Canada monetary policy signals (policy stance, curve slope, funding stress)
Daily-to-monthly monetary-policy signals derived from Bank of Canada Valet data: 30-period annualized change volatility, 3-month momentum, year-over-year change, 3-sigma anomaly flags, naive-drift 1-month forecasts, a per-date cross-series volatility rank, plus the real policy stance (target rate minus YoY CPI inflation), the CORRA-target funding-stress spread, the 10Y-2Y Canadian curve-slope spread and a policy-move streak tracker (consecutive hikes/cuts). Covers the BoC target for the overnight rate, the overnight rate, CORRA, 2Y/10Y benchmark bond yields and total/trim/median/common CPI inflation. All rows are normalized to country_code CAN so they join cleanly with Canadian macro data. Raw data: Bank of Canada (Valet API).
Quality
Attribution
Bank of Canada (Valet API; derived signals by Frontier Data Hub)
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Observation date (Valet field d; YYYY-MM-DD). |
| country | string | |
| country_code | string | |
| series_id | string | Valet series name, e.g. STATIC_ATABLE_V39079 (target for the overnight rate), AVG.INTWO (CORRA), BD.CDN.10YR.DQ.YLD (10-year benchmark bond yield); resolves in the Valet API at https://www.bankofcanada.ca/valet/. |
| series_label | string | Official Bank of Canada series label from the Valet seriesDetail metadata. |
| value | float | Observation value as published by the Bank of Canada for this series (policy rates and bond yields in percent; CORRA in percent; CPI measures as index or year-over-year percent change); see the Bank of Canada's notes for methodology. |
| volatility_30d | float | |
| momentum_3m | float | |
| yoy_change_pct | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| real_target_rate | float | |
| corra_target_spread | float | |
| curve_spread_ca | float | |
| policy_streak | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | volatility_30d | momentum_3m | yoy_change_pct | anomaly_flag | forecast_1m | rank | real_target_rate | corra_target_spread | curve_spread_ca | policy_streak |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1995-01-01 | Canada | CAN | CPI_COMMON | CPI-common | 1.1 | — | — | — | 0 | — | — | — | — | — | 0 |
| 1995-01-01 | Canada | CAN | CPI_MEDIAN | CPI-median | 1.7 | — | — | — | 0 | — | — | — | — | — | 0 |
| 1995-01-01 | Canada | CAN | CPI_TRIM | CPI-trim | 1.8 | — | — | — | 0 | — | — | — | — | — | 0 |
| 1995-01-01 | Canada | CAN | STATIC_TOTALCPICHANGE | Total CPI, percentage change year-over-year (unadjusted) | 0.6 | — | — | — | 0 | — | — | — | — | — | 0 |
| 1995-02-01 | Canada | CAN | CPI_COMMON | CPI-common | 1.2 | — | — | — | 0 | — | — | — | — | — | 0 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/boc_signals/canada_monetary_policy_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/boc_signals/canada_monetary_policy_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/boc_signals/canada_monetary_policy_signals
Tip: fetch /llms.txt for the full machine-readable catalog.