Also called residual momentum, history since 2003
product_id idiosyncratic_momentum_factor_us · 4800+ stocks · daily refresh · since 2003-01-01 · 1 data columns · API/CSV
curl "https://www.kavout.com/api?product_id=idiosyncratic_momentum_factor_us&api_key=YourAPIKey"
symbol / trade_date / field to filter · docs →GET · JSON · CSVIdiosyncratic momentum, or residual momentum, takes into account the three factors that explain a major part of the variation in average returns - market, size and value. Idiosyncratic momentum forecasts high long-term excess returns, and can be used to differentiate between high momentum stocks whose future returns reverse, and those whose do not.
Data through 2026-10-26
Data through 2026-10-26
Idiosyncratic momentum factors are available for all the tradable stock equities on the US stock exchanges, including major securities markets such as NYSE, Nasdaq and Dow Jones Industrial.
| Sector | Count | Type | Start date |
|---|---|---|---|
| Finance | 1,133 | Equities | 2003-01-01 |
| Health Technology | 775 | Equities | 2003-01-01 |
| Technology Services | 392 | Equities | 2003-01-01 |
| Electronic Technology | 387 | Equities | 2003-01-01 |
| Producer Manufacturing | 304 | Equities | 2003-01-01 |
| Consumer Services | 286 | Equities | 2003-01-01 |
| Non-Energy Minerals | 237 | Equities | 2003-01-01 |
| Energy Minerals | 223 | Equities | 2003-01-01 |
| Commercial Services | 223 | Equities | 2003-01-01 |
| Industrial Services | 194 | Equities | 2003-01-01 |
Idiosyncratic momentum factors are calculated daily for thousands of stocks.
This data is available via API and CSV download.
Each month, idiosyncratic momentum estimates the model over the past 36-month window for all stocks in the investment universe. Next the idiosyncratic retuns are calculated. Finally, the idiosyncratic momentum score is the last twelve 2-month volatility mean idiosyncratic return.
In addition to considering price and return, idiosyncratic momentum takes into account the market, size and value factors.
We applied the aforementioned idiosyncratic momentum metrics to a universe of the largest 500 US equities by market capitalization and ranked each stock on its idiosyncratic momentum factor. We then divided the universe into 10 quantiles of stocks, with the top quantile (Q_10) representing stocks with the highest value of that factor and the bottom quantile (Q_1) representing the lowest value of that factor.