Brazil macro signals (Selic, BRL, IPCA)
Brazilian macro signals from the Banco Central do Brasil's SGS system (keyless API): the Selic target rate (daily), the USD/BRL exchange rate (daily) and IPCA consumer-price inflation (monthly), with 63-day/3-month momentum, 30-period change volatility, 3-sigma anomaly flags, drift forecasts, cross-series ranks, the real Selic rate (Selic minus IPCA 12-month), a 12-month BRL depreciation gauge, a restrictive real-rate flag and a 5-year Selic z-score. The first Latin America / emerging-market central-bank lens in the catalog, complementary to em-currency-stress-signals (FX only) and the developed-market policy sets. All rows normalized to country_code BRA. Raw data: Banco Central do Brasil (commercial re-use terms not verifiable from this machine — flagged unclear in the UI).
Quality
Attribution
Banco Central do Brasil (SGS time-series system); derived signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Reference date (BCB SGS field data; DD/MM/YYYY, daily or monthly). |
| country | string | |
| country_code | string | |
| series_id | string | BCB SGS series: SELIC (series 432, Selic target rate), USD_BRL (series 1, USD/BRL selling rate) or IPCA (series 433, IPCA monthly inflation; shipped as 12-month %). |
| series_label | string | Human-readable series label for the SGS series. |
| value | float | Series value (BCB SGS field valor): Selic target rate in % p.a. (daily), USD/BRL selling rate (daily), or IPCA 12-month inflation in % (monthly, compounded from the published monthly % changes). |
| momentum_3m | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| real_selic | float | |
| fx_depreciation_12m_pct | float | |
| high_real_rate_flag | integer | |
| selic_z_5y | float |
Sample rows
| date | country | country_code | series_id | series_label | value | momentum_3m | volatility_30d | anomaly_flag | forecast_1m | rank | real_selic | fx_depreciation_12m_pct | high_real_rate_flag | selic_z_5y |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1980-12-01 | Brazil | BRA | IPCA | IPCA consumer-price inflation (monthly %) | 99.27980254486424 | — | — | 0 | — | 1 | — | — | 0 | — |
| 1981-01-01 | Brazil | BRA | IPCA | IPCA consumer-price inflation (monthly %) | 99.69099703520259 | — | — | 0 | — | 1 | — | — | 0 | — |
| 1981-02-01 | Brazil | BRA | IPCA | IPCA consumer-price inflation (monthly %) | 103.08853072591813 | — | — | 0 | — | 1 | — | — | 0 | — |
| 1981-03-01 | Brazil | BRA | IPCA | IPCA consumer-price inflation (monthly %) | 101.03925943322922 | 1.75945688836498 | — | 0 | — | 1 | — | — | 0 | — |
| 1981-04-01 | Brazil | BRA | IPCA | IPCA consumer-price inflation (monthly %) | 103.27324113649516 | 3.5822441012925736 | — | 0 | — | 1 | — | — | 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/brazil_signals/brazil_macro_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/brazil_signals/brazil_macro_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/brazil_signals/brazil_macro_signals
Tip: fetch /llms.txt for the full machine-readable catalog.