The question
We started with a tempting idea: that the music a market plays might predict where its spending is heading. It was not a wild guess. Peer-reviewed work in the Journal of Financial Economics shows the valence of a country’s music tracks its sentiment, and even its stock returns. If mood is revealed in music, perhaps demand follows.
It was worth testing properly. So we did.
The four tests
We pre-registered each test before running it, so we could not move the goalposts once we had seen the data.
| Test | What it asked | Result |
|---|---|---|
| Country forecast | Does national mood predict spending? | Failed |
| Brand & category backtest | Does it predict brand or category demand? | Failed |
| Powered nowcast | France and Germany, properly powered | Failed |
| Domestic-only re-test | A cleaner home-grown signal | Failed |
All four failed. On the broader outcome, adding music actually made the forecast worse than leaving it out.
What we did about it
We published every result, with the pre-registration and the code, failures included. The claim was falsifiable, and we reported the nulls, not just the wins.
We changed the product, not the data.
The science supports music as a contemporaneous mood proxy. It does not support it as a forecast. So that is exactly how we use it: a read of where a market’s mood and attention are now, not a prediction of demand.
Why publish the failures
An admitted gap earns more confidence than a confident guess.
In a category built on confident guesses, the working is the trust. Every figure in a Cadence read names its public source and date. Negative results are still results, and a predictive tier would reopen only on a future pre-registered test that actually clears.
References
- Edmans, A., Fernández-Pérez, A., Garel, A., & Indriawan, I. (2022). Music sentiment and stock returns around the world. Journal of Financial Economics, 145(2).
- Pre-registrations, test specifications and code for all four backtests are published with the Cadence methodology.