Strategy #0000000087 · Short-horizon price-volume reversal
Price-volume correlation reversal signals
Enter a correlation, assumed return per signal unit and costs to inspect the contrarian scenario.
This family ranks short-window correlations between price (or its rank) and volume, often taking the opposite side. Co-movement may reflect demand, information or liquidity shocks; correlation does not identify the cause. Formulaic Alpha #2 and related rules use different price transforms, volume transforms and windows.
The example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
How does short-window price-volume correlation map to a contrarian scenario?
This family ranks short-window correlations between price (or its rank) and volume, often taking the opposite side. Co-movement may reflect demand, information or liquidity shocks; correlation does not identify the cause. Formulaic Alpha #2 and related rules use different price transforms, volume transforms and windows.
Enter a correlation, assumed return per signal unit and costs to inspect the contrarian scenario.
The example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated.
- Signal inputEnter a correlation, assumed return per signal unit and costs to inspect the contrarian scenario.
- Return scenarioThe example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Signal=-Corr(Rank(Price),Rank(Volume),n),\quad R=Signal\cdot r_{scale}-C
n is the lookback; Signal is the negative correlation score; r_scale is an assumed return per signal unit.
Greeks: the directional intuition
- 資料
- Measures sensitivity to implied volatility.
- 門檻
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
Signal=-Corr(Rank(Price),Rank(Volume),n),\quad R=Signal\cdot r_{scale}-C
Practical context · published observations
Price-volume correlation reversal signals: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
The example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Signals within a family use different assumptions.
Compare horizon, frequency and trend/fade interpretations.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base indicator | Technical signal | This family ranks short-window correlations between price (or its rank) and volume, often taking the opposite side. Co-movement may reflect demand, information or liquidity shocks; correlation does not identify the cause. Formulaic Alpha #2 and related rules use different price transforms, volume transforms and windows. | The example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated. |
| Confirmation version | Multi-indicator filter | Add trend or volume confirmation. | Confirmation can delay entry. |
| Contrarian version | Mean reversion | Fade extreme deviations. | Can lose while a strong trend persists. |
The example inputs a correlation directly and does not compute raw daily bars; signal scaling is not empirically calibrated.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.
- 01Kakushadze (2016), 101 Formulaic Alphasresearch