rythme_versements
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-09-30, from cac-40-dividend-yield.
| societe | place_de_cotation | versements_par_an |
|---|---|---|
| AXA | Paris | 1 |
| Air Liquide | Paris | 1 |
| Airbus | Paris | 1 |
| Crédit Agricole | Paris | 1 |
| Danone | Paris | 1 |
| EssilorLuxottica | Paris | 1 |
| L'Oréal | Paris | 1 |
| Michelin | Paris | 1 |
| Publicis | Paris | 1 |
| Safran | Paris | 1 |
| Sanofi | Paris | 1 |
| Schneider Electric | Paris | 1 |
| Stellantis | Paris | 1 |
| BNP Paribas | Paris | 1.33 |
| Société Générale | Paris | 1.33 |
| Hermès | Paris | 2 |
| Kering | Paris | 2 |
| LVMH | Paris | 2 |
| Vinci | Paris | 2 |
| TotalEnergies | Paris | 3 |
| Coca-Cola | New York | 4 |
| Johnson & Johnson | New York | 4 |
| Procter & Gamble | New York | 4 |
- Rows × columns
- 23 × 3
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
societe |
text | 23 distinct values (AXA, Air Liquide, Airbus…) | |
place_de_cotation |
text | 2 distinct values (New York, Paris) | |
versements_par_an |
number | 1 to 4 |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
SELECT
transform(ticker,
['TTE','SNY','STLA','LVMUY','AIQUY','EADSY','DANOY','BNPQY','SBGSY','SAFRY','LRLCY','HESAY','PUBGY','MGDDY','CRARY','SCGLY','VCISY','ESLOY','AXAHY','PPRUY','KO','JNJ','PG'],
['TotalEnergies','Sanofi','Stellantis','LVMH','Air Liquide','Airbus','Danone','BNP Paribas','Schneider Electric','Safran','L''Oréal','Hermès','Publicis','Michelin','Crédit Agricole','Société Générale','Vinci','EssilorLuxottica','AXA','Kering','Coca-Cola','Johnson & Johnson','Procter & Gamble'],
ticker) AS societe,
if(ticker IN ('KO','JNJ','PG'), 'New York', 'Paris') AS place_de_cotation,
round(versements / 3, 2) AS versements_par_an
FROM
(
SELECT
ticker,
count() AS versements
FROM
(
SELECT DISTINCT ticker, ex_dividend_date
FROM global_markets.stocks_dividends
WHERE ticker IN ('TTE','SNY','STLA','LVMUY','AIQUY','EADSY','DANOY','BNPQY','SBGSY','SAFRY','LRLCY','HESAY','PUBGY','MGDDY','CRARY','SCGLY','VCISY','ESLOY','AXAHY','PPRUY','KO','JNJ','PG')
AND ex_dividend_date >= '2023-01-01'
AND ex_dividend_date < '2026-01-01'
)
GROUP BY ticker
)
ORDER BY versements_par_an ASC, societe ASC
Travaillez ces données dans votre assistant IA
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