Retail Flow
retail_flowQuantifies retail money flow, positioning, and activity and systematically takes contrarian positions.
How the factor is constructed
Retail Flow measures and responds to retail investor activity. By analyzing individual executed trades sourced from exchanges, it identifies assets heavily influenced by retail participation and takes systematically contrarian positions, seeking to exploit predictable patterns of overreaction and herding. Order sizes and types differentiate retail from institutional activity; five distinct techniques quantify trade imbalances and are combined in an ensemble without optimization or parameter fitting.
The universe consists of the most liquid and actively traded assets, identified on a rolling basis and survivorship-bias free. Positions are scaled by the inverse of rolling volatility; the factor is available point-in-time with hourly updates.
Retail Flow
| Period | Return | BTC | Ann. vol | Sharpe | Max DD |
|---|---|---|---|---|---|
| 1 month | -0.35% | +24.10% | — | — | -3.6% |
| 3 months | -2.83% | +17.86% | — | — | -5.9% |
| Year to date | +2.78% | -11.92% | — | — | -6.1% |
| 1 year | -2.91% | -32.28% | 11.2% | -0.23 | -7.5% |
| Since inception (CAGR) | +12.79% | +42.73% | 14.4% | 0.91 | -17.2% |
Putting Retail Flow to work
There are two ways to take Retail Flow from factsheet to live book: overlay it as a sleeve on the portfolio you already run, or use it as a building block in a standalone multi-factor portfolio. Both paths are documented in short, runnable notebooks that work out of the box against the public demo key — no signup required.
Add Retail Flow to an existing portfolio
Size a Retail Flow sleeve alongside your current book and quantify what it changes: correlation to your existing returns, then CAGR, volatility, Sharpe and maximum drawdown before and after the blend. One parameterized notebook runs for any factor — swap in Retail Flow, then bring your own daily returns as a CSV or start from the built-in demo book.
Build a portfolio from scratch
Construct a market-neutral multi-factor portfolio from the ground up: ensemble the raw signals, apply inverse-volatility weights with a per-asset cap, and backtest net of transaction costs. The default factor list reconstructs the 7 Factor Composite — Retail Flow is one of its seven constituents, so its contribution is in the blend from the first run.
New to the platform? The five-step guide covers data access, a proof of concept, and licensing.