Datasets:
pretty_name: All Daily Risk Indicators
language:
- en
license: other
task_categories:
- time-series-forecasting
- tabular-regression
tags:
- finance
- quantitative-trading
- backtesting
- algorithmic-trading
- macroeconomics
- uncertainty
- sentiment
- daily
size_categories:
- 10K<n<100K
extra_gated_prompt: >-
This dataset is free to browse and gated for download. Approval is tied to a
Papers With Backtest subscription, which also covers the other datasets in
this organisation and the strategy catalogue at
https://paperswithbacktest.com. Plans and what each one includes:
https://paperswithbacktest.com/pricing
dataset_info:
features:
- name: datetime
dtype: string
- name: us_epu_daily
dtype: float64
- name: uk_epu_daily
dtype: float64
- name: us_equity_uncertainty_daily
dtype: float64
- name: gpr_daily
dtype: float64
- name: gpr_daily_acts
dtype: float64
- name: gpr_daily_threats
dtype: float64
- name: ads_index
dtype: float64
- name: news_sentiment
dtype: float64
- name: baa_minus_10y_treasury
dtype: float64
- name: aaii_bullish
dtype: float64
- name: aaii_neutral
dtype: float64
- name: aaii_bearish
dtype: float64
All Daily Risk Indicators
Daily economic policy uncertainty (US since 1985, UK since 2001), equity market uncertainty, geopolitical risk with its acts and threats, the ADS business conditions index since 1960, daily news sentiment since 1980, the Baa corporate spread over the 10-year Treasury, and the weekly AAII survey of individual investors since 1987 -- each under its own name, in its own units, from its first real observation.
Shape measured at the next refresh of dataset_cards/facts.json. Refreshed monthly.
Why It Matters
These are the uncertainty, sentiment and business-cycle measures the literature conditions on, as their authors publish them. They replace the corresponding columns of All-Daily-TuringRiskIndex, which carried the same indicators rescaled into VIX units and preceded by a smooth synthetic history back to 1960: here a column is empty before its series existed, nothing is filled between observations, and the values are the published ones, so levels and thresholds mean what the papers say they mean.
The VIX is in Indices-Daily-Price (symbol VIX) and the Treasury curve, hence the term spreads, in All-Daily-Rates; they are not repeated here. Monthly indicators (CFNAI, monthly geopolitical risk, CAPE...) are in All-Monthly-RiskIndicators.
Load It
pip install --upgrade pwb-toolbox
from pwb_toolbox import datasets as pwb_ds
df = pwb_ds.load_dataset("All-Daily-RiskIndicators")
epu = df.set_index("datetime")["us_epu_daily"].dropna()
Columns
| Column Name | Description |
|---|---|
| datetime | Observation day. A row exists when at least one series has a value; the others are null that day. |
| us_epu_daily | US daily economic policy uncertainty index (Baker, Bloom and Davis), newspaper based, from 1985-01-01, every calendar day. |
| uk_epu_daily | UK daily economic policy uncertainty index, same method, from 2001-01-01. |
| us_equity_uncertainty_daily | US daily equity market uncertainty index (same authors), from 1985-01-01. |
| gpr_daily | Daily geopolitical risk index (Caldara and Iacoviello), from 1985-01-01. |
| gpr_daily_acts / gpr_daily_threats | Its geopolitical acts and geopolitical threats components. |
| ads_index | Aruoba-Diebold-Scotti business conditions index (Philadelphia Fed), zero = average conditions, from 1960-03-01. |
| news_sentiment | Daily news sentiment index (San Francisco Fed), from economic news articles, from 1980-01-01. |
| baa_minus_10y_treasury | Moody's seasoned Baa corporate bond yield minus the 10-year Treasury constant-maturity yield, percentage points, business days from 1986-01-02. May end: FRED titles its input, Moody's daily Baa yield, "discontinued" since November 2026; on 2026-11-08 the spread was still updated, last observation 2026-11-05. When it stops, the column keeps its history and ends at its last observation, with nothing filled after it. |
| aaii_bullish / aaii_neutral / aaii_bearish | Shares of respondents to the AAII weekly sentiment survey (fractions, summing to one), on the survey's reported day (a Thursday), from 1987-07-24; the other days are null. Bull-bear spread: aaii_bullish - aaii_bearish. |
Timing
Each value sits on the day it describes, which is not always the day it can be known:
- the policy, equity-market and geopolitical indices of a day are counted from that day's newspapers and are published the next day at the earliest; the geopolitical file is updated weekly;
- the ADS index is re-estimated with every new release, and this is the current vintage: past values carry later information;
- the news sentiment index of a day is a trailing weighted average of the articles published up to that day;
- the AAII shares are released on the reported day itself;
- the Baa spread of a day uses that day's closing yields.
A strategy that trades on a value should lag it by at least one day, more for the revised series.
Sources and Citation
Baker, S., N. Bloom and S. Davis (2016), "Measuring Economic Policy Uncertainty", Quarterly Journal of Economics 131(4), and policyuncertainty.com. Caldara, D. and M. Iacoviello (2022), "Measuring Geopolitical Risk", American Economic Review 112(4). Aruoba, S., F. Diebold and C. Scotti (2009), "Real-Time Measurement of Business Conditions", Journal of Business and Economic Statistics 27(4). Shapiro, A., M. Sudhof and D. Wilson (2022), "Measuring News Sentiment", Journal of Econometrics 228(2). The Baa spread is FRED series BAA10Y (Federal Reserve Bank of St. Louis), computed from Moody's seasoned Baa corporate bond yield; Moody's yields are Moody's data, cite them as such. The survey is the AAII Investor Sentiment Survey of the American Association of Individual Investors (aaii.com).
Access
Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: what each plan includes. The same subscription covers every dataset in this organisation and the strategy catalogue.
Elsewhere
- The strategy catalogue
pwb-toolbox, the loader used in the snippet above- Every dataset in this organisation