Euro Area CISS: Composite Indicator of Systemic Stress, Monthly Since 1999
The Composite Indicator of Systemic Stress (CISS) is the European Central Bank’s measure of contemporaneous financial stress in the euro area. It combines 15 raw, mainly market-based stress measures grouped into five market segments — financial intermediaries, money markets, equity markets, bond markets, and foreign exchange markets — and aggregates them using portfolio theory, so that the index puts more weight on situations where stress is high in several segments at once. The CISS is unit-free and bounded between 0 and 1, where higher values indicate more widespread systemic stress. This dataset covers the euro area CISS as a monthly average from 1999, the financial-conditions companion Eco3min tracks alongside the US for its macro regime work.
Dataset: Euro Area CISS, monthly average (1999–present) · Updated 2026-06-01
Macro Takeaway
What distinguishes the CISS from a simple average of stress indicators is its portfolio-theoretic aggregation: it accounts for the time-varying correlation between market segments, so a given level of stress reads as more systemic when intermediaries, money markets, bonds, equities, and FX are deteriorating together rather than in isolation. That design makes it a measure of whether stress is contained or spreading. For the euro area it plays the role that the Chicago Fed NFCI plays for the United States — the financial-conditions reading Eco3min reads alongside its growth and inflation axes in the macro regime classification.
The index’s record shows how stress clusters in time. The CISS climbed to the highest levels of its history during the autumn 2008 global financial crisis, spiked again through the 2010–2012 euro-area sovereign debt crisis until the ECB’s mid-2012 commitment to backstop the bloc marked the turn, and jumped sharply in March 2020 at the onset of the pandemic. The March 2023 banking turmoil produced a brief, contained rise. Into 2026 the monthly CISS sat near the low end of its range, indicating calm rather than systemic stress across euro-area markets.
Dataset Overview
| Indicator | Composite Indicator of Systemic Stress, euro area (1999–present) |
|---|---|
| Geography | Euro area |
| Frequency | Monthly (average of daily values) |
| Period | 1999–present |
| Variables | date, ciss |
| Format | CSV, Excel (XLSX) |
| Sources | European Central Bank (ECB Data Portal, CISS) |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation month (first day of month) |
ciss | Float | Monthly average of the daily euro area CISS, unit-free and bounded in (0, 1); higher = more systemic stress |
Column names match the CSV headers exactly. The monthly value is the calendar-month mean of the ECB’s daily CISS.
Download the Complete Dataset
The full euro area CISS dataset is available in CSV and Excel formats.
Source Data Access
The CISS is published by the European Central Bank on the ECB Data Portal under series key CISS.D.U2.Z0Z.4F.EC.SS_CI.IDX, available at daily frequency from 1999. Eco3min republishes a monthly-averaged version below.
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/euro-area-ciss-systemic-stress.csv
This URL returns the complete monthly dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.
Using the Dataset in Python
import pandas as pd url = "https://eco3min.fr/dataset/euro-area-ciss-systemic-stress.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df.describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/euro-area-ciss-systemic-stress.csv" df <- read_csv(url) head(df) summary(df)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
Eco3min pulls the daily euro area CISS from the ECB Data Portal (SDMX) API and aggregates it to a monthly series by taking the calendar-month average. The dataset is refreshed daily through an automated pipeline so the latest month tracks incoming daily values; the ECB updates the daily CISS on an ongoing basis.
The CISS itself is constructed by the ECB from 15 raw stress measures split equally across five market segments. Each raw indicator is homogenised through its empirical cumulative distribution function, the three measures in each segment are averaged into a sub-index, and the five sub-indices are combined using a time-varying cross-correlation structure borrowed from portfolio theory. The result is bounded in (0, 1) and weights simultaneous, broad-based stress more heavily than isolated stress (Holló, Kremer and Lo Duca, ECB Working Paper No. 1426, 2012).
Historical Regimes
1999–2007 — Early euro calm. Through the early years of the single currency the CISS stayed low, with only transient rises around events such as the 2001–2002 equity downturn; stress remained concentrated rather than systemic.
2008–2009 — Global financial crisis. The CISS climbed to the highest levels in its history in the autumn of 2008, as stress hit money markets, bank funding, equities, and bonds simultaneously — precisely the cross-segment co-movement the index is designed to capture.
2010–2012 — Sovereign debt crisis. A second sustained surge accompanied the euro-area sovereign crisis, peaking in late 2011 amid stress on Greek, Italian, and Spanish debt; the ECB’s mid-2012 commitment to do “whatever it takes” preceded a marked decline.
2015–2019 — Post-crisis calm. Under sustained ECB accommodation the CISS returned to a low, stable range, with brief upticks around episodes such as the 2015–2016 market turbulence.
2020 — Pandemic shock. The index jumped sharply in March 2020 as the COVID outbreak hit all market segments at once, before ECB and fiscal intervention brought it back down within months.
2022–2026 — Energy shock, banking scare, and return to calm. The 2022 energy crisis and rapid rate rises lifted the CISS moderately; the March 2023 banking turmoil produced a brief, contained spike; and by 2026 the monthly index sat near the low end of its range.
Related Macroeconomic Datasets
Related Research
- Current Macro Regime — how financial-conditions stress feeds the live classification
- Macro Regime Classification Methodology
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- European Central Bank — Composite Indicator of Systemic Stress (ECB Data Portal, series CISS.D.U2.Z0Z.4F.EC.SS_CI.IDX)
- Holló, Kremer and Lo Duca — “CISS: A Composite Indicator of Systemic Stress in the Financial System”, ECB Working Paper No. 1426 (2012), methodology reference
Dataset Reference
Last updated — 3 June 2026
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