Geopolitical-risk signals (Caldara-Iacoviello GPR)
Monthly geopolitical-risk signals from the Caldara-Iacoviello GPR data export (1985 -> latest): the benchmark GPR index plus the threats and acts subindices, with 1-month and 12-month changes, 30-month annualized change volatility, 3-sigma anomaly flags, drift forecasts, 5-year tension-regime z-scores, high-risk and spike flags, and the threat-minus-act spread. The news-risk lens on geopolitics — the geopolitical companion to the policy lens in epu-signals and the financial lens in finstress-signals. Raw data: Caldara & Iacoviello.
Qualité
Attribution
Caldara & Iacoviello, Geopolitical Risk index (derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Reference month (GPR is a monthly index). |
| country | string | World (the GPR index is global). |
| country_code | string | Stable World aggregate code: WLD. |
| series_id | string | GPR series code: GPR (benchmark index), GPRT (threats subindex) or GPRA (acts subindex). |
| series_label | string | Series label as documented on the GPR page. |
| value | float | Geopolitical Risk index value as published: the index is normalized so that its 2000-2009 average equals 100. |
| momentum_3m | float | |
| yoy_change_pct | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| gpr_z_5y | float | |
| high_risk_flag | integer | |
| spike_flag | integer | |
| threat_act_spread | float |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | momentum_3m | yoy_change_pct | volatility_30d | anomaly_flag | forecast_1m | rank | gpr_z_5y | high_risk_flag | spike_flag | threat_act_spread |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1985-01-01 | World | WLD | GPR | Geopolitical Risk index (benchmark, monthly) | 102.17337799072266 | — | — | — | 0 | — | — | — | 0 | 0 | 17.926681518554688 |
| 1985-02-01 | World | WLD | GPR | Geopolitical Risk index (benchmark, monthly) | 117.10202026367188 | 14.928642272949219 | — | — | 0 | — | — | — | 0 | 0 | 29.84105682373047 |
| 1985-03-01 | World | WLD | GPR | Geopolitical Risk index (benchmark, monthly) | 124.77815246582031 | 7.6761322021484375 | — | — | 0 | — | — | — | 0 | 0 | 10.083580017089844 |
| 1985-04-01 | World | WLD | GPR | Geopolitical Risk index (benchmark, monthly) | 87.92900085449219 | -36.849151611328125 | — | — | 0 | — | — | — | 0 | 0 | 20.882400512695312 |
| 1985-05-01 | World | WLD | GPR | Geopolitical Risk index (benchmark, monthly) | 103.26284790039062 | 15.333847045898438 | — | — | 0 | — | — | — | 0 | 0 | 18.883056640625 |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/gpr_signals/gpr_geopolitical_risk_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/gpr_signals/gpr_geopolitical_risk_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)Point d’accès API: https://datazimuts.com/v1/datasets/gpr_signals/gpr_geopolitical_risk_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.