Docs / Operations
Transformations
Transform Functions take a raw time series and convert it into a new signal that reveals structure, behavior, and relationships that are not visible in price alone.
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.
Sample Transformations
Function | Description | Example |
|---|---|---|
| Natural logarithm |
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| Log returns: ln(xₜ / xₜ₋₁) |
|
| Subtract mean from series |
|
| Simple difference: xₜ − xₜ₋₁ |
|
| Alias for |
|
What this unlocks
Return-based analysis instead of price-based
Volatility normalization
Momentum and acceleration modeling
Noise-reduced composite signals
Transformations in SEIOO
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.
log(x)
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))logdiff(x)
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)demean(x)
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))diff(x) or delta(x)
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)Was this helpful?