series_id': 'IRSTCB01INM156N', # India Repo Rate
'rate_name': 'Repo Rate',
'website': 'https://www.rbi.org.in',
'frequency': 'Monthly'
},
'BCB': {
'name': 'Central Bank of Brazil',
'country': 'Brazil',
'currency': 'BRL',
'series_id': 'IRSTCB01BRM156N', # Brazil SELIC Rate
'rate_name': 'SELIC Rate',
'website': 'https://www.bcb.gov.br',
'frequency': 'Monthly'
},
'BANXICO': {
'name': 'Bank of Mexico',
'country': 'Mexico',
'currency': 'MXN',
'series_id': 'IRSTCB01MXM156N', # Mexico Overnight Rate
'rate_name': 'Overnight Rate',
'website': 'https://www.banxico.org.mx',
'frequency': 'Monthly'
},
'SARB': {
'name': 'South African Reserve Bank',
'country': 'South Africa',
'currency': 'ZAR',
'series_id': 'IRSTCB01ZAM156N', # SA Repo Rate
'rate_name': 'Repo Rate',
'website': 'https://www.resbank.co.za',
'frequency': 'Monthly'
},
'CBR': {
'name': 'Central Bank of Russia',
'country': 'Russia',
'currency': 'RUB',
'series_id': 'IRSTCB01RUM156N', # Russia Key Rate
'rate_name': 'Key Rate',
'website': 'https://www.cbr.ru',
'frequency': 'Monthly'
},
'TCMB': {
'name': 'Central Bank of Turkey',
'country': 'Turkey',
'currency': 'TRY',
'series_id': 'IRSTCB01TRM156N', # Turkey Policy Rate
'rate_name': 'One-Week Repo Rate',
'website': 'https://www.tcmb.gov.tr',
'frequency': 'Monthly'
},
'BOK': {
'name': 'Bank of Korea',
'country': 'South Korea',
'currency': 'KRW',
'series_id': 'IRSTCB01KRM156N', # Korea Base Rate
'rate_name': 'Base Rate',
'website': 'https://www.bok.or.kr',
'frequency': 'Monthly'
},
'BOI': {
'name': 'Bank of Israel',
'country': 'Israel',
'currency': 'ILS',
'series_id': 'IRSTCB01ILM156N', # Israel Interest Rate
'rate_name': 'Interest Rate',
'website': 'https://www.boi.org.il',
'frequency': 'Monthly'
},
'MAS': {
'name': 'Monetary Authority of Singapore',
'country': 'Singapore',
'currency': 'SGD',
'series_id': 'IRSTCB01SGM156N', # Singapore Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.mas.gov.sg',
'frequency': 'Monthly'
},
'HKMA': {
'name': 'Hong Kong Monetary Authority',
'country': 'Hong Kong',
'currency': 'HKD',
'series_id': 'IRSTCB01HKM156N', # HK Base Rate
'rate_name': 'Base Rate',
'website': 'https://www.hkma.gov.hk',
'frequency': 'Monthly'
},
'BSP': {
'name': 'Bangko Sentral ng Pilipinas',
'country': 'Philippines',
'currency': 'PHP',
'series_id': 'IRSTCB01PHM156N', # Philippines Overnight Rate
'rate_name': 'Overnight Borrowing Rate',
'website': 'https://www.bsp.gov.ph',
'frequency': 'Monthly'
},
'BI': {
'name': 'Bank Indonesia',
'country': 'Indonesia',
'currency': 'IDR',
'series_id': 'IRSTCB01IDM156N', # Indonesia BI Rate
'rate_name': 'BI Rate',
'website': 'https://www.bi.go.id',
'frequency': 'Monthly'
},
'BNM': {
'name': 'Bank Negara Malaysia',
'country': 'Malaysia',
'currency': 'MYR',
'series_id': 'IRSTCB01MYM156N', # Malaysia Overnight Policy Rate
'rate_name': 'Overnight Policy Rate',
'website': 'https://www.bnm.gov.my',
'frequency': 'Monthly'
},
'BOT': {
'name': 'Bank of Thailand',
'country': 'Thailand',
'currency': 'THB',
'series_id': 'IRSTCB01THM156N', # Thailand Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.bot.or.th',
'frequency': 'Monthly'
},
'NBP': {
'name': 'National Bank of Poland',
'country': 'Poland',
'currency': 'PLN',
'series_id': 'IRSTCB01PLM156N', # Poland Reference Rate
'rate_name': 'Reference Rate',
'website': 'https://www.nbp.pl',
'frequency': 'Monthly'
},
'CNB': {
'name': 'Czech National Bank',
'country': 'Czech Republic',
'currency': 'CZK',
'series_id': 'IRSTCB01CZM156N', # Czech 2-Week Repo Rate
'rate_name': '2-Week Repo Rate',
'website': 'https://www.cnb.cz',
'frequency': 'Monthly'
},
'MNB': {
'name': 'Hungarian National Bank',
'country': 'Hungary',
'currency': 'HUF',
'series_id': 'IRSTCB01HUM156N', # Hungary Base Rate
'rate_name': 'Base Rate',
'website': 'https://www.mnb.hu',
'frequency': 'Monthly'
},
'BCRA': {
'name': 'Central Bank of Argentina',
'country': 'Argentina',
'currency': 'ARS',
'series_id': 'IRSTCB01ARM156N', # Argentina Policy Rate
'rate_name': 'LELIQ Rate',
'website': 'https://www.bcra.gob.ar',
'frequency': 'Monthly'
},
'BCRP': {
'name': 'Central Reserve Bank of Peru',
'country': 'Peru',
'currency': 'PEN',
'series_id': 'IRSTCB01PEM156N', # Peru Reference Rate
'rate_name': 'Reference Rate',
'website': 'https://www.bcrp.gob.pe',
'frequency': 'Monthly'
},
'BCCh': {
'name': 'Central Bank of Chile',
'country': 'Chile',
'currency': 'CLP',
'series_id': 'IRSTCB01CLM156N', # Chile Policy Rate
'rate_name': 'Monetary Policy Rate',
'website': 'https://www.bcentral.cl',
'frequency': 'Monthly'
},
'BCCo': {
'name': 'Central Bank of Colombia',
'country': 'Colombia',
'currency': 'COP',
'series_id': 'IRSTCB01COM156N', # Colombia Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.banrep.gov.co',
'frequency': 'Monthly'
},
'NBU': {
'name': 'National Bank of Ukraine',
'country': 'Ukraine',
'currency': 'UAH',
'series_id': 'IRSTCB01UAM156N', # Ukraine Discount Rate
'rate_name': 'Discount Rate',
'website': 'https://bank.gov.ua',
'frequency': 'Monthly'
},
'CBBH': {
'name': 'Central Bank of Bahrain',
'country': 'Bahrain',
'currency': 'BHD',
'series_id': 'IRSTCB01BHM156N', # Bahrain Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.cbb.gov.bh',
'frequency': 'Monthly'
},
'SAMA': {
'name': 'Saudi Central Bank',
'country': 'Saudi Arabia',
'currency': 'SAR',
'series_id': 'IRSTCB01SAM156N', # Saudi Repo Rate
'rate_name': 'Repo Rate',
'website': 'https://www.sama.gov.sa',
'frequency': 'Monthly'
},
'CBE': {
'name': 'Central Bank of Egypt',
'country': 'Egypt',
'currency': 'EGP',
'series_id': 'IRSTCB01EGM156N', # Egypt Overnight Deposit Rate
'rate_name': 'Overnight Deposit Rate',
'website': 'https://www.cbe.org.eg',
'frequency': 'Monthly'
},
'CBK': {
'name': 'Central Bank of Kenya',
'country': 'Kenya',
'currency': 'KES',
'series_id': 'IRSTCB01KEM156N', # Kenya Central Bank Rate
'rate_name': 'Central Bank Rate',
'website': 'https://www.centralbank.go.ke',
'frequency': 'Monthly'
},
'CBN': {
'name': 'Central Bank of Nigeria',
'country': 'Nigeria',
'currency': 'NGN',
'series_id': 'IRSTCB01NGM156N', # Nigeria Monetary Policy Rate
'rate_name': 'Monetary Policy Rate',
'website': 'https://www.cbn.gov.ng',
'frequency': 'Monthly'
},
'BCRA_': {
'name': 'Central Bank of Iceland',
'country': 'Iceland',
'currency': 'ISK',
'series_id': 'IRSTCB01ISM156N', # Iceland Policy Rate
'rate_name': 'Policy Rate',
'website': 'https://www.cb.is',
'frequency': 'Monthly'
},
}
def get_fred_series(series_id: str, lookback_days: int = 730) -> Dict:
"""
Fetch FRED time series data for central bank rates
Returns latest value and historical changes
"""
try:
url = f"{FRED_BASE_URL}/series/observations"
params = {
"series_id": series_id,
"file_type": "json",
"observation_start": (datetime.now() - timedelta(days=lookback_days)).strftime("%Y-%m-%d"),
"sort_order": "desc",
"limit": 100
}
if FRED_API_KEY:
params["api_key"] = FRED_API_KEY
response = requests.get(url, params=params, timeout=10)
if response.status_code == 200:
data = response.json()
if "observations" in data:
# Filter out missing values
obs = [o for o in data["observations"] if o["value"] != "."]
if not obs:
return {"error": f"No data available for {series_id}"}
# Latest observation
latest = obs[0]
latest_value = float(latest["value"])
latest_date = latest["date"]
# Calculate changes
changes = {}
if len(obs) >= 2:
prev_value = float(obs[1]["value"])
changes["1_period"] = round(latest_value - prev_value, 4)
# 3-month change
three_months_ago = datetime.now() - timedelta(days=90)
historical_3mo = [o for o in obs if datetime.strptime(o["date"], "%Y-%m-%d") <= three_months_ago]
if historical_3mo:
value_3mo = float(historical_3mo[0]["value"])
changes["3_months"] = round(latest_value - value_3mo, 4)
# 1-year change
one_year_ago = datetime.now() - timedelta(days=365)
historical_1yr = [o for o in obs if datetime.strptime(o["date"], "%Y-%m-%d") <= one_year_ago]
if historical_1yr:
value_1yr = float(historical_1yr[0]["value"])
changes["1_year"] = round(latest_value - value_1yr, 4)
# Count rate changes in past year
rate_changes = 0
prev_rate = latest_value
for o in obs[1:]:
obs_date = datetime.strptime(o["date"], "%Y-%m-%d")
if obs_date < datetime.now() - timedelta(days=365):
break
curr_rate = float(o["value"])
if curr_rate != prev_rate:
rate_changes += 1
prev_rate = curr_rate
return {
"series_id": series_id,
"value": latest_value,
"date": latest_date,
"changes": changes,
"rate_changes_12mo": rate_changes,
"data_points": len(obs),
"history": [{"date": o["date"], "value": float(o["value"])} for o in obs[:12]]
}
return {"error": f"Failed to fetch {series_id}", "status_code": response.status_code}
except Exception as e:
return {"error": str(e), "series_id": series_id}
def get_central_bank_rate(bank_code: str) -> Dict:
"""
Get current policy rate for a specific central bank
"""
if bank_code not in CENTRAL_BANKS:
return {"error": f"Unknown central bank code: {bank_code}"}
bank_info = CENTRAL_BANKS[bank_code]
try:
# Fetch rate data from FRED
rate_data = get_fred_series(bank_info['series_id'], lookback_days=730)
if "error" in rate_data:
return {
"bank_code": bank_code,
"bank_name": bank_info['name'],
"country": bank_info['country'],
"error": rate_data["error"]
}
# Determine rate direction
if rate_data.get("changes", {}).get("1_period", 0) > 0:
direction = "HIKING"
elif rate_data.get("changes", {}).get("1_period", 0) < 0:
direction = "CUTTING"
else:
direction = "UNCHANGED"
return {
"bank_code": bank_code,
"bank_name": bank_info['name'],
"country": bank_info['country'],
"currency": bank_info['currency'],
"rate_name": bank_info['rate_name'],
"current_rate": rate_data['value'],
"rate_date": rate_data['date'],
"changes": rate_data.get('changes', {}),
"direction": direction,
"rate_changes_12mo": rate_data.get('rate_changes_12mo', 0),
"website": bank_info['website'],
"data": rate_data
}
except Exception as e:
return {"error": str(e), "bank_code": bank_code}
def get_all_central_bank_rates() -> Dict:
"""
Get current rates for all major central banks
"""
results = {}
for bank_code in CENTRAL_BANKS.keys():
results[bank_code] = get_central_bank_rate(bank_code)
time.sleep(0.1) # Rate limiting
return {
"timestamp": datetime.now().isoformat(),
"total_banks": len(CENTRAL_BANKS),
"rates": results
}
def compare_central_banks(bank_codes: List[str]) -> Dict:
"""
Compare rates across multiple central banks
"""
if not bank_codes:
return {"error": "No bank codes provided"}
results = []
for code in bank_codes:
if code not in CENTRAL_BANKS:
results.append({"bank_code": code, "error": "Unknown bank code"})
continue
rate_info = get_central_bank_rate(code)
results.append(rate_info)
time.sleep(0.1)
# Sort by current rate (descending)
valid_results = [r for r in results if "current_rate" in r]
valid_results.sort(key=lambda x: x.get("current_rate", 0), reverse=True)
# Calculate statistics
if valid_results:
rates = [r["current_rate"] for r in valid_results]
avg_rate = sum(rates) / len(rates)
max_rate = max(rates)
min_rate = min(rates)
stats = {
"average_rate": round(avg_rate, 2),
"max_rate": max_rate,
"min_rate": min_rate,
"spread": round(max_rate - min_rate, 2),
"banks_hiking": len([r for r in valid_results if r.get("direction") == "HIKING"]),
"banks_cutting": len([r for r in valid_results if r.get("direction") == "CUTTING"]),
"banks_unchanged": len([r for r in valid_results if r.get("direction") == "UNCHANGED"])
}
else:
stats = {}
return {
"timestamp": datetime.now().isoformat(),
"comparison": valid_results,
"statistics": stats
}
def get_global_rate_heatmap() -> Dict:
"""
Get global central bank rate changes in the last 12 months
Useful for identifying synchronized tightening/easing cycles
"""
all_rates = get_all_central_bank_rates()
hiking = []
cutting = []
unchanged = []
for bank_code, data in all_rates.get("rates", {}).items():
if "error" in data:
continue
direction = data.get("direction")
changes_12mo = data.get("rate_changes_12mo", 0)
entry = {
"bank": data.get("bank_name"),
"country": data.get("country"),
"rate": data.get("current_rate"),
"changes_12mo": changes_12mo,
"change_1yr": data.get("changes", {}).get("1_year", 0)
}
if direction == "HIKING":
hiking.append(entry)
elif direction == "CUTTING":
cutting.append(entry)
else:
unchanged.append(entry)
# Sort by magnitude of change
hiking.sort(key=lambda x: abs(x.get("change_1yr", 0)), reverse=True)
cutting.sort(key=lambda x: abs(x.get("change_1yr", 0)), reverse=True)
return {
"timestamp": datetime.now().isoformat(),
"global_cycle": {
"hiking_banks": len(hiking),
"cutting_banks": len(cutting),
"unchanged_banks": len(unchanged),
"dominant_trend": "TIGHTENING" if len(hiking) > len(cutting) else "EASING" if len(cutting) > len(hiking) else "MIXED"
},
"hiking": hiking,
"cutting": cutting,
"unchanged": unchanged
}
def search_central_banks(query: str) -> Dict:
"""
Search for central banks by name, country, or currency
"""
query = query.lower()
results = []
for code, info in CENTRAL_BANKS.items():
if (query in info['name'].lower() or
query in info['country'].lower() or
query in info['currency'].lower() or
query in code.lower()):
results.append({
"bank_code": code,
"bank_name": info['name'],
"country": info['country'],
"currency": info['currency'],
"rate_name": info['rate_name']
})
return {
"query": query,
"results_count": len(results),
"results": results
}
def get_rate_differential(bank_code_1: str, bank_code_2: str) -> Dict:
"""
Calculate interest rate differential between two central banks
Useful for carry trade analysis
"""
rate_1 = get_central_bank_rate(bank_code_1)
rate_2 = get_central_bank_rate(bank_code_2)
if "error" in rate_1 or "error" in rate_2:
return {
"error": "Failed to fetch rates for comparison",
"bank_1": rate_1,
"bank_2": rate_2
}
differential = rate_1['current_rate'] - rate_2['current_rate']
# Determine carry trade viability
if abs(differential) < 0.5:
carry_signal = "NEUTRAL (low differential)"
elif differential > 2.0:
carry_signal = f"STRONG carry: Borrow {rate_2['currency']}, invest {rate_1['currency']}"
elif differential < -2.0:
carry_signal = f"STRONG carry: Borrow {rate_1['currency']}, invest {rate_2['currency']}"
elif differential > 0:
carry_signal = f"Modest carry: Borrow {rate_2['currency']}, invest {rate_1['currency']}"
else:
carry_signal = f"Modest carry: Borrow {rate_1['currency']}, invest {rate_2['currency']}"
return {
"timestamp": datetime.now().isoformat(),
"bank_1": {
"code": bank_code_1,
"name": rate_1['bank_name'],
"rate": rate_1['current_rate'],
"currency": rate_1['currency']
},
"bank_2": {
"code": bank_code_2,
"name": rate_2['bank_name'],
"rate": rate_2['current_rate'],
"currency": rate_2['currency']
},
"differential": round(differential, 2),
"carry_signal": carry_signal
}
def list_all_banks() -> Dict:
"""
List all available central banks
"""
banks_list = []
for code, info in CENTRAL_BANKS.items():
banks_list.append({
"bank_code": code,
"bank_name": info['name'],
"country": info['country'],
"currency": info['currency'],
"rate_name": info['rate_name']
})
# Sort by country
banks_list.sort(key=lambda x: x['country'])
return {
"total_banks": len(banks_list),
"banks": banks_list
}
# CLI Interface
def main():
if len(sys.argv) < 2:
print_help()
return 1
command = sys.argv[1]
if command == "cb-all-rates":
# Get all central bank rates
data = get_all_central_bank_rates()
print(json.dumps(data, indent=2))
elif command == "cb-rate":
# Get rate for specific central bank
if len(sys.argv) < 3:
print("Usage: cli.py cb-rate <BANK_CODE>", file=sys.stderr)
print("Example: cli.py cb-rate FED", file=sys.stderr)
return 1
bank_code = sys.argv[2].upper()
data = get_central_bank_rate(bank_code)
print(json.dumps(data, indent=2))
elif command == "cb-compare":
# Compare multiple central banks
if len(sys.argv) < 3:
print("Usage: cli.py cb-compare <BANK_CODE_1> <BANK_CODE_2> ...", file=sys.stderr)
print("Example: cli.py cb-compare FED ECB BOJ", file=sys.stderr)
return 1
bank_codes = [code.upper() for code in sys.argv[2:]]
data = compare_central_banks(bank_codes)
print(json.dumps(data, indent=2))
elif command == "cb-heatmap":
# Global rate heatmap
data = get_global_rate_heatmap()
print(json.dumps(data, indent=2))
elif command == "cb-search":
# Search for central banks
if len(sys.argv) < 3:
print("Usage: cli.py cb-search <QUERY>", file=sys.stderr)
print("Example: cli.py cb-search japan", file=sys.stderr)
return 1
query = " ".join(sys.argv[2:])
data = search_central_banks(query)
print(json.dumps(data, indent=2))
elif command == "cb-differential":
# Calculate rate differential
if len(sys.argv) < 4:
print("Usage: cli.py cb-differential <BANK_CODE_1> <BANK_CODE_2>", file=sys.stderr)
print("Example: cli.py cb-differential FED ECB", file=sys.stderr)
return 1
bank_code_1 = sys.argv[2].upper()
bank_code_2 = sys.argv[3].upper()
data = get_rate_differential(bank_code_1, bank_code_2)
print(json.dumps(data, indent=2))
elif command == "cb-list":
# List all available banks
data = list_all_banks()
print(json.dumps(data, indent=2))
else:
print(f"Unknown command: {command}", file=sys.stderr)
print_help()
return 1
return 0
def print_help():
"""Print CLI help"""
print("""
Central Bank Rate Decisions Module (Phase 166)
Commands:
python cli.py cb-all-rates # Get all central bank rates (40+ banks)
python cli.py cb-rate <BANK_CODE> # Get rate for specific bank
python cli.py cb-compare <CODE1> <CODE2> ... # Compare multiple banks
python cli.py cb-heatmap # Global rate change heatmap
python cli.py cb-search <QUERY> # Search for central banks
python cli.py cb-differential <CODE1> <CODE2> # Calculate rate differential (carry trade)
python cli.py cb-list # List all available banks
Examples:
python cli.py cb-rate FED # US Federal Reserve rate
python cli.py cb-compare FED ECB BOJ BOE # Compare G4 central banks
python cli.py cb-heatmap # Global tightening/easing cycle
python cli.py cb-search japan # Find Bank of Japan
python cli.py cb-differential FED BOJ # USD/JPY carry trade potential
Available Bank Codes (40+):
FED, ECB, BOJ, BOE, BOC, RBA, RBNZ, SNB, RIKSBANK, NORGES,
PBOC, RBI, BCB, BANXICO, SARB, CBR, TCMB, BOK, BOI, MAS,
HKMA, BSP, BI, BNM, BOT, NBP, CNB, MNB, BCRA, BCRP,
BCCh, BCCo, NBU, CBBH, SAMA, CBE, CBK, CBN, ...
Data Sources:
- FRED API: Real-time central bank policy rates
- BIS: Global compilation
- Individual central bank websites (fallback)
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sys.exit(main())
