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    • Logical Operators

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.
Transformations

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

log(x)

Natural logarithm

log(X:BTCUSD.volume)

logdiff(x)

Log returns: ln(xₜ / xₜ₋₁)

logdiff(X:BTCUSD.close)

demean(x)

Subtract mean from series

demean(X:BTCUSD.rsi)

diff(x)

Simple difference: xₜ − xₜ₋₁

diff(X:BTCUSD.close)

delta(x)

Alias for diff()

delta(X:BTCUSD.close)

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)
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