quantforge-miner / docs /Sentiment1.md
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# Sentiment Momentum (Conceptual β€” PV Proxies Only)
Market sentiment can be inferred from collective price-volume behavior. When institutional
players accumulate positions, volume tends to lead price; when they distribute, volume dries
up before price falls. These dynamics are fully capturable using Price-Volume fields.
**PV proxies for market sentiment:**
- **Accumulation vs. Distribution:**
`ts_corr(close, volume, 10)` β€” negative correlation signals distribution (smart money selling
into price strength); positive correlation signals accumulation.
- **Intraday Buying Pressure:**
`(close - low) / (high - low + 1e-6)` β€” a value near 1 means buyers dominated the session
(bullish sentiment); a value near 0 means sellers dominated (bearish sentiment).
- **Volume Intensity Zscore:**
`zscore(volume / adv20, 20)` β€” extreme positive z-scores mark sentiment extremes that
often revert.
- **Nonlinear Volume Anomaly:**
`signed_power(rank(volume / adv20), 2.0)` β€” amplifies extreme volume deviations,
useful for capturing tail-end accumulation events.
- **Median Deviation Signal:**
`(ts_mean(returns, 5) - ts_median(returns, 20))` β€” divergence between short-term mean and
long-term median captures momentum vs. value disagreement.
**Expression building blocks (PV only β€” safe operators):**
```
rank(ts_corr(close, volume, 10)) * -1 # distribution = future reversal
rank((close - low) / (high - low + 1e-6)) # intraday buying pressure rank
signed_power(rank(volume / adv20), 2.0) # amplified volume anomaly
ts_zscore(returns, 20) # standardized momentum signal
```