
If indicators tell you what the market looks like, transform functions tell you how the market behaves. Transform functions operate directly on time series and return a new derived series.
Function | Description | Example |
|---|---|---|
| Natural logarithm |
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| Log returns: ln(xₜ / xₜ₋₁) |
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| Subtract mean from series |
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| Simple difference: xₜ − xₜ₋₁ |
|
| Alias for |
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What this unlocks
Return-based analysis instead of price-based
Volatility normalization
Momentum and acceleration modeling
Noise-reduced composite signals
Indicators describe how the market looks right now. Transform functions describe how the market behaves by reshaping a raw time series into a new derived series. Use them as the first step before normalization, smoothing, thresholds, or composites.
Natural logarithm. Useful to compress large ranges and turn multiplicative changes into additive changes.
log(X:BTCUSD.volume)log(X:BTCUSD.close)zscore(log(X:BTCUSD.volume))Log returns. Measures proportional change between bars, good for return based modeling.
logdiff(X:BTCUSD.close)abs(logdiff(X:BTCUSD.close))ema(logdiff(X:BTCUSD.close), 10)Subtract mean from series. Centers a signal around zero so you can see deviations from typical level.
demean(X:BTCUSD.rsi)zscore(demean(X:BTCUSD.rsi))abs(demean(X:BTCUSD.rsi))Simple difference. Measures raw change per bar in the original units.
diff(X:BTCUSD.close)ema(diff(X:BTCUSD.close), 5)zscore(diff(X:BTCUSD.close))delta(X:BTCUSD.close)abs(delta(X:BTCUSD.close))ema(delta(X:BTCUSD.close), 8)