Comparison Operators

Comparison operators return 1 (true) or 0 (false) and are essential for logic-based signals.

Sample Comparison Operators

What this unlocks

• Threshold-based alerts

• Binary signal creation

• Event detection

• Regime classification

These outputs are not just conditions. They are signals that can be chained, weighted, smoothed, or combined into higher-order logic.

Relational comparisons < > >= <=

Used to detect thresholds, dominance, and relative positioning.

X:BTCUSD.rsi > 70

X:BTCUSD.close < ema(X:BTCUSD.close, 50)

logdiff(X:BTCUSD.close) >= 0

Equality comparisons == !=

Used to detect events, extremes, or state matches.

X:BTCUSD.close == highest(X:BTCUSD.close, 20)

X:BTCUSD.low == lowest(X:BTCUSD.low, 10)

diff(X:BTCUSD.close) != 0

Comparison between two derived series

Used for crossovers, dominance, and regime shifts.

ema(X:BTCUSD.close, 10) > ema(X:BTCUSD.close, 30)

zscore(logdiff(X:BTCUSD.close)) < -1

abs(logdiff(X:BTCUSD.close)) > abs(logdiff(ema(X:BTCUSD.close, 20)))

What this unlocks

• Threshold-based alerts Signals that fire only when behavior crosses a defined boundary.

• Binary signal creation Clean 0/1 outputs ready for weighting, voting, or aggregation.

• Event detection Exact moments like breakouts, extremes, or state transitions.

• Regime classification Market states expressed as logic, not interpretation.

Because these return numeric series, they can be:

• smoothed (ema(condition, n))

• weighted (0.3 * (condition))

• stacked into composite logic engines